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Infection with human immunodeficiency virus (HIV) is associated with neuroimaging alterations. However, little is known about the topological organization of whole-brain networks and the corresponding association with cognition. As such, we examined structural whole-brain white matter connectivity patterns and cognitive performance in 29 HIV+ young adults (mean age = 25.9) with limited or no HIV treatment history. HIV+ participants and demographically similar HIV- controls (n = 16) residing in South Africa underwent magnetic resonance imaging (MRI) and neuropsychological testing. Structural network models were constructed using diffusion MRI-based multi-fiber tractography and T1-weighted MRI-based regional gray matter segmentation. Global network measures included whole-brain structural integration, connection strength, and structural segregation. Cognition was measured using a neuropsychological global deficit score (GDS) as well as individual cognitive domains. Results revealed that HIV+ participants exhibited significant disruptions to whole-brain networks, characterized by weaker structural integration (characteristic path length and efficiency), connection strength, and structural segregation (clustering coefficient) compared to HIV- controls (p values < 0.05). GDS scores and performance on learning/recall tasks were negatively correlated with the clustering coefficient (p < 0.05) in HIV+ participants. Results from the present study indicate disruption to brain network integrity in treatment limited HIV+ young adults with corresponding abnormalities in cognitive performance.
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Topological organization of whole-brain white matter in HIV infection
*Laurie M Baker1, *Sarah A Cooley2 (co-first author), Ryan P Cabeen3, David H Laidlaw4, John
A Joska5, Jacqueline Hoare5, Dan J Stein5,6, Jodi M Heaps-Woodruff7, Lauren E Salminen3,
Robert H Paul1,7
1University of Missouri Saint Louis, Department of Psychology, One University Boulevard,
Stadler Hall 327, Saint Louis, MO 63121, 314-566-3761, lauriebaker@umsl.edu
2Washington University in Saint Louis, School of Medicine, Department of Neurology, Saint
Louis, MO 63110
3University of Southern California, Keck School of Medicine, Los Angeles, CA 90032
4Brown University, Computer Science Department, Providence, RI 02912
5University of Cape Town, Department of Psychiatry and Mental Health, Cape Town,
South Africa
6 MRC Unit on Anxiety & Stress Disorders, Cape Town, South Africa
7Missouri Institute of Mental Health, St. Louis, MO 63134
*= contributed equally
Brain Connectivity
© Mary Ann Liebert, Inc.
DOI: 10.1089/brain.2016.0457
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Brain Connectivity
Topological organization of whole-brain white matter in HIV infection (doi: 10.1089/brain.2016.0457)
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Topological organization of whole-brain white matter in HIV infection (doi: 10.1089/brain.2016.0457)
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Abstract
Infection with human immunodeficiency virus (HIV) is associated with neuroimaging
alterations. However, little is known about the topological organization of whole-brain networks
and the corresponding association with cognition. As such, we examined structural whole-brain
white matter connectivity patterns and cognitive performance in 29 HIV+ young adults (mean
age = 25.9) with limited or no HIV treatment history. HIV+ participants and demographically
similar HIV controls (n = 16) residing in South Africa underwent magnetic resonance imaging
(MRI) and neuropsychological testing. Structural network models were constructed using
diffusion MRI-based multi-fiber tractography and T1-weighted MRI-based regional gray matter
segmentation. Global network measures included whole-brain structural integration, connection
strength, and structural segregation. Cognition was measured using a neuropsychological global
deficit score (GDS) as well as individual cognitive domains. Results revealed that HIV+
participants exhibited significant disruptions to whole-brain networks, characterized by weaker
structural integration (characteristic path length and efficiency), connection strength, and
structural segregation (clustering coefficient) compared to HIV controls (p values < 0.05). GDS
scores and performance on learning/recall tasks were negatively correlated with the clustering
coefficient (p < 0.05) in HIV+ participants. Results from the present study indicate disruption to
brain network integrity in treatment limited HIV+ young adults with corresponding
abnormalities in cognitive performance.
Keywords: HIV; cognition; whole-brain connectivity; network analysis
1.0 Introduction
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Topological organization of whole-brain white matter in HIV infection (doi: 10.1089/brain.2016.0457)
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Topological organization of whole-brain white matter in HIV infection (doi: 10.1089/brain.2016.0457)
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The human immunodeficiency virus (HIV) crosses the blood brain barrier shortly after
seroconversion (~8 days) and prior to marked immune suppression and overt cognitive
dysfunction (Valcour et al., 2012). Despite the efficacy of combination antiretroviral therapy
(cART) in reducing viral load, current treatments do not appear to prevent or reverse existing
brain damage (Ances, Ortega, Vaida, Heaps, & Paul 2013; Harezlak et al., 2011; Heaton et al.,
2011). Importantly, research shows axonal disruption and synaptic injury following HIV
infection (Avdoshina, Bachis, & Mocchetti, 2013; Ellis, Langford, & Masliah, 2007; Everall et
al., 1999; Everall et al., 2010; Masliah et al., 1997). Although specific brain regions appear
uniquely vulnerable, HIV-mediated neuronal damage is present throughout the brain (Ellis,
Langford, & Masliah, 2007; Ragin et al., 2004) and corresponds to neuropsychological
dysfunction (Masliah et al., 1997).
Diffusion tensor imaging (DTI) provides a robust method for identifying disruptions to
the structural connections throughout the brain. Multiple studies utilizing DTI reveal
abnormalities in brain white matter capable of disrupting connectivity across brain regions in
HIV+ individuals (Filippi et al., 2001, Ragin et al., 2004; Thurnher et al., 2005; Gongvatana et
al., 2009; Hoare et al., 2011). Further, using complex network analysis, structural changes in
white matter connections can be effectively modeled by combining diffusion magnetic resonance
imaging (MRI)-based tractography and T1-weighted MRIbased regional gray matter
segmentation. This network-based approach is highly sensitive to alterations in brain integrity
across multiple disease pathologies including schizophrenia, Alzheimer’s disease, and major
depressive disorder (Bullmore and Sporns 2009; Bassett et al., 2010; He et al., 2008; Lo et al.,
2010; Zhang et al., 2011; Bassett et al., 2008; Yu et al., 2011).
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Topological organization of whole-brain white matter in HIV infection (doi: 10.1089/brain.2016.0457)
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Topological organization of whole-brain white matter in HIV infection (doi: 10.1089/brain.2016.0457)
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Complex network analysis has been recently applied to investigate signatures of HIV
neuropathogenesis (Jahanshad et al., 2012). In this study, significant disruptions to brain
connectivity were identified in older HIV+ adults on cART. However, the relationship between
the topological organization of white matter and cognitive function in HIV remains unclear.
Further, no studies have examined connectivity metrics (e.g., structural segregation, structural
integration, and connection strength) in younger HIV+ individuals. It is necessary to fill this gap
in the literature in order to determine the functional relevance of white matter connectivity in
HIV+ individuals, independent of advanced age.
We used diffusion MRI-based tractography and graph-theoretic approaches to investigate
the topological organization of white matter in 29 HIV+ young adults and 16 HIV
demographically similar controls utilizing fiber-bundle length (FBL)-defined whole brain
connectivity metrics (structural segregation, structural integration, and connection strength).
These metrics provide insight into communication between regions of the brain. We also
examined the relationship between whole-brain topological organization and cognitive
performance using a global deficit score (GDS) and individual cognitive domain deficit scores
(learning/recall, psychomotor/processing speed, executive function, fine motor skills and
dexterity, and visuospatial skills). We hypothesized that whole-brain topological organization
would be diminished in HIV+ individuals compared to HIV-controls, and the degree of
abnormalities in the three connectivity metrics would significantly correlate with poorer
cognitive performance in young HIV+ individuals.
2.0 Methods
2.1 Participants
HIV+ participants were recruited from primary care HIV clinics in Cape Town, South
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Topological organization of whole-brain white matter in HIV infection (doi: 10.1089/brain.2016.0457)
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Topological organization of whole-brain white matter in HIV infection (doi: 10.1089/brain.2016.0457)
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Africa. Patients who were in the pretreatment counseling phase were identified from clinic
records. Interested participants completed a comprehensive consent process followed by a
detailed medical and demographic history. All participants were either treatment naïve at
enrollment (83%), or had initiated cART within three months of enrollment (17%). All but five
participants began treatment within one month of enrollment. HIV participants were recruited
from regional Voluntary Counseling and Testing Clinics in Cape Town, South Africa. Table 1
provides demographic information for the 29 HIV+ and 16 HIV participants.
Inclusion criteria for HIV+ participants included: (1) age between the years of 18 and 45;
(2) Xhosa as the primary language; (3) HIV serostatus documented by ELISA and confirmed by
Western blot, plasma HIV RNA, or a second antibody test for the HIV+ group; and (4) at least 7
years of formal education (all but one participant reported at least 10 years of education).
Exclusion criteria for all participants included (1) any major psychiatric condition that could
significantly affect cognitive status (e.g., schizophrenia or bipolar disorder); (2) confounding
neurological disorders including multiple sclerosis and other central nervous system (CNS)
conditions; (3) head injury with loss of consciousness greater than 30 min; (4) clinical evidence
of opportunistic CNS infections (toxoplasmosis, progressive multifocal leukoencephalopathy,
neoplasms); and (5) current substance use disorder determined by the Mini-International
Neuropsychiatric Interview Plus (MINIPlus) (Sheehan et al., 1998). All participants provided
signed informed consent. Study procedures were approved by local university IRB committees.
2.2 HIV viral load and CD4 T-cell counts
EDTA blood samples were collected at the time of study visit and plasma and cell
aliquots were stored at −70 °C. RNA was isolated from patient samples using the Abbott
RealTime HIV-1 amplification reagent kit, according to the manufacturer’s instructions. Viral
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Topological organization of whole-brain white matter in HIV infection (doi: 10.1089/brain.2016.0457)
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Topological organization of whole-brain white matter in HIV infection (doi: 10.1089/brain.2016.0457)
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load was determined using the Abbott m2000sp and the Abbott m2000rt analyzers (Abbott
laboratories, Abbott Park, IL, USA). All HIV+ participants had a detectable viral load (range
183-1,759,510 copies/ml). Analyses of cells from fresh blood samples were completed on the
FACSCalibur flow cytometer in conjunction with the MultiSET V1.1.2 software (BD
Biosciences, San Jose, CA, USA) for CD4 T-cell counts.
2.3 Neuroimaging Acquisition
Neuroimaging was acquired on a 3T Siemens Allegra scanner (Siemens AG, Erlangen
Germany), with a 4-channel phased-array head coil. Thirty unique diffusion gradient directions
at b=1000 s/mm2 were repeated to give a total of 60 diffusion weighted volumes using a
customized single-shot multi-slice echo-planar tensor-encoded imaging sequence. Six baseline
images were acquired and interleaved in the diffusion-weighted scans to improve motion-
correction. Seventy contiguous slices were obtained per contrast with a 128 x 128 matrix and
field of view of 218 x 218 mm (isotropic 1.7 x 1.7 x 1.7 mm3 voxels); TR: 10s, TE: 103 ms using
a full-Fourier transform. We also acquired a T1-weighted 3-dimensional magnetization-prepared
rapid acquisition gradient echo (MP-RAGE) sequence [time of repetition (TR) = 2400 ms, echo
time (TE = 2.38 ms), inversion time (TI) = 1000 ms flip angle = 8 degrees, 162 slices, and voxel
size = 1 x 1 x 1 mm3 for volumetric analyses.
2.4 Neuroimaging analysis
The T1-weighted MR images were processed with Freesurfer version 5.1.0 (Fischl et al.,
2012) to obtain a high-resolution gray matter parcellation. The diffusion-weighted MR images
were processed with a pipeline including FSL 5.0 (Jenkinson et al., 2012) and custom software,
described as follows. First, FSL eddy correct was used to correct for motion and eddy currents by
registering each diffusion-weighted volume to the first baseline with an affine
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Brain Connectivity
Topological organization of whole-brain white matter in HIV infection (doi: 10.1089/brain.2016.0457)
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Topological organization of whole-brain white matter in HIV infection (doi: 10.1089/brain.2016.0457)
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transformation. The gradient-encoding vectors were also rotated to account for the spatial
transformation of each volume (Leemans et al., 2009). Then, FSL BET was run for brain
extraction, and XFIBRES was run to obtain ball-and-sticks diffusion models in each voxel
(Behrens et al., 2007). Model fitting was performed with two stick compartments to improve
tractography in areas with complex anatomy, such as crossing fibers. Whole-brain deterministic
streamline tractography was performed to obtain geometric models of white matter pathways.
Tractography was executed utilizing an extension of the standard streamline approach to
use multiple fibers per voxel with the following parameters: four seeds per voxel, an angle
threshold of 50 degrees, a minimum length of 10 mm, and a minimum volume fraction of
0.1. During tracking, a kernel regression estimation framework (Cabeen et al., 2016) was used
for smooth interpolation of the multi-fiber ball-and-sticks models with a Gaussian kernel using a
spatial bandwidth of 1.5 mm and voxel neighborhood of 7x7x7. Then a subject-specific
structural network model was constructed from the combination of diffusion MR tractography
and T1-weighted MRI gray matter labels from the Desikan-Killiany atlas (Desikan et al., 2006)
and subcortical segmentations obtained from Freesurfer. For each pair of regions, a structural
connection was defined by first selecting fibers with endpoints in pairs of gray matter areas and
then computing the average FBL of the selected fibers to represent connection strength (Correia
et al. 2008). To avoid resampling artifacts, the tractography was performed in native space and
then the curve data were transformed to T1-space to test for intersection with gray matter
regions. This step registered the T1-weighted MRI to the average baseline diffusion scan using
FSL FLIRT with the mutual information criteria and an affine transformation. The resulting
weighted undirected connectivity matrix was analyzed with the Brain Connectivity Toolbox
(http://https://sites.google.com/site/bctnet/) to obtain global network measures of connection
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Topological organization of whole-brain white matter in HIV infection (doi: 10.1089/brain.2016.0457)
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Topological organization of whole-brain white matter in HIV infection (doi: 10.1089/brain.2016.0457)
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strength, structural segregation (clustering coefficient), and structural integration (characteristic
path length and global efficiency) (Figure 1; Rubinov & Sporns 2010).
2.5 Neuropsychological evaluation
The neuropsychological battery included tests of the following domains: Learning/recall-
(1) Hopkins Verbal Learning Test-Revised (HVLT-R; Brandt & Benedict 2001), and (2) Brief
Visuospatial Memory Test-Revised (BVMT-R; Benedict et al., 1996). Total correct on the
immediate and delayed recall trials were defined as the dependent variables for the HVLT-R and
BVMT-R. Psychomotor/processing speed- (1) Color Trails 1 (D’Elia et al., 1996), (2) Trail
Making Test A (Reitan, 1955), and (3) Digit Symbol (Wechsler, 2008). Time to completion was
the dependent variable for Color Trails 1 and Trail Making Test A. Total correct was the
dependent variable for Digit Symbol. Executive function- (1) Color Trails 2 (D’Elia et al., 1996),
and (2) Wisconsin Card Sorting Test (WCST; Grant & Berg, 1993). Time to completion was the
dependent variable for Color Trails 2, and total perseveration errors served as the dependent
variable for the WCST. Visuospatial skills- Block Design from the WAIS-IV (Wechsler 1997).
Total correct was the dependent variable. Fine motor skills and dexterity- Grooved Pegboard
Test (GPT; Kløve, 1963) non-dominant hand. Time to completion was the dependent variable.
2.6 Determination of domain specific and global neuropsychological function
For data reduction purposes, raw data from the neuropsychological test battery were
converted to T scores using mean and standard deviations from a sample of 52 HIV individuals
recruited from South Africa. A deficit score (ranging from 0-5 with a score of 0 indicating
normal range and greater scores indicating greater impairment) for each test was determined
using the methods previously reported by Carey and colleagues (2004). This approach provides a
more sensitive method for generating a summary neuropsychological score than averaging
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Topological organization of whole-brain white matter in HIV infection (doi: 10.1089/brain.2016.0457)
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Topological organization of whole-brain white matter in HIV infection (doi: 10.1089/brain.2016.0457)
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neuropsychological scores (Carey et al., 2004; Heaton et al. 2004). A GDS was then obtained
for each participant, with higher scores indicative of greater impairment. A GDS provides a
continuous measure of impairment with scores > 0.5 providing high rates of specificity (0.89)
and positive predictive value (0.83) in establishing HIV-associated impairment (Carey et al.,
2004; Heaton et al., 2004).
Domain specific deficit scores were calculated using similar methods as the calculation
for the GDS. Specifically, standardized T scores for each neuropsychological test were converted
to a deficit score between 0-5. The deficit scores were averaged to determine domain specific
deficit scores (i.e., learning/recall, psychomotor/processing speed, executive function, fine motor
skills and dexterity, and visuospatial skills).
2.7 Statistical Analysis
All statistical analyses were conducted utilizing SPSS, version 24. Differences in age,
sex, and education between HIV+ and HIV participants were examined using independent
sample t-tests (age and education) and chi-squared analyses (sex) to determine potential
covariates for the primary analyses. Differences in whole-brain topological organization between
groups were examined using three separate analyses of covariance or multivariate analyses of
covariance (ANCOVA/MANCOVA) models, depending on the number of metrics in each
category. HIV serostatus served as the independent variable and individual measures of
topological organization served as dependent variables in each analysis, with intracranial volume
(ICV) as a covariate. The measures of topological organization included structural segregation
(clustering coefficient), structural integration (characteristic path length and global efficiency),
and connection strength. Viral load was natural log transformed to achieve a normal distribution
for correlation analyses. Pearson’s correlations were used to determine if individual measures of
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Topological organization of whole-brain white matter in HIV infection (doi: 10.1089/brain.2016.0457)
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Topological organization of whole-brain white matter in HIV infection (doi: 10.1089/brain.2016.0457)
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connectivity were significantly related to HIV clinical variables (CD4 T-cell count and log
transformed viral load).
With respect to the distribution of GDS and domain specific deficit scores, the
standardized skewness coefficients and the standardized kurtosis coefficients revealed significant
departures from normality in the entire sample and within the HIV+ group. Therefore, a
nonparametric procedure, the Spearman’s rank order correlation (i.e., Spearman's rho), was
performed to address all correlations that included the GDS or domain scores. These analyses
were performed within the HIV+ sample as well as collapsed across the HIV+ and HIV groups.
3.0 Results
Subject characteristics are listed in Table 1. There were no statistically significant
differences in demographic factors (age, education, and sex) between HIV+ and HIV
participants. The ANCOVA/MANCOVA models revealed significantly weaker structural
segregation in HIV+ participants, defined by a lower clustering coefficient (F(1,42) = 11.20, p =
0.002 ), Cohen’s d = 1.06), as well as weaker structural integration defined by higher
characteristic path length and lower global efficiency (Wilks’ Λ = 0.77, F(2,41)= 6.10 , p =
0.005, d = 0.79), with characteristic path length F(1,42)= 12.23, p = 0.001, d = 1.12) and global
efficiency F(1,41)= 12.33 , p = 0.001, d = 1.12) both significantly contributing to the model.
Lastly, HIV+ participants showed weaker connection strength (F(1,42) = 8.29, p = 0.006, d =
0.92) (Table 2). Pearson’s correlational analyses revealed that CD4 T-cell count and viral load
were not significantly associated with any individual measures of connectivity (r values < |0.30|;
p values > 0.05).
Relationships Between GDS Scores and Connectivity Metrics
Collapsed across HIV+ and HIV participants, Spearman’s rho revealed statistically
Page 10 of 33
Brain Connectivity
Topological organization of whole-brain white matter in HIV infection (doi: 10.1089/brain.2016.0457)
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Brain Connectivity
Topological organization of whole-brain white matter in HIV infection (doi: 10.1089/brain.2016.0457)
This paper has been peer-reviewed and accepted for publication, but has yet to undergo copyediting and proof correction. The final published version may differ from this proof.
significant correlations between GDS scores with global characteristic path length (r = 0.34, p =
0.027) and mean connection strength (r = 0.31, p = 0.046). Trend level relationships were also
observed with global efficiency (r = 0.30, p = 0.057) and clustering coefficient (r = 0.30, p =
0.055). Together, these results indicate that poorer cognitive performance is associated with
abnormal network indices. When examined specifically within the HIV+ sample, Spearman’s
rho showed statistically significant negative relationships between the GDS and the clustering
coefficient (r = 0.40, p = 0.042), and trend level negative associations with global efficiency (r
= 0.38, p = 0.056) and connection strength (r = 0.37, p = 0.062). A trend level positive
relationship was observed between the GDS and characteristic path length (r = 0.37, p = 0.060).
Relationships Between Domain-specific Deficit Scores and Connectivity Metrics
Collapsed across HIV+ and HIV participants, poorer learning/recall was significantly
associated with higher global characteristic path length (r = 0.36, p = 0.010), lower mean
connection strength (r = 0.37, p = 0.012), lower global efficiency (r = 0.36, p = 0.016) and
lower clustering coefficient (r = 0.39, p = 0.009). No other significant relationships were
observed between the brain connectivity metrics and psychomotor/processing speed, executive
function, fine motor skills and dexterity, or visuospatial skills (r values < |0.30|, p values > 0.05).
When examined specifically within the HIV+ sample, learning/recall deficit scores were
significantly negatively associated with the clustering coefficient (r = 0.40, p = 0.037).
Negative trend level relationships were observed between learning/recall deficit scores and mean
connection strength (r = 0.36, p = 0.064) and global efficiency (r = 0.36, p = 0.058), whereas a
trend level positive relationship was observed with global characteristic length (r = 0.36, p =
0.052). No significant relationships were observed between the connectivity metrics and
psychomotor/processing speed, executive function, fine motor skills and dexterity, or
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Topological organization of whole-brain white matter in HIV infection (doi: 10.1089/brain.2016.0457)
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Topological organization of whole-brain white matter in HIV infection (doi: 10.1089/brain.2016.0457)
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visuospatial skills (r values < |0.30|, p values > 0.05) in the HIV+ sample.
4.0 Discussion
The current study revealed topological disorganization of brain white matter in HIV,
including abnormalities in structural segregation, structural integration, and connection strength.
Further, these abnormalities in network connectivity metrics were significantly associated with
cognitive dysfunction both across the entire sample and specifically within the HIV+ group.
These abnormalities were not significantly related to HIV clinical status (CD4 T-cell count and
viral load). Findings indicate that younger HIV+ participants with limited or no antiretroviral
treatment history exhibit significantly altered measures of whole-brain connectivity relative to
demographically similar HIV controls. These data suggest that alterations in whole-brain
network disruption are behaviorally relevant in the context of HIV.
Structural segregation refers to neural processing within interconnected regions of the
brain, whereas structural integration refers to the potential to rapidly combine specialized
information from distributed brain networks. The interplay of segregation and integration in
brain networks generates information that is simultaneously diversified and synthesized,
resulting in patterns of high complexity. Extensive research indicates that the dynamic patterns
generated by these networks provide the basis for cognition and perception (Bressler & Kelso,
2001; Frackowiak, 2004; McIntosh, 1999; Varela, Lachaux, Rodriguez, & Martinerie, 2001).
Underlying these global properties is a measure of connectivity between brain regions, which we
examined with the average FBL of tractography curves. Overall lower structural segregation
(clustering coefficient), structural organization (characteristic path length and global efficiency),
and connection strength were observed, indicating that HIV is associated with abnormal whole-
brain network connectivity.
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Topological organization of whole-brain white matter in HIV infection (doi: 10.1089/brain.2016.0457)
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Topological organization of whole-brain white matter in HIV infection (doi: 10.1089/brain.2016.0457)
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Neuroimaging studies have revealed consistent disruptions to subcortical and cortical
brain structures among individuals infected with HIV (Archibald et al., 2004; Stout et al., 1998;
Berger and Arendt 2000; Ances, Ortega, Vaida, Heaps, & Paul, 2012; Becker et al., 2011; Cohen
et al., 2010; Ragin et al., 2012; Heaps et al., 2012). Specifically, reduced volumes have been
observed within the thalamus, caudate, putamen, hippocampus, cortical white matter, and gray
matter (Ances, Ortega, Vaida, Heaps, & Paul, 2012; Holt et al., 2012; Ortega et al., 2013; Paul et
al., 2008; Paul et al., 2016; Thompson et al., 2005). Individuals with more advanced disease
exhibit reduced cortical thickness in primary sensory and motor areas (Thompson et al., 2005),
possibly reflecting distal effects of basal ganglia damage. Results from Jahanshad et al. (2012)
revealed pronounced white matter network disruption in primary motor and sensory areas of the
parietal and frontal lobes of older HIV individuals on stable treatment. Our study extends
previous work by revealing global network disruption in younger HIV+ individuals with immune
suppression and limited or no treatment history.
DTI abnormalities observed using scalar metrics in frontal, callosal, and deep white matter
regions in HIV+ individuals have been associated with poor cognitive performance (Chang et al.,
2008; Chen et al., 2009; Müller-Oehring et al., 2010; Pomara et al., 2001; Thurnher et al., 2005;
reviewed in Hardy and Hinkin, 2002; Hoare et al., 2015; Jernigan et al., 1993; Ortega et al.,
2013; Stout et al., 1998). Our results reveal a strong association between cognitive dysfunction
and diffuse brain network disruption in HIV+ young adults. Collapsed across HIV+ and HIV
participants, we observed significant associations between both GDS and learning/recall with
structural integration (characteristic path length) and connection strength, indicative of reduced
information transfer across networks (Latora and Marchiori, 2001) and reduced FBL.
Conversely, the most prominent relationships in the HIV+ group were observed between
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Topological organization of whole-brain white matter in HIV infection (doi: 10.1089/brain.2016.0457)
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Topological organization of whole-brain white matter in HIV infection (doi: 10.1089/brain.2016.0457)
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structural segregation (clustering coefficient) and both global neuropsychological impairment as
well as learning/recall. This pattern of structural abnormalities provides evidence of cognitive
impairment related to a measure of neural processing within densely interconnected networks.
Inflammation is hypothesized to be one of many important drivers of neuronal injury and
loss in HIV. Inflammation occurs soon after viral entry into the central nervous system (CNS)
and is associated with the release of proinflammatory cytokines, chemokines, and neurotoxic
viral proteins in response to HIV-infected macrophages and microglia (Anthony et al., 2005;
Lentz et al., 2011; Sailasuta et al., 2012; Harezlak et al., 2011; Valcour et al., 2012; Vera et al.,
2016). In turn, these activate uninfected macrophages and microglia to further release neurotoxic
substances that lead to compromised synaptodendritic connections, damage to axonal and myelin
integrity, and potentially neuronal death (Conant et al., 1998; Raja et al., 1997). These injuries
are distributed widely throughout the brain and correspond to white matter damage (Ellis,
Langford, & Masliah, 2007) as well as cognitive impairment (Everall et al., 1999).
An advantage of our study is the tractography method employed to quantify structural
connectivity. Typically, a major challenge of estimating whole-brain connectivity metrics is the
presence of complex configurations of fiber bundle anatomy such as fiber crossings. The
diffusion tensor model does not accurately represent voxels consisting of multiple fiber
populations, which limits the anatomical validity of network models derived using single tensor
models. More sophisticated techniques that represent multiple fibers, such as multi-compartment
and high angular resolution diffusion imaging, offer greater anatomical accuracy and improved
sensitivity in detecting complex anatomical features related to white matter changes due to
disease (Tuch et al., 1999; Tuch et al., 2002). We used the ball-and-sticks multi-compartment
model (Behrens et al., 2007) and a model-based estimation framework (Cabeen et al., 2016) to
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Topological organization of whole-brain white matter in HIV infection (doi: 10.1089/brain.2016.0457)
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15
Brain Connectivity
Topological organization of whole-brain white matter in HIV infection (doi: 10.1089/brain.2016.0457)
This paper has been peer-reviewed and accepted for publication, but has yet to undergo copyediting and proof correction. The final published version may differ from this proof.
improve the accuracy of connectivity mapping. Importantly, while this approach is ideal for the
single shell data, more sophisticated microstructure models that utilize multi-shell acquisitions
may provide improved anatomical accuracy and sensitivity to detect white matter changes.
Future studies may benefit by using neurite orientation dispersion and density imaging (NODDI)
to characterize changes in neurite density and orientation dispersion (Zhang et al., 2012).
Several limitations are important to address. First, we did not have sufficient numbers of
male HIV+ participants to examine sex differences in brain network topology. Previous research
conducted in HIV populations reveals sex differences in brain topology (Gong et al., 2009; Yan
et al., 2010), emphasizing the importance of examining sex differences in future studies.
Additionally, future research is needed to determine whether treatment improves whole-brain
connectivity abnormalities. Lastly, we excluded participants with substance use disorder due to
evidence that structural connectivity is disrupted in substance users independent of HIV (Bava et
al., 2009; Kim et al., 2014). Our approach ensured that the observed effects were not
confounded by substance use. However, our results may not generalize to the population of
HIV+ substance users. Despite these limitations, our findings provide strong evidence for
functionally relevant disruptions to network organization in HIV.
5.0 Conclusions
The current manuscript extends the literature in three novel ways. First, our cohort was
comprised of young HIV+ adults. Second, our sample was predominantly free of treatment
confounds on brain connectivity. Lastly, the present study included measures of cognition that
inform the functional relevance of the connectivity measures. Collectively, the results support a
model of diffuse network changes in young HIV+ individuals with limited or no treatment
history and corresponding cognitive dysfunction. The results provide further evidence of the
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Topological organization of whole-brain white matter in HIV infection (doi: 10.1089/brain.2016.0457)
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utility of anatomical brain connectivity as a noninvasive biomarker of white matter disruption in
HIV infection.
Acknowledgments
There are no actual or potential conflicts of interest for any of the authors on this manuscript.
Funding was supported by the National Institute of Mental Health (MH085604). Dr. Stein is
supported by the Medical Research Council of South Africa.
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Topological organization of whole-brain white matter in HIV infection (doi: 10.1089/brain.2016.0457)
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Topological organization of whole-brain white matter in HIV infection (doi: 10.1089/brain.2016.0457)
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Table 2. Differences in network connectivity between HIV+ and HIV participants
HIV+ (n =29)
HIV (n=16)
p value
Global Clustering Coefficient (mm)
53.18 (4.47)
57.67 (3.37)
0.002
Global Characteristic Path Length (1/mm)
0.015 (0.0012)
0.013 (0.0009)
0.001
Global Efficiency (mm)
77.86 (7.17)
85.62 (6.54)
0.001
Global Connection Strength (mm)
2939.75 (385.99)
3271.76 (312.58)
0.006
Note: Mean (SD)
Table 1. Subject Characteristics
HIV (n=16)
p value
Mean Age ± SD (range)
24.69 ± 4.53 (20-32)
0.55
Mean Education ± SD (range)
10.94 ± 1.29 (7-12)
0.31
Sex (% Male)
31%
0.46
Mean recent CD4 (cells/mm3) ± SD (range)
Mean plasma VL (copies/ml)a ± SD (range)
Mean months of infection± SD (range)
% Prescribed Antiretroviral Therapy
Mean Intracranial Volume (cm3) ± SD (range)
1,345.50 ± 211.64 (961.03-2033.13)
0.60
Mean Global Deficit Score ± SD (range)
0.18 ± 0.22 (0-0.82)
0.06
Note: aViral load log10 transformed
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Table 1. Subject Characteristics
Note: aViral load log10 transformed
Table 2. Differences in network connectivity between HIV+ and HIV individuals
Note: Mean (SD)
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Figure 1. Structural Network Analysis Visualizations
Left: A visualization of imaging-based reconstructions of anatomy, showing diffusion MRI-based
tractography and T1-weighted MRI-based gray matter segmentations. The left hemisphere shows
Desikan-Killiany regions-of-interest, and the right hemisphere shows streamline tractography
curves used to define connectivity between regions.
Right: A visualization of a structural network model derived from neuroimaging data. The left
hemisphere shows Desikan-Killiany regions-of-interest, and the right hemisphere shows a node-
link diagram representing the topological organization of white matter. Nodes are placed at the
centroid of each region and the links are derived from the average fiber bundle length between the
pairs of regions with structural connections.
Figure 1. Structural Network Analysis Visualizations
Figure 1: Left: A visualization of imaging-based reconstructions of anatomy, showing diffusion
MRI-based tractography and T1-weighted MRI-based gray matter segmentations. The left
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33
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Topological organization of whole-brain white matter in HIV infection (doi: 10.1089/brain.2016.0457)
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hemisphere shows Desikan-Killiany regions-of-interest, and the right hemisphere shows
streamline tractography curves used to define connectivity between regions.
Right: A visualization of a structural network model derived from neuroimaging data. The left
hemisphere shows Desikan-Killiany regions-of-interest, and the right hemisphere shows a node-
link diagram representing the topological organization of white matter. Nodes are placed at the
centroid of each region and the links are derived from the average fiber bundle length between
the pairs of regions with structural connections.
Page 33 of 33
Brain Connectivity
Topological organization of whole-brain white matter in HIV infection (doi: 10.1089/brain.2016.0457)
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... The whole brain can be considered as a single graph consisting of nodes linked by edges, with different brain regions being parceled as nodes and white matter tracts between them representing the edges (15)(16)(17). Previous structural network research showed that frontal and motor connections were compromised in older HIV+ patients (18), and young untreated HIV+ patients showed decreased efficiency, characteristic path length, clustering coefficient, and connection strength (19). Bell et al. (20) revealed a lower FA clustering coefficient and lesser MD nodal degree in the thalamus of HIV+ patients on cART. ...
... Furthermore, no significant alterations were discovered at the global level. Previous studies investigated patients with no prior treatment history or those who were mostly treated, and their results were mainly reflected at the global level (19,20). The patients in this study were all on successful cART and their plasma viral load was undetectable. ...
Article
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Objective Even with successful combination antiretroviral therapy (cART), patients with human immunodeficiency virus positive (HIV+) continue to present structural alterations and neuropsychological impairments. The purpose of this study is to investigate structural brain connectivity alterations and identify the hub regions in HIV+ patients with fully suppressed plasma viral loads. Methods In this study, we compared the brain structural connectivity in 48 patients with HIV+ treated with a combination of antiretroviral therapy and 48 healthy controls, using diffusion tensor imaging. Further comparisons were made in 24 patients with asymptomatic neurocognitive impairment (ANI) and 24 individuals with non-HIV-associated neurocognitive disorders forming a subset of HIV+ patients. The graph theory model was used to establish the topological metrics. Rich-club analysis was used to identify hub nodes across groups and abnormal rich-club connections. Correlations of connectivity metrics with cognitive performance and clinical variables were investigated as well. Results At the regional level, HIV+ patients demonstrated lower degree centrality (DC), betweenness centrality (BC), and nodal efficiency (NE) at the occipital lobe and the limbic cortex; and increased BC and nodal cluster coefficient (NCC) in the occipital lobe, the frontal lobe, the insula, and the thalamus. The ANI group demonstrated a significant reduction in the DC, NCC, and NE in widespread brain regions encompassing the occipital lobe, the frontal lobe, the temporal pole, and the limbic system. These results did not survive the Bonferroni correction. HIV+ patients and the ANI group had similar hub nodes that were mainly located in the occipital lobe and subcortical regions. The abnormal connections were mainly located in the occipital lobe in the HIV+ group and in the parietal lobe in the ANI group. The BC in the calcarine fissure was positively correlated with complex motor skills. The disease course was negatively correlated with NE in the middle occipital gyrus. Conclusion The results suggest that the occipital lobe and the subcortical regions may be important in structural connectivity alterations and cognitive impairment. Rich-club analysis may contribute to our understanding of the neuropathology of HIV-associated neurocognitive disorders.
... Graph-based network topology analysis provides a powerful and noninvasive method to probe the topological properties of the whole brain and can help to reveal the underlying neuropathological mechanism. Research on the topological organization of white matter based on graph theoretic approaches revealed HIV+/cART − had a lower clustering coefficient, weaker structural segregation, integration, and connection strength relative to HCs (18). Another study showed HIV+/cART+ had a lower global clustering coefficient indicative of brain network segregation and a lower nodal degree in the left thalamus compared with HCs (19). ...
Article
Full-text available
Background While regional brain structure and function alterations in HIV-infected individuals have been reported, knowledge about the topological organization in gray matter networks is limited. This research aims to investigate the effects of early HIV infection and combination antiretroviral therapy (cART) on gray matter structural covariance networks (SCNs) by employing graph theoretical analysis. Methods Sixty-five adult HIV+ individuals (25–50 years old), including 34 with cART (HIV+/cART+) and 31 medication-naïve (HIV+/cART–), and 35 demographically matched healthy controls (HCs) underwent high-resolution T1-weighted images. A sliding-window method was employed to create “age bins,” and SCNs (based on cortical thickness) were constructed for each bin by calculating Pearson's correlation coefficients. The group differences of network indices, including the mean nodal path length (Nlp), betweenness centrality (Bc), number of modules, modularity, global efficiency, local efficiency, and small-worldness, were evaluated by ANOVA and post-hoc tests employing the network-based statistics method. Results Relative to HCs, less efficiency in terms of information transfer in the parietal and occipital lobe (decreased Bc) and a compensated increase in the frontal lobe (decreased Nlp) were exhibited in both HIV+/cART+ and HIV+/cART– individuals (P < 0.05, FDR-corrected). Compared with HIV+/cART– and HCs, less specialized function segregation (decreased modularity and small-worldness property) and stronger integration in the network (increased Eglob and little changed path length) were found in HIV+/cART+ group (P < 0.05, FDR-corrected). Conclusion Early HIV+ individuals exhibited a decrease in the efficiency of information transmission in sensory regions and a compensatory increase in the frontal lobe. HIV+/cART+ showed a less specialized regional segregation function, but a stronger global integration function in the network.
... The global network efficiency was also reduced in HIV + BSL, suggesting that the communication between different brain regions We and others did not find significant topology difference in structural network of HIV infected individuals (Samboju et al., 2018;Zhuang et al., 2017). However, two studies (Baker et al., 2017;Bell et al., 2018) have shown disrupted structural networks in HIVinfected subjects compared to HC in terms of reduced global clustering coefficient, global network efficiency, and connection strength. ...
Article
Full-text available
MRI-based neuroimaging techniques have been used to investigate brain injury associated with HIV-infection. Whole-brain cortical mean-field dynamic modeling provides a way to integrate structural and functional imaging outcomes, allowing investigation of microscale brain dynamics. In this study, we adopted the relaxed mean-field dynamic modeling to investigate structural and functional connectivity in 42 HIV-infected subjects before and after 12-week of combination antiretroviral therapy (cART) and compared them with 46 age-matched healthy subjects. Microscale brain dynamics were modeled by a set of parameters including two region-specific microscale brain properties, recurrent connection strengths, and subcortical inputs. We also analyzed the relationship between the model parameters (i.e., the recurrent connection and subcortical inputs) and functional network topological characterizations, including smallworldness, clustering coefficient, and network efficiency. The results show that untreated HIV-infected individuals have disrupted local brain dynamics that in part correlate with network topological measurements. Notably, after 12 weeks of cART, both the microscale brain dynamics and the network topological measurements improved and were closer to those in the healthy brain. This was also associated with improved cognitive performance, suggesting that improvement in local brain dynamics translates into clinical improvement.
... The network with both strong global integration and high local specialization is considered to be a more economical network (Watts & Strogatz, 1998). L is a measure of average connectivity degree or overall routing efficiency of the network, Eg represents the ability of parallel information transmission on the network , the two properties are used to characterize network integration in an expanding body of studies (Baker et al., 2017;Park et al., 2018;Sun, Chen, Collinson, Bezerianos, & Sim, 2017;. The Eg of the cortical network of the IA participants increased significantly compared with the HC subjects, while the L exhibited a significant decrease. ...
Article
Full-text available
Background and aims: The working memory (WM) ability of internet addicts and the topology underlying the WM processing in internet addiction (IA) are poorly understood. In this study, we employed a graph theoretical framework to characterize the topological properties of the IA brain network in the source cortical space during WM task. Methods: A sample of 24 subjects with IA and 23 matched healthy controls (HCs) performed visual 2-back task. Exact Low Resolution Electromagnetic Tomography was adopted to project the pre-processed EEG signals into source space. Subsequently, Lagged phase synchronization was calculated between all pairs of Brodmann areas, the graph theoretical approaches were then employed to estimate the brain topological properties of all participants during the WM task. Results: We found better WM behavioral performance in IA subjects compared with the HCs. Moreover, compared to the HC group, more integrated and hierarchical brain network was revealed in the IA subjects in alpha band. And altered regional centrality was mainly resided in frontal and limbic lobes. In addition, significant relationships between the IA severity and the significant altered graph indices were found. Conclusions: In conclusion, these findings provide evidence to support the notion that altered topological configuration may underline changed WM function observed in IA.
... We and others did not find significant topology difference in structural network of HIV infected individuals (Samboju, Philippi, Chan, Cobigo, Fletcher, Robb, Hellmuth, Benjapornpong, Dumrongpisutikul, Pothisri, Paul, Ananworanich, Spudich, Valcour, Search, et al., 2018;Zhuang et al., 2017). However, two studies (Baker et al., 2017;Bell et al., 2018a) have shown disrupted structural networks in HIV-infected subjects compared to HC in terms of reduced global clustering coefficient, global network efficiency, and connection strength. ...
Preprint
Full-text available
In this study, we adopted the relaxed mean-field dynamic modeling to investigate structural and functional connectivity in forty-two HIV-infected subjects before and after 12-week of combination antiretroviral therapy (cART) and compared them with forty-six age-matched healthy subjects. Microscale brain dynamics were modeled by a set of parameters including two region-specific microscale brain properties, recurrent connection strengths, and subcortical inputs. We also analyzed the relationship between the model parameters (i.e. the recurrent connection and subcortical inputs) and functional network topological characterizations. The results show that untreated HIV-infected individuals have disrupted local brain dynamics that in part correlate with network topological measurements. Notably, after 12 weeks of cART, both the microscale brain dynamics and the network topological measurements improved and were closer to those in the healthy brain. This was also associated with improved cognitive performance, suggesting that improvement in local brain dynamics translates into clinical improvement.
... Studies demonstrate high viral aggregation in the basal ganglia [18], and neuroimaging abnormalities in the white matter, caudate, and putamen in the early and later stages of HIV [9,[19][20][21][22]. Neuroimaging abnormalities in the cortex and diffuse disruption to network connectivity have also been reported in PLWH [23], particularly in advanced or untreated disease [24]. These cortical abnormalities likely reflect remote signatures of damage to interconnected subcortical regions rather than isolated injury in the cortical mantle. ...
Article
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Purpose of review: This paper examines the theoretical and empirical basis for neurocognitive phenotyping of HIV. Recent findings: The pattern of neurocognitive symptoms associated with HIV has traditionally been referred to as a "subcortical" phenotype. Recent concern has been raised that the neurocognitive phenotype in the post-ART era has changed to reflect the addition of cortical features, suggestive of synergistic age-related neurodegeneration. Empirical evidence reviewed in this paper suggests that, when present, HIV-related neurocognitive impairment in the post-ART era remains subcortical in nature, regardless of advanced age or treatment status. Persistent neurocognitive impairment among virally suppressed individuals may reflect a combination of HIV disease factors, pre-existing risk factors, and/or emergent health comorbidities such as subcortical ischemic vascular disease in older people living with HIV. An entrenchment of the subcortical neurocognitive phenotype of HIV appears to be unfolding in the post-ART era. Whether new neurocognitive subtypes of HIV exist in the current era requires additional research utilizing harmonized test protocols and advanced computational methods capable of deep phenotyping. Recommendations from other neurological disorders are provided.
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Introduction School-aged children experience crucial developmental changes in white matter (WM) in adolescence. The human immunodeficiency virus (HIV) affects neurodevelopment. Children living with perinatally acquired HIV (CPHIVs) demonstrate hearing and neurocognitive impairments when compared to their uninfected peers (CHUUs), but investigations into the central auditory system (CAS) WM integrity are lacking. The integration of the CAS and other brain areas is facilitated by WM fibers whose integrity may be affected in the presence of HIV, contributing to neurocognitive impairments. Methods We used diffusion tensor imaging (DTI) tractography to map the microstructural integrity of WM between CAS regions, including the lateral lemniscus and acoustic radiation, as well as between CAS regions and non-auditory regions of 11-year-old CPHIVs. We further employed a DTI-based graph theoretical framework to investigate the nodal strength and efficiency of the CAS and other brain regions in the structural brain network of the same population. Finally, we investigated associations between WM microstructural integrity outcomes and neurocognitive outcomes related to auditory and language processing. We hypothesized that compared to the CHUU group, the CPHIV group would have lower microstructural in the CAS and related regions. Results Our analyses showed higher mean diffusivity (MD), a marker of axonal maturation, in the lateral lemniscus and acoustic radiations, as well as WM between the CAS and non-auditory regions predominantly in frontotemporal areas. Most affected WM connections also showed higher axial and radial diffusivity (AD and RD, respectively). There were no differences in the nodal properties of the CAS regions between groups. The MD of frontotemporal and subcortical WM-connected CAS regions, including the inferior longitudinal fasciculus, inferior fronto-occipital fasciculus, and internal capsule showed negative associations with sequential processing in the CPHIV group but not in the CHUU group. Discussion The current results point to reduced axonal maturation in WM, marked by higher MD, AD, and RD, within and from the CAS. Furthermore, alterations in WM integrity were associated with sequential processing, a neurocognitive marker of auditory working memory. Our results provide insights into the microstructural integrity of the CAS and related WM in the presence of HIV and link these alterations to auditory working memory.
Chapter
People living with HIV (PLWH) residing in high-income countries (HICs) are, in theory, well positioned to benefit from clinical care strategies that predict optimal neurocognitive and neuropsychiatric outcomes. However, there is substantial inter-individual variability in access to clinical care, prevalence of co-occurring risk factors, and comorbid health conditions that represent barriers to achieving the full potential of antiretroviral therapy (ART). Complex interactions between these variables translate into heterogeneity in HIV clinical phenotypes, including abnormalities in brain structure and function. The growing population of PLWH in HICs who are now reaching advanced age introduces additional causal pathways of neurocognitive variability among PLWH receiving ART. These patterns foreshadow trends expected to develop globally in response to increased access to ART. This chapter reviews the combination of highly dimensional risk factors for neurocognitive complications among PLWH residing in HICs. We begin with a brief description of the neuropathological, neuroimaging, and neurocognitive signatures of HIV, followed by a summary of controversies regarding the clinical presentation of HIV-associated neurocognitive disorders (HAND), including putative synergies between HIV disease dynamics and advanced age. Finally, we introduce innovative research strategies that have potential to advance the existing conceptual framework of HAND and, ideally, catalyze the development and of clinical interventions needed to achieve HIV treatment and eradication efforts.
Article
Objective: To assess changes in regional brain volumes after 24 months among individuals who initiated combination antiretroviral therapy (cART) within weeks of HIV exposure. Design: Prospective cohort study of Thai participants in the earliest stages of HIV-1 infection. Methods: Thirty-four acutely HIV-infected individuals (AHI; Fiebig I-V) underwent brain magnetic resonance (MR) imaging and MR spectroscopy at 1.5T and immediately initiated cART. Imaging was repeated at 24 months. Regional brain volumes were quantified using FreeSurfer's longitudinal pipeline. Voxel-wise analyses using tensor-based morphometry (TBM) were conducted to verify regional assessments. Baseline brain metabolite levels, blood and cerebrospinal fluid biomarkers assessed by ELISA, and peripheral blood monocyte phenotypes measured by flow cytometry were examined as predictors of significant volumetric change. Results: Participants were 31 ± 8 years old. The estimated mean duration of infection at cART initiation was 15 days. Longitudinal analyses revealed reductions in volumes of putamen (p < 0.001) and caudate (p = 0.006). TBM confirmed significant atrophy in the putamen and caudate, as well as in thalamic and hippocampal regions. In exploratory post-hoc analyses, higher baseline frequency of P-selectin glycoprotein ligand-1 (PSGL-1)-expressing total monocytes correlated with greater caudate volumetric decrease (ρ = 0.67, p = 0.017), while the baseline density of PSGL-1-expressing inflammatory (CD14CD16) monocytes correlated with putamen atrophy (ρ = 0.65, p = 0.022). Conclusion: Suppressive cART initiated during AHI may not prevent brain atrophy. Volumetric decrease appears greater than expected age-related decline, although examination of longitudinal change in demographically similar HIV-uninfected Thai individuals is needed. Mechanisms underlying progressive HIV-related atrophy may include early activation and enhanced adhesive and migratory capacity of circulating monocyte populations.
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Traumatic brain injury (TBI) is likely to disrupt structural network properties due to diffuse white matter pathology. The present study aimed to detect alterations in structural network topology in TBI and relate them to cognitive and real-world behavioral impairment. Twenty-two people with moderate to severe TBI with mostly diffuse pathology and 18 demographically matched healthy controls were included in the final analysis. Graph theoretical network analysis was applied to diffusion tensor imaging (DTI) data to characterize structural connectivity in both groups. Neuropsychological functions were assessed by a battery of psychometric tests and the Frontal Systems Behavior Scale (FrSBe). Local connection-wise analysis demonstrated reduced structural connectivity in TBI arising from subcortical areas including thalamus, caudate, and hippocampus. Global network metrics revealed that shortest path length in participants with TBI was longer compared to controls, and that this reduced network efficiency was associated with worse performance in executive function and verbal learning. The shortest path length measure was also correlated with family-reported FrSBe scores. These findings support the notion that the diffuse form of neuropathology caused by TBI results in alterations in structural connectivity that contribute to cognitive and real-world behavioral impairment. (JINS, 2014, 20, 1-10).
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The human immunodeficiency virus (HIV) has multiple genetic clades with varying prevalence throughout the world. Both HIV clade C (HIV-C) and HIV clade B (HIV-B) can cause cognitive impairment, but it is unclear if these clades are characterized by similar patterns of brain dysfunction. We examined brain volumetrics and neuropsychological performance among highly active antiretroviral therapy (HAART)-naïve HIV-B and HIV-C participants. Thirty-four HAART-naïve HIV-infected (HIV+) participants [17 HIV-B (USA); 17 HIV-C (South Africa)] and 34 age- and education-matched HIV-uninfected (HIV-) participants were evaluated. All participants underwent similar laboratory, neuropsychological, and neuroimaging studies. Brain volume measures were assessed within the caudate, putamen, amygdala, thalamus, hippocampus, corpus callosum, and cortical (gray and white matter) structures. A linear model that included HIV status, region, and their interaction assessed the effects of the virus on brain volumetrics. HIV- and HIV+ individuals were similar in age. On laboratory examination, HIV-C participants had lower CD4 cell counts and higher plasma HIV viral loads than HIV-B individuals. In general, HIV+ participants performed significantly worse on neuropsychological measures of processing speed and memory and had significantly smaller relative volumetrics within the thalamus, hippocampus, corpus callosum, and cortical gray and white matter compared to the respective HIV- controls. Both HIV-B and HIV-C are associated with similar volumetric declines when compared to matched HIV- controls. HIV-B and HIV-C were associated with significant reductions in brain volumetrics and poorer neuropsychological performance; however, no specific effect of HIV clade subtype was evident. These findings suggest that HIV-B and HIV-C both detrimentally affect brain integrity.
Article
Controversy remains regarding the neurotoxicity of clade C human immunodeficiency virus (HIV-C). When examined in preclinical studies, a cysteine to serine substitution in the C31 dicysteine motif of the HIV-C Tat protein (C31S) results in less severe brain injury compared to other viral clades. By contrast, patient cohort studies identify significant neuropsychological impairment among HIV-C individuals independent of Tat variability. The present study clarified this discrepancy by examining neuroimaging markers of brain integrity among HIV-C individuals with and without the Tat substitution. Thirty-seven HIV-C individuals with the Tat C31S substitution, 109 HIV-C individuals without the Tat substitution (C31C), and 34 HIV− controls underwent 3T structural magnetic resonance imaging (MRI) and diffusion tensor imaging (DTI). Volumes were determined for the caudate, putamen, thalamus, corpus callosum, total gray matter, and total white matter. DTI metrics included fractional anisotropy (FA), radial diffusivity (RD), and axial diffusivity (AD). Tracts of interest included the anterior thalamic radiation (ATR), cingulum bundle (CING), uncinate fasciculus (UNC), and corpus callosum (CC). HIV+ individuals exhibited smaller volumes in subcortical gray matter, total gray matter and total white matter compared to HIV− controls. HIV+ individuals also exhibited DTI abnormalities across multiple tracts compared to HIV− controls. By contrast, neither volumetric nor diffusion indices differed significantly between the Tat C31S and C31C groups. Tat C31S status is not a sufficient biomarker of HIV-related brain integrity in patient populations. Clinical attention directed at brain health is warranted for all HIV+ individuals, independent of Tat C31S or clade C status.
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We present and evaluate a method for kernel regression estimation of fiber orientations and associated volume fractions for diffusion MR tractography and population-based atlas construction in clinical imaging studies of brain white matter. This is a model-based image processing technique in which representative fiber models are estimated from collections of component fiber models in model-valued image data. This extends prior work in nonparametric image processing and multi-compartment processing to provide computational tools for image interpolation, smoothing, and fusion with fiber orientation mixtures. In contrast to related work on multi-compartment processing, this approach is based on directional measures of divergence and includes data-adaptive extensions for model selection and bilateral filtering. This is useful for reconstructing complex anatomical features in clinical datasets analyzed with the ball-and-sticks model, and our framework's data-adaptive extensions are potentially useful for general multi-compartment image processing. We experimentally evaluate our approach with both synthetic data from computational phantoms and in vivo clinical data from human subjects. With synthetic data experiments, we evaluate performance based on errors in fiber orientation, volume fraction, compartment count, and tractography-based connectivity. With in vivo data experiments, we first show improved scan-rescan reproducibility and reliability of quantitative fiber bundle metrics, including mean length, volume, streamline count, and mean volume fraction. We then demonstrate the creation of a multi-fiber tractography atlas from a population of 80 human subjects. In comparison to single tensor atlasing, our multi-fiber atlas shows more complete features of known fiber bundles and includes reconstructions of the lateral projections of the corpus callosum and complex fronto-parietal connections of the superior longitudinal fasciculus I, II, and III.
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Objective: To describe the effect of HIV on white matter integrity and neurocognitive function in children vertically infected with HIV, compared to a HIV-negative healthy control group. Design: Cross-sectional. Methods: We compared 75 HIV-infected children aged 6-16 years, including children on antiretroviral therapy (ART) and those who were ART-naive, with 30 controls on diffusion tensor imaging and a neuropsychological battery sensitive to fronto-striatal pathology. In a secondary analysis, we compared 'slow progressor' ART-naive children, children on ART without a diagnosis of encephalopathy and children on ART with HIV encephalopathy. Results: Compared to controls (n = 30), HIV-infected children (n = 75) displayed decreased fractional anisotropy and axial diffusion, and increased mean diffusivity and radial diffusion, indicating damaged neuronal microstructure. HIV-infected children performed poorly on the neuropsychological battery (P = <0.001). Within the HIV-infected group, children with HIV encephalopathy (n = 14) had poor white matter integrity when compared to ART-treated children without encephalopathy (n = 41), and there was significant myelin loss in ART-naive children (n = 20), compared with ART-treated children. ART-treated children had significant axonal damage in the corpus callosum (P = 0.009). Conclusion: Children infected with HIV, irrespective of treatment status, displayed significantly poorer white matter integrity and impaired cognition compared to HIV-negative controls. Our findings suggest that despite immune recovery in children on ART, they remain at risk for developing central nervous system disease, and that initiation of ART as early as possible may reduce the risk of developing white matter damage in ART-naive slow progressors.
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Diffuse white matter pallor is the most frequent neuropathological feature of HIV-1 infection and has been found to be particularly prominent in the advanced stages of the disease. The purpose of this study was to determine whether subtle white matter abnormalities can be detected in medically stable, ambulatory HIV-1 patients, in vivo, using diffusion tensor imaging (DTI). DTI is a magnetic resonance imaging (MRI) technique that is uniquely suited for the study of subtle white matter abnormalities. DTI was performed in six HIV-1 patients and nine controls. The two groups were similar in age. Abnormal fractional anisotropy was found in the white matter of the frontal lobes and internal capsules of the HIV-1 patients, in the absence of group differences in mean diffusivity, computed proton density, and computed T2. DTI may be more sensitive than conventional MRI methods for detecting subtle white matter disruptions in HIV-1 disease.