The relationship between COVID-19, depressive disorder, and anxiety: a bidirectional Mendelian randomization study

Background Previous clinical studies have found that negative mental states such as depression and anxiety are closely related to COVID-19 infection. We used Mendelian randomization (MR) to explore the relationship between depression, anxiety, and COVID-19 infection. Methods Our data were based on publicly available GWAS databases. The COVID-19 samples were obtained from the COVID-19 Host Genetics Initiative (HGI). The depression samples were obtained from the Psychiatric Genomics Consortium (PGC). The anxiety samples were derived from the Finngen database. We used inverse-variance weighting (IVW) as the primary analysis method, with weighted median, MR Egger, and multivariate MRI adjustment. Results There was no causal effect of different COVID-19 infection statuses on depression and anxiety as determined by MR analysis. In addition, in the reverse MR analysis, we found a significant causal effect of anxiety on severe symptoms after COVID-19 infection. The results of the MR Egger regression, weighted median, and weighted mode methods were consistent with the IVW method. Based on sensitivity analyses, horizontal pleiotropy was unlikely to influence the final results. Conclusion Our findings indicate that anxiety is a risk factor for severe symptoms following COVID-19 infection. However, the mechanism of interaction between the two needs further investigation.


. Introduction
From 2019 to 2022, COVID-19 spread worldwide, causing severe public health issues on a global scale.It is an infectious disease caused by the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), with an estimated 2.75 billion persons at risk of infection (1).Despite the end of the pandemic, many patients have been found to have acute SARS-CoV-2 sequelae, also known as long COVID or post-COVID-19 syndrome (2).The World Health Organization (WHO) defines it as a condition in which individuals who have been diagnosed or may have been infected with SARS-CoV-2 in the past have persistent symptoms within 3 months of onset that persist for at least 2 months and cannot be explained by an alternative diagnosis (3).
The main symptoms of COVID-19 sequelae include shortness of breath, cognitive dysfunction, fatigue, anxiety, and depression (4).Compared to the latest WHO incidence rates for common mental health disorders, the incidence of depression in patients with COVID-19 was three times higher (15.97%) than in the general population; The prevalence of anxiety disorders is four times higher than in the general population (15.15% higher than in the general population) (5).
Depression is a prevalent mental illness that affects many individuals.In clinical practice, the most common symptoms are a depressed mood, a lack of interest, and impaired cognitive function (6).According to the most recent data, there are approximately 264 million patients worldwide (7).Major depressive disorder (MDD) can even lead to suicide and death.Depression has arisen as a risk factor for numerous illnesses.Many studies have shown that there is a significant increase in the incidence of depression in people infected with COVID-19 (8).Clinical studies have suggested that anxiety and depression are risk factors for COVID-19 infection and will lead to a longer recovery period after COVID-19 infection (9,10).Due to the negative effects of social isolation and disruptions in health services on people's mental health and wellbeing, researchers believe that the increase in depression following COVID-19 infection is likely to be comparable to the increase following other previous pandemics, such as SARS (severe acute respiratory syndrome) and MERS (Middle East respiratory syndrome coronavirus) (4,11).
Genetic factors significantly influence the susceptibility to and the severity of a wide range of infectious diseases and psychiatric disorders.Several recent studies have found the same genetic factor linking psychiatric disorders and infectious diseases.The presence of numerous SNP sites on the HLA gene associated with psychiatric disorders and mutations in these sites may affect the immune response to foreign antigens, which may account for the increased incidence of infections and inflammation in patients with schizophrenia and bipolar disorder and their parents (12).A large Danish genomic study identified 90 SNPs associated with mental disorders and susceptibility, most notably rs6447952 (13).Chen analyzed GWAS data from populations with psychiatric disorders and COVID-19 infections utilizing polygenic risk scores and found that genetic susceptibility to psychiatric disorders correlated with the risk of COVID-19 and severe COVID-19 (14).
Mendelian randomization (MR) is an epidemiological research technique that uses genetic variants as instrumental variables to infer the causality of a risk factor because it employs genetic variants as instrumental variables (15,16).Mendelian randomization is independent of environmental factors and self-selected lifestyle choices (17).When the sample size is adequate, and the genetic variant is not associated with potential confounders, the quasi-random assignment of that variant outside of the exposure level ought to produce groups with nearly identical characteristics on average.MR analysis is now widely used to analyze causal relationships between diseases and risk factors, e.g., between gut microbes and disease, between two different diseases, and between metabolites and disease (18).Therefore, we used Mendelian randomization to determine whether COVID-19 as the exposure and depression/anxiety as the outcome were directly causally related.
. Materials and methods

. . Design of experiment
We hereby briefly describe the design of the bidirectional MR between COVID-19 and depression/anxiety.Using pooled data from genome-wide association studies (GWAS), we performed two MR analyses to examine bidirectional associations between various COVID-19 statuses and depression/anxiety.Reverse MR analyses used depression/anxiety as exposure and distinct COVID-19 statuses as outcomes.Figure 1 depicts the fundamental hypotheses of MR.Using three guiding principles, this study hypothesizes the following (17, 19, 20): (1) There is a substantial association between genetic variation and exposure.(2) Genetic mutations are unrelated to other confounding variables.
(3) Only exposure is associated with genetic variation and outcome.
Based on summary statistics available to the public, this research did not require ethical approval.

. . Data sources
We attempted to perform MR analysis using the COVID-19 GWAS data.The COVID-19 dataset was obtained from the COVID-19 Host Genetics Initiative (HGI).GWAS provided us with the association between COVID-19 and COVID-19 genetic associations of phenotypes.The GWAS yielded three phenotypes: (1) COVID-19 patients and the general population (38,984 (22,23).The data on patients with anxiety disorders were obtained from the Finngen database (40,191 cases and 277,526 controls).To exclude the influence of ethnicity, we chose a cohort of European populations.Details and sources of the data are given in Table 1.

. . Screen of instrumental variable (IV) for MR analysis
In order to obtain appropriate instrumental variables from different GWAS data, we first selected genome-wide significant SNPs (p < 5 × 10 −8 ) (24).To ensure linkage disequilibrium of instrumental variables, we chose kb = 10,000, r 2 < 0.001 as a condition.Finally, in order to evaluate the tool strength, we made sure the F > 10 ones were used as instrumental variables (25,26).We then harmonized the exposure and outcome datasets  .

. Statistical analysis
Using a random-effects inverse variance weighting (IVW) method, we estimated the bidirectional causality between COVID-19 status and depression/anxiety.The IVW method presupposes that all MR assumptions are legitimate.However, IV influenced the results through other pathways, indicating that horizontal pleiotropic effects may exist and that estimates of IVW causality may be biased.Therefore, we conducted sensitivity analyses utilizing the MR Egger and weighted median methodologies, allowing us to estimate causality accurately even in the presence of invalid SNPs.
As MR relies on the three central IV assumptions of the primary analysis (Figure 1), we hereby describe the methods used to evaluate or demonstrate the validity of these assumptions.The correlation hypothesis calculates r 2 , which indicates the proportion of the exposure variable's variation that can be explained by genetic variation.We calculated the f -statistics to evaluate the instrumental intensity of the relationship between IV and interest exposure risk.F represents weak instrumental vigor.MR Egger regression intercepts and their respective 95% confidence intervals (CIs) were utilized to examine the extent to which directional pleiotropy, which precludes limiting assumptions, leads to bias in arbitrary estimates.Moreover, horizontal pleiotropy was evaluated using the Mendelian randomized pleiotropy residuals and outliers (MR-PRESSO) global test, and the outlier SNPs were excluded using the MR-PRESSO outlier test.Additionally, after removing the peripheral IV, we examined whether there was a statistically significant difference between the new IV and the previous one.Using Cochran's Q statistic and funnel diagrams, we also examined the IVW and MR Egger methods for heterogeneity.Then, various sensitivity analyses (such as leave-one-out and individual SNP analyses) were conducted to determine whether individual SNPs affected primary causality.Using odds ratios (OR) and 95% confidence intervals (CIs), we estimated causality for binary outcomes.We presented causal estimates, p-values, and their standard errors for both binary and continuous outcomes.Each p-value is bilateral.All analyses were conducted utilizing the R (version 4.3.0,www.r-project.org)TwoSampleMR and Mendelian randomization packages.

FIGURE
MR analysis of depression and anxiety as outcomes using di erent infections of COVID-as exposure.

. Discussion
In this study, we explored whether there is causal between As described in the results, we found that there does not appear to be a highly significant causal link between COVID-19 infection and anxiety/depression.Only anxiety disorders were causally associated with severe reactions after COVID-19 infection, and anxiety disorders may be a risk factor for severe illness after COVID-19 infection.
Previous observational clinical studies have found that more than 50% of the infected patients have depression or anxietylike symptoms after COVID-19 infection, and anxiety and depression are also the typical symptoms of COVID-19 sequelae considered by the WHO (27, 28).In addition, researchers from the United Kingdom discovered that those infected with COVID-19 who were hospitalized were 49% more likely to be diagnosed with depression, anxiety, or a mental condition than those infected but not hospitalized (29, 30).This finding is consistent with what was discovered in the Nordic countries, where patients who had been hospitalized for more than 7 days had a significantly higher risk of depression and anxiety than those who had not been hospitalized (31).According to the results of our investigation, the presence of COVID-19 infection, the severity of the COVID-19 disease, and hospitalization for COVID-19, all appeared to have no direct causal effect on the development of depression or anxiety.As a consequence of the findings of other investigations that have been published, a number of theories have been developed.One possible explanation for the depressive and anxious symptoms exhibited by patients is that these conditions are at least partially caused by the patients' social environment (32).This may include social isolation and high levels of stress.The main sources of stress during the COVID-19 pandemic were fear of infection, frustration, boredom, lack of supplies, and economic loss (33).Fear of infection and occupational stress (increased work pressure on healthcare workers during a pandemic, increased unemployment due to changes in FIGURE MR analysis of di erent infections of COVID-as outcomes using depression and anxiety as exposure. the socio-economic environment, increased uncertainty about the future due to a pandemic and thus academic stress, etc.) were the main causes of increased stress during a pandemic (34-37).Excessive stress is one of the major causes of disorders such as depression and anxiety (38).
During COVID-19 pandemic, many individuals have been required to maintain a safe distance from one another to prevent the spread of COVID-19, resulting in social isolation (39).It is believed that social isolation causes sleep disturbances (40).Insomnia and sleep disorders are recognized as major risk factors for the development of depression and anxiety (41).Regarding social isolation-induced insomnia as a mechanism leading to melancholy and anxiety, scientists believe social isolation results in hypothalamic-pituitary-adrenal (HPA) axis dysfunction (42).The disorder of the HPA axis induces hyperexcitation and sleeplessness in the human body (43).The prevalence of insomnia symptoms (36.7%) and insomnia 19 pandemic was approximately double the prevalence reported during non-pandemic periods, with higher rates in Brazil, Canada, the United Kingdom, and the United States, where depression and anxiety rates have also increased (44).
Intensive research on inflammation and psychiatry suggests that immune system perturbations triggered by infection may specifically promote psychopathology, increasing the psychological stress of living with a potentially fatal illness and stress-related inflammation (45).Interactions between the innate and adaptive immune system and neurotransmitters underlie mood disorders, psychosis, and anxiety disorders.Similar results have been observed in the past for similar pandemics.Some researchers believe that this is due to the virus infecting the neural tissue, resulting in the latter's inflammatory response.It has been demonstrated that coronavirus has neurophilic properties and can infect brain tissues.Additionally, COVID-19 has been detected in the cerebrospinal fluid (46)(47)(48)(49).
Mental factors such as depression and are important risk factors for many diseases, such as cardiovascular diseases, digestive tract diseases, and susceptibility to viruses (50,51).Our study found a genetic causal link between anxiety disorders and symptom severity following COVID-19 infection.This is consistent with the current clinical studies that have found anxiety or depression to be a risk factor for COVID-19 infection.Patients who are depressed or anxious are not only more likely to be infected with COVID-19 than the general population but also appear to have more severe symptoms after infection (52).In addition, some studies have found that patients with depression and anxiety have a longer recovery period after COVID-19 infection, which may be related to immune dysregulation caused by the HPA system (53).The detection of serum cortisol in infected patients revealed that COVID patients had higher cortisol levels and that elevated cortisol levels were positively correlated with mortality after COVID-19 infection (54, 55).Cortisol plays a key role in the development of depression and anxiety.Is it the elevated cortisol caused by depression and anxiety that makes patients more susceptible to COVID-19 infection and more severe symptoms?Whether the increased cortisol caused by COVID-19 may lead to subsequent increases in depression and anxiety requires further research.
The very interesting finding in our study is that anxiety seems to be a risk factor for developing severe illness after a COVID-19 infection.However, depression does not seem to increase the risk of developing severe illness after COVID-19 infection.Anxiety disorders are often accompanied by autonomic arousal compared to depression (56).In addition, clinical studies have found that depressed patients have lower catecholamine levels than the normal population, while anxious patients have higher catecholamine levels than the normal population (57, 58).During the inflammatory response, catecholamine concentrations are elevated, which in turn exacerbate inflammation by promoting the secretion of pro-inflammatory cytokines such as IL-6, IL-1β, and tumor necrosis factor, especially in myeloid cells (59).This inflammatory response may be exacerbated by the higher catecholamine levels in patients with anxiety disorders themselves, leading to a more severe inflammatory response after COVID-19 infection than in normally infected individuals, with a higher chance of causing a severe reaction.
However, the results regarding the causal relationship between anxiety and the risk of severe illness after COVID-19 infection do not seem to be strong.Meanwhile, a large number of clinical studies have shown that a poor psychological state prior to COVID-19 infection is a key factor in triggering severe COVID-19 disease after infection (60).Chen et al. also analyzed GWAS data from the UK Biobank.They found that depression and anxiety were more likely to result in severe and fatal COVID-19 infections (14).We therefore consider our results to be plausible.
This study also has some limitations.First, the data we selected were from a European population lacking generalizability.We also needed more specific raw data for subgroup analyses.In future studies, we will increase the sample size, expand the population to include different ethnic groups, and collect appropriate subgroup information for more in-depth analyses.

. Conclusion
We used a much broader population sequence than in previous studies.Our study identified anxiety disorders as a risk factor for the development of severe symptoms following COVID-19 infection.Patients with anxiety disorders are more likely to have severe symptoms after COVID-19 infection than the general population.Although this association does not appear to be strong, given that anxiety disorders are risk factors for a wide range of diseases, we should pay more attention to people with anxiety disorders during future infectious disease pandemics.

FIGURE
FIGUREDescription of this bidirectional Mendelian randomization experiment.
TABLE Association of di erent COVID-statuses with depression in MR analysis.
TABLE Association of di erent COVID-statuses with anxiety in MR analysis.
TABLE Association of anxiety/depression with di erent COVID-statuses in MR analysis.