Blood-based DNA methylation and exposure risk scores predict PTSD with high accuracy in military and civilian cohorts.

Background: Incorporating genomic data into risk prediction has become an increasingly useful approach for rapid identification of individuals most at risk for complex disorders such as PTSD. Our goal was to develop and validate Methylation Risk Scores (MRS) using machine learning to distinguish individuals who have PTSD from those who do not. Methods: Elastic Net was used to develop three risk score models using a discovery dataset (n = 1226; 314 cases, 912 controls) comprised of 5 diverse cohorts with available blood-derived DNA methylation (DNAm) measured on the Illumina Epic BeadChip. The first risk score, exposure and methylation risk score (eMRS) used cumulative and childhood trauma exposure and DNAm variables; the second, methylation-only risk score (MoRS) was based solely on DNAm data; the third, methylation-only risk scores with adjusted exposure variables (MoRSAE) utilized DNAm data adjusted for the two exposure variables. The potential of these risk scores to predict future PTSD based on pre-deployment data was also assessed. External validation of risk scores was conducted in four independent cohorts. Results: The eMRS model showed the highest accuracy (92%), precision (91%), recall (87%), and f1-score (89%) in classifying PTSD using 3730 features. While still highly accurate, the MoRS (accuracy = 89%) using 3728 features and MoRSAE (accuracy = 84%) using 4150 features showed a decline in classification power. eMRS significantly predicted PTSD in one of the four independent cohorts, the BEAR cohort (beta = 0.6839, p-0.003), but not in the remaining three cohorts. Pre-deployment risk scores from all models (eMRS, beta = 1.92; MoRS, beta = 1.99 and MoRSAE, beta = 1.77) displayed a significant (p < 0.001) predictive power for post-deployment PTSD. Conclusion: Results, especially those from the eMRS, reinforce earlier findings that methylation and trauma are interconnected and can be leveraged to increase the correct classification of those with vs. without PTSD. Moreover, our models can potentially be a valuable tool in predicting the future risk of developing PTSD. As more data become available, including additional molecular, environmental, and psychosocial factors in these scores may enhance their accuracy in predicting the condition and, relatedly, improve their performance in independent cohorts.

Inflammatory biomarkers link perceived stress with metabolic dysregulation.

Objective: Perceived stress has been identified as a risk factor for metabolic syndrome. However, the intermediate pathways underlying this relationship are not well understood. Inflammatory responses may be one process by which stress leads to metabolic dysregulation. Prior work has shown that chronic stress is associated with elevated systemic inflammation and that altered inflammatory activity contributes to the pathogenesis of metabolic syndrome. The current analyses tested this hypothesis by examining inflammation as a pathway by which perceived stress affects metabolic health. Methods: Data from the Midlife in the United States Study (MIDUS) (N = 648; Mean age = 52.3) provided measures of perceived stress, inflammatory biomarkers [C-reactive protein (CRP), interleukin-6 (IL-6), E-selectin, fibrinogen, intracellular adhesion molecule-1 (ICAM-1)] and metabolic health markers. Confirmatory factor analysis (CFA) was used to confirm the fit of a hierarchical model of metabolic syndrome in our sample. Structural equation modeling (SEM) was used to test the assumption that inflammation mediates the association between perceived stress and the latent factor representing metabolic syndrome. Results: The CFA of metabolic syndrome demonstrated excellent goodness of fit to our sample [CFI = 0.97, TLI = 0.95, RMSEA = 0.06, SMSR = 0.05]. Mediation analysis with SEM revealed that the indirect pathway linking stress to metabolic dysregulation through inflammation was significant [B = 0.08, SE = 0.01, z = 3.69, p < .001, 95% confidence interval CI (0.04, 0.13)]. Conclusions: These results suggest that inflammatory biomarkers are a viable explanatory pathway for the relationship between perceived stress and metabolic health consequences. Interventions that target psychosocial stress may serve as cost-effective and accessible treatment options for mitigating inflammatory health risks.

Primary and Secondary Risk Factors Associated With Concussion Symptom Clusters in Collegiate Athletes: Results From the NCAA-DoD Grand Alliance CARE Consortium.

Background: There is a broad and diverse range of symptoms after a concussion, from irritability to nausea. This heterogeneity of symptoms is a challenge for clinicians managing the different presentations among injuries. Prior research has investigated the structure of postconcussive symptoms to determine if they can be grouped into clusters of related symptoms. Purpose/Hypothesis: The purpose of this study was to identify symptom clusters during the acute phase after a sports-related concussion using exploratory factor analysis and to understand the relationship between risk factors for postconcussion symptoms (ie, demographics, injury characteristics, mental health, and sleep qualities) and different symptom clusters. We hypothesized that certain factors would be predictive of specific symptom clusters. Study Design: Cross-sectional study; Level of evidence, 3. Methods: Collegiate athletes (N = 1104) from the Concussion, Assessment, Research, and Education (CARE) Consortium completed the Sport Concussion Assessment Tool-Third Edition symptom assessment tool 24 to 48 hours after concussion. Exploratory factor analysis was conducted on the symptom evaluation to determine symptom clusters 24 to 48 hours after concussion. Regression analysis was used to examine the effects of pre- and postinjury characteristics. Results: Exploratory factor analysis revealed a 4-cluster structure for acute postconcussive symptoms that explained 62% of the variance in symptom reporting: vestibular-cognitive, migrainous, cognitive fatigue, and affective. Delayed reporting, less sleep before assessment, female sex, and being hurt outside of competition (during practice/training) was correlated with increased symptoms for 4 symptom clusters. Depression predicted higher vestibular-cognitive and affective symptoms. Amnesia was correlated with higher vestibular-cognitive and migrainous symptoms, whereas migraine history was associated with more migrainous and affective symptoms. Conclusion: Symptoms can be grouped into 1 of 4 distinct clusters. Certain variables were associated with increased symptoms across multiple clusters and may be indicative of greater injury severity. Other factors (ie, migraine history, depression, amnesia) were associated with a more specific symptom presentation and may be mechanistically related to concussion outcomes and biological markers.

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.

Genetic Risk for Alzheimer Disease and Plasma Tau Are Associated With Accelerated Parietal Cortex Thickness Change in Middle-Aged Adults.

Background and Objectives: Neuroimaging and biomarker studies in Alzheimer disease (AD) have shown well-characterized patterns of cortical thinning and altered biomarker concentrations of tau and ß-amyloid (Aß). However, earlier identification of AD has great potential to advance clinical care and determine candidates for drug trials. The extent to which AD risk markers relate to cortical thinning patterns in midlife is unknown. The first objective of this study was to examine cortical thickness change associated with genetic risk for AD among middle-aged military veterans. The second objective was to determine the relationship between plasma tau and Aß and change in brain cortical thickness among veterans stratified by genetic risk for AD. Methods: Participants consisted of post-9/11 veterans (N = 155) who were consecutively enrolled in the Translational Research Center for TBI and Stress Disorders prospective longitudinal cohort and were assessed for mild traumatic brain injury (TBI) and posttraumatic disorder (PTSD). Genome-wide polygenic risk scores (PRSs) for AD were calculated using summary results from the International Genomics of Alzheimer's Disease Project. T-tau and Aß40 and Aß42 plasma assays were run using Simoa technology. Whole-brain MRI cortical thickness change estimates were obtained using the longitudinal stream of FreeSurfer. Follow-up moderation analyses examined the AD PRS × plasma interaction on change in cortical thickness in AD-vulnerable regions. Results: Higher AD PRS, signifying greater genetic risk for AD, was associated with accelerated cortical thickness change in a right hemisphere inferior parietal cortex cluster that included the supramarginal gyrus, angular gyrus, and intraparietal sulcus. Higher tau, but not Aß42/40 ratio, was associated with greater cortical thickness change among those with higher AD PRS. Mild TBI and PTSD were not associated with cortical thickness change. Discussion: Plasma tau, particularly when combined with genetic stratification for AD risk, can be a useful indicator of brain change in midlife. Accelerated inferior parietal cortex changes in midlife may be an important factor to consider as a marker of AD-related brain alterations.

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.

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.

Plasma biomarkers associated with deployment trauma and its consequences in post-9/11 era veterans: initial findings from the TRACTS longitudinal cohort.

Mild traumatic brain injury (mTBI) is among the most common injuries sustained by post-9/11 veterans; however, these injuries often occur within the context of psychological trauma. Blast exposure, even in the absence of a diagnosable TBI, leads to changes in neural connectivity and congitive functioning. Therefore, considering clinical comorbidities and injury characteristics is critical to understanding the long-term effects of mTBI. Research is moving towards identifying diagnostic and prognostic blood-based biomarkers for TBI; however, few studies include other prevalent clinical and medical comorbidities related to deployment. Here, we present the initial cross-sectional relationships between plasma biomarkers, clinical, and medical comorbidities in a well-characterized longitudinal sample of 550 post-9/11 veteran men and women. We examined biomarkers associated with inflammation (interleukin 6 and 10, tumor necrosis factor α, and eotaxin) and neurodegeneration (neurofilament light, glial fibrillary acidic protein (GFAP), tau, brain derived neurotrophic factor, amyloid ß 40 and 42, phosphorylated neurofilament heavy chain, and neuron specific enolase). Univariate analyses of covariance (ANCOVA) were conducted to determine mean level differences between close blast (blasts that occur within 0-10 meters) and mTBI groups. Our primary findings were twofold: (1) Inflammatory markers were consistently higher in participants exposed to close blasts and were strongly related to deployment-related psychopathology. (2) GFAP was consistently lower in participants exposed to blast and mTBI and lower GFAP was associated with more severe psychological symptoms. More research is clearly needed; however, our findings indicate that chronic increased inflammation and decreased GFAP may be related to close blast exposure.

Partial Least Squares Analysis of Alzheimer's Disease Biomarkers, Modifiable Health Variables, and Cognition in Older Adults with Mild Cognitive Impairment.

OBJECTIVES: To identify novel associations between modifiable physical and health variables, Alzheimer's disease (AD) biomarkers, and cognitive function in a cohort of older adults with Mild Cognitive Impairment (MCI). METHODS: Metrics of cardiometabolic risk, stress, inflammation, neurotrophic/growth factors, AD, and cognition were assessed in 154 MCI participants (Mean age = 74.1 years) from the Alzheimer's Disease Neuroimaging Initiative. Partial Least Squares analysis was employed to examine associations among these physiological variables and cognition. RESULTS: Latent variable 1 revealed a unique combination of AD biomarkers, neurotrophic/growth factors, education, and stress that were significantly associated with specific domains of cognitive function, including episodic memory, executive function, processing speed, and language, representing 45.2% of the cross-block covariance in the data. Age, body mass index, and metrics tapping basic attention or premorbid IQ were not significant. CONCLUSIONS: Our data-driven analysis highlights the significant relationships between metrics associated with AD pathology, neuroprotection, and neuroplasticity, primarily with tasks tapping episodic memory, executive function, processing speed, and verbal fluency rather than more basic tasks that do not require mental manipulation (basic attention and vocabulary). These data also indicate that biological metrics are more strongly associated with episodic memory, executive function, and processing speed than chronological age in older adults with MCI.

The association between blast exposure and transdiagnostic health symptoms on systemic inflammation.

Chronic elevation of systemic inflammation is observed in a wide range of disorders including PTSD, depression, and traumatic brain injury. Although previous work has demonstrated a link between inflammation and various diagnoses separately, few studies have examined transdiagnostic symptoms and inflammation within the same model. The objective of this study was to examine relationships between psychiatric and health variables and systemic inflammation and to determine whether mild traumatic brain injury (mTBI) and/or exposure to blast munitions moderate these relationships. Confirmatory factor analysis in a large sample (N = 357) of post-9/11 Veterans demonstrated a good fit to a four-factor model reflecting traumatic stress, affective, somatic, and metabolic latent variables. Hierarchical regression models revealed that each of the latent variables were associated with higher levels of systemic inflammation. However, the strongest relationship with inflammation emerged among those who had both war-zone blast exposures and metabolic dysregulation, even after adjusting for mental health latent variables. Exploratory analyses showed that blast exposure was associated with metabolic dysregulation in a dose-response manner, with self-reported closer blast proximity associated with the greatest metabolic dysregulation. Together, these results provide a greater understanding of the types of symptoms most strongly associated with inflammation and underscore the importance of maintaining a healthy lifestyle to reduce the impact of obesity and other metabolic symptoms on future chronic disease in younger to middle-aged Veterans.

Trauma and posttraumatic stress disorder modulate polygenic predictors of hippocampal and amygdala volume.

The volume of subcortical structures represents a reliable, quantitative, and objective phenotype that captures genetic effects, environmental effects such as trauma, and disease effects such as posttraumatic stress disorder (PTSD). Trauma and PTSD represent potent exposures that may interact with genetic markers to influence brain structure and function. Genetic variants, associated with subcortical volumes in two large normative discovery samples, were used to compute polygenic scores (PGS) for the volume of seven subcortical structures. These were applied to a target sample enriched for childhood trauma and PTSD. Subcortical volume PGS from the discovery sample were strongly associated in our trauma/PTSD enriched sample (n = 7580) with respective subcortical volumes of the hippocampus (p = 1.10 × 10-20), thalamus (p = 7.46 × 10-10), caudate (p = 1.97 × 10-18), putamen (p = 1.7 × 10-12), and nucleus accumbens (p = 1.99 × 10-7). We found a significant association between the hippocampal volume PGS and hippocampal volume in control subjects from our sample, but was absent in individuals with PTSD (GxE; (beta = -0.10, p = 0.027)). This significant GxE (PGS × PTSD) relationship persisted (p < 1 × 10-19) in four out of five threshold peaks (0.024, 0.133, 0.487, 0.730, and 0.889) used to calculate hippocampal volume PGSs. We detected similar GxE (G × ChildTrauma) relationships in the amygdala for exposure to childhood trauma (rs4702973; p = 2.16 × 10-7) or PTSD (rs10861272; p = 1.78 × 10-6) in the CHST11 gene. The hippocampus and amygdala are pivotal brain structures in mediating PTSD symptomatology. Trauma exposure and PTSD modulate the effect of polygenic markers on hippocampal volume (GxE) and the amygdala volume PGS is associated with PTSD risk, which supports the role of amygdala volume as a risk factor for PTSD.

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.

Coordinating Global Multi-Site Studies of Military-Relevant Traumatic Brain Injury: Opportunities, Challenges, and Harmonization Guidelines.

Traumatic brain injury (TBI) is common among military personnel and the civilian population and is often followed by a heterogeneous array of clinical, cognitive, behavioral, mood, and neuroimaging changes. Unlike many neurological disorders that have a characteristic abnormal central neurologic area(s) of abnormality pathognomonic to the disorder, a sufficient head impact may cause focal, multifocal, diffuse or combination of injury to the brain. This inconsistent presentation makes it difficult to establish or validate biological and imaging markers that could help improve diagnostic and prognostic accuracy in this patient population. The purpose of this manuscript is to describe both the challenges and opportunities when conducting military-relevant TBI research and introduce the Enhancing NeuroImaging Genetics through Meta-Analysis (ENIGMA) Military Brain Injury working group. ENIGMA is a worldwide consortium focused on improving replicability and analytical power through data sharing and collaboration. In this paper, we discuss challenges affecting efforts to aggregate data in this patient group. In addition, we highlight how "big data" approaches might be used to understand better the role that each of these variables might play in the imaging and functional phenotypes of TBI in Service member and Veteran populations, and how data may be used to examine important military specific issues such as return to duty, the late effects of combat-related injury, and alteration of the natural aging processes.

Altered white matter microstructural organization in posttraumatic stress disorder across 3047 adults: results from the PGC-ENIGMA PTSD consortium.

A growing number of studies have examined alterations in white matter organization in people with posttraumatic stress disorder (PTSD) using diffusion MRI (dMRI), but the results have been mixed which may be partially due to relatively small sample sizes among studies. Altered structural connectivity may be both a neurobiological vulnerability for, and a result of, PTSD. In an effort to find reliable effects, we present a multi-cohort analysis of dMRI metrics across 3047 individuals from 28 cohorts currently participating in the PGC-ENIGMA PTSD working group (a joint partnership between the Psychiatric Genomics Consortium and the Enhancing NeuroImaging Genetics through Meta-Analysis consortium). Comparing regional white matter metrics across the full brain in 1426 individuals with PTSD and 1621 controls (2174 males/873 females) between ages 18-83, 92% of whom were trauma-exposed, we report associations between PTSD and disrupted white matter organization measured by lower fractional anisotropy (FA) in the tapetum region of the corpus callosum (Cohen's d = -0.11, p = 0.0055). The tapetum connects the left and right hippocampus, for which structure and function have been consistently implicated in PTSD. Results were consistent even after accounting for the effects of multiple potentially confounding variables: childhood trauma exposure, comorbid depression, history of traumatic brain injury, current alcohol abuse or dependence, and current use of psychotropic medications. Our results show that PTSD may be associated with alterations in the broader hippocampal network.

The ENIGMA sports injury working group:- an international collaboration to further our understanding of sport-related brain injury.

Sport-related brain injury is very common, and the potential long-term effects include a wide range of neurological and psychiatric symptoms, and potentially neurodegeneration. Around the globe, researchers are conducting neuroimaging studies on primarily homogenous samples of athletes. However, neuroimaging studies are expensive and time consuming, and thus current findings from studies of sport-related brain injury are often limited by small sample sizes. Further, current studies apply a variety of neuroimaging techniques and analysis tools which limit comparability among studies. The ENIGMA Sports Injury working group aims to provide a platform for data sharing and collaborative data analysis thereby leveraging existing data and expertise. By harmonizing data from a large number of studies from around the globe, we will work towards reproducibility of previously published findings and towards addressing important research questions with regard to diagnosis, prognosis, and efficacy of treatment for sport-related brain injury. Moreover, the ENIGMA Sports Injury working group is committed to providing recommendations for future prospective data acquisition to enhance data quality and scientific rigor.

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.

An epigenome-wide association study of posttraumatic stress disorder in US veterans implicates several new DNA methylation loci.

BACKGROUND: Previous studies using candidate gene and genome-wide approaches have identified epigenetic changes in DNA methylation (DNAm) associated with posttraumatic stress disorder (PTSD). METHODS: In this study, we performed an EWAS of PTSD in a cohort of Veterans (n = 378 lifetime PTSD cases and 135 controls) from the Translational Research Center for TBI and Stress Disorders (TRACTS) cohort assessed using the Illumina EPIC Methylation BeadChip which assesses DNAm at more than 850,000 sites throughout the genome. Our model included covariates for ancestry, cell heterogeneity, sex, age, and a smoking score based on DNAm at 39 smoking-associated CpGs. We also examined in EPIC-based DNAm data generated from pre-frontal cortex (PFC) tissue from the National PTSD Brain Bank (n = 72). RESULTS: The analysis of blood samples yielded one genome-wide significant association with PTSD at cg19534438 in the gene G0S2 (p = 1.19 × 10-7, padj = 0.048). This association was replicated in an independent PGC-PTSD-EWAS consortium meta-analysis of military cohorts (p = 0.0024). We also observed association with the smoking-related locus cg05575921 in AHRR despite inclusion of a methylation-based smoking score covariate (p = 9.16 × 10-6), which replicates a previously observed PGC-PTSD-EWAS association (Smith et al. 2019), and yields evidence consistent with a smoking-independent effect. The top 100 EWAS loci were then examined in the PFC data. One of the blood-based PTSD loci, cg04130728 in CHST11, which was in the top 10 loci in blood, but which was not genome-wide significant, was significantly associated with PTSD in brain tissue (in blood p = 1.19 × 10-5, padj = 0.60, in brain, p = 0.00032 with the same direction of effect). Gene set enrichment analysis of the top 500 EWAS loci yielded several significant overlapping GO terms involved in pathogen response, including "Response to lipopolysaccharide" (p = 6.97 × 10-6, padj = 0.042). CONCLUSIONS: The cross replication observed in independent cohorts is evidence that DNA methylation in peripheral tissue can yield consistent and replicable PTSD associations, and our results also suggest that that some PTSD associations observed in peripheral tissue may mirror associations in the brain.

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.

Identifying Suicide Typologies Among Trauma-Exposed Veterans.

Background: Suicide among veterans has increased in recent years, making the identification of those at greatest risk for self-injurious behavior a high research priority. Aims: We investigated whether affective impulsivity and risky behaviors distinguished typologies of self-injurious thoughts and behaviors in a sample of trauma-exposed veterans. Method: A total of 95 trauma-exposed veterans (ages 21-55; 87% men) completed self-report measures of self-injurious thoughts and behaviors, impulsivity, and clinical symptoms. Results: A latent profile analysis produced three classes that differed in suicidal ideation, suicide attempts and nonsuicidal self-injury (NSSI): A low class that reported little to no self-injurious thoughts or behaviors; a self-injurious thoughts (ST) class that endorsed high levels of ideation but no self-harm behaviors; and a self-injurious thoughts and behaviors (STaB) class that reported ideation, suicide attempts and NSSI. Membership in the STaB class was associated with greater affective impulsivity, disinhibition, and distress/arousal than the other two classes. Limitations: Limitations include an overrepresentation of males in our sample, the cross-sectional nature of the data, and reliance on self-report measures. Conclusion: Findings point to affective impulsivity and risky behaviors as important characteristics of veterans who engage in self-injurious behaviors.