Genetic Predisposition Between COVID-19 and Four Mental Illnesses: A Bidirectional, Two-Sample Mendelian Randomization Study

Genetic analyses point to alterations in immune-related pathways underpinning the association between psychiatric disorders and COVID-19

Current literature suggests that people with psychiatric disorders have a higher risk of COVID-19 infection and a worse prognosis of the disease. We aimed to study the genetic contribution to these associations across seven psychiatric disorders as well as a general psychopathology factor (P-factor) and determine whether these are unique or shared across psychiatric disorders using statistical genetic techniques. Using the largest available genome-wide association studies (GWAS), we found a significant genetic overlap between depression, ADHD, PTSD, and the P-factor with both COVID-19 infection and hospitalization, and between anxiety and COVID-19 hospitalization. We used pairwise GWAS to examine this overlap on a fine-grained scale and identified specific regions of the genome shared between several psychiatric disorders, the P-factor, and COVID-19. Gene-based analysis in these genomic regions suggested possible links with immune-related pathways such as thyroid homeostasis, inflammation, and stress response. Finally, we show preliminary evidence for causal associations between depression, ADHD, PTSD, and the P-factor, and higher COVID-19 infection and hospitalization using Mendelian Randomization and Latent Causal Variable methods. Our results support the hypothesis that the relationship between psychiatric disorders and COVID-19 risk is likely due to shared alterations in immune-related pathways and is not a result of environmental factors alone, shedding light on potentially viable therapeutic targets.

Causes and consequences of major depressive disorder: An encompassing Mendelian randomization study

Background

Major depressive disorder (MDD) is a prevalent and debilitating disorder that has been associated with a range of risk factors and outcomes. Causal pathways between MDD and other traits can be studied using genetic variants as instrumental variables.

Methods

A literature review was conducted to identify 201 MDD-associated traits. For 115 traits, there were well-powered genome-wide association study (GWAS) results available that could be used to assess the genetic correlation with MDD. Of these, there were 89 meeting criteria for investigating causal associations in both directions using two-sample Mendelian randomization (TSMR). Of the traits that were not captured by GWAS, 43 could be included as outcomes of MDD using one-sample MR (OSMR). A range of methods and sensitivity tests was applied to gauge robustness of results, together with statistical power analyses to aid interpretation.

Outcomes

Moderate to strong genetic overlap was found between MDD and most traits. Support for causal effects of MDD liability were found for circadian, cognitive, diet, medical disease, endocrine, functional, inflammatory, metabolic, mortality, physical activity, reproduction, risk behavior, social, socioeconomic, and suicide outcomes. Most associations were bidirectional, although there was less evidence for diet, disease, and endocrine traits causing MDD risk. Results were robust across sensitivity analyses.

Interpretation

This study provides a systematic overview of traits putatively causally related to MDD, confirming previous findings as well as identifying new associations. Our results highlight the importance of MDD as a risk factor cross-cutting across medical, functional, and psychosocial domains and emphasize the need for concerted efforts at reducing this highly prevalent disorder.

Association of mental disorders with sepsis: a bidirectional Mendelian randomization study

Background

Substantial research evidence supports the correlation between mental disorders and sepsis. Nevertheless, the causal connection between a particular psychological disorder and sepsis remains unclear.

Methods

For investigating the causal relationships between mental disorders and sepsis, genetic variants correlated with mental disorders, including anorexia nervosa (AN), attention-deficit hyperactivity disorder (ADHD), autism spectrum disorder (ASD), bipolar disorder (BD), major depressive disorder (MDD), obsessive-compulsive disorder (OCD), panic disorder (PD), posttraumatic stress disorder (PTSD), schizophrenia (SCZ), and tourette syndrome (TS), were all extracted from the Psychiatric Genomics Consortium (PGC). The causal estimates and direction between these mental disorders and sepsis were evaluated employing a two-sample bidirectional MR strategy. The inverse variance weighted (IVW) method was the primary approach utilized. Various sensitivity analyses were performed to confirm the validity of the causal effect. Meta-analysis, multivariable MR, and mediation MR were conducted to ensure the credibility and depth of this research.

Results

The presence of AN was in relation to a greater likelihood of sepsis (OR 1.08, 95% CI 1.02-1.14; p = 0.013). A meta-analysis including validation cohorts supported this observation (OR 1.06, 95% CI 1.02-1.09). None of the investigated mental disorders appeared to be impacted when sepsis was set as the exposure factor. Even after adjusting for confounding factors, AN remained statistically significant (OR 1.08, 95% CI 1.02-1.15; p = 0.013). Mediation analysis indicated N-formylmethionine levels (with a mediated proportion of 7.47%), cystatin D levels (2.97%), ketogluconate Metabolism (17.41%) and N10-formyl-tetrahydrofolate biosynthesis (20.06%) might serve as mediators in the pathogenesis of AN-sepsis.

Conclusion

At the gene prediction level, two-sample bidirectional MR analysis revealed that mental disorder AN had a causal association with an increased likelihood of sepsis. In addition, N-formylmethionine levels, cystatin D levels, ketogluconate metabolism and N10-formyl-tetrahydrofolate biosynthesis may function as potential mediators in the pathophysiology of AN-sepsis. Our research may contribute to the investigation of novel therapeutic strategies for mental illness and sepsis.

The impact of COVID-19 on pulmonary, neurological, and cardiac outcomes: evidence from a Mendelian randomization study

Background

Long COVID is a clinical entity characterized by persistent health problems or development of new diseases, without an alternative diagnosis, following SARS-CoV-2 infection that affects a significant proportion of individuals globally. It can manifest with a wide range of symptoms due to dysfunction of multiple organ systems including but not limited to cardiovascular, hematologic, neurological, gastrointestinal, and renal organs, revealed by observational studies. However, a causal association between the genetic predisposition to COVID-19 and many post-infective abnormalities in long COVID remain unclear.

Methods

Here we employed Mendelian randomization (MR), a robust genetic epidemiological approach, to investigate the potential causal associations between genetic predisposition to COVID-19 and long COVID symptoms, namely pulmonary (pneumonia and airway infections including bronchitis, emphysema, asthma, and rhinitis), neurological (headache, depression, and Parkinson's disease), cardiac (heart failure and chest pain) diseases, and chronic fatigue. Using two-sample MR, we leveraged genetic data from a large COVID-19 genome-wide association study and various disorder-specific datasets.

Results

This analysis revealed that a genetic predisposition to COVID-19 was significantly causally linked to an increased risk of developing pneumonia, airway infections, headache, and heart failure. It also showed a strong positive correlation with chronic fatigue, a frequently observed symptom in long COVID patients. However, our findings on Parkinson's disease, depression, and chest pain were inconclusive.

Conclusion

Overall, these findings provide valuable insights into the genetic underpinnings of long COVID and its diverse range of symptoms. Understanding these causal associations may aid in better management and treatment of long COVID patients, thereby alleviating the substantial burden it poses on global health and socioeconomic systems.

Causal associations between COVID-19 and childhood mental disorders

BACKGROUND

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) can invade both the peripheral and central nervous systems and impact the function of the brain. Therefore, it is necessary to evaluate the mutual influences between COVID-19 outcomes and childhood mental disorders.

METHODS

We examined genetic correlations and potential causalities between three childhood mental disorders and three COVID-19 phenotypes by genetically proxied analyses. The three mental disorders included attention-deficit/hyperactivity disorder (ADHD, N = 292,548), Tourette's syndrome (TS, N = 14,307), and autism spectrum disorder (ASD, N = 46,350). The three COVID-19 traits included SARS-CoV-2 infection (N = 2,597,856), hospitalized COVID-19 (N = 2,095,324), and critical COVID-19 (N = 1,086,211). Literature-based analysis was used to build gene-based pathways connecting ADHD and COVID-19.

RESULTS

ADHD was positively correlated with the three COVID-19 outcomes (Rg: 0.22 ~ 0.30). Our Mendelian randomization (MR) analyses found that ADHD confers a causal effect on hospitalized COVID-19 (odds ratio (OR): 1.36, 95% confidence interval (CI): 1.10-1.69). TS confers a causal effect on critical COVID-19 (OR: 1.14, 95% CI: 1.04-1.25). Genetic liability to the COVID-19 outcomes may not increase the risk for the childhood mental disorders. Pathway analysis identified several immunity-related genes that may link ADHD to COVID-19, including CRP, OXT, IL6, PON1, AR, TNFSF12, and IL10.

CONCLUSIONS

Our study suggests that both ADHD and TS may augment the severity of COVID-19 through immunity-related pathways. However, our results did not support a causal role of COVID-19 in the risk for the childhood mental disorders.

Unraveling COVID-19 Relationship with Anxiety Disorders and Symptoms

Background

While COVID-19 outcomes are associated with increased anxiety, individuals affected by anxiety disorders are more likely to develop severe COVID-19 outcomes.

Methods

We used genome-wide data from UK Biobank (up to 420,531 participants), FinnGen Project (up to 329,077 participants), Million Veteran Program (175,163 participants), and COVID-19 Host Genetics Initiative (up to 122,616 cases and 2,475,240 controls) to investigate possible causal effects and shared genetic mechanisms linking COVID-19 outcomes to anxiety disorders and symptoms.

Results

We observed a strong genetic correlation of anxiety disorder with COVID-19 positive status (rg=0.35, p=2 × 10 -4 ) and COVID-19 hospitalization (rg=0.31, p=7.2 × 10 -4 ). Among anxiety symptoms, "Tense, sore, or aching muscles during worst period of anxiety" was genetically correlated with COVID-19 positive status (rg=0.33, p=0.001), while "Frequent trouble falling or staying asleep during worst period of anxiety" was genetically correlated with COVID-19 hospitalization (rg=0.24, p=0.004). Through a latent causal variable analysis, we observed that COVID-19 outcomes have statistically significant genetic causality proportion (gcp) on anxiety symptoms (e.g., COVID-19 positive status→"Recent easy annoyance or irritability" │gcp│=0.18, p=6.72 × 10 -17 ). Conversely, anxiety disorders appear to have a possible causal effect on COVID-19 (│gcp│=0.38, p=3.17 × 10 -9 ). Additionally, we also identified multiple loci with evidence of local genetic correlation between anxiety and COVID-19. These appear to be related to genetic effects shared with lung function, brain morphology, alcohol and tobacco use, and hematologic parameters.

Conclusions

This study provided important insights into the relationship between COVID-19 and mental health, differentiating the dynamics linking anxiety disorders to COVID-19 from the effect of COVID-19 on anxiety symptoms.

Genetic Predisposition of Both Waist Circumference and Hip Circumference Increased the Risk of Venous Thromboembolism

BACKGROUND

 Obesity, especially abdominal obesity, is an independent indicator of increased cardiovascular risk. Observational studies have shown an observational association between obesity and venous thromboembolism (VTE). As a type of VTE, pulmonary embolism (PE) is also associated with obesity. However, it is unclear whether the observed associations are causal or caused by confounding bias or reverse causality.

METHODS

 We performed a two-sample test by obtaining the exposure dataset of waist circumference (WC) and hip circumference (HC) from the Neale Laboratory Consortium's genome-wide association study summary data and the summary-level outcome data of VTE and PE from FinnGen Biobank of European ancestry to determine the causal effect of WC and HC on VTE and PE.

RESULTS

 All three Mendelian randomization methods displayed a positive association between WC/HC and VTE/PE. WC and HC were positively associated with VTE (odds ratio [OR] = 1.803 per 1 standard deviation [SD] increase in WC, 95% confidence interval [CI] = 1.393-2.333; p < 0.001; OR = 1.479 per 1 SD increase in HC, 95% CI = 1.219-1.796; p < 0.001, respectively). Furthermore, we found a causal association between genetically predicted WC/HC and a higher risk of PE (OR = 1.929 per 1 SD increase in WC, 95% CI = 1.339-2.778, p < 0.001; OR = 1.431 per 1 SD increase in HC, 95% CI =1.095-1.869; p = 0.009, respectively).

CONCLUSION

 There is a significant causal relationship between WC/HC and VTE/PE, which is consistent with observational studies. Taking measures to reduce WC/HC of obesity may help reduce the incidence of VTE/PE.

Genetically predicted green tea intake and the risk of arterial embolism and thrombosis

Background

In previous observational studies, green tea intake has been demonstrated to protect against arterial embolism and thrombosis. However, whether there is a causative connection between green tea intake and arterial embolism and thrombosis is currently unclear.

Methods

A two-sample Mendelian randomization (MR) study has been designed to explore whether there is a causal association between green tea intake and arterial embolism and thrombosis by acquiring exposure and outcome data from previously published research. Data from the MRC-IEU (data on green tea intake, 64,949 participants) consortium and the FinnGen project (data on arterial embolism and thrombosis, 278 cases of arterial thrombosis and 92,349 control participants) has been utilized to determine the causal impact of green tea intake on arterial embolism and thrombosis.

Results

We found that genetically predicted green tea intake was causally associated with a lower risk of arterial embolism and thrombosis (IVW odds ratio [OR] per SD decrease in green tea intake = 0.92 [95% confidence interval, 0.85-0.99]; p = 0.032). Moreover, the sensitivity analysis (both MR Egger regression and weighted median) yielded comparable estimates but with low precision. No directional pleiotropic effect between green tea intake and arterial embolism and thrombosis was observed in both funnel plots and MR-Egger intercepts.

Conclusions

Our study provided causal evidence that genetically predicted green tea intake may be a protective factor against arterial embolism and thrombosis.

Association Between ADHD and COVID-19 Infection and Clinical Outcomes: A Retrospective Cohort Study From Electronic Medical Records

OBJECTIVE

Though psychiatric illnesses have been associated with increased COVID-19 infection risk, limited information exists about the relationship between ADHD and COVID-19.

METHODS

Using the TriNetX COVID-19 Research Network, we examined the impact of ADHD diagnosis and treatment on COVID-19 infection rates and outcomes.

RESULTS

ADHD patients had greater risk of COVID-19 (risk ratio (RR) 1.11, 95% CI [1.09, 1.12]). Increased risk was higher in females than males, and highest among Asian and Black patients. Within 60 days after COVID-19 diagnosis, ADHD patients had lower rates of hospitalization (RR 0.91, 95% CI [0.86, 0.96]) and mechanical ventilation (RR 0.69, 95% CI [0.58, 0.83]), and a nonsignificant reduced death rate (RR 0.65, 95% CI [0.42, 1.02]). Patients who recently received ADHD medication had higher rates of COVID-19 (RR 1.13; 95% CI [1.10, 1.15]).

CONCLUSION

ADHD poses increased risk for COVID-19, but may reduce risk of severe outcomes. ADHD medications modestly impacted COVID-19 risk.

Causal associations between disorders of lipoprotein metabolism and ten cardiovascular diseases

Disorders of lipoprotein metabolism have been linked with an increased risk of cardiovascular diseases (CVDs) but the causal association is unclear. In this study, we investigated the causal association between disorders of lipoprotein metabolism and CVDs using two-sample Mendelian randomization (MR). The exposure was obtained from Finn genome-wide association studies (14,010 cases, 197,259 controls), and the corresponding CVDs were extracted from the largest published genome-wide association studies. A random-effects inverse-variance weighted method was used for the main analyses with a complementary analysis using the weighted median and MR-Egger approaches. Multiple sensitivity analyses were performed to assess horizontal pleiotropy. The MR analysis indicated positive associations of disorders of lipoprotein metabolism with coronary artery disease (odds ratio [OR] 1.670, 95% confidence interval [CI] 1.373–2.031; p < 0.001), aortic aneurysm (OR 1.394, 95% CI 1.199–1.619; p < 0.001), heart failure (OR 1.20, 95% CI 1.115–1.294; p < 0.001), hypertension (OR 1.011, 95% CI 1.006–1.091; p < 0.001), old myocardial infarction (OR 1.004, 95% CI 1.002–1.007; p = 0.001), and stroke (OR 1.002, 95% CI 1.001–1.003; p = 0.002). There is a suggestive causal relationship between disorders of lipoprotein metabolism and atrial fibrillation (OR 1.047, 95% CI 1.006–1.091; p = 0.026) and acute myocardial infarction (OR 1.003, 95% CI 1.001–1.005; p = 0.012). There was limited evidence of a causal association between disorders of lipoprotein metabolism and peripheral vascular disease and venous thromboembolism. Our findings indicate a significant causal association between disorders of lipoprotein metabolism and many CVDs, including coronary artery disease, aortic aneurysm, heart failure, hypertension, old myocardial infarction, and stroke. These associations may be useful for development of treatment strategies that regulate lipoprotein metabolism in patients with CVD.

Genetically predicted body fat mass and distribution with diabetic kidney disease: A two-sample Mendelian randomization study

The aim of this study is to apply a Mendelian randomization (MR) design to investigate the potential causal associations between the body mass index (BMI), body fat mass such as trunk fat mass and waist circumference (WC), and diabetic kidney disease (DKD). A two-sample MR study was conducted to obtain exposure and outcome data from previously published studies. The instrumental variables for BMI, trunk fat mass, and WC were selected from genome-wide association study datasets based on summary-level statistics. The random-effects inverse-variance weighted (IVW) method was used for the main analyses, and the weighted median and MR-Egger approaches were complementary. In total, three MR methods suggested that genetically predicted BMI, trunk fat mass, and WC were positively associated with DKD. Using IVW, we found evidence of causal relationships between BMI [odds ratio (OR) = 1.99; 95% confidence interval (CI), 1.47–2.69; p = 7.89 × 10−6], trunk fat mass (OR = 1.80; 95% CI, 1.28–2.53; p = 6.84 × 10−4), WC (OR = 2.48; 95% CI, 1.40–4.42; p = 1.93 × 10−3), and DKD. MR-Egger and weighted median regression also showed directionally similar estimates. Both funnel plots and MR-Egger intercepts showed no directional pleiotropic effects involving the aforementioned variables and DKD. Our MR analysis supported the causal effect of BMI, trunk fat mass, and WC on DKD. Individuals can substantially reduce DKD risk by reducing body fat mass and modifying their body fat distribution.

Hyperhomocysteinemia and intracranial aneurysm: A mendelian randomization study

Objective

To investigate the link between genetic variants associated with plasma homocysteine levels and risk of intracranial aneurysm (IA) using two-sample Mendelian randomization.

Methods

We used single-nucleotide polymorphisms associated with human plasma homocysteine levels as instrumental variables for the primary analysis in a genome-wide association study of 44,147 subjects of European ancestry. Summary-level statistics were obtained for 79,429 individuals, including 7,495 IA cases and 71,934 controls. To enhance validity, five different Mendelian randomization methods (MR-Egger, weighted median, inverse variance weighted, simple mode, and weighted mode) were used for the analyses.

Results

The inverse variance weighted analysis method produced P-values of 0.398 for aneurysmal subarachnoid hemorrhage [odds ratio (OR): 1.104; 95% confidence interval (CI): 0.878–1.387], 0.246 for IA (OR: 1.124; 95% CI: 0.923–1.368), and 0.644 for unruptured IA (OR: 1.126; 95% CI: 0.682–1.858). The MR-Egger analysis showed no association between IAs and homocysteine, with all P > 0.05.

Conclusion

Using gene-related instrumental variables, the Mendelian randomization analyses demonstrated a lack of an association between plasma homocysteine levels and IAs or aneurysmal subarachnoid hemorrhage.

The UK Biobank: A Shining Example of Genome-Wide Association Study Science with the Power to Detect the Murky Complications of Real-World Epidemiology

Genome-wide association studies (GWASs) have successfully identified thousands of genetic variants that are reliably associated with human traits. Although GWASs are restricted to certain variant frequencies, they have improved our understanding of the genetic architecture of complex traits and diseases. The UK Biobank (UKBB) has brought substantial analytical opportunity and performance to association studies. The dramatic expansion of many GWAS sample sizes afforded by the inclusion of UKBB data has improved the power of estimation of effect sizes but, critically, has done so in a context where phenotypic depth and precision enable outcome dissection and the application of epidemiological approaches. However, at the same time, the availability of such a large, well-curated, and deeply measured population-based collection has the capacity to increase our exposure to the many complications and inferential complexities associated with GWASs and other analyses. In this review, we discuss the impact that UKBB has had in the GWAS era, some of the opportunities that it brings, and exemplar challenges that illustrate the reality of using data from this world-leading resource.

Investigating the association of atopic dermatitis with ischemic stroke and coronary heart disease: A mendelian randomization study

Background: Atopic dermatitis (AD) is the most common chronic skin inflammatory disease. Prior observational studies have reported inconsistent results on the association of AD with ischemic stroke and coronary heart disease. In this study, we applied two-sample Mendelian randomization (MR) to evaluate the causal effect of AD on ischemic stroke and coronary heart disease.

Methods: Twelve single-nucleotide polymorphisms robustly associated with AD (p < 5 × 10^–8) were obtained from a genome-wide association study that included 10,788 cases and 30,047 controls by the EArly Genetics and Life course Epidemiology (EAGLE) Consortium (excluding the 23andMe study). The corresponding data for ischemic stroke (34,217 cases and 406,111 controls), large artery stroke (4,373 cases and 406,111 controls), cardioembolic stroke (7,193 cases and 406,111 controls), small vessel stroke (5,386 cases and 192,662 controls), coronary heart disease (122,733 cases and 424,528 controls), and myocardial infarction (43,676 cases and 128,199 controls) were obtained from the MR-Base platform. In the primary MR analyses, we applied the inverse variance weighted method to evaluate the associations. We performed a sensitivity analysis using weighted median, MR-Egger, weighted mode, simple mode, Mendelian Pleiotropy RESidual Sum and Outlier (MR-PRESSO), and leave-one-out methods.

Results: In the primary MR analyses, we found no causal association of genetically predicted AD with ischemic stroke [odds ratio (OR) = 1.00, 95% confidence interval (CI): 0.95–1.06], large artery stroke (OR = 1.02, 95% CI: 0.88–1.17), cardioembolic stroke (OR = 1.06, 95% CI: 0.94–1.18), small vessel stroke (OR = 1.05, 95% CI: 0.94–1.17), coronary heart disease (OR = 1.00, 95% CI: 0.94–1.05), and myocardial infarction (OR = 1.03, 95% CI: 0.98–1.09). The results from the primary MR analyses were supported in sensitivity analyses using the weighted median, weighted mode, simple mode, and MR-Egger methods and multivariable MR analyses adjusting for asthma and several traditional risk factors for ischemic stroke and coronary heart disease. MR-Egger intercepts provided no evidence of directional pleiotropy. The MR-PRESSO and leave-one-out analyses did not indicate any outlier instruments.

Conclusion: Our MR study does not support a causal association of genetically predicted AD with ischemic stroke, large artery stroke, cardioembolic stroke, small vessel stroke, coronary heart disease, and myocardial infarction.

COVID-19 infection, vaccine status, and avoidance behaviors in adults with attention deficit and hyperactivity disorder: A cross-sectional study

Objective

We aim to examine infection risk and vaccine status of COVID-19 in attention deficit and hyperactivity disorder and evaluate the impact of demographic, clinical, and COVID-19-related factors on the infection status and behavioral avoidance of COVID-19.

Methods

This cross-sectional study assessed adults with attention deficit and hyperactivity disorder recruited from an outpatient psychiatry clinic. Patients and healthy controls completed a survey on sociodemographic data, COVID-19 infection status, and vaccine status. COVID-19 Disease Perception Scale, COVID-19 Avoidance Attitudes Scale, Attitudes toward COVID-19 Vaccine Scale, Adult Attention Deficit and Hyperactivity Disorder Self-report Screening Scale for DSM-5, Adult Attention Deficit and Hyperactivity Disorder Self-Report Scale Symptoms Checklist, Patient Health Questionnaire-9, and State-Trait Anxiety Inventory were applied.

Results

Ninety patients and 40 healthy controls participated. Patients did not differ from controls in COVID-19 infection and vaccine status, and behavioral avoidance of COVID-19. No demographic and clinical factor significantly affected the COVID-19 infection status. Patients scored higher than controls in the perception of COVID-19 as contagious (p = 0.038), cognitive avoidance of COVID-19 (p = 0.008), and positive attitudes toward the COVID-19 vaccine (p = 0.024). After adjustment of possible factors, a positive perception of the COVID-19 vaccine and a perception of COVID-19 as dangerous were the two factors significantly affecting behavioral avoidance of COVID-19 [R 2 = 0. 17, F(2) = 13.189, p < 0.0001].

Conclusion

Infection and vaccine status of COVID-19 in patients did not significantly differ from controls. No demographic and clinical factor significantly affected the COVID-19 infection status. Approximately four-fifths of the patients were fully vaccinated as recommended by national and global health organizations. This has increased the knowledge base showing that the COVID-19 vaccine is acceptable and receiving the vaccine is endorsed by ADHD patients. Attention deficit and hyperactivity disorder itself may provoke no kind of mental disturbance in sense of perception of the danger of this disease. Our findings have increased the knowledge base showing that the COVID-19 vaccine is acceptable and the actual practice of receiving the vaccine is endorsed in this population. Our message for practice would be to take into account not only the core symptoms and the comorbidities of the disorder but also the perception of the disease while exploring its link with COVID-19.

Identifying factors contributing to increased susceptibility to COVID-19 risk: a systematic review of Mendelian randomization studies

BACKGROUND

To summarize modifiable factors for coronavirus disease 2019 (COVID-19) suggested by Mendelian randomization studies.

METHODS

In this systematic review, we searched PubMed, EMBASE and MEDLINE, from inception to 15 November 2021, for Mendelian randomization studies in English. We selected studies that assessed associations of genetically predicted exposures with COVID-19-related outcomes (severity, hospitalization and susceptibility). Risk of bias of the included studies was evaluated based on the consideration of the three main assumptions for instrumental variable analyses.

RESULTS

We identified 700 studies through systematic search, of which 50 Mendelian randomization studies were included. Included studies have explored a wide range of socio-demographic factors, lifestyle attributes, anthropometrics and biomarkers, predisposition to diseases and druggable targets in COVID-19 risk. Mendelian randomization studies suggested that increases in smoking, obesity and inflammatory factors were associated with higher risk of COVID-19. Predisposition to ischaemic stroke, combined bipolar disorder and schizophrenia, attention-deficit and hyperactivity disorder, chronic kidney disease and idiopathic pulmonary fibrosis was potentially associated with higher COVID-19 risk. Druggable targets, such as higher protein expression of histo-blood group ABO system transferase (ABO), interleukin (IL)-6 and lower protein expression of 2'-5' oligoadenylate synthetase 1 (OAS1) were associated with higher risk of COVID-19. There was no strong genetic evidence supporting the role of vitamin D, glycaemic traits and predisposition to cardiometabolic diseases in COVID-19 risk.

CONCLUSION

This review summarizes modifiable factors for intervention (e.g. smoking, obesity and inflammatory factors) and proteomic signatures (e.g. OAS1 and IL-6) that could help identify drugs for treating COVID-19.

Causal Associations between Paternal Longevity and Risks of Cardiovascular Diseases

Background: Observational studies have suggested that paternal longevity is associated with reduced risks of cardiovascular diseases, yet the causal association remains to be determined. Objectives: To investigate whether Mendelian randomization (MR) results support a causal role of paternal longevity for risks of cardiovascular diseases. Methods: Genetic variants associated with paternal longevity and cardiovascular diseases were obtained from public genome-wide association study data. We used inverse variance weighted MR under a random-effects model to provide causal estimates between paternal longevity and cardiovascular diseases. Results: Paternal longevity was associated with decreased risks of coronary heart disease (odds ratio (OR): 0.08; 95% confidence interval (CI): 0.02–0.37; p = 0.001) and peripheral artery disease (OR: 0.15; 95% CI: 0.03–0.65; p = 0.011). No significant differences were observed in hypertension, atrial fibrillation, heart failure, transient ischemic attack, ischemic stroke, or cardiac death. The weighted median method revealed consistent results between genetically instrumented paternal longevity and decreased risk of coronary heart disease and peripheral artery disease. No significant differences were observed in the MR-Egger results. Multivariable MR consistently indicated causal associations between paternal longevity and decreased cardiovascular diseases. The leave-one-out analysis suggested that the causal associations were not affected by individual single-nucleotide polymorphisms. The intercept of the MR-Egger estimator and funnel plot revealed no indication of horizontal pleiotropic effects. Conclusions: Our MR analyses supported a causal role of paternal longevity for decreased risks of coronary heart disease and peripheral artery disease, which highlighted the need for better monitoring and intervention of cardiovascular diseases in populations with premature paternal death.

Genetic Predisposition of Anti-Cytomegalovirus Immunoglobulin G Levels and the Risk of 9 Cardiovascular Diseases

Background

Accumulating evidence has indicated that persistent human cytomegalovirus (HCMV) infection is associated with several cardiovascular diseases including atherosclerosis and coronary artery disease. However, whether there is a causal association between the level of anti-HCMV immune response and the risk of cardiovascular diseases remains unknown.

Methods

Single-nucleotide polymorphisms associated with anti-cytomegalovirus immunoglobulin (Ig) G levels were used as instrumental variables to estimate the causal effect of anti-cytomegalovirus IgG levels on 9 cardiovascular diseases (including atrial fibrillation, coronary artery disease, hypertension, heart failure, peripheral artery disease, pulmonary embolism, deep vein thrombosis of the lower extremities, rheumatic valve diseases, and non-rheumatic valve diseases). For each cardiovascular disease, Mendelian randomization (MR) analyses were performed. Inverse variance-weighted meta-analysis (IVW) with a random-effects model was used as a principal analysis. In addition to this, the weighted median approach and MR-Egger method were used for further sensitivity analysis.

Results

In the IVW analysis, genetically predicted anti-cytomegalovirus IgG levels were suggestively associated with coronary artery disease with an odds ratio (OR) of 1.076 [95% CI, 1.009–1.147; p = 0.025], peripheral artery disease (OR 1.709; 95% CI, 1.039–2.812; p = 0.035), and deep vein thrombosis (OR 1.002; 95% CI, 1.000–1.004; p = 0.025). In the further analysis, similar causal associations were obtained from weighted median analysis and MR-Egger analysis with lower precision. No notable heterogeneities and horizontal pleiotropies were observed (p > 0.05).

Conclusions/Interpretation

Our findings first provide direct evidence that genetic predisposition of anti-cytomegalovirus IgG levels increases the risk of coronary artery disease, peripheral artery disease, and deep vein thrombosis.

Clinical and Socio-Demographic Variables Associated with the Diagnosis of Long COVID Syndrome in Youth: A Population-Based Study

This study examines the demographic, clinical and socioeconomic factors associated with diagnosis of long COVID syndrome (LCS). Data of 20,601 COVID-19-positive children aged 5 to 18 years were collected between 2020 and 2021 in an Israeli database. Logistic regression analysis was used to evaluate the adjusted odds ratio for the characteristics of the COVID-19 infection and pre-COVID-19 morbidities. Children with LCS were significantly more likely to have been severely symptomatic, required hospitalization, and experienced recurrent acute infection within 180 days. In addition, children with LCS were significantly more likely to have had ADHD, chronic urticaria, and allergic rhinitis. Diagnosis of LCS is significantly associated with pre-COVID-19 ADHD diagnosis, suggesting clinicians treating ADHD children who become infected with COVID-19 remain vigilant for the possibility of LCS. Although the risk of severe COVID-19 infection and LCS in children is low, further research on possible morbidity related to LCS in children is needed.

Causal relationship between physical activity, leisure sedentary behaviors and COVID-19 risk: a Mendelian randomization study

BACKGROUND

The 2019 coronavirus disease pandemic (COVID-19) poses an enormous threat to public health worldwide, and the ensuing management of social isolation has greatly decreased opportunities for physical activity (PA) and increased opportunities for leisure sedentary behaviors (LSB). Given that both PA and LSB have been established as major influencing factors for obesity, diabetes and cardiometabolic syndrome, whether PA/LSB in turn affects the susceptibility to COVID-19 by disrupting metabolic homeostasis remains to be explored. In this study, we aimed to systematically evaluate the causal relationship between PA/LSB and COVID-19 susceptibility, hospitalization and severity using a Mendelian randomization study.

METHODS

Data were obtained from a large-scale PA dataset (N = 377,000), LSB dataset (N = 422,218) and COVID-19 Host Genetics Initiative (N = 2,586,691). The causal effects were estimated with inverse variance weighted, MR-Egger, weighted median and MR-PRESSO. Sensitivity analyses were implemented with Cochran's Q test, MR-Egger intercept test, MR-PRESSO, leave-one-out analysis and the funnel plot. Risk factor analyses were further conducted to investigate the potential mediators.

RESULTS

Genetically predicted accelerometer-assessed PA decreased the risk for COVID-19 hospitalization (OR = 0.93, 95% CI 0.88-0.97; P = 0.002), while leisure television watching significantly increased the risk of COVID-19 hospitalization (OR = 1.55, 95% CI 1.29-1.88; P = 4.68 × 10-6) and disease severity (OR = 1.85, 95% CI 1.33-2.56; P = 0.0002) after Bonferroni correction. No causal effects of self-reported moderate to vigorous physical activity (MVPA), accelerometer fraction of accelerations > 425 milligravities, computer use or driving on COVID-19 progression were observed. Risk factor analyses indicated that the above causal associations might be mediated by several metabolic risk factors, including smoking, high body mass index, elevated serum triglyceride levels, insulin resistance and the occurrence of type 2 diabetes.

CONCLUSION

Our findings supported a causal effect of accelerometer-assessed PA on the reduced risk of COVID-19 hospitalization as well as television watching on the increased risk of COVID-19 hospitalization and severity, which was potentially mediated by smoking, obesity and type 2 diabetes-related phenotypes. Particular attention should be given to reducing leisure sedentary behaviors and encouraging proper exercise during isolation and quarantine for COVID-19.

Causal Effects of Genetically Predicted Cystatin C on Osteoporosis: A Two-Sample Mendelian Randomization Study

Objectives: Although it has long been reported that high levels of cystatin C could contribute to the development of osteoporosis in some studies, no evidence has established a causal association between them thus far. Methods: A Mendelian randomization (MR) study was conducted to determine the causal effect of cystatin C on osteoporosis based on public databases obtained from separately published genome-wide association studies (GWASs). The single-nucleotide polymorphisms (SNPs) for cystatin C were extracted from the MR-Base (CKDGen, 33,152 participants), and the SNPs for osteoporosis were extracted from the United Kingdom Biobank project (United Kingdom Biobank, including 5,266 osteoporosis cases and 331,893 controls). We defined the odds ratio (OR) of IVW methods as the primary outcome. In addition, weighted median and MR-Egger regressions were used in the sensitivity analysis. Results: In IVW, we found that genetically predicted cystatin C was causally associated with the risk of osteoporosis with an OR of 1.02 [95% confidence interval (CI) = 1.003-1.025, p = 0.01]. In the further sensitivity analysis, weighted median regression also showed directionally similar estimates (OR = 1.02, 95% CI = 1.005-1.03, p = 0.005), and MR-Egger regression (OR = 1.02, 95% CI = 1.000-1.036, p = 0.15) revealed similar estimates but with lower precision. The funnel plot, MR-Egger intercept, and MR-PRESSO all indicate that no directional pleiotropic effect was observed. Conclusion: In conclusion, our MR study showed evidence of a causal association between serum cystatin C levels and osteoporosis, which also needs to be verified by studies with larger sample sizes in the future. Early monitoring of cystatin C may enable us to prevent osteoporosis-related diseases.