Posttraumatic stress disorder symptom severity is associated with reduced Montreal Cognitive Assessment scores in a sample of Vietnam War Veterans.

The goal of the present study was to examine associations between posttraumatic stress disorder (PTSD) symptom severity, the number of stressors experienced, and cognitive outcomes in a sample of U.S. Vietnam War Veterans (N = 274). Adults between 60 and 85 years of age completed a Vietnam Veterans Alzheimer's Disease Neuroimaging Initiative Project visit. A modified version of the Life Stressor Checklist-Revised (LSC-R) was used to assess the number of stressful experiences participants experienced, current PTSD severity scores were measured via the Clinician-Administered PTSD Scale for DSM-IV (CAPS-IV), and cognition was assessed using the Montreal Cognitive Assessment (MoCA). Linear regressions were conducted to examine the effect of CAPS-IV and LSC-R scores on cognitive performance. Higher CAPS-IV scores were associated with worse cognitive outcomes on the MoCA, ΔF(1, 264) = 12.686, p < .001, R2 = .142. In contrast, the number of reported stressful experiences was not associated with cognitive outcomes. After accounting for multiple comparisons, findings indicated that CAPS-IV severity scores were significantly associated with the MoCA memory index. In a sample of older Veterans, PTSD symptom severity, but not the number of reported stressors, was associated with poorer performance on a well-established cognitive function screening tool. Analyses of specific MoCA domains indicated that memory may be driving this association. These findings suggest that highly arousing stressors characteristic of PTSD, rather than stressful experiences more broadly, contribute to this association. Future work can use these findings to explore whether treating PTSD symptoms may help maintain cognitive function during the aging process.

Higher Cerebrospinal Fluid Levels of Amyloid-ß40 Following Traumatic Brain Injury Relate to Confrontation Naming Performance.

Background: Traumatic brain injury (TBI) may confer risk for Alzheimer's disease (AD) through amyloid-ß (Aß) overproduction. However, the relationship between TBI and Aß levels in cerebrospinal fluid (CSF) remains unclear. Objective: To explore whether Aß overproduction is implicated in the relationship between TBI and AD, we compared CSF levels of Aß in individuals with a TBI history versus controls (CTRLs) and related CSF Aß levels to cognitive markers associated with preclinical AD. Methods: Participants were 112 non-impaired Veterans (TBI = 56, CTRL = 56) from the Alzheimer's Disease Neuroimaging Initiative-Department of Defense database with available cognitive data (Boston Naming Test [BNT], Rey Auditory Verbal Learning Test [AVLT]) and CSF measures of Aß42, Aß40, and Aß38. Mediation models explored relationships between TBI history and BNT scores with Aß peptides as mediators. Results: The TBI group had higher CSF Aß40 (t = -2.43, p = 0.017) and Aß38 (t = -2.10, p = 0.038) levels than the CTRL group, but groups did not differ in CSF Aß42 levels or Aß42/Aß40 ratios (p > 0.05). Both Aß peptides negatively correlated with BNT (Aß40: rho = -0.20, p = 0.032; Aß38: rho = -0.19, p = 0.048) but not AVLT (p > 0.05). Aß40 had a significant indirect effect on the relationship between TBI and BNT performance (ß= -0.16, 95% CI [-0.393, -0.004], PM = 0.54). Conclusions: TBI may increase AD risk and cognitive vulnerability through Aß overproduction. Biomarker models incorporating multiple Aß peptides may help identify AD risk among those with TBI.

Posttraumatic stress symptom severity predicts cognitive decline beyond the effect of Alzheimer's disease biomarkers in Veterans.

Chronic stress is a risk factor for dementia but whether it explains unique variance in cognitive decline in older adults above Alzheimer's disease (AD) biomarkers is unknown. In a preclinical cohort of Vietnam Veterans, we examined the relationship between posttraumatic stress disorder (PTSD) symptom severity, AD biomarkers of beta-amyloid (Aß) and tau, and change in cognitive performance on two widely-used screeners, the Mini-Mental State Examination (MMSE) and the Montreal Cognitive Assessment (MoCA). Analyses indicated that PTSD symptom severity was associated with a greater decline on the MMSE (p < 0.04) and MoCA (p < 0.024) after adjusting for biomarkers of AD, notably on the attention scale of the MoCA and the memory index of the MMSE. These analyses survived multiple comparison corrections. Taken together, PTSD symptom severity is associated with accelerated cognitive decline. Treating PTSD should be considered instrumental to maintaining cognitive function as adults age.

Age of First Concussion and Cognitive, Psychological, and Physical Outcomes in NCAA Collegiate Student Athletes.

OBJECTIVE: Concussions are common among youth athletes and could disrupt critical neurodevelopment. This study examined the association between age of first concussion (AFC) and neurocognitive performance, psychological distress, postural stability, and symptoms commonly associated with concussion in healthy collegiate men and women student athletes. METHODS: Participants included 4267 collegiate athletes from various contact, limited-contact, and non-contact sports (1818 women and 2449 men) who completed baseline assessments as part of the Concussion Assessment, Research and Education (CARE) Consortium. Psychological distress was assessed with the Brief Symptom Inventory 18; neurocognitive performance was assessed with the Immediate Post-Concussion Assessment and Cognitive Testing (ImPACT); symptoms commonly associated with concussion were assessed with the ImPACT Post-Concussion Symptom Scale; postural stability was assessed with the Balance Error Scoring System. Generalized linear models were used to examine the effects of AFC on clinical outcomes separately in men and women. RESULTS: Later AFC was associated with lower global (Exp(B) = 0.96, P = 0.001) and somatic (Exp(B) = 0.96, P = 0.002) psychological distress on the Brief Symptom Inventory 18 and faster ImPACT reaction time (B = - 0.003, P = 0.001) in women. AFC was not associated with any clinical outcomes in men. CONCLUSION: Younger AFC was associated with some differences in psychological distress and reaction time among women but not men; however, these results are likely not clinically meaningful. Sociodemographic disparities, pre-existing conditions, and sport type may impact clinical and cognitive outcomes in collegiate athletes more than concussion history. Future work should examine the relationship between AFC and lifespan-related outcomes.

Machine learning identifies novel markers predicting functional decline in older adults.

The ability to carry out instrumental activities of daily living, such as paying bills, remembering appointments and shopping alone decreases with age, yet there are remarkable individual differences in the rate of decline among older adults. Understanding variables associated with a decline in instrumental activities of daily living is critical to providing appropriate intervention to prolong independence. Prior research suggests that cognitive measures, neuroimaging and fluid-based biomarkers predict functional decline. However, a priori selection of variables can lead to the over-valuation of certain variables and exclusion of others that may be predictive. In this study, we used machine learning techniques to select a wide range of baseline variables that best predicted functional decline in two years in individuals from the Alzheimer's Disease Neuroimaging Initiative dataset. The sample included 398 individuals characterized as cognitively normal or mild cognitive impairment. Support vector machine classification algorithms were used to identify the most predictive modality from five different data modality types (demographics, structural MRI, fluorodeoxyglucose-PET, neurocognitive and genetic/fluid-based biomarkers). In addition, variable selection identified individual variables across all modalities that best predicted functional decline in a testing sample. Of the five modalities examined, neurocognitive measures demonstrated the best accuracy in predicting functional decline (accuracy = 74.2%; area under the curve = 0.77), followed by fluorodeoxyglucose-PET (accuracy = 70.8%; area under the curve = 0.66). The individual variables with the greatest discriminatory ability for predicting functional decline included partner report of language in the Everyday Cognition questionnaire, the ADAS13, and activity of the left angular gyrus using fluorodeoxyglucose-PET. These three variables collectively explained 32% of the total variance in functional decline. Taken together, the machine learning model identified novel biomarkers that may be involved in the processing, retrieval, and conceptual integration of semantic information and which predict functional decline two years after assessment. These findings may be used to explore the clinical utility of the Everyday Cognition as a non-invasive, cost and time effective tool to predict future functional decline.

Body Mass Index and Polygenic Risk for Alzheimer's Disease Predict Conversion to Alzheimer's Disease.

Body mass index (BMI) is a risk factor for Alzheimer's disease (AD) although the relationship is complex. Obesity in midlife is associated with increased risk for AD, whereas evidence supports both higher and lower BMI increasing risk for AD in late life. This study examined the influence of individual differences in genetic risk for AD to further clarify the relationship between late-life BMI and conversion to AD. Participants included 52 individuals diagnosed as having mild cognitive impairment (MCI) at baseline who converted to AD within 24 months and 52 matched MCI participants from the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort. BMI was measured at baseline. Genetic risk for AD was assessed via genome-wide polygenic risk scores. Conditional logistic regression models were run to determine if BMI and polygenic risk predicted conversion to AD. Results showed an interaction between BMI and genetic risk, such that individuals with lower BMI and higher polygenic risk were more likely to convert to AD relative to individuals with higher BMI. These results remained significant after adjusting for cerebrospinal fluid biomarkers of AD. Exploratory sex-stratified analyses revealed this relationship only remained significant in males. These results show that higher genetic risk in the context of lower BMI predicts conversion to AD in the next 24 months, particularly among males. These findings suggest that genetic risk for AD in the context of lower BMI may serve as a prodromal risk factor for future conversion to AD.

Genetic Risk for Alzheimer's Disease Moderates the Association Between Medial Temporal Lobe Volume and Episodic Memory Performance Among Older Adults.

BACKGROUND: A complex set of interactions between biological, genetic, and environmental factors likely underlies the development of Alzheimer's disease (AD). Identifying which of these factors is most associated with AD is important for early diagnosis and treatment. OBJECTIVE: We sought to examine genetic risk and structural brain volume on episodic memory in a sample of older adults ranging from cognitively normal to those diagnosed with AD. METHODS: 686 adults (55-91 years old) completed a 3T MRI scan, baseline cognitive assessments, and biospecimen collection through the Alzheimer's Disease Neuroimaging Initiative. Hierarchical linear regression analyses examined main and interaction effects of medial temporal lobe (MTL) volume and polygenic hazard score (PHS), indicating genetic risk for AD, on a validated episodic memory composite score. RESULTS: Genetic risk moderated the relationship between MTL volume and memory, such that individuals with high PHS and lower hippocampal and entorhinal volume had lower memory composite scores [ΔF (1,677) = 4.057, p = 0.044, ΔR2 = 0.002]. Further analyses showed this effect was driven by the left hippocampus [ΔF(1,677) = 5.256, p = 0.022, ΔR2 = 0.003] and right entorhinal cortex [ΔF (1,677) = 6.078, p = 0.014, ΔR2 = 0.003]. CONCLUSIONS: Among those with high genetic risk for AD, lower volume was associated with poorer memory. Results suggest that the interaction between AD genetic risk and MTL volume increases the likelihood for memory impairment among older adults. Results from this study suggest that genetic risk and brain volume should be considered key factors in tracking cognitive decline.

Body mass index is associated with smaller medial temporal lobe volume in those at risk for Alzheimer's disease.

Body mass index (BMI) has a complex relationship with Alzheimer's disease (AD); in midlife, high BMI is associated with increased risk for AD, whereas the relationship in late-life is still unclear. To clarify the relationship between late-life BMI and risk for AD, this study examined the extent to which genetic predisposition for AD moderates BMI and AD-related biomarker associations. Participants included 126 cognitively normal older adults at baseline from the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort. Genetic risk for AD was assessed via polygenic hazard score. AD-related biomarkers assessed were medial temporal lobe volume and cerebrospinal fluid (CSF) biomarkers. Hierarchical linear regressions were implemented to examine the effects of BMI and polygenic hazard score on AD-related biomarkers. Results showed that BMI moderated the relationship between genetic risk for AD and medial temporal lobe volume, such that individuals with high BMI and high genetic risk for AD showed lower volume in the entorhinal cortex and hippocampus. In sex-stratified analyses, these results remained significant only in females. Finally, BMI and genetic risk for AD were independently associated with CSF biomarkers of AD. These results provide evidence that high BMI is associated with lower volume in AD-vulnerable brain regions in individuals at genetic risk for AD, particularly females. The genetic pathways of AD may be exacerbated by high BMI. Environmental and genetic risk factors rarely occur in isolation, which underscores the importance of looking at their synergistic effects, as they provide insight into early risk factors for AD that prevention methods could target.