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Post-traumatic 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 that the biological alterations of the disorder can manifest themselves 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, i.e. the process in which traumatic experiences in our social environments are manifested in our body by genomic mechanisms. To date, gene expression studies that examine the whole transcriptome are scarce and limited to single-timepoint assessments. Here we applied a transcriptome-wide gene expression screen with RNA-sequencing to whole blood samples to elucidate the gene expression signatures associated with the development of PTSD. The study participants (N=72, of whom 21 eventually developed PTSD) are a trauma exposed subsample of participants enrolled in a longitudinal and 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. We found 45 differentially expressed genes associated with PTSD development with an estimated log2fold change > 1.5 at a nominal p value (pPAX6,TSPAN7,PXDN,VWC2,SULF1andNFATC4were also ubiquitously expressed in all brain regions examined. Subsequent gene set enrichment analysis identified several pathways relating to brain and immune functioning to be enriched in individuals developing PTSD. Longitudinal sampling provides a promising mean to elucidate the pathophysiology underlying the embodiment of trauma.

Living in adverse neighborhood environments have been linked to increased risk of aging-related diseases and mortality; however, the biological mechanisms explaining this observation remain poorly understood. DNA methylation (DNAm), a proposed biomarker of biological aging responsive to environmental stressors, offers promising insight into molecular pathways. We examined associations of three measures of neighborhood conditions (poverty, quality, and social cohesion) with three different epigenetic clocks (Horvath, Hannum, and Levine) using data from the Detroit Neighborhood Health Study (n=158). Using linear regression models, we evaluated associations in the total sample and stratified by gender and social cohesion. Differential effects by gender were found between men and women. Neighborhood poverty was associated with PhenoAge acceleration among women, but not among men (women: β = 1.4; 95% CI: −0.4, 3.3 vs. men: β = −0.3; 95% CI: −2.2, 1.5) in fully adjusted models. In models stratified on social cohesion, association 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 conditions can speed up epigenetic aging, while positive neighborhood characteristics may buffer effects.

Flexibility in the regulation of the hypothalamic–pituitary–adrenal (HPA) axis is an important mediator of stress resilience as it helps organisms adjust to, avoid, or compensate for acute and chronic challenges across changing environmental contexts. Glucocorticoids remain the favorite metric from medicine to conservation biology to attempt to quantify stress resilience despite the skepticism around their consistency in relation to individual health, welfare, and fitness. We suggest that a cochaperone molecule related to heat shock proteins and involved in glucocorticoid receptor activity, FKBP5, may mediate HPA flexibility and therefore stress resilience because it affects how individuals can regulate glucocorticoids and therefore capacitates their abilities to adjust phenotypes appropriately to prevailing, adverse conditions. Although the molecule is well studied in the biomedical literature, FKBP5 research in wild vertebrates is limited. In the present article, we highlight the potential major role of FKBP5 as mediator of HPA axis flexibility in response to adversity in humans and lab rodents.

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; taû2 estimator: DL) was applied. Data extraction, synthesis, and meta-analysis were carried out using R. RESULTS: The total of 2957 out of 11746 individuals suffered from PTSD. The summary proportion is 25 % (95% CI=0.16,0.36). The taû2 is 0.06 (95% CI=0.03,0.14) in the absence of subgroups, and the Q-statistic is 2827.65 (p

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.

The mechanisms by which neighborhood environmental exposures influence health are poorly understood, although immune system dysregulation represents a potential biological pathway. While many neighborhood exposures have been investigated, there is little research on residential proximity to brownfield waste. Using biomarker data from 262 participants in the Detroit Neighborhood Health Study (DNHS), we estimated the association between proximity to brownfields and heavy traffic and signal-joint T-cell Receptor Excision Circles (sjTRECs, a measure of naïve T-cell production), C-reactive protein (CRP, a measure of systemic inflammation), and interleukin 6 (IL-6, a proinflammatory cytokine). We assessed residential proximity ≤200 meters from brownfields and highways on all three biomarkers using multivariate regression. We demonstrated that living ≤200m from a brownfield site was associated with a 0.30 (95% CI = 0.59, 0.02, p = 0.04) log(e)-unit decrease in sjTRECs per million whole blood cells, as well as non-significantly elevated levels of CRP and IL-6. Heavy traffic was not associated with any biomarker. Persons living in close proximity to brownfield sites had significantly lower naïve T-cell production, suggesting accelerated immune aging. Decreased T-cell production associated with brownfield proximity may be caused by toxicant exposure in brownfield sites, or may serve as a marker of other neighborhood stressors.

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.

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 paper, 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 sub-populations. Specifically, mediators in different sub-populations 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 sub-populations 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 sub-groups 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.

Item does not contain fulltext 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. eng

Item does not contain fulltext 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. eng

Post-traumatic stress disorder (PTSD) is a debilitating mental disorder precipitated by trauma exposure. However, only some persons exposed to trauma develop PTSD. There are sex differences in risk; twice as many women as men develop a lifetime diagnosis of PTSD. Methylomic profiles derived from peripheral blood are well-suited for investigating PTSD because DNA methylation (DNAm) encodes individual response to trauma and may play a key role in the immune dysregulation characteristic of PTSD pathophysiology. In the current study, we leveraged recent methodological advances to investigate sex-specific differences in DNAm-based leukocyte composition that are associated with lifetime PTSD. We estimated leukocyte composition on a combined methylation array dataset (483 participants, ~450k CpG sites) consisting of two civilian cohorts, the Detroit Neighborhood Health Study and Grady Trauma Project. Sex-stratified Mann-Whitney U test and two-way ANCOVA revealed that lifetime PTSD was associated with a significantly higher monocyte proportions in males, but not in females (Holm-adjusted p-val < 0.05). No difference in monocyte proportions was observed between current and remitted PTSD cases in males, suggesting that this sex-specific difference may reflect a long-standing trait of lifetime history of PTSD, rather than current state of PTSD. Associations with lifetime PTSD or PTSD status were not observed in any other leukocyte subtype and our finding in monocytes was confirmed using cell estimates based on a different deconvolution algorithm, suggesting that our sex-specific findings are robust across cell estimation approaches. Overall, our main finding of elevated monocyte proportions in males, but not in females with lifetime history of PTSD provides evidence for a sex-specific difference in peripheral blood leukocyte composition that is detectable in methylomic profiles and that may reflect long-standing changes associated with PTSD diagnosis.

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.

BackgroundA 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.MethodsWe 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).ResultsML 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.ConclusionMultiple 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.

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.

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 20 variables including psychosocial factors, blood cell composition and asthma symptoms. Importantly, we found 174 genes associated with asthma that are regulated by psychosocial factors, and 349 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.

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 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.

Background Neighborhood characteristics are robust predictors of overall health and mortality risk for residents. Though there has been some investigation of the role that molecular indicators may play in mediating neighborhood exposures, there has been little effort to incorporate newly developed epigenetic biomarkers into our understanding of neighborhood characteristics and health outcomes. Methods Using 157 participants of the Detroit Neighborhood Health Study with detailed assessments of neighborhood characteristics and genome-wide DNA methylation profiling via the Illumina 450K methylation array, we assessed the relationship between objective neighborhood characteristics and a validated DNA methylation-based epigenetic mortality risk score (eMRS). Associations were adjusted for age, race, sex, ever smoking, ever alcohol usage, education, years spent in neighborhood, and employment. A secondary model additionally adjusted for personal neighborhood perception. We summarized 19 neighborhood quality indicators assessed for participants into 9 principal components which explained over 90% of the variance in the data and served as metrics of objective neighborhood quality exposures. Results Of the nine principal components utilized for this study, one was strongly associated with the eMRS (β = 0.15; 95% confidence interval = 0.06–0.24; P = 0.002). This principal component (PC7) was most strongly driven by the presence of abandoned cars, poor streets, and non-art graffiti. Models including both PC7 and individual indicators of neighborhood perception indicated that only PC7 and not neighborhood perception impacted the eMRS. When stratified on neighborhood indicators of greenspace, we observed a potentially protective effect of large mature trees as this feature substantially attenuated the observed association. Conclusion Objective measures of neighborhood disadvantage are significantly associated with an epigenetic predictor of mortality risk, presenting a potential novel avenue by which neighborhood-level exposures may impact health. Associations were independent of an individual’s perception of their neighborhood and attenuated by neighborhood greenspace features. More work should be done to determine molecular risk factors associated with neighborhoods, and potentially protective neighborhood features against adverse molecular effects.

Aim: Trauma exposure is a necessary, but not deterministic, contributor to post-traumatic stress disorder (PTSD). Epigenetic factors may distinguish between trauma-exposed individuals with versus without PTSD. Materials & methods: We conducted a meta-analysis of PTSD epigenome-wide association studies in trauma-exposed cohorts drawn from civilian contexts. Whole blood-derived DNA methylation levels were analyzed in 545 study participants, drawn from the three civilian cohorts participating in the PTSD working group of the Psychiatric Genomics Consortium. Results: Two CpG sites significantly associated with current PTSD in NRG1 (cg23637605) and in HGS (cg19577098). Conclusion: PTSD is associated with differential methylation, measured in blood, within HGS and NRG1 across three civilian cohorts.

The glucocorticoid receptor gene NR3C1 is an important down-regulator of inflammation and is typically under-expressed in individuals with low socioeconomic status (SES). Negative emotionality has been suggested as a potential mediator of SES disparities in health outcomes. In this study, we expand this literature by naturalistically assessing negative emotionality in a key emotional environment: the family. In a sample of 104 youth with asthma (10–17 years) and their primary caregiver, we assessed SES via caregiver report, emotional expression by youth and parents in the home over four days using the electronically activated recorder (EAR), and NR3C1 expression via blood collected from youth. Although there was not a direct effect of SES on NR3C1 expression, bootstrapping mediation analyses showed a significant indirect path such that lower SES was associated with a more negative family emotional climate, which in turn predicted reduced NR3C1 expression. No mediation effects were found for family positive emotional climate. This research demonstrates the importance of examining the effects of SES on emotion expression in the family context and suggests a critical biopsychosocial pathway underlying SES-based health disparities that may extend beyond youth.

The rapid and accurate diagnosis of patients with minimally invasive procedures was once only found in science fiction. However, the discovery of extracellular vesicles (EVs) and their near ubiquity in body fluids, coupled with the advent of inexpensive next generation sequencing techniques and EV purification protocols, promises to make science fiction a reality. Purifying and sequencing the RNA content of EV from routine blood draws and urine samples are likely to enable pathologists and physicians to diagnose and track the progress of diseases in many inaccessible tissues in the near future. Here we present the evolutionary background of EV, summarize the biology of EV formation and cargo selection, and discuss the current barriers to making continuous liquid biopsies through the use of EV a science reality.

Research has demonstrated links between adult romantic attachment and one’s own physical health; little is known about links between adult attachment orientations and offspring health. Prior work has shown that parents’ greater attachment anxiety and avoidance predict less warmth toward their children. Extensive work has also shown that lower maternal warmth has negative downstream effects on offspring health. We tested the novel hypothesis that mothers’ dispositional romantic attachment would be linked—via maternal warmth—to their children’s expression of the glucocorticoid receptor gene NR3C1, higher expression of which is associated with healthier stress regulation and inflammatory response. In a sample of 132 youth with asthma, we found that mothers’ attachment anxiety and avoidance were both negatively associated with children’s expression of NR3C1, explained by lower youth-rated maternal warmth. Associations held after adjusting for demographic and psychosocial covariates. Implications for parents’ attachment influencing the health of offspring are discussed.

The Psychiatric Genomics Consortium-Posttraumatic Stress Disorder group (PGC-PTSD) combined genome-wide case-control molecular genetic data across 11 multiethnic studies to quantify PTSD heritability, to examine potential shared genetic risk with schizophrenia, bipolar disorder, and major depressive disorder and to identify risk loci for PTSD. Examining 20 730 individuals, we report a molecular genetics-based heritability estimate (h 2 SNP) for European-American females of 29% that is similar to h 2 SNP for schizophrenia and is substantially higher than h 2 SNP in European-American males (estimate not distinguishable from zero). We found strong evidence of overlapping genetic risk between PTSD and schizophrenia along with more modest evidence of overlap with bipolar and major depressive disorder. No single-nucleotide polymorphisms (SNPs) exceeded genome-wide significance in the transethnic (overall) meta-analysis and we do not replicate previously reported associations. Still, SNP-level summary statistics made available here afford the best-available molecular genetic index of PTSD - for both European- and African-American individuals - and can be used in polygenic risk prediction and genetic correlation studies of diverse phenotypes. Publication of summary statistics for 1/410 000 African Americans contributes to the broader goal of increased ancestral diversity in genomic data resources. In sum, the results demonstrate genetic influences on the development of PTSD, identify shared genetic risk between PTSD and other psychiatric disorders and highlight the importance of multiethnic/racial samples. As has been the case with schizophrenia and other complex genetic disorders, larger sample sizes are needed to identify specific risk loci.

Post-traumatic stress disorder (PTSD) is a debilitating mental disorder precipitated by trauma exposure. However, only some persons exposed to trauma develop PTSD. There are sex differences in risk; twice as many women as men, develop a lifetime diagnosis of PTSD. Methylomic profiles derived from peripheral blood are well-suited for investigating PTSD because DNA methylation (DNAm) encodes individual response to trauma and may play a key role in the immune dysregulation characteristic of PTSD pathophysiology. In the current study, we leveraged recent methodological advances to investigate sex-specific shifts in DNAm-based leukocyte composition that are associated with lifetime PTSD. We estimated leukocyte composition on a combined methylation array dataset (483 participants, ∼450k CpG sites) consisting of two civilian cohorts, the Detroit Neighborhood Health Study and Grady Trauma Project. Sex-stratified Mann-Whitney U test and two-way ANCOVA revealed that lifetime PTSD was associated with a small but significant elevation in monocyte proportions in males, but not in females (Holm-adjusted p-val < 0.05). No difference in monocyte proportions was observed between current and remitted PTSD cases in males, suggesting that this sex-specific peak shift reflects a long-standing trait of lifetime history of PTSD, rather than current state of PTSD. Associations with lifetime PTSD or PTSD status were not observed in any other leukocyte subtype and our finding in monocytes was confirmed using cell estimates based on a different deconvolution algorithm, suggesting that our sex-specific findings are robust across cell estimation approaches. Overall, our main finding of elevated monocyte proportions in males, but not in females with lifetime history of PTSD provides evidence for a sex-specific shift in peripheral blood leukocyte composition that is detectable in methylomic profiles and that reflects long-standing changes associated with PTSD diagnosis.

Background Use of the Genome Analysis Toolkit (GATK) continues to be the standard practice in genomic variant calling in both research and the clinic. Recently the toolkit has been rapidly evolving. Significant computational performance improvements have been introduced in GATK3.8 through collaboration with Intel in 2017. The first release of GATK4 in early 2018 revealed rewrites in the code base, as the stepping stone toward a Spark implementation. As the software continues to be a moving target for optimal deployment in highly productive environments, we present a detailed analysis of these improvements, to help the community stay abreast with changes in performance. Results We re-evaluated multiple options, such as threading, parallel garbage collection, I/O options and data-level parallelization. Additionally, we considered the trade-offs of using GATK3.8 and GATK4. We found optimized parameter values that reduce the time of executing the best practices variant calling procedure by 29.3% for GATK3.8 and 16.9% for GATK4. Further speedups can be accomplished by splitting data for parallel analysis, resulting in run time of only a few hours on whole human genome sequenced to the depth of 20X, for both versions of GATK. Nonetheless, GATK4 is already much more cost-effective than GATK3.8. Thanks to significant rewrites of the algorithms, the same analysis can be run largely in a single-threaded fashion, allowing users to process multiple samples on the same CPU. Conclusions In time-sensitive situations, when a patient has a critical or rapidly developing condition, it is useful to minimize the time to process a single sample. In such cases we recommend using GATK3.8 by splitting the sample into chunks and computing across multiple nodes. The resultant walltime will be nnn.4 hours at the cost of $41.60 on 4 c5.18xlarge instances of Amazon Cloud. For cost-effectiveness of routine analyses or for large population studies, it is useful to maximize the number of samples processed per unit time. Thus we recommend GATK4, running multiple samples on one node. The total walltime will be ∼34.1 hours on 40 samples, with 1.18 samples processed per hour at the cost of $2.60 per sample on c5.18xlarge instance of Amazon Cloud.

Socioeconomic disadvantage may contribute to poor health through immune-related biological mechanisms. We examined the associations between socioeconomic status, as measured by annual household income, and T-cell markers of aging, including the ratios of CD4 and CD8 effector cells to naïve cells (E/N ratio) and the CD4/CD8 T-cell ratio. We hypothesized that participants with a lower income would have higher E/N ratios and lower CD4/CD8 ratios compared with participants with a higher income, and that these associations would be partially mediated by elevated cytomegalovirus (CMV) IgG antibody levels, a virus implicated in aging and clonal expansion of T cells.Data were from 79 individuals who participated in the population-based Detroit Neighborhood Health Study. We used linear regression to quantify the association between a $10,000 decrease in income and each ratio outcome.After adjustment for age, sex, race, smoking, medication use, and lifetime history of mental health conditions, lower income was associated with a 0.41 (95% confidence interval = 0.09-0.72) log-unit increase in the CD4 E/N ratio and a 0.20 (95% confidence interval = 0.02-0.39) log-unit increase in the CD8 E/N ratio. CMV immunoglobulin G antibody level partially mediated these associations.Our study suggests that low socioeconomic status is associated with immunological aging as measured by the E/N ratio and that impaired immune control of CMV may partially mediate these associations.

The thymus is critical for mounting an effective immune response and maintaining health. However, epidemiologic studies characterizing thymic function in the population setting are lacking. Using data from 263 adults in the Detroit Neighborhood Health Study, we examined thymic function as measured by the number of signal joint T-cell receptor excision circles (sjTREC) and assessed associations with established indicators of physiological health. Overall, increasing age and male gender were significantly associated with reduced thymic function. Adjusting for covariates, individuals with elevated levels of the pro-inflammatory biomarkers C-reactive protein (β: -0.50 [95% CI: -0.82, -0.18] for moderate elevation, β: -0.29 [95% CI: -0.59, 0.00] for high elevation) and interleukin-6 (β: -0.60 [95% CI: -0.92, -0.28] for moderate elevation, β: -0.43 [95% CI: -0.77, -0.08] for severe elevation) also had lower thymic function. Compared to individuals with a BMI < 25, individuals who were overweight (β: 0.36 [95% CI: 0.07, 0.64]) or obese (β: 0.27 [95% CI: -0.03, 0.56]) had higher thymic function. Differences by self-rated health were not statistically significant. Our findings underscore demographic- and health-related gradients in thymic function among adult residents of Detroit, suggesting thymic function may be an important biomarker of health status in adults at the population level.

As reliable, efficient genome sequencing becomes more ubiquitous, the need for similarly reliable and efficient variant calling becomes increasingly important. The Genome Analysis Toolkit (GATK), maintained by the Broad Institute, is currently the widely accepted standard for variant calling software. However, alternative solutions may provide faster variant calling without sacrificing accuracy. One such alternative is Sentieon DNASeq, a toolkit analogous to GATK but built on a highly optimized backend. We evaluated the DNASeq single-sample variant calling pipeline in comparison to that of GATK. Our results confirm the near-identical accuracy of the two software packages, showcase perfect scalability and great speed from Sentieon, and describe computational performance considerations for the deployment of Sentieon DNASeq.

Objectives: The most pronounced effect of high altitude (>2700m) on reproductive outcomes is reduced birth weight. Indigenous Bolivians (Andean Native Americans) residing for generations at high altitudes have higher birth weights relative to more recent migrants of primarily European ancestry. Previous research demonstrated that the placenta is a key contributor to the preservation of Andean birth weight at high altitude. Our current research investigated how gene expression and epigenetics contributes to the conservation of birth weight at high altitude by examining mRNA expression and DNA methylation differences between placentas of Andeans and those of European ancestry residing at high and low altitude.Methods: Genome-wide mRNA expression and DNA methylation of villous placenta tissue was quantified utilizing microarray technology. Subjects were of Andean and European ancestry and resident at high (3600m) or low (400m) altitudes. Differentially expressed genes (DEGs) associated with altitude or ancestry were identified (FDR1.25). To predict which DEGs could be regulated by methylation we tested for correlation between gene expression and methylation values.Results: 69 DEGs associated with altitude (n=36) or ancestry (n=34) were identified. Altitude-associated DEGs included members of the AP-1 transcription factor family. Ancestry-associated DEGs were implicated in inflammatory pathways and associated with pro-angiogenic macrophages. More ancestry-associated DEGs correlated significantly (n=17) (FDRConclusions:Compared to altitude-associated DEGs, methylation regulates more ancestry-associated DEGs, potentially allowing for rapid modification in the expression of inflammatory genes to attract pro-angiogenic macrophages as a means of promoting placental capillary growth in Andeans, regardless of altitude.

Use of the Genome Analysis Toolkit (GATK) continues to be the standard practice in genomic variant calling in both research and the clinic. Recently the toolkit has been rapidly evolving. Significant computational performance improvements have been introduced in GATK3.8 through collaboration with Intel in 2017. The first release of GATK4 in early 2018 revealed significant rewrites in the code base, as the stepping stone toward a Spark implementation. As the software continues to be a moving target for optimal deployment in highly productive environments, we present a detailed analysis of these improvements, to help the community stay abreast with changes in performance. We re-evaluated the options previously identified as advantageous, such as threading, parallel garbage collection, I/O options and data-level parallelization. Based on our results, we consider the performance and cost trade-offs of using GATK3.8 and GATK4 for different types of analyses.