Gene expression differences in PTSD are uniquely related to the intrusion symptom cluster: A transcriptome-wide analysis in military service members

Genetic association between post-traumatic stress disorder and cardiovascular disease: A scoping review

INTRODUCTION

Post-traumatic stress disorder (PTSD) is a complex psychiatric disorder associated with adverse long-term health outcomes, including cardiovascular disease (CVD). Despite growing evidence that PTSD is positively associated with CVD, the biological mechanisms underlying this association are poorly understood. This review provides an overview of the current state of science on the genetic association between PTSD and CVD.

MATERIAL AND METHODS

This scoping review identified studies from Pubmed, Embase, PsycINFO, and Web of Science. The search terms were a combination of PTSD, CVD/CVD-related traits, and a set of genetic molecules and related terms. This review followed the PRISMA Extension for Scoping Reviews guidelines. Eligible criteria included original studies that have genetic factors related to PTSD or CVD, conducted in humans, written in English, and published between 2003 and 2023 in peer-reviewed journals.

RESULTS

A total of twenty-three studies were included; PTSD correlated with genetic variants in CVD-related traits and gene expression in regulatory pathways contributing to CVD development. Common CVD-related traits involved in genetic associations with PTSD were inflammation, cellular aging, increased blood pressure, hypothalamus-pituitary-adrenal axis dysregulation, metabolic syndrome, and oxidative stress. These traits may explain potential underlying mechanisms between PTSD and CVD. Evidence of a causal relationship between the two diseases was insufficient.

DISCUSSION

PTSD and CVD/CVD-related traits are genetically associated. Further research is needed to comprehensively explore gene-environment interactions and the cumulative impact of behavioral and psychological factors on the pathophysiological mechanisms between PTSD and CVD.

Androgen synthesis cell-specific CREBZF deficiency alters adrenal cortex steroid secretion and develops behavioral abnormalities in adult male mice

The global challenge of male infertility is escalating, notably due to the decreased testosterone (T) synthesis in testicular Leydig cells under stress, underscoring the critical need for a more profound understanding of its regulatory mechanisms. CREBZF, a novel basic region-leucine zipper transcription factor, regulates testosterone synthesis in mouse Leydig cells in vitro; however, further validation through in vivo experiments is essential. Our study utilized Cyp17a1-Cre to knock out CREBZF in androgen-synthesis cells and explored the physiological roles of CREBZF in fertility, steroid hormone synthesis, and behaviors in adult male mice. Conditional knockout (cKO) CREBZF did not affect fertility and serum testosterone level in male mice. Primary Leydig cells isolated from CREBZF-cKO mice showed impaired testosterone secretion and decreased mRNA levels of Star, Cyp17a1, and Hsd3b1. Loss of CREBZF resulted in thickening of the adrenal cortex, especially X-zone, with elevated serum corticosterone and dehydroepiandrosterone levels and decreased serum dehydroepiandrosterone sulfate levels. Immunohistochemical staining revealed increased expression of StAR, Cyp11a1, and 17β-Hsd3 in the adrenal cortex of CREBZF-cKO mice, while the expression of AR was significantly reduced. Along with the histological changes and abnormal steroid levels in the adrenal gland, CREBZF-cKO mice showed higher anxiety-like behavior and impaired memory in the elevated plus maze and Barnes maze, respectively. In summary, CREBZF is dispensable for fertility, and CREBZF deficiency in Leydig cells promotes adrenal function in adult male mice. These results shed light on the requirement of CREBZF for fertility, adrenal steroid synthesis, and stress response in adult male mice, and contribute to understanding the crosstalk between testes and adrenal glands.

Exploring heterogeneity in PTSD symptoms and associated predictors and outcomes in Afghanistan veterans: A latent profile analysis

Research on posttraumatic stress symptoms (PTSS) typically focuses on diagnosis or symptom severity, however, this overlooks the variety of symptom patterns that exist. Latent profile analysis was used to explore PTSS profiles in a sample of Norwegian Afghanistan veterans (n = 4052, 91.7% males). Multinomial logistic regression analyses were conducted to examine predictors and outcomes associated with PTSS profile membership. Three profiles emerged: Low Symptoms profile (85%); High Numbing and Arousal profile (13%); and High Symptoms profile (2%). Being female, lower number of deployments, barriers to disclose war-related experiences, and higher number of potentially morally injurious events (PMIEs) were associated with belonging to the High Symptoms profile compared to the High Numbing and Arousal (Male gender: OR = 0.37, p < .05; Number of deployments: OR = 0.68, p < .05; Barriers to disclose: OR = 1.39, p < .001; PMIEs: OR = 1.15. p < .05), or Low Symptoms profile (Male gender: OR = 0.36, p < .05; Number of deployments: OR = 0.67, p < .01; Barriers to disclose: OR = 1.80, p < .001; PMIEs: OR = 1.32. p < .001). Participants in the High Symptoms profile had the highest probability of mental health service use (0.37) and endorsing suicidal ideation (0.38), compared to the two other profiles (p < .01). Participants in the High Numbing and Arousal profile had a higher probability of seeking professional mental health care (0.17), endorsing suicidal ideation (0.16), and reporting more suicide attempts compared to the Low Symptom profile (0.02 vs. 0.00, p < .001). These findings highlight the importance of considering the heterogeneity of PTSS profiles and understanding the predictors and responses of individuals who exhibit elevated PTSS symptoms.

A novel enzyme-linked ligand-sorbent assay (ELLSA) to screening pulmonary tuberculosis: a retrospective cross-sectional study

BACKGROUND

Little knowledge of antigen existence in the pulmonary tuberculosis (PTB) patient serum impeded its development in antigen detection technology, despite its considerable potential.

METHODS

Human ligand proteins and their adsorbent Mycobacterium tuberculosis (M.tb) proteins in the serum of PTB patients were identified using human protein chip (HuProt™) and LC-MS/MS, successively. The monoclonal antibody of ligand proteins, C5orf24, and polyclonal antibody of 9 M.tb proteins were prepared on mice and rabbits which were used to develop a novel enzyme-linked ligand-sorbent assay (ELLSA). The 412 volunteers were divided into the PTB group (n = 250) and the healthy control (n = 162). The PTB group was further divided into ATB (n = 131), LTBI (n = 18), Clinical diagnosis (n = 18), and Suspected (n = 73). All samples were tested by ELLSA to evaluate the diagnostic performance of ELLSA in PTB patients.

RESULTS

Nine ligand proteins specific to PTB patients were identified on chips, with Chromosome 5 Open Reading Frame 24 (C5orf24) and kinocilin (KNCN) showing significantly higher signals. Proteomic analysis of the C5orf24-and KNCN-adsorbent protein complexes revealed 10 and 10 of the M.tb proteins, respectively. According to the composition reference of standard, the ELLSA based on C5orf24 ligand demonstrated a higher sensitivity of 69.6% and specificity of 90.18% in ATB patients and had a sensitivity of 64.22% in bacterial negative pulmonary tuberculosis, whereas the sensitivity of MGIT 960 and Xpert M.tb/RIF were 0%, respectively.

CONCLUSIONS

M.tb proteins in serum can be enriched by ligand proteins and detected by ELLSA which proved to have excellent diagnostic performance for PTB.

Can RNA Affect Memory Modulation? Implications for PTSD Understanding and Treatment

Memories are a central aspect of our lives, but the mechanisms underlying their formation, consolidation, retrieval, and extinction remain poorly understood. In this review, we explore the molecular mechanisms of memory modulation and investigate the effects of RNA on these processes. Specifically, we examine the effects of time and location on gene expression alterations. We then discuss the potential for harnessing these alterations to modulate memories, particularly fear memories, to alleviate post-traumatic stress disorder (PTSD) symptoms. The current state of research suggests that transcriptional changes play a major role in memory modulation and targeting them through microRNAs may hold promise as a novel approach for treating memory-related disorders such as PTSD.

Identifying genetic loci that are associated with changes in gene expression in PTSD in a South African cohort

The molecular mechanisms underlying posttraumatic stress disorder (PTSD) are yet to be fully elucidated, especially in underrepresented population groups. Expression quantitative trait loci (eQTLs) are DNA sequence variants that influence gene expression, in a local (cis-) or distal (trans-) manner, and subsequently impact cellular, tissue, and system physiology. This study aims to identify genetic loci associated with gene expression changes in a South African PTSD cohort. Genome-wide genotype and RNA-sequencing data were obtained from 32 trauma-exposed controls and 35 PTSD cases of mixed-ancestry, as part of the SHARED ROOTS project. The first approach utilised 108 937 single-nucleotide polymorphisms (SNPs) (MAF > 10%) and 11 312 genes with Matrix eQTL to map potential eQTLs, while controlling for covariates as appropriate. The second analysis was focused on 5638 SNPs related to a previously calculated PTSD polygenic risk score for this cohort. SNP-gene pairs were considered eQTLs if they surpassed Bonferroni correction and had a false discovery rate <0.05. We did not identify eQTLs that significantly influenced gene expression in a PTSD-dependent manner. However, several known cis-eQTLs, independent of PTSD diagnosis, were observed. rs8521 (C > T) was associated with TAGLN and SIDT2 expression, and rs11085906 (C > T) was associated with ZNF333 expression. This exploratory study provides insight into the molecular mechanisms associated with PTSD in a non-European, admixed sample population. This study was limited by the cross-sectional design and insufficient statistical power. Overall, this study should encourage further multi-omics approaches towards investigating PTSD in diverse populations.

Treatment-associated mRNA co-expression changes in monocytes of patients with posttraumatic stress disorder

PTSD is a prevalent mental disorder that results from exposure to extreme and stressful life events and comes at high costs for both the individual and society. Therapeutic treatment presents the best way to deal with PTSD-the mechanisms underlying change after treatment, however, remain poorly understood. While stress and immune associated gene expression changes have been associated with PTSD development, studies investigating treatment effects at the molecular level so far tended to focus on DNA methylation. Here we use gene-network analysis on whole-transcriptome RNA-Seq data isolated from CD14⁺ monocytes of female PTSD patients (N = 51) to study pre-treatment signatures of therapy response and therapy-related changes at the level of gene expression. Patients who exhibited significant symptom improvement after therapy showed higher baseline expression in two modules involved in inflammatory processes (including notable examples IL1R2 and FKBP5) and blood coagulation. After therapy, expression of an inflammatory module was increased, and expression of a wound healing module was decreased. This supports findings reporting an association between PTSD and dysregulations of the inflammatory and the hemostatic system and mark both as potentially treatment sensitive.

Factor structure of the posttraumatic stress disorder checklist (PCL-17) in 279,897 million veteran program participants

The Million Veteran Program (MVP) uses the posttraumatic stress disorder symptoms (PTSD) Checklist 17 (PCL-17) self-report to assess PTSD. Existing literature suggests that the five-factor dysphoric arousal model best represents the PTSD symptom clusters; this can be tested within MVP, one of the largest samples collected with suitable data. We compared factor models within MVP across genetically defined subsamples (ancestry [European, African, admixed American, and East Asian], sex) via multi-group confirmatory factor analyses in a sample of 279,897 participants. The five-factor dysphoric arousal model best fit the PCL-17 data, consistent with previous findings. The factor structure could also be imposed across all groups tested. Verifying the factor structure provides a framework for future phenotypic and genotypic analyses within MVP and other samples.

Aberrant white matter microstructure evaluation by automated fiber quantification in typhoon-related post-traumatic stress disorder

Super typhoons can lead to post-traumatic stress disorder (PTSD), which can adversely affect a person's mental health after a disaster. Neuroimaging studies suggest that patients with PTSD may have post-exposure abnormalities of the white matter. However, little is known about these defects, if they are localized to specific regions of the white matter fibers, or whether they may be potential biomarkers for PTSD. Typhoon survivors with PTSD (n = 27), trauma-exposed controls (TEC) (n = 33), and healthy controls (HCs) (n = 30) were enrolled. We used automated fiber quantification (AFQ) to process the participants' DTI and compared diffusion metrics among the three groups. To evaluate diagnostic value, we used support vector machine (SVM) and a random forest (RF) classifier to build a machine learning model. White matter fiber segmentation between the three groups was found to be statistically significant for the fractional anisotropy (FA) value of the right anterior thalamic radiation (ATR) (26-50 nodes) and right uncinate fasciculus (UF) (60-72 nodes) (FDR correction, p < 0.05). By analyzing the characteristics of the machine learning model, the two most important variables were the right ATR and right UF for differentiating PTSD and trauma-exposed controls (TEC) from the healthy controls (HC). In addition, the left cingulum cingulate and left UF were the most critical variables in the differentiation of PTSD and TEC. AFQ with machine learning can localize abnormalities in specific regions of white matter fibers. These regions may be used as a diagnostic biomarker for PTSD.

Stress and the brain transcriptome: Identifying commonalities and clusters in standardized data from published experiments

Interpretation of transcriptomic experiments is hindered by many problems including false positives/negatives inherent to big-data methods and changes in gene nomenclature. To find the most consistent effect of stress on brain transcriptome, we retrieved data from 79 studies applying animal models and 3 human studies investigating post-traumatic stress disorder (PTSD). The analyzed data were obtained either with microarrays or RNA sequencing applied to samples collected from more than 1887 laboratory animals and from 121 human subjects. Based on the initial database containing a quarter million differential expression effect sizes representing transcripts in three species, we identified the most frequently reported genes in 223 stress-control comparisons. Additionally, the analysis considers sex, individual vulnerability and contribution of glucocorticoids. We also found an overlap between gene expression in PTSD patients and animals which indicates relevance of laboratory models for human stress response. Our analysis points to genes that, as far as we know, were not specifically tested for their role in stress response (Pllp, Arrdc2, Midn, Mfsd2a, Ccn1, Htra1, Csrnp1, Tenm4, Tnfrsf25, Sema3b, Fmo2, Adamts4, Gjb1, Errfi1, Fgf18, Galnt6, Slc25a42, Ifi30, Slc4a1, Cemip, Klf10, Tom1, Dcdc2c, Fancd2, Luzp2, Trpm1, Abcc12, Osbpl1a, Ptp4a2). Provided transcriptomic resource will be useful for guiding the new research.

Severe, but not moderate asthmatics share blood transcriptomic changes with post-traumatic stress disorder and depression

Asthma, an inflammatory disorder of the airways, is one of the most common chronic illnesses worldwide and is associated with significant morbidity. There is growing recognition of an association between asthma and mood disorders including post-traumatic stress disorder (PTSD) and major depressive disorder (MDD). Although there are several hypotheses regarding the relationship between asthma and mental health, there is little understanding of underlying mechanisms and causality. In the current study we utilized publicly available datasets of human blood mRNA collected from patients with severe and moderate asthma, MDD, and PTSD. We performed differential expression (DE) analysis and Gene Set Enrichment Analysis (GSEA) on diseased subjects against the healthy subjects from their respective datasets, compared the results between diseases, and validated DE genes and gene sets with 4 more independent datasets. Our analysis revealed that commonalities in blood transcriptomic changes were only found between the severe form of asthma and mood disorders. Gene expression commonly regulated in PTSD and severe asthma, included ORMDL3 a gene known to be associated with asthma risk and STX8, which is involved in TrkA signaling. We also identified several pathways commonly regulated to both MDD and severe asthma. This study reveals gene and pathway regulation that potentially drives the comorbidity between severe asthma, PTSD, and MDD and may serve as foci for future research aimed at gaining a better understanding of both the relationship between asthma and PTSD, and the pathophysiology of the individual disorders.

Central and Peripheral Immune Dysregulation in Posttraumatic Stress Disorder: Convergent Multi-Omics Evidence

Posttraumatic stress disorder (PTSD) is a chronic and multifactorial disorder with a prevalence ranging between 6–10% in the general population and ~35% in individuals with high lifetime trauma exposure. Growing evidence indicates that the immune system may contribute to the etiology of PTSD, suggesting the inflammatory dysregulation as a hallmark feature of PTSD. However, the potential interplay between the central and peripheral immune system, as well as the biological mechanisms underlying this dysregulation remain poorly understood. The activation of the HPA axis after trauma exposure and the subsequent activation of the inflammatory system mediated by glucocorticoids is the most common mechanism that orchestrates an exacerbated immunological response in PTSD. Recent high-throughput analyses in peripheral and brain tissue from both humans with and animal models of PTSD have found that changes in gene regulation via epigenetic alterations may participate in the impaired inflammatory signaling in PTSD. The goal of this review is to assess the role of the inflammatory system in PTSD across tissue and species, with a particular focus on the genomics, transcriptomics, epigenomics, and proteomics domains. We conducted an integrative multi-omics approach identifying TNF (Tumor Necrosis Factor) signaling, interleukins, chemokines, Toll-like receptors and glucocorticoids among the common dysregulated pathways in both central and peripheral immune systems in PTSD and propose potential novel drug targets for PTSD treatment.

Blood transcriptome analysis: Ferroptosis and potential inflammatory pathways in post-traumatic stress disorder

BACKGROUND

Transcriptome-wide analysis of peripheral blood in post-traumatic stress disorder (PTSD) indicates widespread changes in immune-related pathways and function. Ferroptosis, an iron-dependent regulated cell death, is closely related to oxidative stress. However, little is known as to whether ferroptosis plays a role in PTSD.

METHODS

We conducted a comprehensive analysis of combined data from six independent peripheral blood transcriptional studies in the Gene Expression Omnibus (GEO) database, covering PTSD and control individuals. Differentially expressed genes (DEGs) were extracted by comparing PTSD patients with control individuals, from which 29 ferroptosis-related genes (FRGs) were cross-matched and obtained. The weighted gene co-expression network analysis (WGCNA), the Extreme Gradient Boosting (XGBoost) model with Bayesian Optimization, and the least absolute shrinkage and selection operator (LASSO) Cox regression were utilized to construct a PTSD prediction model. Single-sample Gene Set Enrichment Analysis (ssGSEA) and CIBERSORT revealed the disturbed immunologic state in PTSD high-risk patients.

RESULTS

Three crucial FRGs (ACSL4, ACO1, and GSS) were identified and used to establish a predictive model of PTSD. The receiver operating characteristic (ROC) curve verifies its risk prediction ability. Remarkably, ssGSEA and CIBERSORT demonstrated changes in cellular immunity and antigen presentation depending on the FRGs model.

CONCLUSION

These findings collectively provide evidence that ferroptosis may change immune status in PTSD and be related to the occurrence of PTSD, which may help delineate mechanisms and discover treatment biomarkers for PTSD.

CPEB3-dowregulated Nr3c1 mRNA translation confers resilience to developing posttraumatic stress disorder-like behavior in fear-conditioned mice

Susceptibility or resilience to posttraumatic stress disorder (PTSD) depends on one's ability to appropriately adjust synaptic plasticity for coping with the traumatic experience. Activity-regulated mRNA translation synthesizes plasticity-related proteins to support long-term synaptic changes and memory. Hence, cytoplasmic polyadenylation element-binding protein 3-knockout (CPEB3-KO) mice, showing dysregulated translation-associated synaptic rigidity, may be susceptible to PTSD-like behavior. Here, using a context-dependent auditory fear conditioning and extinction paradigm, we found that CPEB3-KO mice exhibited traumatic intensity-dependent PTSD-like fear memory. A genome-wide screen of CPEB3-bound transcripts revealed that Nr3c1, encoding glucocorticoid receptor (GR), was translationally suppressed by CPEB3. Thus, CPEB3-KO neurons with elevated GR expression exhibited increased corticosterone-induced calcium influx and decreased mRNA and protein levels of brain-derived neurotrophic factor (Bdnf). Moreover, the reduced expression of BDNF was associated with increased GR level during fear extinction in CPEB3-KO hippocampi. Intracerebroventricular delivery of BDNF before extinction training mitigated spontaneous fear intrusion in CPEB3-KO mice during extinction recall. Analysis of two GEO datasets revealed decreased transcriptomic expression of CPEB3 but not NR3C1 in peripheral blood mononuclear cells of humans with PTSD. Collectively, this study reveals that CPEB3, as a potential PTSD-risk gene, downregulates Nr3c1 translation to maintain proper GR-BDNF signaling for fear extinction.

Gene Expression Analysis in Three Posttraumatic Stress Disorder Cohorts Implicates Inflammation and Innate Immunity Pathways and Uncovers Shared Genetic Risk With Major Depressive Disorder

Posttraumatic stress disorder (PTSD) is a complex psychiatric disorder that can develop following exposure to traumatic events. The Psychiatric Genomics Consortium PTSD group (PGC-PTSD) has collected over 20,000 multi-ethnic PTSD cases and controls and has identified both genetic and epigenetic factors associated with PTSD risk. To further investigate biological correlates of PTSD risk, we examined three PGC-PTSD cohorts comprising 977 subjects to identify differentially expressed genes among PTSD cases and controls. Whole blood gene expression was quantified with the HumanHT-12 v4 Expression BeadChip for 726 OEF/OIF veterans from the Veterans Affairs (VA) Mental Illness Research Education and Clinical Center (MIRECC), 155 samples from the Injury and Traumatic Stress (INTRuST) Clinical Consortium, and 96 Australian Vietnam War veterans. Differential gene expression analysis was performed in each cohort separately followed by meta-analysis. In the largest cohort, we performed co-expression analysis to identify modules of genes that are associated with PTSD and MDD. We then conducted expression quantitative trait loci (eQTL) analysis and assessed the presence of eQTL interactions involving PTSD and major depressive disorder (MDD). Finally, we utilized PTSD and MDD GWAS summary statistics to identify regions that colocalize with eQTLs. Although not surpassing correction for multiple testing, the most differentially expressed genes in meta-analysis were interleukin-1 beta (IL1B), a pro-inflammatory cytokine previously associated with PTSD, and integrin-linked kinase (ILK), which is highly expressed in brain and can rescue dysregulated hippocampal neurogenesis and memory deficits. Pathway analysis revealed enrichment of toll-like receptor (TLR) and interleukin-1 receptor genes, which are integral to cellular innate immune response. Co-expression analysis identified four modules of genes associated with PTSD, two of which are also associated with MDD, demonstrating common biological pathways underlying the two conditions. Lastly, we identified four genes (UBA7, HLA-F, HSPA1B, and RERE) with high probability of a shared causal eQTL variant with PTSD and/or MDD GWAS variants, thereby providing a potential mechanism by which the GWAS variant contributes to disease risk. In summary, we provide additional evidence for genes and pathways previously reported and identified plausible novel candidates for PTSD. These data provide further insight into genetic factors and pathways involved in PTSD, as well as potential regions of pleiotropy between PTSD and MDD.

Excessive daytime sleepiness is associated with altered gene expression in military personnel and veterans with posttraumatic stress disorder: an RNA sequencing study

STUDY OBJECTIVES

Posttraumatic stress disorder (PTSD) is a common condition for military personnel and veterans. PTSD has been shown to impact gene expression, however, to date no study has examined comorbid conditions which may also impact gene expression, for example, excessive daytime sleepiness (EDS). As such, this study sought to examine gene expression using RNA sequencing across three group comparisons of military personnel and veterans: (1) PTSD with EDS (PTSDwEDS) versus PTSD without EDS (PTSDw/outEDS), (2) Controls (no PTSD or EDS) versus PTSDwEDS, and (3) Controls versus PTSDw/outEDS.

METHODS

We performed experimental RNA-seq using Illumina's HiSeq 2500 Sequencing System. We also used Ingenuity Pathway Analysis (IPA), a bioinformatics application, to identify gene pathways and networks which may be disrupted.

RESULTS

There were only two genes that were significantly dysregulated between the Controls and PTSDw/outEDS, therefore IPA analysis was not conducted. However, comparisons revealed that there was significant gene dysregulation between Controls and the PTSDwEDS (251 genes), and the PTSDwEDS versus the PTSDw/outEDS (1,873 genes) groups. Four candidate networks were identified via the IPA software for analysis. Significantly dysregulated genes across the four candidate networks were associated with sleep and circadian function, metabolism, mitochondrial production and function, ubiquitination, and the glutamate system.

CONCLUSIONS

These results suggest that PTSD with concurrent EDS is associated with gene dysregulation. This dysregulation may present additional biological and health consequences for these military personnel and veterans. Further research, to track these gene changes over time and to determine the cause of the EDS reported, is vital.

Analysis of 12 GWAS-Linked Loci With Parkinson's Disease in the Chinese Han Population

A recent large-scale European-originated genome-wide association study identified 38 novel independent risk signals in 37 loci for Parkinson's disease (PD). However, whether these new loci are associated with PD in Asian populations remains elusive. The present study aimed to explore the relationship between the 12 most relevant loci with larger absolute values for these new risk loci and PD in the Chinese Han population. We performed a case-control study including 527 PD patients and 435 healthy controls. In the allele model, it was found that rs10748818/GBF1 was associated with PD in the Chinese Han population [p = 0.035, odds ratio (OR) 1.221, 95% confidence interval (CI) 1.014–1.472

Symptom severity impacts sympathetic dysregulation and inflammation in post-traumatic stress disorder (PTSD)

Post-traumatic stress disorder (PTSD) is associated with a greater risk of incident hypertension and cardiovascular disease. Inflammation, impaired baroreflex sensitivity (BRS) decreased parasympathetic nervous system (PNS) and overactive sympathetic nervous system (SNS) activity are suggested as contributing mechanisms. Increasing severity of PTSD symptoms has been linked to greater cardiovascular risk; however, the impact of PTSD symptom severity on inflammation and autonomic control of blood pressure has not yet been explored. We hypothesized that increasing PTSD symptom severity is linked to higher inflammation, greater SNS activity, lower PNS reactivity and impaired BRS. Seventy Veterans participated in this study: 28 with severe PTSD ((Clinical Administered PTSD Scale (CAPS) > 60; S-PTSD), 16 with moderate PTSD (CAPS ≥ 45 ≤ 60; M-PTSD) and 26 Controls (CAPS < 45; NO-PTSD). We recorded continuous blood pressure (BP), heart rate (HR) via EKG, heart rate variability (HRV) markers reflecting PNS and muscle sympathetic nerve activity (MSNA) at rest, during arterial baroreflex sensitivity (BRS) testing via the modified Oxford technique, and during 3 min of mental stress via mental arithmetic. Blood samples were analyzed for 12 biomarkers of systemic and vascular inflammation. While BP was comparable between severity groups, HR tended to be higher (p = 0.055) in S-PTSD (76 ± 2 beats/min) than in Controls (67 ± 2 beats/min) but comparable to M-PTSD (70 ± 3 beats/min). There were no differences in resting HRV and MSNA between groups; however, cardiovagal BRS was blunted (p = 0.021) in S-PTSD (10 ± 1 ms/mmHg) compared to controls (16 ± 3 ms/mmHg) but comparable to M-PTSD (12 ± 2 ms/mmHg). Veterans in the S-PTSD group had a higher (p < 0.001) combined inflammatory score compared to both M-PTSD and NO-PTSD. Likewise, while mental stress induced similar SNS and cardiovascular responses between the groups, there was a greater reduction in HRV in S-PTSD compared to both M-PTSD and NO-PTSD. In summary, individuals with severe PTSD symptoms have higher inflammation, greater impairment of BRS, a trend towards higher resting HR and exaggerated PNS withdrawal at the onset of mental stress that may contribute to cardiovascular risk in severe PTSD.