- Academic Editors
†These authors contributed equally.
Objective: We aimed to evaluate bidirectional genetic relationships between posttraumatic stress disorder (PTSD) and COVID-19. Methods: We investigated potential causal associations between PTSD and two COVID-19 conditions (COVID-19 hospitalization and SARS-CoV-2 infection) via Mendelian randomization (MR) analyses. Three genome-wide association study (GWAS) summary datasets were used in the study, including PTSD (N = 174,659), SARS-CoV-2 infection (N = 2,597,856), and COVID-19 hospitalization (N = 2,095,324). We performed a literature-based analysis to uncover molecular pathways connecting PTSD and COVID-19. Results: We found that PTSD exerts a causal effect on SARS-CoV-2 infection (odds ratio (OR): 1.10, 95% confidence interval (CI): 1.00–1.21, p = 0.048) and hospitalized COVID-19 (OR: 1.34, 95% CI: 1.07–1.67, p = 0.001). However, both SARS-CoV-2 infection and hospitalized COVID-19 were not associated with the risk of PTSD. Pathway analysis revealed that several immunity-related genes may link PTSD to COVID-19. Conclusions: Our study suggests that PTSD was associated with increased risks for COVID-19 susceptibility and severity. Early diagnosis and effective treatment of PTSD in individuals infected with the coronavirus may improve the management of the outcomes of COVID-19.
To date, numerous risk factors of COVID-19 have been identified, including cardiovascular diseases, diabetes, obesity, and smoking [1, 2, 3, 4]. The SARS-CoV-2 virus infiltrates the central nervous system, leading to neuropsychiatric manifestations [5]. The outcomes of COVID-19 are remarkably influenced by neuropsychiatric diseases and vice versa [6, 7, 8, 9, 10, 11].
Posttraumatic stress disorder (PTSD) is a common mental disorder with a prevalence of 6–8% in the general population and even higher rates in special groups [12]. The risk for PTSD depends both on genetics and past trauma history. Pathophysiology of PTSD involves dysregulation of fear- and threat-related behavior and learning within the amygdala-hippocampus-medial prefrontal cortex circuit [12, 13]. There is growing evidence indicating a higher occurrence of PTSD during the COVID-19 pandemic [14, 15, 16]. Notably, in COVID-19 survivors, total scores on the PTSD checklist for the diagnostic and statistical manual of mental disorders (DSM)-5 score were significantly higher compared with controls [17]. Overall scoping of the literature suggests that studies of PTSD as it relates to COVID-19 were mostly performed in populations stressed by the spread of SARS-Cov-2 and related public health measures rather than in COVID-19 survivors affected by the virus itself.
The mendelian randomization (MR) design can be leveraged to detect causative associations between an exposure phenotype and an outcome by utilizing genetic variants as instrumental variables [18]. The MR technique is widely used to infer causality between an exposure and an outcome [19, 20]. Previous MR studies have reported a myriad of causal risk factors for COVID-19, including obesity, higher basal metabolic rate, smoking, and others [2, 21, 22, 23].
It’s not known whether PTSD may promote the risk of COVID-19, or whether PTSD could be triggered by COVID-19 outcomes. We sought to assess the mutual causal relationships between PTSD and COVID-19 and explore molecular pathways underlying their connections.
In this study, the Genome-Wide Association Study (GWAS) data we used were obtained from two sources: the Psychiatric Genomics Consortium (PGC) and the COVID-19 Host Genetic Initiative (HGI) [24]. The PTSD GWAS summary dataset consisted of 23,212 cases and 151,447 controls [25]. The PTSD data included a wide range of participant profiles, who were exposed to various types of trauma, encompassing both civilian and military contexts, and in most cases, they also had a history of trauma exposure during childhood.
The COVID-19 datasets used in the study consisted of data on SARS-CoV-2 infections (COVID vs. population), which included 122,616 cases and 2,475,240 controls, as well as data on hospitalized COVID-19 (Hospitalized COVID vs. Population), which included 32,519 cases and 2,062,805 controls. The SARS-CoV-2 infection dataset provides insights into the general vulnerability to the virus. Because hospitalized COVID-19 was a severe outcome of the disease, we called it “severe COVID-19”.
The MR analysis was achieved by the inverse variance weighting (IVW) model in
the TwoSampleMR package (https://github.com/MRCIEU/TwoSampleMR) (version 0.5.6)
[26]. The weighted median (WM) and MR-Egger models were employed as complementary
measures to assess the sensitivity of the MR analysis. Potential horizontal
pleiotropy was gauged by the intercept of the MR-Egger regression, and
heterogeneity by both Cochran’s Q test (p
First, we evaluated the causal effects of PTSD on the two COVID-19 phenotypes.
The PTSD dataset was used as exposure and the three COVID-19 datasets were used
as outcomes. Then, we performed the reverse MR analyses by using the three
COVID-19 datasets as exposures and the PTSD dataset as outcomes. For each MR
analysis, we selected single nucleotide polymorphisms (SNPs) associated with the
exposure trait (p
To unravel molecular connections between PTSD and COVID-19, we leveraged the Pathway Studio environment to perform literature-based data mining [27]. The downstream targets and upstream regulators of PTSD and COVID-19 were obtained. Molecular pathways were then constructed between PTSD and COVID-19. More details were described previously [6]. In this study, we called the molecules/genes connecting PTSD and COVID-19 “mediating molecules/genes”.
In the MR analyses of the causal effects of PTSD on COVID-19 outcomes, we
obtained a total of 37 independent SNPs associated with PTSD at a significance
level of p
Exposure | Outcome | Method | b (se) | OR [95% CI] | N_IV | Q_p | I |
Egger_intercept | p_pleiotropy | p |
PTSD | SARS-CoV-2 infection | IVW | 0.094 (0.047) | 1.10 [1.00–1.21] | 37 | 0.695 | –0.15 | NA | NA | 0.048 |
PTSD | SARS-CoV-2 infection | WM | 0.018 (0.071) | 1.02 [0.89–1.17] | 37 | NA | NA | NA | NA | 0.796 |
PTSD | SARS-CoV-2 infection | MR Egger | 0.162 (0.112) | 1.18 [0.94–1.46] | 37 | 0.673 | –0.17 | –0.002 | 0.507 | 0.156 |
PTSD | Hospitalized COVID-19 | IVW | 0.292 (0.112) | 1.34 [1.07–1.67] | 37 | 0.251 | 0.128 | NA | NA | 9.29 × 10 |
PTSD | Hospitalized COVID-19 | WM | 0.174 (0.147) | 1.19 [0.89–1.59] | 37 | NA | NA | NA | NA | 0.237 |
PTSD | Hospitalized COVID-19 | MR Egger | –0.073 (0.262) | 0.93 [0.56–1.55] | 37 | 0.307 | 0.069 | 0.011 | 0.134 | 0.783 |
WM, Weighted median; IVW, inverse variance weighted; CI, confidence interval; OR, odds ratio; b, effect size; N_IV, number of instrumental variables; se, standard error; Q_P, p-value of heterogeneity analysis; PTSD, posttraumatic stress disorder; MR, Mendelian randomization; NA, not applicable.
Causal associations between PTSD and COVID-19. The upper panel shows the causal effects of PTSD on COVID-19 outcomes. Each point represents a specific SNP. The x-axis represents the SNPs’ effect on the exposure factor (PTSD), and the y-axis represents the SNPs’ effect on the disease outcomes (SARS-CoV-2 infection and hospitalized COVID-19, respectively). The lower panel displays the causal influences of COVID-19 outcomes on PTSD. The x-axis represents the SNPs’ effect on the exposure factor (SARS-CoV-2 infection and hospitalized COVID-19, respectively), and the y-axis represents the SNPs’ effect on the disease outcome (PTSD). The three lines represent the effect sizes (b) of the exposure on the disease calculated by three statistical methods: WM, IVW, and MR Egger. PTSD, posttraumatic stress disorder; SNP, single nucleotide polymorphism; WM, weighted median; IVW, inverse variance weighted; MR, Mendelian randomization.
In the MR analyses of the causal effects of the COVID-19 outcomes on PTSD, we obtained IVs from the three COVID-19 datasets. The numbers of IVs were 14 for SARS-CoV-2 infection and 33 for hospitalized COVID-19. We found that neither SARS-CoV-2 infection (OR: 0.99, 95% CI: 0.95–1.03, p = 0.702) nor hospitalized COVID-19 (OR: 1.00, 95% CI: 0.98–1.01, p = 0.836) exerted a causal effect on PTSD (Table 2 and Fig. 1).
Exposure | Outcome | Method | b (se) | OR [95% CI] | N_IV | Q_p | I |
Egger_intercept | p_pleiotropy | p |
SARS-CoV-2 infection | PTSD | IVW | –0.008 (0.021) | 0.99 [0.95–1.03] | 14 | 0.359 | 0.085 | NA | NA | 0.702 |
SARS-CoV-2 infection | PTSD | WM | –0.011 (0.027) | 0.99 [0.94–1.04] | 14 | NA | NA | NA | NA | 0.686 |
SARS-CoV-2 infection | PTSD | MR Egger | 0.017 (0.037) | 1.02 [0.95–1.09] | 14 | 0.339 | 0.031 | –0.002 | 0.418 | 0.643 |
Hospitalized COVID-19 | PTSD | IVW | –0.001 (0.007) | 1.00 [0.98–1.01] | 33 | 0.462 | 0.0029 | NA | NA | 0.836 |
Hospitalized COVID-19 | PTSD | WM | –0.001 (0.011) | 1.00 [0.98–1.02] | 33 | NA | NA | NA | NA | 0.947 |
Hospitalized COVID-19 | PTSD | MR Egger | 0.006 (0.013) | 1.01 [0.98–1.03] | 33 | 0.436 | –0.012 | –0.001 | 0.495 | 0.639 |
WM, Weighted median; IVW, inverse variance weighted; CI, confidence interval; OR, odds ratio; b, effect size; se, standard error; Q_P, p-value of heterogeneity analysis; N_IV, number of instrumental variables; PTSD, posttraumatic stress disorder; NA, not applicable.
The results of the sensitivity analyses revealed consistent directions of causal
effects among the various methods employed (Tables 1,2). The MR-Egger regression
test did not provide evidence of directional pleiotropy (with an MR-Egger
intercept
Mining of the molecular pathways discovered a total of 17 genes mediating the connections between PTSD and COVID-19 (Fig. 2). A set of 13 PTSD-related genes which quantitatively change in PTSD and also enhance COVID-19 includes angiotensin II, arginine vasopressin (AVP), C-reactive protein (CRP), C-X-C motif chemokine ligand 8 (CXCL8), interleukin (IL)10, IL17A, IL2, IL6, insulin (INS), oxytocin (OXT), perforin 1 (PRF1), substance P, and tumor necrosis factor (TNF). A total of 4 PTSD-driven genetic changes may suppress the risk of COVID-19, including albumin (ALB), cluster of differentiation 4 (CD4), steroid 5 alpha-reductase 1 (SRD5A1), and IL1A.
Molecular pathways connecting PTSD and COVID-19. Promoting
effects are shown in red, and inhibitory effects are shown in green. The line
“–+
Following the pandemic, there have been numerous reports of elevated levels of mental disorders [14]. Conversely, mental disorders and psychiatric conditions might contribute to a higher susceptibility to COVID-19 [28, 29]. So far, evidence for associations between COVID-19 and psychiatric conditions was chiefly derived from correlational studies made in serial clinical observations. In this study, we conducted an MR analysis to explore the reciprocal relationship between PTSD and COVID-19. Our results indicated that individuals diagnosed with PTSD had a 10% greater likelihood of contracting SARS-CoV-2 and a 34% higher risk of being hospitalized due to COVID-19. Our result is consistent with a previous study showing a higher risk for severe COVID-19 outcomes in individuals with PTSD [30].
Observational studies have documented a higher likelihood of PTSD associated with COVID-19, with the prevalence of PTSD being 15.45~21.94% among COVID-19-affected populations [14, 16]. However, our results did not detect a causal effect of COVID-19 on PTSD. It is known that the COVID-19 pandemic served as a vital traumatic stressor [31]. Our analysis points out that post-pandemic PTSD may chiefly be caused by psychological reactions caused by COVID-19, rather than by COVID-19 itself, and that the high rate of psychological distress caused by COVID-19 [14] should be taken into account. It seems that COVID-19 and PTSD form a vicious circle, aggravating the risk for one another.
By using literature-based analysis, we explore potential mechanisms underlining
the connection between PTSD and COVID-19. The severity of COVID-19 may be
influenced by underlying genetics, and by prior environmental exposures, through
the induced priming of microglia [32]. Previous studies of PTSD cohorts revealed
increased circulatory levels of inflammatory cytokines, such as TNF-
Another interesting molecule connecting PTSD with the severe course of COVID-19
is the perforin which is encoded by PRF1. This gene harbors highly
prevalent, variant c.272C
Another interesting bridge between PTSD and COVID-19 is substance P and its receptor NK1 [39]. An increase in levels of substance P in cerebrospinal fluid samples of PTSD patients led to the development of selective neurokinin-1 receptor (NK-1R) antagonists as anti-PTSD candidates capable of alleviating hyperarousal [40]. As NK1 antagonism may uncouple the perception of pain from the downstream cytokine storm, nociceptive blocker Aprepitant has also been suggested as a treatment for COVID-19 [41, 42].
Individuals with PTSD exhibit a chronic stress response, leading to elevated
levels of systemic inflammation. This is evidenced by an increase in the levels
of soluble pro-inflammatory markers such as Vascular Cell Adhesion Molecule-1
(VCAM-1), TNF-
Moreover, neuroimaging-based studies have revealed that alterations in inflammatory markers can impact both the structure and function of brain-related regions [45]. The reduced levels of anti-inflammatory hormones, such as corticosteroids, also influence the inflammatory response of neural cells [46]. Thus, pre-existing neuroinflammatory changes seen in individuals with PTSD lay the groundwork for their heightened vulnerability to COVID-19, exacerbating inflammation of the nervous system responding to viral infection.
On one hand, PTSD patients tend to engage ins unhealthy lifestyles or behaviors, such as maintaining a poor diet, smoking, or lacking exercise, which may weaken their overall health status, thereby increasing their susceptibility to contracting symptomatic SARS-CoV-2. On the other hand, as previously discussed, the pre-existing state of chronic inflammation and altered pro-inflammatory hormone levels may further reduce the resistance of PTSD patients to infections, also increasing the risks. This stress, which overloads an entire body, may trigger a cytokine storm, leading to a worsening of COVID-19 condition, thereby, increasing the need for hospitalization. In the presence of neuroinflammation, the patient’s condition exacerbates further, creating a vicious cycle.
Because ethnic differences play an important role in heredity, there may be genetic composition and genetic variation differences among different populations. This can lead to differences in disease susceptibility and treatment response in specific populations, indicating that ethnic differences can impact data analysis. Since our GWAS data only includes individuals of European descent, caution is necessary when generalizing our analysis results to the overall population. Further research is needed to determine the applicability in other populations.
Additionally, since genetic variations are inherent and directly related to an individual’s genome, they are less influenced by confounding factors. Therefore, possible differences in age distributions did not affect our analysis results significantly. However, it is undeniable that age is an important factor in the severity and prognosis of COVID-19. Elderly populations with PTSD may face a higher risk of COVID-19. Therefore, in practical life, it is, indeed, important to pay more attention to elderly PTSD patients and take appropriate preventive and intervention measures.
Our study showed that PTSD is associated with an increased risk of COVID-19, primarily through the priming of neuroinflammatory cascades. Early diagnosis and treatment of PTSD in individuals infected with the coronavirus may improve the management of the outcomes of COVID-19.
Data sharing is not applicable as no data were generated or analyzed.
FZ conceived the project and supervised the study. FZ performed the research and analysed the data. HC provided help and advice on the research. AB and LF interpreted the data. YS collected and sorted references. LF, YS, and AB draft the manuscript. FZ, YS, and HC reviseded the manuscript. All authors contributed to editorial changes in the manuscript. All authors read and approved the final manuscript. All authors have participated sufficiently in the work and agreed to be accountable for all aspects of the work.
Not applicable.
The authors thank all investigators and participants from the COVID-19 Host Genetics Initiative and other groups for sharing these data.
This research received no external funding.
The authors declare no conflict of interest.
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