Epigenetics influence and are influenced by the impact of social and environmental challenges on biological outcomes. Therefore, pinpointing epigenetic factors associated with social adversity and traumatic stress enables understanding of the mechanisms underlying vulnerability and resilience. We hypothesized that micro-RNAs (miRNAs) expression may be associated with post-traumatic stress disorder symptom severity (i.e., PTSS) following exposure to social adversity. To test this hypothesis, we leveraged blood-derived RNA samples (n=632) and social adversity data from 483 unique participants in the Detroit Neighborhood Health Study, a community-based, prospective cohort of predominantly African Americans. Results identified 86 miRNAs that are associated with social adversities (financial difficulties, perceived discrimination, cumulative trauma) and PTSS. These miRNAs are primarily involved in the immune response, brain and neural function, as well as cell cycle and differentiation, and 22(25%) have previously been associated with conditions related to PTSD, including traumatic brain injury and stress response. Our findings offer a fresh perspective on understanding the epigenetic role of miRNA in the interaction between social adversity and traumatic stress.

Post-traumatic stress disorder (PTSD) is associated with increased cardiovascular disease (CVD) risk, yet the epigenetic mechanisms underlying this link remain unclear. We investigated whether DNA methylation (DNAm) within Conserved Regions of Systemic Interindividual Variation (CoRSIVs), genomic regions showing stable within-individual, but variable between-individual methylation, mediates the association between PTSD symptom severity (PTSS) and CVD. We analyzed blood-derived DNAm from three cohorts (DNHS: discovery; GTP and NHS: replication), focusing on 7,694 CoRSIV CpGs profiled with the Illumina MethylationEPIC BeadChip. Logistic regression related CpGs to PTSS and CVD, adjusting for demographic and trauma-related covariates. CpGs nominally associated (p<0.05) with both PTSS and CVD in DNHS were then tested using causal mediation analysis. In DNHS, 27 CpGs were nominally associated with both PTSS and CVD, with seven showing nominal mediation (p<0.05). Across cohorts, six of these seven displayed mediation effects in a consistent direction in at least one replication cohort, and three CpGs showed concordant mediation directions across all three cohorts. Notably, cg07941916 (C5orf56/IRF1-AS1) and cg20545458 (intergenic) exhibited positive mediation in DNHS with the same direction in GTP, implying that higher PTSS is associated with methylation changes that correspond to higher CVD risk, whereas all mediation effects in NHS were negative, consistent with its healthier, lower-risk profile. These loci map to immune and inflammatory pathways, alongside other mediators annotated to neuronal/stress-aging and autonomic processes. Overall, DNAm variation within CoRSIVs may partially mediate PTSD-related CVD risk and nominates specific CpGs as hypothesis-generating epigenetic biomarkers that require validation in larger, ancestrally diverse longitudinal cohorts.

Urine contains extracellular RNA (exRNA) carried by extracellular vesicles (EVs) and other biomolecular complexes. There is currently a need for studies focused on female cohorts to develop new methods for non-invasive analysis of biofluids to create reference profiles and for identification of biomarkers of reproductive and pregnancy disorders. The objective of this study was therefore to identify optimal methods for transcriptomic profiling of urine by testing different exRNA isolation and scalable library preparation methods that enable detection of biomarkers that reflect pregnancy-associated changes in the placenta and maternal tissues. RNA was extracted from pooled and individual urine samples obtained from normal non-pregnant and pregnant females, as well as males, using input volumes of either 0.6 mL, 1 mL, or 4 mL. Samples were extracted using methods that focused either on isolating vesicular (EV-associated) or total (EV-associated and non EV-associated) exRNA. Small RNA libraries (n=208) were prepared using the NEBNext Small RNA Library Prep kit and long RNA libraries (n=97) were prepared using the SMART-Seq v4 Ultra Low Input RNA or the SMARTer Stranded Total RNA-Seq Kit v2 Pico Input kits (Takara). Principal component analysis showed that the greatest source of variance amongst technical replicates of small RNA libraries (n=176 which passed quality control) was exRNA isolation method, and amongst long RNA libraries (n=97 which passed quality control) was library preparation method. Long RNA libraries prepared from exRNA extracted using miRCURY showed that the SMART-Seq v4 method yielded significantly more uniquely mapped reads compared to the Pico v2 method (p<0.05). We have established a scalable pipeline for small and long RNA-Seq profiling of exRNA in urine in a reproducible manner, which we used to identify differentially expressed urinary exRNAs in pregnancy, and will enable transcriptomic profiling of urinary exRNA in disorders of pregnancy, including preeclampsia.

DNA methylation (DNAm) has been shown to mediate causal effects from traumatic experiences to post-traumatic stress disorder (PTSD). However, the scientific question about whether the mediation effect changes over time remains unclear. In this paper, we develop time-varying structural equation models to identify cytosine-phosphate-guanine (CpG) sites where DNAm mediates the effect of trauma exposure on PTSD, and to capture dynamic changes in mediation effects. The proposed methodology is motivated by the Detroit Neighborhood Health Study (DNHS) with high-dimensional and longitudinal DNAm measurements. To handle the non-monotone missing DNAm in the dataset, we propose a novel Longitudinal Multiple Imputation (LMI) method utilizing dependency among repeated measurements, and employ the generalized method of moments to integrate the multiple imputations. Simulations confirm that the proposed method outperforms existing approaches in various longitudinal settings. In DNHS data analysis, our method identifies several CpG sites where DNAm exhibits dynamic mediation effects. Some of the corresponding genes have been shown to be associated with PTSD in the existing literature, and our findings on their time-varying effects could deepen the understanding of the mediation role of DNAm on the causal path from trauma exposure to PTSD risk.

BACKGROUND:Epigenetic modifications, including DNA methylation (DNAm), can change in response to traumatic stress exposure, and may help to distinguish between individuals with and without PTSD. Here, we examine the DNAm patterns specific to immune cell types and inflammation in those with PTSD. METHODS:This study includes 3,277 participants from 11 cohorts participating in the Psychiatric Genomics Consortium (PGC) PTSD Epigenetics Workgroup. DNAm was assayed from blood with the MethylationEPIC BeadChip. A standardized QC pipeline was applied and used to impute cell composition. Within each cohort, we identified cell-type-specific DNAm patterns associated with PTSD, controlling for sex (if applicable), age, and ancestry. Meta-analyses were performed from summary statistics. RESULTS:PTSD cases had lower proportions of B cells and NK cells as well as higher proportions of neutrophils when compared to trauma-exposed controls. Overall, we identified 96 PTSD-associated CpGs across six types of immune cells. Most of these differences were identified in B cells, with 95 % exhibiting lower methylation levels in those with PTSD. Interestingly, the PTSD-associated CpGs annotated to a gene in B cells were enriched in a recent GWAS of PTSD (p < 0.0001). CONCLUSIONS:This study identifies novel PTSD-associated CpGs in individual immune cell types and supports the role of immune dysregulation and inflammation in PTSD.

The link between childhood adversity and adulthood depression is well-established; however, the underlying mechanisms are still being explored. Recent research suggests biological age may mediate the relationship between childhood adversity and depression in later life. This study examines if biological age mediates the relationship between childhood adversity and depression symptoms using an expanded set of biological age measures in an urban population-based cohort. Data from waves 1-3 of the Detroit Neighborhood Health Study (DNHS) were used in this analysis. Questions about abuse during childhood were coded to form a childhood adversity score similar to the Adverse Childhood Experience measure. Multiple dimensions of biological age, defined as latent variables, were considered, including systemic biological age (GrimAge, PhenoAge), epigenetic age (Horvath, SkinBlood), and immune age (cytomegalovirus, herpes simplex virus type 1, C-reactive protein, interleukin-6). Depression symptoms, modeled as a latent variable, were captured through the Patient Health Questionnaire-9 (PHQ-9). Models were adjusted for age, gender, race, parent education, and past depressive symptoms. Total and direct effects of childhood adversity on depression symptoms and indirect effects mediated by biological age were estimated. For total and direct effects, we observed a dose-dependent relationship between cumulative childhood adversity and depression symptoms, with emotional abuse being particularly influential. However, contrary to prior studies, in this sample, we found few direct effects of childhood adversity on biological age or biological age on depression symptoms and no evidence of mediation through the measures of biological age considered in this study. Further research is needed to understand how childhood maltreatment experiences are embodied to influence health and wellness.

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.

Abstract Background The occurrence of post-traumatic stress disorder (PTSD) following a traumatic event is associated with biological differences that can represent the susceptibility to PTSD, the impact of trauma, or the sequelae of PTSD itself. These effects include differences in DNA methylation (DNAm), an important form of epigenetic gene regulation, at multiple CpG loci across the genome. Moreover, these effects can be shared or specific to both central and peripheral tissues. Here, we aim to identify blood DNAm differences associated with PTSD and characterize the underlying biological mechanisms by examining the extent to which they mirror associations across multiple brain regions. Methods As the Psychiatric Genomics Consortium (PGC) PTSD Epigenetics Workgroup, we conducted the largest cross-sectional meta-analysis of epigenome-wide association studies (EWASs) of PTSD to date, involving 5077 participants (2156 PTSD cases and 2921 trauma-exposed controls) from 23 civilian and military studies. PTSD diagnosis assessments were harmonized following the standardized guidelines established by the PGC-PTSD Workgroup. DNAm was assayed from blood using Illumina HumanMethylation450 or MethylationEPIC (850 K) BeadChips. Within each cohort, DNA methylation was regressed on PTSD, sex (if applicable), age, blood cell proportions, and ancestry. An inverse variance-weighted meta-analysis was performed. We conducted replication analyses in tissue from multiple brain regions, neuronal nuclei, and a cellular model of prolonged stress. Results We identified 11 CpG sites associated with PTSD in the overall meta-analysis (1.44e − 09 < p < 5.30e − 08), as well as 14 associated in analyses of specific strata (military vs civilian cohort, sex, and ancestry), including CpGs in AHRR and CDC42BPB. Many of these loci exhibit blood–brain correlation in methylation levels and cross-tissue associations with PTSD in multiple brain regions. Out of 9 CpGs annotated to a gene expressed in blood, methylation levels at 5 CpGs showed significant correlations with the expression levels of their respective annotated genes. Conclusions This study identifies 11 PTSD-associated CpGs and leverages data from postmortem brain samples, GWAS, and genome-wide expression data to interpret the biology underlying these associations and prioritize genes whose regulation differs in those with PTSD.

Most genome-wide association studies (GWAS) of major depression (MD) have been conducted in samples of European ancestry. Here we report a multi-ancestry GWAS of MD, adding data from 21 cohorts with 88,316 MD cases and 902,757 controls to previously reported data. This analysis used a range of measures to define MD and included samples of African (36% of effective sample size), East Asian (26%) and South Asian (6%) ancestry and Hispanic/Latin American participants (32%). The multi-ancestry GWAS identified 53 significantly associated novel loci. For loci from GWAS in European ancestry samples, fewer than expected were transferable to other ancestry groups. Fine mapping benefited from additional sample diversity. A transcriptome-wide association study identified 205 significantly associated novel genes. These findings suggest that, for MD, increasing ancestral and global diversity in genetic studies may be particularly important to ensure discovery of core genes and inform about transferability of findings.

Observational studies have shown an association between post-traumatic stress disorder (PTSD) and ischemic stroke (IS) but given the susceptibility to confounding it is unclear if these associations represent causal effects. Mendelian randomization (MR) facilitates causal inference that is robust to the influence of confounding. Using two sample MR, we investigated the causal effect of genetic liability to PTSD on IS risk. Ancestry-specific genetic instruments of PTSD and four quantitative sub-phenotypes of PTSD, including hyperarousal, avoidance, re-experiencing, and total symptom severity score (PCL-Total) were obtained from the Million Veteran Programme (MVP) using a threshold P value ( P) of <5 × 10 −7 , clumping distance of 1000 kilobase (Mb) and r 2 < 0.01. Genetic association estimates for IS were obtained from the MEGASTROKE consortium ( N cases = 34,217, N controls = 406,111) for European ancestry individuals and from the Consortium of Minority Population Genome-Wide Association Studies of Stroke (COMPASS) ( N cases = 3734, N controls = 18,317) for African ancestry individuals. We used the inverse-variance weighted (IVW) approach as the main analysis and performed MR-Egger and the weighted median methods as pleiotropy-robust sensitivity analyses. In European ancestry individuals, we found evidence of an association between genetic liability to PTSD avoidance, and PCL-Total and increased IS risk (odds ratio (OR)1.04, 95% Confidence Interval (CI) 1.007–1.077, P = 0.017 for avoidance and (OR 1.02, 95% CI 1.010–1.040, P = 7.6 × 10 −4 for PCL total). In African ancestry individuals, we found evidence of an association between genetically liability to PCL-Total and reduced IS risk (OR 0.95 (95% CI 0.923–0.991, P = 0.01) and hyperarousal (OR 0.83 (95% CI 0.691–0.991, P = 0.039) but no association was observed for PTSD case-control, avoidance, or re-experiencing. Similar estimates were obtained with MR sensitivity analyses. Our findings suggest that specific sub-phenotypes of PTSD, such as hyperarousal, avoidance, PCL total, may have a causal effect on people of European and African ancestry’s risk of IS. This shows that the molecular mechanisms behind the relationship between IS and PTSD may be connected to symptoms of hyperarousal and avoidance. To clarify the precise biological mechanisms involved and how they may vary between populations, more research is required.

Introduction: The placenta mediates fetal growth by regulating gas and nutrient exchange between the mother and the fetus. The cell type in the placenta where this nutrient exchange occurs is called the syncytiotrophoblast, which is the barrier between the fetal and maternal blood. Residence at high-altitude is strongly associated with reduced 3rd trimester fetal growth and increased rates of complications such as preeclampsia. We asked whether altitude and/or ancestry-related placental gene expression contributes to differential fetal growth under high-altitude conditions, as native populations have greater fetal growth than migrants to high-altitude. Methods: We have previously shown that methylation differences largely accounted for altitude-associated differences in placental gene expression that favor improved fetal growth among high-altitude natives. We tested for differences in DNA methylation between Andean and European placental samples from Bolivia [La Paz (∼3,600 m) and Santa Cruz, Bolivia (∼400 m)]. One group of genes showing significant altitude-related differences are those involved in cell fusion and membrane repair in the syncytiotrophoblast. Dysferlin (DYSF) shows greater expression levels in high- vs. low-altitude placentas, regardless of ancestry. DYSF has a single nucleotide variant (rs10166384;G/A) located at a methylation site that can potentially stimulate or repress DYSF expression. Following up with individual DNA genotyping in an expanded sample size, we observed three classes of DNA methylation that corresponded to individual genotypes of rs10166384 (A/A < A/G < G/G). We tested whether these genotypes are under Darwinian selection pressure by sequencing a ∼2.5 kb fragment including the DYSF variants from 96 Bolivian samples and compared them to data from the 1000 genomes project. Results: We found that balancing selection (Tajima's D = 2.37) was acting on this fragment among Andeans regardless of altitude, and in Europeans at high-altitude (Tajima's D = 1.85). Discussion: This supports that balancing selection acting on dysferlin is capable of altering DNA methylation patterns based on environmental exposure to high-altitude hypoxia. This finding is analogous to balancing selection seen frequency-dependent selection, implying both alleles are advantageous in different ways depending on environmental circumstances. Preservation of the adenine (A) and guanine (G) alleles may therefore aid both Andeans and Europeans in an altitude dependent fashion.

Epigenetic factors, including DNA methylation (DNAm), participate in adaptation to traumatic stress, and may help to distinguish between individuals with and without PTSD. Here, we present the results of the largest epigenome-wide association study (EWAS) of PTSD to date.

BACKGROUND:Historical trauma experienced by Indigenous peoples of North America is correlated with health disparities and is hypothesized to be associated with DNA methylation. Massive group traumas such as genocide, loss of land and foodways, and forced conversion to Western lifeways may be embodied and affect individuals, families, communities, cultures, and health. This study approaches research with Alaska Native people using a community-engaged approach designed to create mutually-beneficial partnerships, including intentional relationship development, capacity building, and sample and data care.METHODS:A total of 117 Alaska Native individuals from two regions of Alaska joined the research study. Participants completed surveys on cultural identification, historical trauma (historical loss scale and historical loss associated symptoms scale), and general wellbeing. Participants provided a blood sample which was used to assess DNA methylation with the Illumina Infinium MethylationEPIC array.RESULTS:We report an association between historical loss associated symptoms and DNA methylation at five CpG sites, evidencing the embodiment of historical trauma. We further report an association between cultural identification and general wellbeing, complementing evidence from oral narratives and additional studies that multiple aspects of cultural connection may buffer the effects of and/or aid in the healing process from historical trauma.CONCLUSION:A community-engaged approach emphasizes balanced partnerships between communities and researchers. Here, this approach helps better understand embodiment of historical trauma in Alaska Native peoples. This analysis reveals links between the historical trauma response and DNA methylation. Indigenous communities have been stigmatized for public health issues instead caused by systemic inequalities, social disparities, and discrimination, and we argue that the social determinants of health model in Alaska Native peoples must include the vast impact of historical trauma and ongoing colonial violence.

Posttraumatic stress disorder (PTSD) is a common and debilitating psychiatric disorder that may occur in individuals exposed to traumatic events such as accidents, interpersonal violence, war, combat, or natural disasters. Additionally, PTSD has been implicated in the development of a variety of chronic conditions, including cardiovascular and metabolic diseases, suggesting the biological alterations associated with the disorder can manifest as chronic diseases in those suffering from PTSD. The biological underpinnings of the disorder are not well understood. Gene expression studies can illuminate the complex physiology of PTSD reflecting the embodiment of trauma, that is, the process in which traumatic experiences in our social environments could potentially manifest in our body by genomic mechanisms. To date, gene expression studies that examine the whole transcriptome are scarce and limited to single-time-point assessments. Here we applied a transcriptome-wide gene expression screen with RNA-seq to whole blood samples from predominantly African American community-dwelling participants to elucidate the gene expression signatures associated with the development of PTSD. The study participants (N = 72) comprised a trauma-exposed subsample of participants enrolled in a longitudinal, prospective cohort study of adults living in Detroit, Michigan. PTSD was assessed in a structured telephone interview, and whole blood samples were taken both before and after trauma exposure. Among the 72 study participants, 10 had PTSD at baseline and 21 developed it during the study. We found 45 differentially expressed genes associated with PTSD development with an estimated log2-fold change > 1.5 at a nominal p-value of

Since the first reported outbreak in China, the Coronavirus disease 2019 (COVID-19) has raised serious concerns globally. The COVID-19 pandemic has caused a severe psychological impact on healthcare workers (HCWs), and especially nurses, who are the most numerous and exposed frontline group. This systematic review and meta-analysis aims to summarise extant literature on the effects of the COVID-19 pandemic on the psychological health of nurses, particularly concerning the prevalence and risk factors for post-traumatic stress disorder (PTSD). A systematic search was conducted on PubMed , Embase and PsycInfo from March 2020 to July 2023. Articles were included/excluded on predetermined eligibility criteria. A random-effect meta-analysis was performed using proportions to determine the pooled prevalence for PTSD among nurses. Subgroup analyses were also performed, and heterogeneity across studies was analysed using meta-regression. Relatively high prevalence rates of PTSD were reported among nurse populations during the COVID-19 pandemic in twenty-six different countries, globally. Risk factors associated with PTSD include having prior mental health co-morbidities, being a female, having high exposure/contact with COVID-19 patients, having insufficient protective conditions and having intensive workloads. The overall pooled prevalence was 29.1% (95% C.I. = 23.5%, 35.5%) using a random-effects model in 55 studies. The regression test of funnel plot asymmetry indicated a significant level of publication bias among studies. The COVID-19 pandemic is associated with significant levels of PTSD among frontline nurses globally. A high level of heterogeneity was observed across studies. Psychological, social and administrative interventions should be implemented to mitigate heavy psychological distress in nurses.