Aside from cortical damage associated with age, cerebrovascular and neurodegenerative diseases, it's an outstanding question if factors of global health, including normal variation in blood markers of metabolic and systemic function, may also be associated with individual variation in brain structure. This cross-sectional study included 138 individuals between 40 to 86 years old who were physically healthy and cognitively intact. Eleven markers (total cholesterol, HDL, LDL, triglycerides, insulin, fasting glucose, glycated hemoglobin, creatinine, blood urea nitrogen, albumin, total protein) and five derived indicators (estimated glomerular filtration rate, creatinine clearance rate, insulin-resistance, average glucose, and cholesterol/HDL ratio) were obtained from blood sampling of all participants. T1-weighted 3T MRI scans were used to evaluate gray matter cortical thickness. The markers were clustered into five factors, and factor scores were related to cortical thickness by general linear model. Two factors, one linked to insulin/metabolic health and the other to kidney function (KFF) showed regionally selective associations with cortical thickness including lateral and medial temporal, temporoparietal, and superior parietal regions for both factors and frontoparietal regions for KFF. An association between the increasing cholesterol and greater thickness in frontoparietal and occipital areas was also noted. Associations persisted independently of age, presence of cardiovascular risk factors and ApoE gene status. These findings may provide information on distinct mechanisms of inter-individual cortical variation as well as factors contributing to trajectories of cortical thinning with advancing age.
BACKGROUND: White matter signal abnormalities (WMSA) (also known as 'hyperintensities') on MRI are commonly seen in normal aging and increases have been noted in Alzheimer's disease (AD), but whether there is a spatial specificity to these increases is unknown.
OBJECTIVE: To discern whether or not there is a spatial pattern of WMSA in the brains of individuals with AD that differs from those who exhibit cognitively healthy aging.
METHOD: Structural MRI data from the Alzheimer's Disease Neuroimaging Initiative public database were used to quantify WMSA in 35 regions of interest (ROIs). Regional measures were compared between cognitively healthy older controls (OC; n = 107) and individuals with a clinical diagnosis of AD (n = 127). Regional WMSA volume was also assessed in individuals with mild cognitive impairment (MCI; n = 74) who were 6, 12, and 24 months away from AD conversion.
RESULTS: WMSA volume was significantly greater in AD compared to OC in 24 out of 35 ROIs after controlling for age, and nine were significantly higher after normalizing for total WMSA. Regions with greater WMSA volume in AD included rostral frontal, inferior temporal, and inferior parietal WM. In MCI, frontal and temporal regions demonstrated significantly greater WMSA volume with decreasing time-to-AD-conversion.
DISCUSSION: Individuals with AD have greater regional volume of WMSA compared to OC regardless of age or total WMSA volume. Accumulation of regional WMSA is linked to time to AD conversion in individuals with MCI. These findings indicate WMSA is an important pathological component of AD development.
White matter lesions, quantified as 'white matter signal abnormalities' (WMSA) on neuroimaging, are common incidental findings on brain images of older adults. This tissue damage is linked to cerebrovascular dysfunction and is associated with cognitive decline. The regional distribution of WMSA throughout the cerebral white matter has been described at a gross scale; however, to date no prior study has described regional patterns relative to cortical gyral landmarks which may be important for understanding functional impact. Additionally, no prior study has described how regional WMSA volume scales with total global WMSA. Such information could be used in the creation of a pathologic 'staging' of WMSA through a detailed regional characterization at the individual level. Magnetic resonance imaging data from 97 cognitively-healthy older individuals (OC) aged 52-90 from the Alzheimer's Disease Neuroimaging Initiative (ADNI) study were processed using a novel WMSA labeling procedure described in our prior work. WMSA were quantified regionally using a procedure that segments the cerebral white matter into 35 bilateral units based on proximity to landmarks in the cerebral cortex. An initial staging was performed by quantifying the regional WMSA volume in four groups based on quartiles of total WMSA volume (quartiles I-IV). A consistent spatial pattern of WMSA accumulation was observed with increasing quartile. A clustering procedure was then used to distinguish regions based on patterns of scaling of regional WMSA to global WMSA. Three patterns were extracted that showed high, medium, and non-scaling with global WMSA. Regions in the high-scaling cluster included periventricular, caudal and rostral middle frontal, inferior and superior parietal, supramarginal, and precuneus white matter. A data-driven staging procedure was then created based on patterns of WMSA scaling and specific regional cut-off values from the quartile analyses. Individuals with Alzheimer's disease (AD) and mild cognitive impairment (MCI) were then additionally staged, and significant differences in the percent of each diagnostic group in Stages I and IV were observed, with more AD individuals residing in Stage IV and more OC and MCI individuals residing in Stage I. These data demonstrate a consistent regional scaling relationship between global and regional WMSA that can be used to classify individuals into one of four stages of white matter disease. White matter staging could play an important role in a better understanding and the treatment of cerebrovascular contributions to brain aging and dementia.
We previously demonstrated 2 statistically distinct factors of degeneration in Alzheimer's disease: one strongly related to white matter damage and age interpreted as "age- and vascular-related", and the other related to cortical atrophy thought to represent "neurodegenerative changes associated with Alzheimer's disease". Those factors are now replicated in a distinct cross-sectional data set of 364 participants from the Alzheimer's Disease Neuroimaging Initiative and their interpretation is improved using correlations with CSF biomarkers. Furthermore, we now show that changes in both factors over 2 years are independently associated with decline in Mini-Mental State Examination score in a longitudinal subset of 116 individuals with mild cognitive impairment. Progression in the "age- and vascular-related" factor was greater for individuals with 2 APOE ε4 alleles and linked to a greater attributable change in Mini-Mental State Examination than the "neurodegenerative" factor. These results suggest benefits of targeting white matter and vascular health to complement interventions focused on the neurodegenerative aspect of the disease, even in individuals with little discernable vascular comorbidity.
A cross-sectional group study of the effects of aging on brain metabolism as measured with (18)F-FDG-PET was performed using several different partial volume correction (PVC) methods: no correction (NoPVC), Meltzer (MZ), Müller-Gärtner (MG), and the symmetric geometric transfer matrix (SGTM) using 99 subjects aged 65-87years from the Harvard Aging Brain study. Sensitivity to parameter selection was tested for MZ and MG. The various methods and parameter settings resulted in an extremely wide range of conclusions as to the effects of age on metabolism, from almost no changes to virtually all of cortical regions showing a decrease with age. Simulations showed that NoPVC had significant bias that made the age effect on metabolism appear to be much larger and more significant than it is. MZ was found to be the same as NoPVC for liberal brain masks; for conservative brain masks, MZ showed few areas correlated with age. MG and SGTM were found to be similar; however, MG was sensitive to a thresholding parameter that can result in data loss. CSF uptake was surprisingly high at about 15% of that in gray matter. The exclusion of CSF from SGTM and MG models, which is almost universally done, caused a substantial loss in the power to detect age-related changes. This diversity of results reflects the literature on the metabolism of aging and suggests that extreme care should be taken when applying PVC or interpreting results that have been corrected for partial volume effects. Using the SGTM, significant age-related changes of about 7% per decade were found in frontal and cingulate cortices as well as primary visual and insular cortices.
Diffusion magnetic resonance imaging (dMRI) is a unique technology that allows the noninvasive quantification of microstructural tissue properties of the human brain in healthy subjects as well as the probing of disease-induced variations. Population studies of dMRI data have been essential in identifying pathological structural changes in various conditions, such as Alzheimer's and Huntington's diseases (Salat et al., 2010; Rosas et al., 2006). The most common form of dMRI involves fitting a tensor to the underlying imaging data (known as diffusion tensor imaging, or DTI), then deriving parametric maps, each quantifying a different aspect of the underlying microstructure, e.g. fractional anisotropy and mean diffusivity. To date, the statistical methods utilized in most DTI population studies either analyzed only one such map or analyzed several of them, each in isolation. However, it is most likely that variations in the microstructure due to pathology or normal variability would affect several parameters simultaneously, with differing variations modulating the various parameters to differing degrees. Therefore, joint analysis of the available diffusion maps can be more powerful in characterizing histopathology and distinguishing between conditions than the widely used univariate analysis. In this article, we propose a multivariate approach for statistical analysis of diffusion parameters that uses partial least squares correlation (PLSC) analysis and permutation testing as building blocks in a voxel-wise fashion. Stemming from the common formulation, we present three different multivariate procedures for group analysis, regressing-out nuisance parameters and comparing effects of different conditions. We used the proposed procedures to study the effects of non-demented aging, Alzheimer's disease and mild cognitive impairment on the white matter. Here, we present results demonstrating that the proposed PLSC-based approach can differentiate between effects of different conditions in the same region as well as uncover spatial variations of effects across the white matter. The proposed procedures were able to answer questions on structural variations such as: "are there regions in the white matter where Alzheimer's disease has a different effect than aging or similar effect as aging?" and "are there regions in the white matter that are affected by both mild cognitive impairment and Alzheimer's disease but with differing multivariate effects?"
Structural magnetic resonance imaging data are frequently analysed to reveal morphological changes of the human brain in dementia. Most contemporary imaging biomarkers are scalar values, such as the volume of a structure, and may miss the localized morphological variation of early presymptomatic disease progression. Neuroanatomical shape descriptors, however, can represent complex geometric information of individual anatomical regions and may demonstrate increased sensitivity in association studies. Yet, they remain largely unexplored. In this article, we introduce a novel technique to study shape asymmetries of neuroanatomical structures across subcortical and cortical brain regions. We demonstrate that neurodegeneration of subcortical structures in Alzheimer's disease is not symmetric. The hippocampus shows a significant increase in asymmetry longitudinally and both hippocampus and amygdala show a significantly higher asymmetry cross-sectionally concurrent with disease severity above and beyond an ageing effect. Our results further suggest that the asymmetry in these structures is undirectional and that primarily the anterior hippocampus becomes asymmetric. Based on longitudinal asymmetry measures we subsequently study the progression from mild cognitive impairment to dementia, demonstrating that shape asymmetry in hippocampus, amygdala, caudate and cortex is predictive of disease onset. The same analyses on scalar volume measurements did not produce any significant results, indicating that shape asymmetries, potentially induced by morphometric changes in subnuclei, rather than size asymmetries are associated with disease progression and can yield a powerful imaging biomarker for the early presymptomatic classification and prediction of Alzheimer's disease. Because literature has focused on contralateral volume differences, subcortical disease lateralization may have been overlooked thus far.
Age-associated cerebrovascular disease impacts brain tissue integrity, but other factors, including normal variation in blood markers of systemic health, may also influence the structural integrity of the brain. This cross-sectional study included 139 individuals between 40 to 86 years old who were physically healthy and cognitively intact. Eleven markers (total-cholesterol, high-density lipoprotein, low-density lipoprotein, triglyceride, insulin, fasting glucose, glycated hemoglobin, creatinine, blood urea nitrogen, albumin, total protein) and five derived indicators (estimated glomerular filtration rate, creatinine clearance rate, insulin-resistance, average glucose, and cholesterol/high-density lipoprotein ratio) were obtained from blood sampling. Diffusion tensor imaging was used to evaluate white matter tissue health. Blood markers were clustered into five factors. The first factor (defined as insulin/high-density lipoprotein factor) was associated with markers of integrity in the deep white matter and projection fiber systems, while the third factor (defined as kidney function factor) was associated with different markers of integrity in the periventricular and watershed white matter regions. Differential segregated associations for insulin and high-density lipoprotein levels and serum markers of kidney function may provide information about distinct mechanisms of brain changes across the lifespan. These results emphasize the need to determine whether therapeutic modulation of systemic health and organ function may prevent decline in brain structural integrity.
BACKGROUND: Accumulating evidence suggests that posttraumatic stress disorder (PTSD) may accelerate cellular aging and lead to premature morbidity and neurocognitive decline.
METHODS: This study evaluated associations between PTSD and DNA methylation (DNAm) age using recently developed algorithms of cellular age by Horvath (2013) and Hannum et al. (2013). These estimates reflect accelerated aging when they exceed chronological age. We also examined if accelerated cellular age manifested in degraded neural integrity, indexed via diffusion tensor imaging.
RESULTS: Among 281 male and female veterans of the conflicts in Iraq and Afghanistan, DNAm age was strongly related to chronological age (rs ∼.88). Lifetime PTSD severity was associated with Hannum DNAm age estimates residualized for chronological age (β=.13, p=.032). Advanced DNAm age was associated with reduced integrity in the genu of the corpus callosum (β=-.17, p=.009) and indirectly linked to poorer working memory performance via this region (indirect β=-.05, p=.029). Horvath DNAm age estimates were not associated with PTSD or neural integrity.
CONCLUSIONS: Results provide novel support for PTSD-related accelerated aging in DNAm and extend the evidence base of known DNAm age correlates to the domains of neural integrity and cognition.
Blast-related mild traumatic brain injury (mTBI) is a common injury among Iraq and Afghanistan military veterans due to the frequent use of improvised explosive devices. A significant minority of individuals with mTBI report chronic postconcussion symptoms (PCS), which include physical, emotional, and cognitive complaints. However, chronic PCS are nonspecific and are also associated with mental health disorders such as posttraumatic stress disorder (PTSD). Identifying the mechanisms that contribute to chronic PCS is particularly challenging in blast-related mTBI, where the incidence of comorbid PTSD is high. In this study, we examined whether blast-related mTBI is associated with diffuse white matter changes, and whether these neural changes are associated with chronic PCS. Ninety Operation Enduring Freedom/Operation Iraqi Freedom (OEF/OIF) veterans were assigned to one of three groups including a blast-exposed no - TBI group, a blast-related mTBI without loss of consciousness (LOC) group (mTBI - LOC), and a blast-related mTBI with LOC group (mTBI + LOC). PCS were measured with the Rivermead Postconcussion Questionnaire. Results showed that participants in the mTBI + LOC group had more spatially heterogeneous white matter abnormalities than those in the no - TBI group. These white matter abnormalities were significantly associated with physical PCS severity even after accounting for PTSD symptoms, but not with cognitive or emotional PCS severity. A mediation analysis revealed that mTBI + LOC significantly influenced physical PCS severity through its effect on white matter integrity. These results suggest that white matter abnormalities are associated with chronic PCS independent of PTSD symptom severity and that these abnormalities are an important mechanism explaining the relationship between mTBI and chronic physical PCS. Hum Brain Mapp 37:220-229, 2016. Published 2015. This article is a U.S. Government work and is in the public domain in the USA.
White matter lesions are highly prevalent in individuals with Alzheimer's disease (AD). Although these lesions are presumed to be of vascular origin and linked to small vessel disease in older adults, little information exists about their relationship to markers of classical AD neurodegeneration. Thus, we examined the link between these white matter changes (WMC) segmented on T1-weighted MRI and imaging markers presumed to be altered due to primary AD neurodegenerative processes. Tissue microstructure of WMC was quantified using diffusion tensor imaging and the relationship of WMC properties and volume to neuroimaging markers was examined in 219 cognitively healthy older adults and individuals with mild cognitive impairment and AD using data from the Alzheimer's Disease Neuroimaging Initiative. No significant group differences in WMC properties were found. However, there were strong associations between diffusivity of WMC and ventricular volume, volume of WMC and total WM volume. In comparison, group differences in parahippocampal white matter microstructure were found for all diffusion metrics and were largely explained by hippocampal volume. Factor analysis on neuroimaging markers suggested two independent sets of covarying degenerative changes, with potentially age- and vascular-mediated tissue damage contributing to one factor and classical neurodegenerative changes associated with AD contributing to a second factor. These data demonstrate two potentially distinct classes of degenerative change in AD, with one factor strongly linked to aging, ventricular expansion, and both volume and tissue properties of white matter lesions, while the other factor related to classical patterns of cortical and hippocampal neurodegeneration in AD.
We examined the interactive effects of apolipoprotein ∊4 (APOE-∊4), a risk factor for Alzheimer's disease (AD), and diabetes risk on cortical thickness among 107 healthy elderly participants; in particular, participants included 27 APOE-∊4+ and 80 APOE-∊4- controls using T1-weighted structural magnetic resonance imaging. Regions of interests included select frontal, temporal, and parietal cortical regions. Among APOE-∊4, glucose abnormalities independently predicted reduced cortical thickness among temporoparietal regions but failed to predict changes for noncarriers. However, among noncarriers, age independently predicted reduced cortical thickness among temporoparietal and frontal regions. Diabetes risk is particularly important for the integrity of cortical gray matter in APOE-∊4 and demonstrates a pattern of thinning that is expected in preclinical AD. However, in the absence of this genetic factor, age confers risk for reduced cortical thickness among regions of expected compromise. This study supports aggressive management of cerebrovascular factors and earlier preclinical detection of AD among individuals presenting with genetic and metabolic risks.
Degenerative brain changes in Alzheimer's disease may occur in reverse order of normal brain development based on the retrogenesis model. This study tested whether evidence of reverse myelination was observed in mild cognitive impairment (MCI) using a data-driven analytic approach based on life span developmental data. Whole-brain high-resolution diffusion tensor imaging scans were obtained for 31 patients with MCI and 79 demographically matched healthy older adults. Comparisons across corpus callosum (CC) regions of interest (ROIs) showed decreased fractional anisotropy (FA) in the body but not in the genu or splenium; early-, middle-, and late-myelinating ROIs restricted to the CC revealed decreased FA in late- but not early- or middle-myelinating ROIs. Voxelwise group differences revealed areas of lower FA in MCI, but whole-brain differences were equally distributed across early-, middle-, and late-myelinating regions. Overall, results within the CC support the retrogenesis model, although caution is needed when generalizing these results beyond the CC.
Abstract Although much prior work has focused on the known cortical pathology that defines Alzheimer’s disease (AD) histologically, recent work has additionally demonstrated substantial damage to the cerebral white matter in this condition. While there is large evidence of diffuse damage to the white matter in AD, it is unclear whether specific white matter tracts exhibit a more accelerated pattern of damage and whether the damage is associated with the classical neurodegenerative changes of AD. In this study, we investigated microstructural differences in the large fascicular bundles of the cerebral white matter of individuals with \AD\ and mild cognitive impairment (MCI), using recently developed automated diffusion tractography procedures in the Alzheimer’s disease Neuroimaging Initiative (ADNI) dataset. Eighteen major fiber bundles in a total of 36 individuals with AD, 81 \MCI\ and 60 control participants were examined with the \TRActs\ Constrained by UnderLying Anatomy (TRACULA) procedure available as part of the FreeSurfer image processing software package. For each fiber bundle, the mean fractional anisotropy (FA), and mean, radial and axial diffusivities were calculated. Individuals with \AD\ had increased diffusivities in both left and right cingulum-angular bundles compared to control participants (p < 0.001). Individuals with \MCI\ also had increased axial and mean diffusivities and increased \FA\ in both cingulum-angular bundles compared to control participants (p < 0.05) and decreased radial diffusivity compared to individuals with \AD\ (p < 0.05). We additionally examined how white matter deterioration relates to hippocampal volume, a traditional imaging measure of \AD\ pathology, and found the strongest negative correlations in \AD\ patients between hippocampal volume and the diffusivities of the cingulum-angular and cingulum-cingulate gyrus bundles and of the corticospinal tracts (p < 0.05). However, statistically controlling for hippocampal volume did not remove all group differences in white matter measures, suggesting a unique contribution of white matter damage to \AD\ unexplained by this disease biomarker. These results suggest that (1) AD-associated deterioration of white matter fibers is greatest in tracts known to be connected to areas of pathology in \AD\ and (2) lower white matter tract integrity is more diffusely associated with lower hippocampal volume indicating that the pathology in the white matter follows to some degree the neurodegenerative staging and progression of this condition.
Methylation of the SKA2 (spindle and kinetochore-associated complex subunit 2) gene has recently been identified as a promising biomarker of suicide risk. Based on this finding, we examined associations between SKA2 methylation, cortical thickness and psychiatric phenotypes linked to suicide in trauma-exposed veterans. About 200 trauma-exposed white non-Hispanic veterans of the recent conflicts in Iraq and Afghanistan (91% male) underwent clinical assessment and had blood drawn for genotyping and methylation analysis. Of all, 145 participants also had neuroimaging data available. Based on previous research, we examined DNA methylation at the cytosine-guanine locus cg13989295 as well as DNA methylation adjusted for genotype at the methylation-associated single nucleotide polymorphism (rs7208505) in relationship to whole-brain cortical thickness, posttraumatic stress disorder symptoms (PTSD) and depression symptoms. Whole-brain vertex-wise analyses identified three clusters in prefrontal cortex that were associated with genotype-adjusted SKA2 DNA methylation (methylationadj). Specifically, DNA methylationadj was associated with bilateral reductions of cortical thickness in frontal pole and superior frontal gyrus, and similar effects were found in the right orbitofrontal cortex and right inferior frontal gyrus. PTSD symptom severity was positively correlated with SKA2 DNA methylationadj and negatively correlated with cortical thickness in these regions. Mediation analyses showed a significant indirect effect of PTSD on cortical thickness via SKA2 methylation status. Results suggest that DNA methylationadj of SKA2 in blood indexes stress-related psychiatric phenotypes and neurobiology, pointing to its potential value as a biomarker of stress exposure and susceptibility.Molecular Psychiatry advance online publication, 1 September 2015; doi:10.1038/mp.2015.134.
Although there is emerging data on the effects of blast-related concussion (or mTBI) on cognition, the effects of blast exposure itself on the brain have only recently been explored. Toward this end, we examine functional connectivity to the posterior cingulate cortex, a primary region within the default mode network (DMN), in a cohort of 134 Iraq and Afghanistan Veterans characterized for a range of common military-associated comorbidities. Exposure to a blast at close range (<10 meters) was associated with decreased connectivity of bilateral primary somatosensory and motor cortices, and these changes were not different from those seen in participants with blast-related mTBI. These results remained significant when clinical factors such as sleep quality, chronic pain, or post traumatic stress disorder were included in the statistical model. In contrast, differences in functional connectivity based on concussion history and blast exposures at greater distances were not apparent. Despite the limitations of a study of this nature (e.g., assessments long removed from injury, self-reported blast history), these data demonstrate that blast exposure per se, which is prevalent among those who served in Iraq and Afghanistan, may be an important consideration in Veterans' health. It further offers a clinical guideline for determining which blasts (namely, those within 10 meters) are likely to lead to long-term health concerns and may be more accurate than using concussion symptoms alone.
Although normal aging is known to reduce cortical structures globally, the effects of aging on local structures and functions of early visual cortex are less understood. Here, using standard retinotopic mapping and magnetic resonance imaging morphologic analyses, we investigated whether aging affects areal size of the early visual cortex, which were retinotopically localized, and whether those morphologic measures were associated with individual performance on visual perceptual learning. First, significant age-associated reduction was found in the areal size of V1, V2, and V3. Second, individual ability of visual perceptual learning was significantly correlated with areal size of V3 in older adults. These results demonstrate that aging changes local structures of the early visual cortex, and the degree of change may be associated with individual visual plasticity.
Cerebral amyloid angiopathy is a common form of small-vessel disease and an important risk factor for cognitive impairment. The mechanisms linking small-vessel disease to cognitive impairment are not well understood. We hypothesized that in patients with cerebral amyloid angiopathy, multiple small spatially distributed lesions affect cognition through disruption of brain connectivity. We therefore compared the structural brain network in patients with cerebral amyloid angiopathy to healthy control subjects and examined the relationship between markers of cerebral amyloid angiopathy-related brain injury, network efficiency, and potential clinical consequences. Structural brain networks were reconstructed from diffusion-weighted magnetic resonance imaging in 38 non-demented patients with probable cerebral amyloid angiopathy (69 ± 10 years) and 29 similar aged control participants. The efficiency of the brain network was characterized using graph theory and brain amyloid deposition was quantified by Pittsburgh compound B retention on positron emission tomography imaging. Global efficiency of the brain network was reduced in patients compared to controls (0.187 ± 0.018 and 0.201 ± 0.015, respectively, P < 0.001). Network disturbances were most pronounced in the occipital, parietal, and posterior temporal lobes. Among patients, lower global network efficiency was related to higher cortical amyloid load (r = -0.52; P = 0.004), and to magnetic resonance imaging markers of small-vessel disease including increased white matter hyperintensity volume (P < 0.001), lower total brain volume (P = 0.02), and number of microbleeds (trend P = 0.06). Lower global network efficiency was also related to worse performance on tests of processing speed (r = 0.58, P < 0.001), executive functioning (r = 0.54, P = 0.001), gait velocity (r = 0.41, P = 0.02), but not memory. Correlations with cognition were independent of age, sex, education level, and other magnetic resonance imaging markers of small-vessel disease. These findings suggest that reduced structural brain network efficiency might mediate the relationship between advanced cerebral amyloid angiopathy and neurologic dysfunction and that such large-scale brain network measures may represent useful outcome markers for tracking disease progression.
BACKGROUND: Understanding the neural causes and consequences of posttraumatic stress disorder (PTSD) and mild traumatic brain injury (mTBI) is a high research priority, given the high rates of associated disability and suicide. Despite remarkable progress in elucidating the brain mechanisms of PTSD and mTBI, a comprehensive understanding of these conditions at the level of brain networks has yet to be achieved. The present study sought to identify functional brain networks and topological properties (measures of network organization and function) related to current PTSD severity and mTBI.
METHODS: Graph theoretic tools were used to analyze resting-state functional magnetic resonance imaging data from 208 veterans of Operation Enduring Freedom, Operation Iraqi Freedom, and Operation New Dawn, all of whom had experienced a traumatic event qualifying for PTSD criterion A. Analyses identified brain networks and topological network properties linked to current PTSD symptom severity, mTBI, and the interaction between PTSD and mTBI.
RESULTS: Two brain networks were identified in which weaker connectivity was linked to higher PTSD re-experiencing symptoms, one of which was present only in veterans with comorbid mTBI. Re-experiencing was also linked to worse functional segregation (necessary for specialized processing) and diminished influence of key regions on the network, including the hippocampus.
CONCLUSIONS: Findings of this study demonstrate that PTSD re-experiencing symptoms are linked to weakened connectivity in a network involved in providing contextual information. A similar relationship was found in a separate network typically engaged in the gating of working memory, but only in veterans with mTBI.
OBJECTIVE: Aging is associated with reduced neural integrity, yet there are remarkable individual differences in brain health among older adults (OA). One factor that may attenuate age-related neural decline is cardiorespiratory fitness (CRF). The primary aim of this study was to link CRF to neural white matter microstructure using diffusion tensor imaging in OA.
METHODS: Young adults (YA; n = 32) and OA (n = 27) completed a graded maximal exercise test to evaluate CRF and diffusion tensor magnetic resonance imaging to examine neural white matter integrity.
RESULTS: As expected, pervasive age-related declines in white matter integrity were observed when OA were compared to YA. Further, peak VO2 was positively associated with fractional anisotropy (FA), an indicator of white matter integrity, in multiple brain regions in OA, but not YA. In multiple posterior regions such as the splenium, sagittal stratum, posterior corona radiata, and superior parietal white matter, FA values were similar in YA and OA classified as higher fit, with both groups having greater FA than lower fit OA. However, age-related differences in FA values remained in other regions, including the body and genu of the corpus callosum, precuneus, and superior frontal gyrus.
INTERPRETATION: CRF is positively associated with neural white matter microstructure in aging. The relationship between peak VO2 and FA appears to be tract-specific, as equivalent FA values were observed in higher fit OA and YA in some white matter tracts, but not others. Further, the association between peak VO2 and FA appears to be age-dependent.