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.

Multi-ancestry genome-wide association study of major depression aids locus discovery, fine mapping, gene prioritization and causal inference.

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.

Does biological age mediate the relationship between childhood adversity and depression? Insights from the Detroit Neighborhood Health Study.

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.

The prevalence and risk factors of PTSD symptoms among nurses during the COVID-19 pandemic-A systematic review and meta-analysis.

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.

Association between gene methylation and experiences of historical trauma in Alaska Native peoples.

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.

A Mendelian randomization study of genetic liability to post-traumatic stress disorder and risk of ischemic stroke.

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 r2 < 0.01. Genetic association estimates for IS were obtained from the MEGASTROKE consortium (Ncases = 34,217, Ncontrols = 406,111) for European ancestry individuals and from the Consortium of Minority Population Genome-Wide Association Studies of Stroke (COMPASS) (Ncases = 3734, Ncontrols = 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.

Ancestry dependent balancing selection of placental dysferlin at high-altitude.

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.

Differentially Expressed Heterogeneous Overdispersion Genes Testing for Count Data.

The mRNA-seq data analysis is a powerful technology for inferring information from biological systems of interest. Specifically, the sequenced RNA fragments are aligned with genomic reference sequences, and we count the number of sequence fragments corresponding to each gene for each condition. A gene is identified as differentially expressed (DE) if the difference in its count numbers between conditions is statistically significant. Several statistical analysis methods have been developed to detect DE genes based on RNA-seq data. However, the existing methods could suffer decreasing power to identify DE genes arising from overdispersion and limited sample size. We propose a new differential expression analysis procedure: heterogeneous overdispersion genes testing (DEHOGT) based on heterogeneous overdispersion modeling and a post-hoc inference procedure. DEHOGT integrates sample information from all conditions and provides a more flexible and adaptive overdispersion modeling for the RNA-seq read count. DEHOGT adopts a gene-wise estimation scheme to enhance the detection power of differentially expressed genes. DEHOGT is tested on the synthetic RNA-seq read count data and outperforms two popular existing methods, DESeq and EdgeR, in detecting DE genes. We apply the proposed method to a test dataset using RNAseq data from microglial cells. DEHOGT tends to detect more differently expressed genes potentially related to microglial cells under different stress hormones treatments.

Serum lead, mercury, manganese, and copper and DNA methylation age among adults in Detroit, Michigan.

Although the effects of lead, mercury, manganese, and copper on individual disease processes are well understood, estimating the health effects of long-term exposure to these metals at the low concentrations often observed in the general population is difficult. In addition, the health effects of joint exposure to multiple metals are difficult to estimate. Biological aging refers to the integrative progression of multiple physiologic and molecular changes that make individuals more at risk of disease. Biomarkers of biological aging may be useful to estimate the population-level effects of metal exposure prior to the development of disease in the population. We used data from 290 participants in the Detroit Neighborhood Health Study to estimate the effect of serum lead, mercury, manganese, and copper on three DNA methylation-based biomarkers of biological aging (Horvath Age, PhenoAge, and GrimAge). We used mixed models and Bayesian kernel machine regression and controlled for participant sex, race, ethnicity, cigarette use, income, educational attainment, and block group poverty. We observed consistently positive estimates of the effects between lead and GrimAge acceleration and mercury and PhenoAge acceleration. In contrast, we observed consistently negative associations between manganese and PhenoAge acceleration and mercury and Horvath Age acceleration. We also observed curvilinear relationships between copper and both PhenoAge and GrimAge acceleration. Increasing total exposure to the observed mixture of metals was associated with increased PhenoAge and GrimAge acceleration and decreased Horvath Age acceleration. These findings indicate that an increase in serum lead or mercury from the 25th to 75th percentile is associated with a ∼0.25-year increase in two epigenetic markers of all-cause mortality in a population of adults in Detroit, Michigan. While few of the findings were statistically significant, their consistency and novelty warrant interest.

Community engagement in epigenomic and neurocognitive research on post-traumatic stress disorder in Rwandans exposed to the 1994 genocide against the Tutsi: lessons learned.

Epigenomic and neurocognitive studies have provided new perspectives on post-traumatic stress disorder and its intergenerational transmission. This article outlines the lessons learned from community engagement (CE) in such research on Rwandan genocide survivors. A strong trauma-related response was observed within the research project-targeted community (genocide survivors) during explanation of the project. CE also revealed privacy concerns, as community members worried that any leakage of genetic/(epi)genomic data could affect not only themselves but also their close relatives. Adopting a culture of CE in the process of research implementation enables the prioritization of targeted community needs and interests. Furthermore, CE has stimulated the development of mental healthcare interventions, which married couples can apply to protect their offspring and thus truly break the cycle of inherited vulnerability.

Studies of how human genes are affected by the environment (epigenomic studies) have provided new perspectives on post-traumatic stress disorder and its intergenerational transmission. This article describes the lessons learned from community engagement (CE) in this type of research in a Rwandan genocide-exposed population. A strong trauma-related response was observed within the community while explaining the project. CE also revealed the participants' privacy concerns related to leakage of genetic/(epi)genomic data that could also affect their close relatives. Adopting a culture of CE in the process of research implementation enables the prioritization of community needs and interests. CE has furthermore stimulated the development of preventive interventions for married couples to protect their offspring and thus truly break the cycle of inherited vulnerability.

DNA methylation of Nuclear Factor of Activated T Cells 1 mediates the prospective relation between exposure to different traumatic event types and post-traumatic stress disorder.

The mechanisms through which exposure to differing trauma types become biologically embedded to shape the risk for post-traumatic stress disorder (PTSD) is unclear. DNA methylation (5-mC), particularly in stress-relevant genes, may play a role in this relationship. Here, we conducted path analysis using generalized structural equation modeling to investigate whether blood-derived 5-mC in Nuclear Factor of Activated T Cells 1 (NFATC1) mediates the prospective association between each of five different trauma types ("assaultive violence", "other injury or shocking experience", "learning of trauma to loved one", "sudden, unexpected death of a close friend or relative", and "other") and lifetime PTSD. All five trauma types were significantly associated with reduced methylation at NFATC1 CpG site, cg17057218. Two of the five trauma types were significantly associated with increased methylation at NFATC1 CpG site, cg22324981. Moreover, methylation at cg17057218 significantly mediated 21-32% of the total effect for four of the five trauma types, while methylation at cg22324981 mediated 27-40% of the total effect for two of the five trauma types. These CpG sites were differentially associated with transcription factor binding sites and chromatin state signatures. NFATC1 5-mC may be a potential mechanism in the relationship between some trauma types and prospective risk for PTSD.

Leukocyte methylomic imprints of exposure to the genocide against the Tutsi in Rwanda: a pilot epigenome-wide analysis.

Aim & methods: We conducted a pilot epigenome-wide association study of women from Tutsi ethnicity exposed to the genocide while pregnant and their resulting offspring, and a comparison group of women who were pregnant at the time of the genocide but living outside of Rwanda.Results: Fifty-nine leukocyte-derived DNA samples survived quality control: 33 mothers (20 exposed, 13 unexposed) and 26 offspring (16 exposed, 10 unexposed). Twenty-four significant differentially methylated regions (DMRs) were identified in mothers and 16 in children. Conclusions:In utero genocide exposure was associated with CpGs in three of the 24 DMRs: BCOR, PRDM8 and VWDE, with higher DNA methylation in exposed versus unexposed offspring. Of note, BCOR and VWDE show significant correlation between brain and blood DNA methylation within individuals, suggesting these peripherally derived signals of genocide exposure may have relevance to the brain.

Lay abstract The 1994 Rwandan genocide against ethnic Tutsi has been associated with adverse mental health outcomes in survivors decades later, but the molecular mechanisms that contribute to this association remain poorly characterized. Epigenetic mechanisms such as DNA methylation regulate gene function and change in response to life experiences. We identified differentially methylated regions (DMRs) in genocide-exposed versus unexposed mothers and children. In utero genocide exposure was linked with methylation differences in three maternal DMRs, with higher methylation in exposed offspring. Two of three DMRs show correlation between brain and blood methylation within individuals, suggesting that peripherally derived signals of genocide exposure may be relevant to the brain.

Heterogeneous Mediation Analysis on Epigenomic PTSD and Traumatic Stress in a Predominantly African American Cohort.

DNA methylation (DNAm) has been suggested to play a critical role in post-traumatic stress disorder (PTSD), through mediating the relationship between trauma and PTSD. However, this underlying mechanism of PTSD for African Americans still remains unknown. To fill this gap, in this article, we investigate how DNAm mediates the effects of traumatic experiences on PTSD symptoms in the Detroit Neighborhood Health Study (DNHS) (2008-2013) which involves primarily African Americans adults. To achieve this, we develop a new mediation analysis approach for high-dimensional potential DNAm mediators. A key novelty of our method is that we consider heterogeneity in mediation effects across subpopulations. Specifically, mediators in different subpopulations could have opposite effects on the outcome, and thus could be difficult to identify under a traditional homogeneous model framework. In contrast, the proposed method can estimate heterogeneous mediation effects and identifies subpopulations in which individuals share similar effects. Simulation studies demonstrate that the proposed method outperforms existing methods for both homogeneous and heterogeneous data. We also present our mediation analysis results of a dataset with 125 participants and more than 450,000 CpG sites from the DNHS study. The proposed method finds three subgroups of subjects and identifies DNAm mediators corresponding to genes such as HSP90AA1 and NFATC1 which have been linked to PTSD symptoms in literature. Our finding could be useful in future finer-grained investigation of PTSD mechanism and in the development of new treatments for PTSD.

Psychosocial experiences modulate asthma-associated genes through gene-environment interactions.

Social interactions and the overall psychosocial environment have a demonstrated impact on health, particularly for people living in disadvantaged urban areas. Here, we investigated the effect of psychosocial experiences on gene expression in peripheral blood immune cells of children with asthma in Metro Detroit. Using RNA-sequencing and a new machine learning approach, we identified transcriptional signatures of 19 variables including psychosocial factors, blood cell composition, and asthma symptoms. Importantly, we found 169 genes associated with asthma or allergic disease that are regulated by psychosocial factors and 344 significant gene-environment interactions for gene expression levels. These results demonstrate that immune gene expression mediates the link between negative psychosocial experiences and asthma risk.

Socioeconomic status, financial stress, and glucocorticoid resistance among youth with asthma: Testing the moderation effects of maternal involvement and warmth.

OBJECTIVES: Children who grow up in more socioeconomically disadvantaged homes experience greater levels of inflammation and worse asthma symptoms than children from more advantaged families. However, recent evidence suggests that certain family-level factors can mitigate health disparities associated with socioeconomic status (SES). In a sample of youth with asthma, we investigated the potential buffering effects of maternal involvement and warmth on SES disparities in asthma-related immune responses, assessed via glucocorticoid resistance (GR) of immune cells. METHODS: One hundred and forty-three youth (10-16 years of age) with asthma completed measures of maternal involvement and warmth, and their primary caregivers reported their levels of education, income, and financial stress. Peripheral blood mononuclear cells from youth's blood were isolated, cultured, and assayed to determine mitogen-stimulated (PMA/INO + Etho) and mitogen/hydrocortisone-stimulated (PMA/INO + Cort) levels of two Th-2 cytokines (i.e., interleukin-5, interleukin-13) and one Th-1 cytokine (i.e., interferon-γ). GR was calculated by subtracting log-transformed cytokine concentration in the PMA/INO + Etho samples from log-transformed cytokine concentration in the PMA/INO + Cort samples. RESULTS: Both maternal involvement and warmth moderated the indirect pathway from family SES to GR of Th-2 cytokines via financial stress. Specifically, we found that low family SES was associated with elevated GR of Th-2 cytokines via increased financial stress among youth reporting low levels of maternal involvement and warmth, but not among those reporting high levels of maternal involvement or warmth. CONCLUSIONS: These results highlight the protective role of maternal involvement and warmth in health-related biological processes modulated by family SES among youth with asthma.

Neighborhood environment, social cohesion, and epigenetic aging.

Living in adverse neighborhood environments has been linked to risk of aging-related diseases and mortality; however, the biological mechanisms explaining this observation remain poorly understood. DNA methylation (DNAm), a proposed mechanism and biomarker of biological aging responsive to environmental stressors, offers promising insight into potential molecular pathways. We examined associations between three neighborhood social environment measures (poverty, quality, and social cohesion) and three epigenetic clocks (Horvath, Hannum, and PhenoAge) using data from the Detroit Neighborhood Health Study (n=158). Using linear regression models, we evaluated associations in the total sample and stratified by sex and social cohesion. Neighborhood quality was associated with accelerated DNAm aging for Horvath age acceleration (ß = 1.8; 95% CI: 0.4, 3.1), Hannum age acceleration (ß = 1.7; 95% CI: 0.4, 3.0), and PhenoAge acceleration (ß = 2.1; 95% CI: 0.4, 3.8). In models stratified on social cohesion, associations of neighborhood poverty and quality with accelerated DNAm aging remained elevated for residents living in neighborhoods with lower social cohesion, but were null for those living in neighborhoods with higher social cohesion. Our study suggests that living in adverse neighborhood environments can speed up epigenetic aging, while positive neighborhood attributes may buffer effects.

The impact of psychopathology, social adversity and stress-relevant DNA methylation on prospective risk for post-traumatic stress: A machine learning approach.

BACKGROUND: A range of factors have been identified that contribute to greater incidence, severity, and prolonged course of post-traumatic stress disorder (PTSD), including: comorbid and/or prior psychopathology; social adversity such as low socioeconomic position, perceived discrimination, and isolation; and biological factors such as genomic variation at glucocorticoid receptor regulatory network (GRRN) genes. This complex etiology and clinical course make identification of people at higher risk of PTSD challenging. Here we leverage machine learning (ML) approaches to identify a core set of factors that may together predispose persons to PTSD. METHODS: We used multiple ML approaches to assess the relationship among DNA methylation (DNAm) at GRRN genes, prior psychopathology, social adversity, and prospective risk for PTS severity (PTSS). RESULTS: ML models predicted prospective risk of PTSS with high accuracy. The Gradient Boost approach was the top-performing model with mean absolute error of 0.135, mean square error of 0.047, root mean square error of 0.217, and R2 of 95.29%. Prior PTSS ranked highest in predicting the prospective risk of PTSS, accounting for >88% of the prediction. The top ranked GRRN CpG site was cg05616442, in AKT1, and the top ranked social adversity feature was loneliness. CONCLUSION: Multiple factors including prior PTSS, social adversity, and DNAm play a role in predicting prospective risk of PTSS. ML models identified factors accounting for increased PTSS risk with high accuracy, which may help to target risk factors that reduce the likelihood or course of PTSD, potentially pointing to approaches that can lead to early intervention. LIMITATION: One of the limitations of this study is small sample size.

Transcriptomic profiling of fetal membranes of mice deficient in biglycan and decorin as a model of preterm birth†.

Approximately, 25% of all preterm births are due to preterm premature rupture of membranes. Mice deficient in proteoglycans biglycan (Bgn) and decorin (Dcn) display abnormal fetal membranes and increased incidence of preterm birth. We conducted RNA-Seq to profile fetal membranes and identify molecular pathways that may lead to preterm birth in double knockout (DKO) mice (Bgn-/-; Dcn-/-) compared to wild-type (WT) at two different gestational stages, E12 and E18 (n = 3 in each group). 3264 transcripts were differentially regulated in E18 DKO vs. WT fetal membranes, and 96 transcripts differentially regulated in E12 DKO vs. WT fetal membranes (FDR < 0.05, log 2 FC ≥ 1). Differentially regulated transcripts in E18 DKO fetal membranes were significantly enriched for genes involved in cell cycle regulation, extracellular matrix-receptor interaction, and the complement cascade. Fifty transcripts involved in the cell cycle were altered in E18 DKO fetal membranes (40↓, 10↑, FDR < 0.05), including p21 and p57 (↑), and Tgfb2, Smad3, CycA, Cdk1, and Cdk2(↓). Thirty-one transcripts involved in the complement cascade were altered (11↓, 20↑, FDR < 0.05) in E18 DKO fetal membranes, including C1q, C2, and C3 (↑). Differentially expressed genes in the top three molecular pathways (1) showed evidence of negative or purifying selection, and (2) were significantly enriched (Z-score > 10) for transcription factor binding sites for Nr2f1 at E18. We propose that in DKO mice, cell cycle arrest results in lack of cell proliferation in fetal membranes, inability to contain the growing fetus, and preterm birth.

Burden of post-traumatic stress disorder in postgenocide Rwandan population following exposure to 1994 genocide against the Tutsi: A meta-analysis.

BACKGROUND: The 1994 genocide against Tutsi resulted in a massive death toll that reached one million people. Despite the tremendous efforts made to mitigate the adverse effects of the genocide, a substantial burden of mental health disorders still exists including the notably high prevalence of post-traumatic stress disorder (PTSD) among genocide survivors. However, a synthesized model of PTSD vulnerability in this population is currently lacking. METHODS: A meta-analysis of 19 original research studies that reported PTSD prevalence (n = 12,610). Medline-PubMed and Science.gov were key search engines. Random-Effects Model (k = 19; tau^2 estimator: DL) was applied. Data extraction, synthesis, and meta-analysis were carried out using R. RESULTS: The total of 2957 out of 11,746 individuals suffered from PTSD. The summary proportion is 25% (95% CI=0.16,0.36). The tau^2 is 0.06 (95% CI=0.03,0.14) in the absence of subgroups, and the Q-statistic is 2827.65 (p<0.0001), all of which suggests high heterogeneity in the effect sizes. Year of data collection and Year of publication were significant moderators. PTSD pooled prevalence in the genocide survivor category was estimated at 37% (95% CI=0.21,0.56). CONCLUSION: The PTSD prevalence among genocide survivors is considerably higher compared to the general Rwandan population. The burden of PTSD in the general Rwandan population declined significantly over time, likely due to treatment of symptoms through strong national mental health programs, peace building and resolution of symptoms over time. To the best of our knowledge little evidence has reported the burden of PTSD prevalence in African post conflict zones particularly in Rwanda. LIMITATION: Limitations of our review include the use of retrospective studies and studies with very small sample sizes, as well as language criterion.

Advancing human health in the decade ahead: pregnancy as a key window for discovery: A Burroughs Wellcome Fund Pregnancy Think Tank.

Recent revolutionary advances at the intersection of medicine, omics, data sciences, computing, epidemiology, and related technologies inspire us to ponder their impact on health. Their potential impact is particularly germane to the biology of pregnancy and perinatal medicine, where limited improvement in health outcomes for women and children has remained a global challenge. We assembled a group of experts to establish a Pregnancy Think Tank to discuss a broad spectrum of major gestational disorders and adverse pregnancy outcomes that affect maternal-infant lifelong health and should serve as targets for leveraging the many recent advances. This report reflects avenues for future effects that hold great potential in 3 major areas: developmental genomics, including the application of methodologies designed to bridge genotypes, physiology, and diseases, addressing vexing questions in early human development; gestational physiology, from immune tolerance to growth and the timing of parturition; and personalized and population medicine, focusing on amalgamating health record data and deep phenotypes to create broad knowledge that can be integrated into healthcare systems and drive discovery to address pregnancy-related disease and promote general health. We propose a series of questions reflecting development, systems biology, diseases, clinical approaches and tools, and population health, and a call for scientific action. Clearly, transdisciplinary science must advance and accelerate to address adverse pregnancy outcomes. Disciplines not traditionally involved in the reproductive sciences, such as computer science, engineering, mathematics, and pharmacology, should be engaged at the study design phase to optimize the information gathered and to identify and further evaluate potentially actionable therapeutic targets. Information sources should include noninvasive personalized sensors and monitors, alongside instructive "liquid biopsies" for noninvasive pregnancy assessment. Future research should also address the diversity of human cohorts in terms of geography, racial and ethnic distributions, and social and health disparities. Modern technologies, for both data-gathering and data-analyzing, make this possible at a scale that was previously unachievable. Finally, the psychosocial and economic environment in which pregnancy takes place must be considered to promote the health and wellness of communities worldwide.