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

Background Poor family emotional health (FEH) during childhood is prevalent and impactful, and likely confers similar neurodevelopmental risks as other adverse social environments. Pointed FEH study efforts are underdeveloped, and the mechanisms by which poor FEH are biologically embedded are unclear. The current exploratory study examined whether variability in 5-methyl-cytosine (5mC) and fronto-limbic grey matter volume may represent pathways through which FEH may become biologically embedded. Results In 98 university students aged 18–22 years, retrospective self-reported childhood FEH was associated with right hemisphere hippocampus ( b = 10.4, p = 0.005), left hemisphere amygdala ( b = 5.3, p = 0.009), and right hemisphere amygdala ( b = 5.8, p = 0.016) volumes. After pre-processing and filtering to 5mC probes correlated between saliva and brain, analyses showed that childhood FEH was associated with 49 5mC principal components (module eigengenes; MEs) ( p range = 3 × 10 –6 to 0.047). Saliva-derived 5mC MEs partially mediated the association between FEH and right hippocampal volume (Burlywood ME indirect effect b = − 111, p = 0.014), and fully mediated the FEH and right amygdala volume relationship (Pink4 ME indirect effect b = − 48, p = 0.026). Modules were enriched with probes falling in genes with immune, central nervous system (CNS), cellular development/differentiation, and metabolic functions. Conclusions Findings extend work highlighting neurodevelopmental variability associated with adverse social environment exposure during childhood by specifically implicating poor FEH, while informing a mechanism of biological embedding. FEH-associated epigenetic signatures could function as proxies of altered fronto-limbic grey matter volume associated with poor childhood FEH and inform further investigation into primarily affected tissues such as endocrine, immune, and CNS cell types.

The microarray-based Illumina Infinium MethylationEpic BeadChip (Epic 850k) has become a useful and standard tool for epigenome wide deoxyribonucleic acid (DNA) methylation profiling. Data from this technology may suffer from batch effects due to improper handling of the samples during the plating process. Batch effects are a significant issue and can give rise to spurious and inaccurate results and reduction in power to detect real biological differences. Careful study design, such as randomizing the samples to uniformly distribute the samples across the factors responsible for batch effects, is crucial to address batch effects and other technical artifacts. Randomization helps to reduce the likelihood of bias and impact of difference among groups. This process of randomizing the samples can be a tedious, error-prone, and time-consuming task without a user-friendly and efficient tool. We present RANDOMIZE, a web-based application designed to perform randomization of relevant metadata to evenly distribute samples across the factors typically responsible for batch effects in DNA methylation microarrays, such as rows, chips and plates. We demonstrate that the tool is efficient, fast and easy to use. The tool is freely available online at https://coph-usf.shinyapps.io/RANDOMIZE/ and can be accessed using any web browser. Sample data and tutorial is also available with the tool.

Accumulating evidence suggests that dysregulation of placental DNA methylation (DNAm) is a mechanism linking maternal weight during pregnancy to metabolic programming outcomes. The common marmoset, Callithrix jaccus, is a platyrrhine primate species that has provided much insight into studies of the primate placenta, maternal condition, and metabolic programming, yet the relationships between maternal weight and placental DNAm are unknown. Here, we report genome-wide DNAm from term marmoset placentas using reduced representation bisulfite sequencing. We identified 74 genes whose DNAm pattern is associated with maternal weight during gestation. These genes are predominantly involved in energy metabolism and homeostasis, including the regulation of glycolytic and lipid metabolic processes pathways.

Abstract 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. Summary sentence We have conducted transcriptomic profiling of fetal membranes from mice deficient in biglycan and decorin and identified molecular pathways of interest.

ABSTRACT 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.

Connectivity modeling in functional neuroimaging has become widely used method of analysis for understanding functional architecture. One method for deriving directed connectivity models is Group Iterative Multiple Model Estimation (GIMME; Gates and Molenaar, 2012). GIMME looks for commonalities across the sample to detect signal from noise and arrive at edges that exist across the majority in the group (“group-level edges”) and individual-level edges. In this way, GIMME obtains generalizable results via the group-level edges while also allowing for between subject heterogeneity in connectivity, moving the field closer to obtaining reliable personalized connectivity maps. In this article, we present a novel extension of GIMME, confirmatory subgrouping GIMME, which estimates subgroup-level edges for a priori known groups (e.g. typically developing controls vs. clinical group). Detecting edges that consistently exist for individuals within predefined subgroups aids in interpretation of the heterogeneity in connectivity maps and allows for subgroup-specific inferences. We describe this algorithm, as well as several methods to examine the results. We present an empirical example that finds similarities and differences in resting state functional connectivity among four groups of children: typically developing controls (TDC), children with autism spectrum disorder (ASD), children with Inattentive (ADHD-I) and Combined (ADHD-C) Type ADHD. Findings from this study suggest common involvement of the left Broca's area in all the clinical groups, as well as several unique patterns of functional connectivity specific to a given disorder. Overall, the current approach and proof of principle findings highlight a novel and reliable tool for capturing heterogeneity in complex mental health disorders.

The need for portable and reproducible genomics analysis pipelines is growing globally as well as in Africa, especially with the growth of collaborative projects like the Human Health and Heredity in Africa Consortium (H3Africa). The Pan-African H3Africa Bioinformatics Network (H3ABioNet) recognized the need for portable, reproducible pipelines adapted to heterogeneous computing environments, and for the nurturing of technical expertise in workflow languages and containerization technologies. Building on the network’s Standard Operating Procedures (SOPs) for common genomic analyses, H3ABioNet arranged its first Cloud Computing and Reproducible Workflows Hackathon in 2016, with the purpose of translating those SOPs into analysis pipelines able to run on heterogeneous computing environments and meeting the needs of H3Africa research projects. This paper describes the preparations for this hackathon and reflects upon the lessons learned about its impact on building the technical and scientific expertise of African researchers. The workflows developed were made publicly available in GitHub repositories and deposited as container images on Quay.io.

The need for portable and reproducible genomics analysis pipelines is growing globally as well as in Africa, especially with the growth of collaborative projects like the Human Health and Heredity in Africa Consortium (H3Africa). The Pan-African H3Africa Bioinformatics Network (H3ABioNet) recognized the need for portable, reproducible pipelines adapted to heterogeneous computing environments, and for the nurturing of technical expertise in workflow languages and containerization technologies. Building on the network’s Standard Operating Procedures (SOPs) for common genomic analyses, H3ABioNet arranged its first Cloud Computing and Reproducible Workflows Hackathon in 2016, with the purpose of translating those SOPs into analysis pipelines able to run on heterogeneous computing environments and meeting the needs of H3Africa research projects. This paper describes the preparations for this hackathon and reflects upon the lessons learned about its impact on building the technical and scientific expertise of African researchers. The workflows developed were made publicly available in GitHub repositories and deposited as container images on Quay.io.

Background: Recent studies examining the association between posttraumatic stress disorder (PTSD) and accelerated aging, as defined by DNA methylation-based estimates of cellular age that exceed chronological age, have yielded mixed results. Methods: We conducted a meta-analysis of trauma exposure and PTSD diagnosis and symptom severity in association with accelerated DNA methylation age using data from 9 cohorts contributing to the Psychiatric Genomics Consortium PTSD Epigenetics Workgroup (combined N = 2186). Associations between demographic and cellular variables and accelerated DNA methylation age were also examined, as was the moderating influence of demographic variables. Results: Meta-analysis of regression coefficients from contributing cohorts revealed that childhood trauma exposure (when measured with the Childhood Trauma Questionnaire) and lifetime PTSD severity evidenced significant, albeit small, meta-analytic associations with accelerated DNA methylation age (ps = 0.028 and 0.016, respectively). Sex, CD4T cell proportions, and natural killer cell proportions were also significantly associated with accelerated DNA methylation age (all ps < 0.02). PTSD diagnosis and lifetime trauma exposure were not associated with advanced DNA methylation age. There was no evidence of moderation of the trauma or PTSD variables by demographic factors. Conclusions: Results suggest that traumatic stress is associated with advanced epigenetic age and raise the possibility that cells integral to immune system maintenance and responsivity play a role in this. This study highlights the need for additional research into the biological mechanisms linking traumatic stress to accelerated DNA methylation age and the importance of furthering our understanding of the neurobiological and health consequences of PTSD.

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.

BACKGROUND:The Pan-African bioinformatics network, H3ABioNet, comprises 27 research institutions in 17 African countries. H3ABioNet is part of the Human Health and Heredity in Africa program (H3Africa), an African-led research consortium funded by the US National Institutes of Health and the UK Wellcome Trust, aimed at using genomics to study and improve the health of Africans. A key role of H3ABioNet is to support H3Africa projects by building bioinformatics infrastructure such as portable and reproducible bioinformatics workflows for use on heterogeneous African computing environments. Processing and analysis of genomic data is an example of a big data application requiring complex interdependent data analysis workflows. Such bioinformatics workflows take the primary and secondary input data through several computationally-intensive processing steps using different software packages, where some of the outputs form inputs for other steps. Implementing scalable, reproducible, portable and easy-to-use workflows is particularly challenging.RESULTS:H3ABioNet has built four workflows to support (1) the calling of variants from high-throughput sequencing data; (2) the analysis of microbial populations from 16S rDNA sequence data; (3) genotyping and genome-wide association studies; and (4) single nucleotide polymorphism imputation. A week-long hackathon was organized in August 2016 with participants from six African bioinformatics groups, and US and European collaborators. Two of the workflows are built using the Common Workflow Language framework (CWL) and two using Nextflow. All the workflows are containerized for improved portability and reproducibility using Docker, and are publicly available for use by members of the H3Africa consortium and the international research community.CONCLUSION:The H3ABioNet workflows have been implemented in view of offering ease of use for the end user and high levels of reproducibility and portability, all while following modern state of the art bioinformatics data processing protocols. The H3ABioNet workflows will service the H3Africa consortium projects and are currently in use. All four workflows are also publicly available for research scientists worldwide to use and adapt for their respective needs. The H3ABioNet workflows will help develop bioinformatics capacity and assist genomics research within Africa and serve to increase the scientific output of H3Africa and its Pan-African Bioinformatics Network.

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.

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.

We studied the simulated replication and growth of prebiotic vesicles composed of 140 phospholipids and cholesterol using our R-GARD (Real Graded Autocatalysis Replication Domain) formalism that utilizes currently extant lipids that have known rate constants of lipid-vesicle interactions from published experimental data. R-GARD normally modifies kinetic parameters of lipid-vesicle interactions based on vesicle composition and properties. Our original R-GARD model tracked the growth and division of one vesicle at a time in an environment with unlimited lipids at a constant concentration. We explore here a modified model where vesicles compete for a finite supply of lipids. We observed that vesicles exhibit complex behavior including initial fast unrestricted growth, followed by intervesicle competition for diminishing resources, then a second growth burst driven by better-adapted vesicles, and ending with a final steady state. Furthermore, in simulations without kinetic parameter modifications ("invariant kinetics"), the initial replication was an order of magnitude slower, and vesicles' composition variability at the final steady state was much lower. The complex kinetic behavior was not observed either in the previously published R-GARD simulations or in additional simulations presented here with only one lipid component. This demonstrates that both a finite environment (inducing selection) and multiple components (providing variation for selection to act upon) are crucial for portraying evolution-like behavior. Such properties can improve survival in a changing environment by increasing the ability of early protocellular entities to respond to rapid environmental fluctuations likely present during abiogenesis both on Earth and possibly on other planets. This in silico simulation predicts that a relatively simple in vitro chemical system containing only lipid molecules might exhibit properties that are relevant to prebiotic processes. Key Words: Phospholipid vesicles-Prebiotic compartments-Prebiotic vesicle competition-Prebiotic vesicle variability. Astrobiology 18, 419-430.

BACKGROUND: Recent conceptual models argue that early life adversity (ELA) accelerates development, which may contribute to poor mental and physical health outcomes. Evidence for accelerated development in youths comes from studies of telomere shortening or advanced pubertal development following circumscribed ELA experiences and neuroimaging studies of circuits involved in emotional processing. It is unclear whether all ELA is associated with accelerated development across global metrics of biological aging or whether this pattern emerges following specific adversity types. METHODS: In 247 children and adolescents 8 to 16 years of age with wide variability in ELA exposure, we evaluated the hypothesis that early environments characterized by threat, but not deprivation, would be associated with accelerated development across two global biological aging metrics: DNA methylation (DNAm) age and pubertal stage relative to chronological age. We also examined whether accelerated development explained associations of ELA with depressive symptoms and externalizing problems. RESULTS: Exposure to threat-related ELA (e.g., violence) was associated with accelerated DNAm age and advanced pubertal stage, but exposure to deprivation (e.g., neglect, food insecurity) was not. In models including both ELA types, threat-related ELA was uniquely associated with accelerated DNAm age (beta = .18) and advanced pubertal stage (beta = .28), whereas deprivation was uniquely associated with delayed pubertal stage (beta = -.21). Older DNAm age was related to greater depressive symptoms, and a significant indirect effect of threat exposure on depressive symptoms was observed through DNAm age. CONCLUSIONS: Early threat-related experiences are particularly associated with accelerated biological aging in youths, which may be a mechanism linking ELA with depressive symptoms.

We conducted an epigenome-wide association study of Major Depressive Disorder (MDD) in brain-derived DNA using two analytic approaches. DNA methylation data (GSE41826) was used in differential methylation (DM) analyses controlling for age, sex, suicide status, and post-mortem interval; and in weighted gene co-methylation network analyses (WGCNA) in probes mapping to transcription start sites. No probes in the DM analysis survived FDR correction. Nominally significant DM probes were enriched in synaptic function-related genes. WGCNA revealed one module correlated with MDD, enriched in genes associated with mitochondrial function. DM and WGCNA both showed enrichment of genes involved in transcription and DNA binding.

Recent research shows that gene expression changes appear to correlate well with the progression of many types of cancers. Using changes in gene expression as a basis, this paper proposes a data-driven 2-player game-theoretic model to predict the risk of adenocarcinoma based on Nash equilibrium. A key innovation in this work is the pay-off function which is a weighted composite of the expression of a cohort of tumor-suppressor genes (as one player) and an analogous cohort of oncogenes (as the other player). Another novelty of the model is its ability to predict the risk that a healthy sample will develop adenocarcinoma, if its associated gene expression is comparable to that of early-stage tumor samples. The model is validated using two of the largest publicly available adenocarcinoma datasets. The results show that i) the model is able to distinguish between healthy and cancerous samples with an accuracy of 93%, and ii) 95% of the healthy samples said to be at risk had gene expressions comparable to those of samples with stage I or stage II tumors, thereby predicting the imminent onset of adenocarcinoma.