Prospective memory performance in veterans with and without histories of mild traumatic brain injury: effect of the apolipoprotein E (APOE) ε4 genotype.

OBJECTIVE: Identifying factors that moderate cognitive outcomes following mild traumatic brain injury (mTBI) is crucial. Prospective memory (PM) is a cognitive domain of interest in mTBI recovery as it may be especially sensitive to TBI-related changes. Since studies show that genetic status - particularly possession of the apolipoprotein E (APOE) ε4 allele - can modify PM performance, we investigated associations between mTBI status and APOE-ε4 genotype on PM performance in a well-characterized sample of Veterans with neurotrauma histories. METHODS: 59 Veterans (mTBI = 33, Military Controls [MCs] = 26; age range: 24-50; average years post-injury = 10.41) underwent a structured clinical interview, neuropsychological assessment, and genotyping. The Memory for Intentions Test (MIST) measured PM across multiple subscales. ANCOVAs, adjusting for age and posttraumatic stress symptoms, tested the effects of mTBI status (mTBI vs. MC) and ε4 status (ε4+ vs. ε4-) on MIST scores. RESULTS: Veterans with mTBI history performed more poorly compared to MCs on the MIST 15-min delay (p=.002, ηp2 =.160), Time Cue (p = .003, ηp2 =.157), and PM Total (p = .016, ηp2 =.102). Those with at least one copy of the ε4 allele performed more poorly compared to ε4- Veterans on the MIST 15-min delay (p = .011, ηp2 =.113) and PM Total (p = .048, ηp2 = .071). No significant interactions were observed between mTBI and APOE-ε4 status on MIST outcomes (ps>.25). Within the mTBI group, APOE-ε4+ Veterans performed worse than APOE-ε4- Veterans on the MIST 15-min delay subscale (p = .031, ηp2 = .150). CONCLUSIONS: mTBI history and APOE-ε4 genotype status were independently associated with worse PM performance compared to those without head injury histories or possession of the APOE-e4 genotype. Performance on the MIST 15-min delay was worse in Veterans with both risk factors (mTBI history and APOE-ε4 positivity). Findings suggest that genetic status may modify outcomes even in relatively young Veterans with mTBI histories. Future research examining longitudinal associations and links to neuroimaging and biomarker data are needed.

Cognition and Amyloid-ß in Older Veterans: Characterization and Longitudinal Outcomes of Data-Derived Phenotypes.

Background: Within older Veterans, multiple factors may contribute to cognitive difficulties. Beyond Alzheimer's disease (AD), psychiatric (e.g., PTSD) and health comorbidities (e.g., TBI) may also impact cognition. Objective: This study aimed to derive subgroups based on objective cognition, subjective cognitive decline (SCD), and amyloid burden, and then compare subgroups on clinical characteristics, biomarkers, and longitudinal change in functioning and global cognition. Methods: Cluster analysis of neuropsychological measures, SCD, and amyloid PET was conducted on 228 predominately male Vietnam-Era Veterans from the Department of Defense-Alzheimer's Disease Neuroimaging Initiative. Cluster-derived subgroups were compared on baseline characteristics as well as 1-year changes in everyday functioning and global cognition. Results: The cluster analysis identified 3 groups. Group 1 (n = 128) had average-to-above average cognition with low amyloid burden. Group 2 (n = 72) had the lowest memory and language, highest SCD, and average amyloid burden; they also had the most severe PTSD, pain, and worst sleep quality. Group 3 (n = 28) had the lowest attention/executive functioning, slightly low memory and language, elevated amyloid and the worst AD biomarkers, and the fastest rate of everyday functioning and cognitive decline. CONCLUSIONS: Psychiatric and health factors likely contributed to Group 2's low memory and language performance. Group 3 was most consistent with biological AD, yet attention/executive function was the lowest score. The complexity of older Veterans' co-morbid conditions may interact with AD pathology to show attention/executive dysfunction (rather than memory) as a prominent early symptom. These results could have important implications for the implementation of AD-modifying drugs in older Veterans.

Association of Vascular Risk Factors and CSF and Imaging Biomarkers With White Matter Hyperintensities in Former American Football Players.

BACKGROUND AND OBJECTIVES: Recent data link exposure to repetitive head impacts (RHIs) from American football with increased white matter hyperintensity (WMH) burden. WMH might have unique characteristics in the context of RHI beyond vascular risk and normal aging processes. We evaluated biological correlates of WMH in former American football players, including markers of amyloid, tau, inflammation, axonal injury, neurodegeneration, and vascular health. METHODS: Participants underwent clinical interviews, MRI, and lumbar puncture as part of the Diagnostics, Imaging, and Genetics Network for the Objective Study and Evaluation of Chronic Traumatic Encephalopathy Research Project. Structural equation modeling tested direct and indirect effects between log-transformed total fluid-attenuated inversion recovery (FLAIR) lesion volumes (TLV) and the revised Framingham stroke risk profile (rFSRP), MRI-derived global metrics of cortical thickness and fractional anisotropy (FA), and CSF levels of amyloid ß1-42, p-tau181, soluble triggering receptor expressed on myeloid cells 2 (sTREM2), and neurofilament light. Covariates included age, race, education, body mass index, APOE ε4 carrier status, and evaluation site. Models were performed separately for former football players and a control group of asymptomatic men unexposed to RHI. RESULTS: In 180 former football players (mean age = 57.2, 36% Black), higher log(TLV) had direct associations with the following: higher rFSRP score (B = 0.26, 95% CI 0.07-0.40), higher p-tau181 (B = 0.17, 95% CI 0.01-0.43), lower FA (B = -0.28, 95% CI -0.42 to -0.13), and reduced cortical thickness (B = -0.25, 95% CI -0.45 to -0.08). In 60 asymptomatic unexposed men (mean age = 59.3, 40% Black), there were no direct effects on log(TLV) (rFSRP: B = -0.03, 95% CI -0.48 to 0.57; p-tau181: B = -0.30, 95% CI -1.14 to 0.37; FA: B = -0.07, 95% CI -0.48 to 0.42; or cortical thickness: B = -0.28, 95% CI -0.64 to 0.10). The former football players showed stronger associations between log(TLV) and rFSRP (1,069% difference in estimates), p-tau181 (158%), and FA (287%) than the unexposed men. DISCUSSION: Risk factors and biological correlates of WMH differed between former American football players and asymptomatic unexposed men. In addition to vascular health, p-tau181 and diffusion tensor imaging indices of white matter integrity showed stronger associations with WMH in the former football players. FLAIR WMH may have specific risk factors and pathologic underpinnings in RHI-exposed individuals.

Comparing neuropsychological, typical, and ADNI criteria for the diagnosis of mild cognitive impairment in Vietnam-era veterans.

OBJECTIVE: Neuropsychological criteria for mild cognitive impairment (MCI) more accurately predict progression to Alzheimer's disease (AD) and are more strongly associated with AD biomarkers and neuroimaging profiles than ADNI criteria. However, research to date has been conducted in relatively healthy samples with few comorbidities. Given that history of traumatic brain injury (TBI) and post-traumatic stress disorder (PTSD) are risk factors for AD and common in Veterans, we compared neuropsychological, typical (Petersen/Winblad), and ADNI criteria for MCI in Vietnam-era Veterans with histories of TBI or PTSD. METHOD: 267 Veterans (mean age = 69.8) from the DOD-ADNI study were evaluated for MCI using neuropsychological, typical, and ADNI criteria. Linear regressions adjusting for age and education assessed associations between MCI status and AD biomarker levels (cerebrospinal fluid [CSF] p-tau181, t-tau, and Aß42) by diagnostic criteria. Logistic regressions adjusting for age and education assessed the effects of TBI severity and PTSD symptom severity simultaneously on MCI classification by each criteria. RESULTS: Agreement between criteria was poor. Neuropsychological criteria identified more Veterans with MCI than typical or ADNI criteria, and were associated with higher CSF p-tau181 and t-tau. Typical and ADNI criteria were not associated with CSF biomarkers. PTSD symptom severity predicted MCI diagnosis by neuropsychological and ADNI criteria. History of moderate/severe TBI predicted MCI by typical and ADNI criteria. CONCLUSIONS: MCI diagnosis using sensitive neuropsychological criteria is more strongly associated with AD biomarkers than conventional diagnostic methods. MCI diagnostics in Veterans would benefit from incorporation of comprehensive neuropsychological methods and consideration of the impact of PTSD.

Exploring Interactions Between Traumatic Brain Injury History and Gender on Medical Comorbidities in Military Veterans: An Epidemiological Analysis in the VA Million Veteran Program.

Epidemiological studies of medical comorbidities and possible gender differences associated with traumatic brain injury (TBI) are limited, especially among military veterans. The purpose of this study was to examine relationships between TBI history and a wide range of medical conditions in a large, national sample of veterans, and to explore interactions with gender. Participants of this cross-sectional epidemiological study included 491,604 veterans (9.9% TBI cases; 8.3% women) who enrolled in the VA Million Veteran Program (MVP). Outcomes of interest were medical comorbidities (i.e., neurological, mental health, circulatory, and other medical conditions) assessed using the MVP Baseline Survey, a self-report questionnaire. Logistic regression models adjusting for age and gender showed that veterans with TBI history consistently had significantly higher rates of medical comorbidities than controls, with the greatest differences observed across mental health (odds ratios [ORs] = 2.10-3.61) and neurological (ORs = 1.57-6.08) conditions. Similar patterns were found when evaluating men and women separately. Additionally, significant TBI-by-gender interactions were observed, particularly for mental health and neurological comorbidities, such that men with a history of TBI had greater odds of having several of these conditions than women with a history of TBI. These findings highlight the array of medical comorbidities experienced by veterans with a history of TBI, and illustrate that clinical outcomes differ for men and women with TBI history. Although these results are clinically informative, more research is needed to better understand the role of gender on health conditions in the context of TBI and how gender interacts with other social and cultural factors to influence clinical trajectories following TBI. Ultimately, understanding the biological, psychological, and social mechanisms underlying these comorbidities may help with tailoring TBI treatment by gender and improve quality of life for veterans with TBI history.

Subjective memory complaints are associated with decreased cortical thickness in Veterans with histories of mild traumatic brain injury.

Objective: Memory problems are frequently endorsed in Veterans following mild traumatic brain injury (mTBI), but subjective complaints are poorly associated with objective memory performance. Few studies have examined associations between subjective memory complaints and brain morphometry. We investigated whether self-reported memory problems were associated with objective memory performance and cortical thickness in Veterans with a history of mTBI. Methods: 40 Veterans with a history of remote mTBI and 29 Veterans with no history of TBI completed the Prospective-Retrospective Memory Questionnaire (PRMQ), PTSD Checklist (PCL), California Verbal Learning Test-2nd edition (CVLT-II), and 3 T T1 structural magnetic resonance imaging. Cortical thickness was estimated in 14 a priori frontal and temporal regions. Multiple regressions adjusting for age and PCL scores examined associations between PRMQ, CVLT-II scores, and cortical thickness within each Veteran group. Results: Greater subjective memory complaints on the PRMQ were associated with lower cortical thickness in the right middle temporal gyrus (ß = 0.64, q = .004), right inferior temporal gyrus (ß = 0.56, q = .014), right rostral middle frontal gyrus (ß = 0.45, q = .046), and right rostral anterior cingulate gyrus (ß = 0.58, q = .014) in the mTBI group but not the control group (q's > .05). These associations remained significant after adjusting for CVLT-II learning. CVLT-II performance was not associated with PRMQ score or cortical thickness in either group. Conclusions: Subjective memory complaints were associated with lower cortical thickness in right frontal and temporal regions, but not with objective memory performance, in Veterans with histories of mTBI. Subjective complaints post-mTBI may indicate underlying brain morphometry independently of objective cognitive testing.

Combining MRI and cognitive evaluation to classify concussion in university athletes.

Current methods of concussion assessment lack the objectivity and reliability to detect neurological injury. This multi-site study uses combinations of neuroimaging (diffusion tensor imaging and resting state functional MRI) and cognitive measures to train algorithms to detect the presence of concussion in university athletes. Athletes (29 concussed, 48 controls) completed symptom reports, brief cognitive evaluation, and MRI within 72 h of injury. Hierarchical linear regression compared groups on cognitive and neuroimaging measures while controlling for sex and data collection site. Logistic regression and support vector machine models were trained using cognitive and neuroimaging measures and evaluated for overall accuracy, sensitivity, and specificity. Concussed athletes reported greater symptoms than controls (∆R2 = 0.32, p < .001), and performed worse on tests of concentration (∆R2 = 0.07, p < .05) and delayed memory (∆R2 = 0.17, p < .001). Concussed athletes showed lower functional connectivity within the frontoparietal and primary visual networks (p < .05), but did not differ on mean diffusivity and fractional anisotropy. Of the cognitive measures, classifiers trained using delayed memory yielded the best performance with overall accuracy of 71%, though sensitivity was poor at 46%. Of the neuroimaging measures, classifiers trained using mean diffusivity yielded similar accuracy. Combining cognitive measures with mean diffusivity increased overall accuracy to 74% and sensitivity to 64%, comparable to the sensitivity of symptom report. Trained algorithms incorporating both MRI and cognitive performance variables can reliably detect common neurobiological sequelae of acute concussion. The integration of multi-modal data can serve as an objective, reliable tool in the assessment and diagnosis of concussion.

Corticospinal tract structure and excitability in patients with anterior cruciate ligament reconstruction: A DTI and TMS study.

BACKGROUND: Underlying neural factors contribute to poor outcomes following anterior cruciate ligament reconstruction (ACLR). Neurophysiological adaptations have been identified in corticospinal tract excitability, however limited evidence exists on neurostructural changes that may influence motor recovery in ACLR patients. OBJECTIVE: To 1) quantify hemispheric differences in structural properties of the corticospinal tract in patients with a history of ACLR, and 2) assess the relationship between excitability and corticospinal tract structure. METHODS: Ten participants with ACLR (age: 22.6 ± 1.9 yrs; height: 166.3 ± 7.5 cm; mass: 65.4 ± 12.6 kg, months from surgery: 70.0 ± 23.6) volunteered for this cross-sectional study. Corticospinal tract structure (volume; fractional anisotropy [FA]; axial diffusivity [AD]; radial diffusivity [RD]; mean diffusivity [MD]) was assessed using diffusion tensor imaging, and excitability was assessed using transcranial magnetic stimulation (motor evoked potentials normalized to maximal muscle response [MEP]) for each hemisphere. Hemispheric differences were evaluated using paired samples t-tests. Correlational analyses were conducted on structural and excitability outcomes. RESULTS: The hemisphere of the ACLR injured limb (i.e. hemisphere contralateral to the ACLR injured limb) demonstrated lower volume, lower FA, higher MD, and smaller MEPs compared to the hemisphere of the non-injured limb, indicating disrupted white matter structure and a reduction in excitability of the corticospinal tract. Greater corticospinal tract excitability was associated with larger corticospinal tract volume. CONCLUSIONS: ACLR patients demonstrated asymmetry in structural properties of the corticospinal tract that may influence the recovery of motor function following surgical reconstruction. More research is warranted to establish the influence of neurostructural measures on patient outcomes and response to treatment in ACLR populations.

Comparing tract-based spatial statistics and manual region-of-Interest labeling as diffusion analysis methods to detect white matter abnormalities in infants with hypoxic-Ischemic encephalopathy.

PURPOSE: To compare manual region of interest (ROI) labeling and tract-based spatial statistics (TBSS) by their ability to detect group-wise differences in fractional anisotropy (FA) in the neonatal brain. MATERIALS AND METHODS: Diffusion-weighted data were obtained for nine infants with hypoxic-ischemic encephalopathy (HIE) (six males, three females; gestational age [GA] range, 36-40 weeks; mean GA, 37.8 weeks) and 11 healthy-control infants (10 males, 1 female; GA range, 36-40 weeks; mean GA, 38.4 weeks) at 3T. For manual ROI labeling, ROIs were drawn freehand for each subject in eight, clinically relevant brain regions. For TBSS, all FA data underwent an optimized, automated protocol for neonates. Each method was evaluated for detection of decreased FA in HIE infants, sensitivity, specificity, and variability. RESULTS: FA values from manual ROI and TBSS were strongly correlated (r = 0.94, P < 0.0001). Both methods found decreased FA in most ROIs for HIE infants. There was no significant interaction between method and group, indicating a similar ability to detect FA differences (F(1,19) = 0.599, P = 0.449). Sensitivity (manual: 0.709, TBSS: 0.694, 95% CI [-0.136, 0.163], P = 0.856), specificity (manual and TBSS: 0.716, 95% CI [-0.133, 0.133], P = 1), and standard error (manual: 0.009, TBSS: 0.007) were comparable. CONCLUSION: Manual ROI labeling and TBSS are comparable methods of diffusion analysis to detect group differences in FA in the neonatal brain.