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 popular 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=0.006), 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: The inclusion of exposure variables adds to the predictive power of MRS. Classification-based MRS may be useful in predicting risk of future PTSD in populations with anticipated trauma exposure. As more data become available, including additional molecular, environmental, and psychosocial factors in these scores may enhance their accuracy in predicting PTSD and, relatedly, improve their performance in independent cohorts.

No Replication of Alzheimer's Disease Genetics as a Moderator of Combat Exposure's Association with PTSD risk in 138,592 Combat Veterans.

Large-scale cohort and epidemiological studies suggest that posttraumatic stress disorder (PTSD) confers risk for late-onset Alzheimer's disease (AD) and related dementias (ADRD); however, the basis for this association remains unclear. Several prior studies of military Veterans have reported that carriers of the apolipoprotein E (APOE) ε4 gene variant are at heightened risk for the development of PTSD following combat exposure, suggesting that PTSD and ADRD may share some genetic risk. This cohort study was designed to further examine the hypothesis that ADRD genetic risk also confers risk for PTSD. To do so, we examined APOE ε4 and ε2 genotypes, an AD polygenic risk score (PRS), and other Veteran-relevant risk factors for PTSD in age-stratified groups of individuals of European (n = 123,372) and African (n = 15,220) ancestry in the US Department of Veterans Affairs' Million Veteran Program. Analyses revealed no significant main effect associations between the APOE ε4 (or ε2) genotype or the AD PRS on PTSD severity or diagnosis. There were also no significant interactions between measures of AD genetic risk and either combat exposure severity or history of head injury in association with PTSD in any age group. We conclude that the association between PTSD and the primary ADRD genetic risk factor, APOE ε4, that was reported previously was not replicable in the largest relevant dataset in the world. Thus, the epidemiological association between PTSD and ADRD is not likely to be driven by the major genetic factors underlying ADRD risk.

Epigenetic Age Acceleration and Disparities in Posttraumatic Stress in Women in Southeast Louisiana: NIMHD Social Epigenomics Program.

Importance: Disasters experienced by an entire community provide opportunities to understand individual differences in risk for adverse health outcomes over time. DNA methylation (DNAm) differences may help to distinguish individuals at increased risk following large-scale disasters. Objective: To examine the association of epigenetic age acceleration with probable posttraumatic stress disorder (PTSD) and PTSD symptom severity in women. Design, Setting, and Participants: This prospective cohort study examined data from participants in the Women and Their Children's Health cohort, who were characterized longitudinally following the Deepwater Horizon oil spill (DHOS) in 2010 and through numerous hurricanes in the Gulf Coast region of the US. Wave 1 occurred August 6, 2012, through June 26, 2014, and wave 2 occurred September 2, 2014, through May 27, 2016. Data were analyzed between August 18 and November 4, 2023. Address-based sampling was used to recruit women aged 18 to 80 years and residing in 1 of the 7 Louisiana parishes surrounding the DHOS-affected region. Recruitment consisted of 2-stage sampling that (1) undersampled the 2 more urban parishes to maximize probability of participant oil exposure and (2) proportionally recruited participants across census tracts in the 5 other parishes closest to the spill. Exposure: Posttraumatic stress subsequent to the DHOS. Main Outcome and Measures: Epigenetic age acceleration was measured by DNAm assayed from survey wave 1 blood samples. Posttraumatic stress disorder was assessed using the PTSD Checklist for DSM-5 at survey wave 2, and lifetime trauma exposure was assessed using the Life Events Checklist for DSM-5. General linear models were used to examine the association between wave 1 DNAm age and wave 2 probable PTSD diagnosis and symptom severity. Results: A total of 864 women (mean [SD] age, 47.1 [12.0] years; 328 Black [38.0%], 19 American Indian [2.2%], 486 White [56.3%], and 30 of other racial groups, including uknown or unreported [3.5%]) were included. Black and American Indian participants had a higher age acceleration at wave 1 compared with White participants (ß = 1.64 [95% CI, 1.02-2.45] and 2.34 [95% CI, 0.33-4.34], respectively), and they had higher PTSD symptom severity at wave 2 (ß = 7.10 [95% CI, 4.62-9.58] and 13.08 [95% CI, 4.97-21.18], respectively). Epigenetic age acceleration at wave 1 was associated with PTSD symptom severity at wave 2 after adjusting for race, smoking, body mass index, and household income (ß = 0.38; 95% CI, 0.11-0.65). Conclusions and Relevance: In this cohort study, epigenetic age acceleration was higher in minoritized racial groups and associated with future PTSD diagnosis and severity. These findings support the need for psychoeducation about traumatic responses to increase the likelihood that treatment is sought before years of distress and entrenchment of symptoms and comorbidities occur.

Subjective cognitive concerns, APOE ε4, PTSD symptoms, and risk for dementia among older veterans.

BACKGROUND: Posttraumatic stress disorder (PTSD) and traumatic brain injury (TBI) are associated with self-reported problems with cognition as well as risk for Alzheimer's disease and related dementias (ADRD). Overlapping symptom profiles observed in cognitive disorders, psychiatric disorders, and environmental exposures (e.g., head injury) can complicate the detection of early signs of ADRD. The interplay between PTSD, head injury, subjective (self-reported) cognitive concerns and genetic risk for ADRD is also not well understood, particularly in diverse ancestry groups. METHODS: Using data from the U.S. Department of Veterans Affairs (VA) Million Veteran Program (MVP), we examined the relationship between dementia risk factors (APOE ε4, PTSD, TBI) and subjective cognitive concerns (SCC) measured in individuals of European (n = 140,921), African (n = 15,788), and Hispanic (n = 8,064) ancestry (EA, AA, and HA, respectively). We then used data from the VA electronic medical record to perform a retrospective survival analysis evaluating PTSD, TBI, APOE ε4, and SCC and their associations with risk of conversion to ADRD in Veterans aged 65 and older. RESULTS: PTSD symptoms (B = 0.50-0.52, p < 1E-250) and probable TBI (B = 0.05-0.19, p = 1.51E-07 - 0.002) were positively associated with SCC across all three ancestry groups. APOE ε4 was associated with greater SCC in EA Veterans aged 65 and older (B = 0.037, p = 1.88E-12). Results of Cox models indicated that PTSD symptoms (hazard ratio [HR] = 1.13-1.21), APOE ε4 (HR = 1.73-2.05) and SCC (HR = 1.18-1.37) were positively associated with risk for ADRD across all three ancestry groups. In the EA group, probable TBI also contributed to increased risk of ADRD (HR = 1.18). CONCLUSIONS: The findings underscore the value of SCC as an indicator of ADRD risk in Veterans 65 and older when considered in conjunction with other influential genetic, clinical, and demographic risk factors.

Systems biology dissection of PTSD and MDD across brain regions, cell types, and blood.

The molecular pathology of stress-related disorders remains elusive. Our brain multiregion, multiomic study of posttraumatic stress disorder (PTSD) and major depressive disorder (MDD) included the central nucleus of the amygdala, hippocampal dentate gyrus, and medial prefrontal cortex (mPFC). Genes and exons within the mPFC carried most disease signals replicated across two independent cohorts. Pathways pointed to immune function, neuronal and synaptic regulation, and stress hormones. Multiomic factor and gene network analyses provided the underlying genomic structure. Single nucleus RNA sequencing in dorsolateral PFC revealed dysregulated (stress-related) signals in neuronal and non-neuronal cell types. Analyses of brain-blood intersections in >50,000 UK Biobank participants were conducted along with fine-mapping of the results of PTSD and MDD genome-wide association studies to distinguish risk from disease processes. Our data suggest shared and distinct molecular pathology in both disorders and propose potential therapeutic targets and biomarkers.

Effects of genetically predicted posttraumatic stress disorder on autoimmune phenotypes.

Observational studies suggest that posttraumatic stress disorder (PTSD) increases risk for various autoimmune diseases. Insights into shared biology and causal relationships between these diseases may inform intervention approaches to PTSD and co-morbid autoimmune conditions. We investigated the shared genetic contributions and causal relationships between PTSD, 18 autoimmune diseases, and 3 immune/inflammatory biomarkers. Univariate MiXeR was used to contrast the genetic architectures of phenotypes. Genetic correlations were estimated using linkage disequilibrium score regression. Bi-directional, two-sample Mendelian randomization (MR) was performed using independent, genome-wide significant single nucleotide polymorphisms; inverse variance weighted and weighted median MR estimates were evaluated. Sensitivity analyses for uncorrelated (MR PRESSO) and correlated horizontal pleiotropy (CAUSE) were also performed. PTSD was considerably more polygenic (10,863 influential variants) than autoimmune diseases (median 255 influential variants). However, PTSD evidenced significant genetic correlation with nine autoimmune diseases and three inflammatory biomarkers. PTSD had putative causal effects on autoimmune thyroid disease (p = 0.00009) and C-reactive protein (CRP) (p = 4.3 × 10-7). Inferences were not substantially altered by sensitivity analyses. Additionally, the PTSD-autoimmune thyroid disease association remained significant in multivariable MR analysis adjusted for genetically predicted inflammatory biomarkers as potential mechanistic pathway variables. No autoimmune disease had a significant causal effect on PTSD (all p values > 0.05). Although causal effect models were supported for associations of PTSD with CRP, shared pleiotropy was adequate to explain a putative causal effect of CRP on PTSD (p = 0.18). In summary, our results suggest a significant genetic overlap between PTSD, autoimmune diseases, and biomarkers of inflammation. PTSD has a putative causal effect on autoimmune thyroid disease, consistent with existing epidemiologic evidence. A previously reported causal effect of CRP on PTSD is potentially confounded by shared genetics. Together, results highlight the nuanced links between PTSD, autoimmune disorders, and associated inflammatory signatures, and suggest the importance of targeting related pathways to protect against disease and disability.

An EWAS of dementia biomarkers and their associations with age, African ancestry, and PTSD.

BACKGROUND: Large-scale cohort and epidemiological studies suggest that PTSD confers risk for dementia in later life but the biological mechanisms underlying this association remain unknown. This study examined this question by assessing the influences of PTSD, APOE ε4 genotypes, DNA methylation, and other variables on the age- and dementia-associated biomarkers Aß40, Aß42, GFAP, NfL, and pTau-181 measured in plasma. Our primary hypothesis was that PTSD would be associated with elevated levels of these markers. METHODS: Analyses were based on data from a PTSD-enriched cohort of 849 individuals. We began by performing factor analyses of the biomarkers, the results of which identified a two-factor solution. Drawing from the ATN research framework, we termed the first factor, defined by Aß40 and Aß42, "Factor A" and the second factor, defined by GFAP, NfL and pTau-181, "Factor TN." Next, we performed epigenome-wide association analyses (EWAS) of the two-factor scores. Finally, using structural equation modeling (SEM), we evaluated (a) the influence of PTSD, age, APOE ε4 genotype and other covariates on levels of the ATN factors, and (b) tested the mediating influence of the EWAS-significant DNAm loci on these associations. RESULTS: The Factor A EWAS identified one significant locus, cg13053408, in FANCD2OS. The Factor TN analysis identified 3 EWAS-significant associations: cg26033520 near ASCC1, cg23156469 in FAM20B, and cg15356923 in FAM19A4. The SEM showed age to be related to both factors, more so with Factor TN (ß = 0.581, p < 0.001) than Factor A (ß = 0.330, p < 0.001). Genotype-determined African ancestry was associated with lower Factor A (ß = 0.196, p < 0.001). Contrary to our primary hypothesis, we found a modest negative bivariate correlation between PTSD and the TN factor scores (r = - 0.133, p < 0.001) attributable primarily to reduced levels of GFAP (r = - 0.128, p < 0.001). CONCLUSIONS: This study identified novel epigenetic associations with ATN biomarkers and demonstrated robust age and ancestral associations that will be essential to consider in future efforts to develop the clinical applications of these tests. The association between PTSD and reduced GFAP, which has been reported previously, warrants further investigation.

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.

Trauma exposure and transdiagnostic distress: Examining shared and posttraumatic stress disorder-specific associations.

We examined transdiagnostic and posttraumatic stress disorder (PTSD)-specific associations with multiple forms of trauma exposure within a nationwide U.S. sample (N = 1,649, 50.0% female) of military veterans overselected for PTSD. A higher-order Distress factor was estimated using PTSD, major depressive disorder (MDD), and generalized anxiety disorder (GAD) symptoms as indicators. A structural equation model spanning three assessment points over an average of 3.85 years was constructed to examine the unique roles of higher-order Distress and PTSD-specific variance in accounting for the associations between trauma exposure, measured using the Life Events Checklist (LEC) and Deployment Risk and Resiliency Inventory Combat subscale (DRRI-C), and psychosocial impairment. The results suggest the association between trauma exposure and PTSD symptoms was primarily mediated by higher-order distress (70.7% of LEC effect, 63.2% of DRRI-C effect), but PTSD severity retained a significant association with trauma exposure independent of distress, LEC: ß = .10, 95% CI [.06, .13]; DRRI-C: ß = .11, 95% CI [.07, .14]. Both higher-order distress, ß = .31, and PTSD-specific variance, ß = .36, were necessary to account for the association between trauma exposure and future impairment. Findings suggest that trauma exposure may contribute to comorbidity across a range of internalizing symptoms as well as to PTSD-specific presentations.

MMPI-2-RF Profiles of Treatment-Seeking Veterans in a VA Pain Clinic and Associations with Markers of Physical Performance.

Chronic pain is a debilitating condition for many military Veterans and is associated with posttraumatic stress disorder (PTSD). This study examined the Minnesota Multiphasic Personality Inventory-2-Restructured Form (MMPI-2-RF) in 144 Veterans (88.2% male, mean age = 57.95 years) recruited from a VA outpatient pain clinic and associations with self-reported pain severity, pain-related interference in daily activities, prescription opioid use, and objective metrics of physical performance on tasks impacted by pain (walking, stair climbing, grip strength, indexed by a single latent variable). Among the cohort with valid responses on the MMPI-2-RF (n = 117) and probable PTSD, mean Somatic Complaints (RC1) and Ideas of Persecution (RC6) scores were clinically elevated. All MMPI-2-RF scales were more strongly correlated with self-reported pain interference than severity. Regressions revealed associations between self-rated pain interference (but not pain or PTSD severity) and physical performance scores (ß = .36, p = .001). MMPI-2-RF overreporting Validity and Higher-Order scales contributed incremental variance in predicting physical performance, including Infrequent Psychopathology Responses (ß = .33, p = .002). PTSD severity was associated with prescription opioid use when accounting for the effects of over-reported somatic and cognitive symptoms (odds ratio 1.05, p ≤ .025). Results highlight the role of symptom overreporting and perceptions of functional impairment to observable behaviors among individuals with chronic pain.

Longitudinal study of traumatic-stress related cellular and cognitive aging.

Traumatic stress is associated with both accelerated epigenetic age and increased risk for dementia. Accelerated epigenetic age might link symptoms of traumatic stress to dementia-associated biomarkers, such as amyloid-beta (Aß) proteins, neurofilament light (NFL), and inflammatory molecules. We tested this hypothesis using longitudinal data obtained from 214 trauma-exposed military veterans (85 % male, mean age at baseline: 53 years, 75 % White) who were assessed twice over the course of an average of 5.6 years. Cross-lagged panel mediation models evaluated measures of lifetime posttraumatic stress disorder and internalizing and externalizing comorbidity (assessed at Time 1; T1) in association with T1 epigenetic age (per the GrimAge algorithm) and T1 plasma markers of neuropathology along with bidirectional temporal paths between T1 and T2 epigenetic age and the plasma markers. Results revealed that a measure of externalizing comorbidity was associated with accelerated epigenetic age (ß = 0.30, p <.01), which in turn, was associated with subsequent increases in Aß-40 (ß = 0.20, p <.001), Aß-42 (ß = 0.18, p <.001), and interleukin-6 (ß = 0.18, p <.01). T1 advanced epigenetic age and the T1 neuropathology biomarkers NFL and glial fibrillary acidic protein predicted worse performance on T2 neurocognitive tasks assessing working memory, executive/attentional control, and/or verbal memory (ps = 0.03 to 0.009). Results suggest that advanced GrimAge is predictive of subsequent increases in neuropathology and inflammatory biomarkers as well as worse cognitive function, highlighting the clinical significance of this biomarker with respect to cognitive aging and brain health over time. The finding that advanced GrimAge mediated the association between psychiatric comorbidity and future neuropathology is important for understanding potential pathways to neurodegeneration and early identification of those at greatest risk.

PTSD and Alcohol Use Disorders Predict the Pace of Cellular Aging.

Advanced epigenetic age is associated with psychopathology and may help to explain the link between psychopathology and physical health morbidity and mortality. Using a longitudinal sample of 171 trauma-exposed Veterans, we modeled the rate of change in epigenetic age across two time points (averaging 5.58 years apart) using two epigenetic age algorithms (GrimAge and Horvath) and tested associations with posttraumatic stress disorder (PTSD), alcohol use disorder (AUD), and depression. Results showed that PTSD (ß = .199) and AUD (ß = .186) were associated with a quickened pace of epigenetic aging over time (ps < .021). Results replicate and extend prior work and offer foundational support for identifying interventions that slow the pace of biological aging among those with psychopathology.

Single-Nucleus Transcriptome Profiling of Dorsolateral Prefrontal Cortex: Mechanistic Roles for Neuronal Gene Expression, Including the 17q21.31 Locus, in PTSD Stress Response.

OBJECTIVE: Multidisciplinary studies of posttraumatic stress disorder (PTSD) and major depressive disorder (MDD) implicate the dorsolateral prefrontal cortex (DLPFC) in disease risk and pathophysiology. Postmortem brain studies have relied on bulk-tissue RNA sequencing (RNA-seq), but single-cell RNA-seq is needed to dissect cell-type-specific mechanisms. The authors conducted the first single-nucleus RNA-seq postmortem brain study in PTSD to elucidate disease transcriptomic pathology with cell-type-specific resolution. METHOD: Profiling of 32 DLPFC samples from 11 individuals with PTSD, 10 with MDD, and 11 control subjects was conducted (∼415K nuclei; >13K cells per sample). A replication sample included 15 DLPFC samples (∼160K nuclei; >11K cells per sample). RESULTS: Differential gene expression analyses identified significant single-nucleus RNA-seq differentially expressed genes (snDEGs) in excitatory (EX) and inhibitory (IN) neurons and astrocytes, but not in other cell types or bulk tissue. MDD samples had more false discovery rate-corrected significant snDEGs, and PTSD samples had a greater replication rate. In EX and IN neurons, biological pathways that were differentially enriched in PTSD compared with MDD included glucocorticoid signaling. Furthermore, glucocorticoid signaling in induced pluripotent stem cell (iPSC)-derived cortical neurons demonstrated greater relevance in PTSD and opposite direction of regulation compared with MDD, especially in EX neurons. Many snDEGs were from the 17q21.31 locus and are particularly interesting given causal roles in disease pathogenesis and DLPFC-based neuroimaging (PTSD: ARL17B, LINC02210-CRHR1, and LRRC37A2; MDD: LRRC37A and LRP4), while others were regulated by glucocorticoids in iPSC-derived neurons (PTSD: SLC16A6, TAF1C; MDD: CDH3). CONCLUSIONS: The study findings point to cell-type-specific mechanisms of brain stress response in PTSD and MDD, highlighting the importance of examining cell-type-specific gene expression and indicating promising novel biomarkers and therapeutic targets.

Neurobiological and genetic correlates of the dissociative subtype of posttraumatic stress disorder.

Approximately 10%-30% of individuals with posttraumatic stress disorder (PTSD) exhibit a dissociative subtype of the condition defined by symptoms of depersonalization and derealization. This study examined the psychometric evidence for the dissociative subtype of PTSD in a sample of young, primarily male post-9/11-era Veterans (n = 374 at baseline and n = 163 at follow-up) and evaluated its biological correlates with respect to resting state functional connectivity (default mode network [DMN]; n = 275), brain morphology (hippocampal subfield volume and cortical thickness; n = 280), neurocognitive functioning (n = 337), and genetic variation (n = 193). Multivariate analyses of PTSD and dissociation items suggested a class structure was superior to dimensional and hybrid ones, with 7.5% of the sample comprising the dissociative class; this group showed stability over 1.5 years. Covarying for age, sex, and PTSD severity, linear regression models revealed that derealization/depersonalization severity was associated with: decreased DMN connectivity between bilateral posterior cingulate cortex and right isthmus (p = .015; adjusted-p [padj] = .097); increased bilateral whole hippocampal, hippocampal head, and molecular layer head volume (p = .010-.034; padj = .032-.053); worse self-monitoring (p = .018; padj = .079); and a candidate genetic variant (rs263232) in the adenylyl cyclase 8 gene (p = .026), previously associated with dissociation. Results converged on biological structures and systems implicated in sensory integration, the neural representation of spatial awareness, and stress-related spatial learning and memory, suggesting possible mechanisms underlying the dissociative subtype of PTSD. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

African ancestry GWAS of dementia in a large military cohort identifies significant risk loci.

While genome wide association studies (GWASs) of Alzheimer's Disease (AD) in European (EUR) ancestry cohorts have identified approximately 83 potentially independent AD risk loci, progress in non-European populations has lagged. In this study, data from the Million Veteran Program (MVP), a biobank which includes genetic data from more than 650,000 US Veteran participants, was used to examine dementia genetics in an African descent (AFR) cohort. A GWAS of Alzheimer's disease and related dementias (ADRD), an expanded AD phenotype including dementias such as vascular and non-specific dementia that included 4012 cases and 18,435 controls age 60+ in AFR MVP participants was performed. A proxy dementia GWAS based on survey-reported parental AD or dementia (n = 4385 maternal cases, 2256 paternal cases, and 45,970 controls) was also performed. These two GWASs were meta-analyzed, and then subsequently compared and meta-analyzed with the results from a previous AFR AD GWAS from the Alzheimer's Disease Genetics Consortium (ADGC). A meta-analysis of common variants across the MVP ADRD and proxy GWASs yielded GWAS significant associations in the region of APOE (p = 2.48 × 10-101), in ROBO1 (rs11919682, p = 1.63 × 10-8), and RNA RP11-340A13.2 (rs148433063, p = 8.56 × 10-9). The MVP/ADGC meta-analysis yielded additional significant SNPs near known AD risk genes TREM2 (rs73427293, p = 2.95 × 10-9), CD2AP (rs7738720, p = 1.14 × 10-9), and ABCA7 (rs73505251, p = 3.26 × 10-10), although the peak variants observed in these genes differed from those previously reported in EUR and AFR cohorts. Of the genes in or near suggestive or genome-wide significant associated variants, nine (CDA, SH2D5, DCBLD1, EML6, GOPC, ABCA7, ROS1, TMCO4, and TREM2) were differentially expressed in the brains of AD cases and controls. This represents the largest AFR GWAS of AD and dementia, finding non-APOE GWAS-significant common SNPs associated with dementia. Increasing representation of AFR participants is an important priority in genetic studies and may lead to increased insight into AD pathophysiology and reduce health disparities.

Alzheimer's disease and related dementias among aging veterans: Examining gene-by-environment interactions with post-traumatic stress disorder and traumatic brain injury.

INTRODUCTION: Post-traumatic stress disorder (PTSD) and traumatic brain injury (TBI) confer risk for Alzheimer's disease and related dementias (ADRD). METHODS: This study from the Million Veteran Program (MVP) evaluated the impact of apolipoprotein E (APOE) ε4, PTSD, and TBI on ADRD prevalence in veteran cohorts of European ancestry (EA; n = 11,112 ADRD cases, 170,361 controls) and African ancestry (AA; n = 1443 ADRD cases, 16,191 controls). Additive-scale interactions were estimated using the relative excess risk due to interaction (RERI) statistic. RESULTS: PTSD, TBI, and APOE ε4 showed strong main-effect associations with ADRD. RERI analysis revealed significant additive APOE ε4 interactions with PTSD and TBI in the EA cohort and TBI in the AA cohort. These additive interactions indicate that ADRD prevalence associated with PTSD and TBI increased with the number of inherited APOE ε4 alleles. DISCUSSION: PTSD and TBI history will be an important part of interpreting the results of ADRD genetic testing and doing accurate ADRD risk assessment.

PTSD, major depression, and advanced transcriptomic age in brain tissue.

BACKGROUND: Psychiatric disorders have been associated with advanced epigenetic age in DNA methylation, yet this relationship has not been studied in the brain transcriptome. We examined transcriptomic age using an RNA-based algorithm recently developed by Ren and Kuan ("RNAAgeCalc") and the associations between posttraumatic stress disorder (PTSD), major depressive disorder (MDD), and alcohol use disorder with age-adjusted RNA age ("RNA age residuals") in three brain regions: dorsolateral prefrontal cortex, ventromedial prefrontal cortex (vmPFC), and motor cortex. METHODS: RNA sequencing was used to measure gene expression in postmortem brain tissue from the VA National PTSD Brain Bank (n = 94; 59% male). RESULTS: Linear models revealed that diagnoses of PTSD and/or MDD were positively associated with RNA age residuals in vmPFC only (p-adj = 0.012). Three genes in the RNAAgeCalc algorithm (KCNJ16, HYAL2, and CEBPB) were also differentially expressed in association with PTSD/MDD in vmPFC (p-adj = 6.45E-05 to 0.02). Enrichment analysis revealed that inflammatory and immune-related pathways were overrepresented (p-adj < 0.05) among the 43 genes in RNAAgeCalc that were also at least nominally associated with PTSD/MDD in vmPFC relative to the 448 RNAAgeCalc genes. Endothelial and mural cells were negatively associated with RNA age residuals in vmPFC (both p-adj = 0.028) and with PTSD/MDD (both p-adj = 0.017). CONCLUSIONS: Results highlight the importance of inflammation and immune system dysregulation in the link between psychopathology and accelerated cellular aging and raise the possibility that blood-brain barrier degradation may play an important role in stress-related accelerated brain aging.

For whom the bell tolls: psychopathological and neurobiological correlates of a DNA methylation index of time-to-death.

Psychopathology is a risk factor for accelerated biological aging and early mortality. We examined associations between broad underlying dimensions of psychopathology (reflecting internalizing and externalizing psychiatric symptoms), PTSD, and age-adjusted GrimAge ("GrimAge residuals"), a DNA methylation biomarker of mortality risk relative to age. We also examined neurobiological correlates of GrimAge residuals, including neurocognitive functioning, blood-based biomarkers (of inflammation, neuropathology, metabolic disease), and cortical thickness. Data from two independent trauma-exposed military cohorts (n = 647 [62.9% male, Mage = 52], n = 434 [90% male, Mage = 32]) were evaluated using linear regression models to test associations between GrimAge residuals, psychopathology, and health correlates. Externalizing psychopathology significantly predicted GrimAge residuals in both cohorts (ps < 0.028). PTSD predicted GrimAge residuals in the younger (p = 0.001) but not the older cohort. GrimAge residuals were associated with several neurobiological variables available in the younger cohort, including cognitive disinhibition (padj = 0.021), poorer memory recall (padj = 0.023), cardiometabolic pathology (padj < 0.001), oxidative stress (padj = 0.003), astrocyte damage (padj = 0.021), inflammation (C-reactive protein: padj < 0.001; IL-6: padj < 0.001), and immune functioning (padj < 0.001). A subset of inflammatory and neuropathology analytes were available in the older cohort and showed associations with GrimAge residuals (IL-6: padj < 0.001; TNF-α: padj < 0.001). GrimAge residuals were also associated with reduced cortical thickness in right lateral orbitofrontal cortex (padj = 0.018) and left fusiform gyrus (padj = 0.030), which are related to emotion regulation and facial recognition, respectively. Psychopathology may be a common risk factor for elevated mortality risk. GrimAge could help identify those at risk for adverse health outcomes and allow for early disease identification and treatment.

Conceptualizing traumatic stress and the structure of posttraumatic psychopathology through the lenses of RDoC and HiTOP.

Trauma-related psychopathology, most notably posttraumatic stress disorder (PTSD), poses unique challenges for psychiatric nosology due to the wide range of symptoms and diagnoses associated with trauma and challenges representing the impact of trauma exposure on psychopathology. In this paper, we review the literature on categorical (i.e., Diagnostic and Statistical Manual of Mental Disorders and International Classification of Diseases systems) versus dimensional conceptualizations of trauma-related symptoms with an emphasis on the Research Domain Criteria (RDoC) and the Hierarchical Taxonomy of Psychopathology (HiTOP) frameworks. We identify strengths of each approach and challenges in accommodating the full range of trauma-related psychopathology and the clinical implications thereof. We discuss several potential approaches for improving the representation of traumatic stress, including the use of PTSD subtypes, trauma-related specifiers for psychiatric diagnoses, and the development of a dimension that we call the traumatic stress spectrum, which spans both adaptive and adverse reactions to trauma. These approaches to representing traumatic stress can be evaluated empirically and further refined. We also discuss how the use of an integrated RDoC-HiTOP approach to reconceptualize traumatic stress might maximize the ability to model valid and reliable trauma-related phenotypes, which would aid in the investigation of clinically relevant biological correlates.