Significant Positive Genetic Correlations Research Articles

Gastroesophageal reflux disease increases predisposition to severe COVID-19: Insights from integrated Mendelian randomization and genetic analysis.

This study aims to investigate the potential causal relationship, shared genomic loci, as well as potential molecular pathways and tissue-specific expression patterns between gastroesophageal reflux disease (GERD) and the risk of hospitalized/severe 2019 coronavirus disease (COVID-19). We employed linkage disequilibrium score regression and bidirectional Mendelian randomization (MR) analysis to explore potential genetic associations between GERD (N=602,604) and hospitalized COVID-19 (N=2095,324) as well as severe COVID-19 (N=1086,211). Additionally, shared genomic loci were extracted from common pivotal regions, further confirmed through corresponding colocalization analyses. GERD-driven molecular pathway network was constructed using extensive literature data mining to understand the molecular-level impacts of GERD on COVID-19. Our results revealed a significant positive genetic correlation between GERD and both hospitalized (rg = 0.418) and severe COVID-19 (rg = 0.314). Furthermore, the MR analysis demonstrated a unidirectional causal effect of genetic predisposition to GERD on COVID-19 outcomes, including hospitalized COVID-19 (odds ratio [OR]: 1.33, 95% confidence interval [CI]: 1.27-1.44, p=9.17e-12) and severe COVID-19 (OR: 1.27, 95% CI: 1.18-1.37, p=1.20e-05). Additionally, GERD and both COVID-19 conditions shared one genomic locus with lead-SNPs rs1011407 and rs1123573, corresponding to the transcription factor BCL11A. Colocalization analysis further demonstrated a significant positive correlation between genome-wide association study and expression quantitative trait locus (eQTL) abnormalities, including rs1011407 (eQTL_p=2.35e-07) and rs1123573 (eQTL_p=2.74e-05). Molecular pathway analysis indicated that GERD might promote the progression of COVID-19 by inducting immune-activated and inflammation-related pathways. These findings confirm that genetically determined GERD may increase the susceptibility to hospitalized/severe COVID-19. The shared genetic loci and the potential molecular pathways offer valuable insights into causal connections between GERD and COVID-19.

Investigating the shared genetic links between hypothyroidism and psychiatric disorders: a large-scale genomewide cross-trait analysis

BackgroundAssociations between thyroid diseases and psychiatric disorders have been mainly described before. However, the genetic mechanism behind hypothyroidism and psychiatric disorders remains unexplained. MethodsWe examined the genetic architecture of hypothyroidism and 8 psychiatric disorders. Firstly, the global and local genetic relationship between the paired traits was explored. Secondly, cross-trait analysis was performed to investigate the genomic loci and genes between psychiatric disorders and hypothyroidism. Thirdly, the significant expression of these genes and the causal relationships were investigated. Lastly, enrichment analysis was conducted on these genes to explore their biological mechanisms. ResultsWe observed significant positive genetic correlations between psychiatric disorders and hypothyroidism. The cross-trait meta-analysis identified 62 shared genetic loci between hypothyroidism and psychiatric disorders. The colocalization analysis additionally revealed 15 potential pleiotropic loci with a posterior probabilities.H4 (PP·H4) value >0.7. We also found 2308 genes shared between both traits, which were highly enriched in biological pathways such as immune cell differentiation and autoimmune diseases, as well as in tissue structures like the frontal cortex and cerebral cortex. Especially, many pleiotropic genes were significantly expressed for multiple pairwise traits, such as BCL11B, RERE, and SUOX. Lastly, the Latent causal variable model (LCV) analysis did not find any causal components in the genetic structure between them. LimitationsThe limitations of this study include that the conclusions were drawn from a European population. ConclusionsThese findings not only deepens our understanding of their biological mechanisms but also has significant implications for the intervention and treatment of these diseases.

Exploring the shared genetic basis of major depressive disorder and frailty

BackgroundMajor depressive disorder (MDD) and frailty impose substantial health and economic burdens. MDD is recognized as a significant risk factor for frailty, but the genetic associations between these conditions remain unclear. This study investigates the genetic correlation, shared pleiotropic loci, causal relationships, and comorbid genes between MDD and frailty. MethodsThe genetic correlation between MDD and frailty was assessed using linkage disequilibrium score regression (LDSC) based on data from genome-wide association studies (GWAS). A detailed analysis was performed to identify shared pleiotropic loci and causal relationships through cross-phenotype association tests and Mendelian randomization. Additionally, tissue enrichment analysis was conducted using stratified LDSC, gene-based associations with both conditions were assessed using Multimarker Analysis of Genomic Annotation (MAGMA), and pathway analysis of comorbid genes was performed using the g: GOSt tool. ResultsOur findings revealed a significant positive genetic correlation between MDD and frailty (rg = 0.65, P = 1.49E-219). We identified 57 shared risk SNPs between the two conditions, including 6 novel SNPs. Mendelian randomization analyses indicated robust causal effects of MDD on frailty and vice versa. Furthermore, we observed tissue-specific heritability enrichment in 9 brain tissues. By combining MAGMA and CPASSOC analyses, we identified 10 comorbid genes associated with both MDD and frailty, primarily involved in synapse formation, modulation, plasticity, and desaturase activity. ConclusionThis study provides strong evidence for a shared genetic basis between MDD and frailty. The identification of comorbid genes offers new insights into the mechanisms underlying the relationship between these conditions.

The shared genetic etiology of antisocial behavior and psychiatric disorders: Insights from pleiotropy and causality analysis

BackgroundAntisocial behavior (ASB) infringes on the rights of others and significantly disrupts social order. Studies have shown that ASB is phenotypically associated with various psychiatric disorders. However, these studies often neglected the importance of genetic foundations. MethodsThis study utilized genome-wide association studies and pleiotropy analysis to explore the genetic correlation between ASB and psychiatric disorders. Linkage disequilibrium score regression (LDSC) and high-definition likelihood (HDL) methods were employed to assess genetic correlations, and the PLACO method was used for pleiotropy analysis. Functional annotation and biological pathway analysis of identified pleiotropic genes were performed using enrichment analysis. Furthermore, Mendelian randomization (MR) analysis was conducted to validate these causal relationships. ResultsLDSC and HDL analysis showed that significant positive genetic correlations were between ASB and attention deficit hyperactivity disorder (ADHD), schizophrenia (SCZ), major depressive disorder (MDD), and post-traumatic stress disorder (PTSD). Multiple potential pleiotropic genetic loci were identified, particularly the FOXP2 and MDFIC genes located at the 7q31.1 locus. Enrichment analysis showed that these pleiotropic genes are highly expressed in several brain regions (such as the hypothalamus, cerebellar hemisphere, cortex, and amygdala) and immune-related cells. MR analysis further confirmed the causal effects ADHD, SCZ, and MDD on ASB risk. ConclusionThis study reveals significant genetic correlations and potential causal mechanisms between ASB and various psychiatric disorders. The MR analysis confirmed the causal effects of psychiatric disorders on ASB. These findings deepen our understanding of the genetic architecture of psychiatric disorders and ASB.

Investigating Genetic Overlap between Alzheimer's Disease, Lipids, and Coronary Artery Disease: A Large-Scale Genome-Wide Cross Trait Analysis.

There is evidence to support a link between abnormal lipid metabolism and Alzheimer's disease (AD) risk. Similarly, observational studies suggest a comorbid relationship between AD and coronary artery disease (CAD). However, the intricate biological mechanisms of AD are poorly understood, and its relationship with lipids and CAD traits remains unresolved. Conflicting evidence further underscores the ongoing investigation into this research area. Here, we systematically assess the cross-trait genetic overlap of AD with 13 representative lipids (from eight classes) and seven CAD traits, leveraging robust analytical methods, well-powered large-scale genetic data, and rigorous replication testing. Our main analysis demonstrates a significant positive global genetic correlation of AD with triglycerides and all seven CAD traits assessed-angina pectoris, cardiac dysrhythmias, coronary arteriosclerosis, ischemic heart disease, myocardial infarction, non-specific chest pain, and coronary artery disease. Gene-level analyses largely reinforce these findings and highlight the genetic overlap between AD and three additional lipids: high-density lipoproteins (HDLs), low-density lipoproteins (LDLs), and total cholesterol. Moreover, we identify genome-wide significant genes (Fisher's combined p value [FCPgene] < 2.60 × 10-6) shared across AD, several lipids, and CAD traits, including WDR12, BAG6, HLA-DRA, PHB, ZNF652, APOE, APOC4, PVRL2, and TOMM40. Mendelian randomisation analysis found no evidence of a significant causal relationship between AD, lipids, and CAD traits. However, local genetic correlation analysis identifies several local pleiotropic hotspots contributing to the relationship of AD with lipids and CAD traits across chromosomes 6, 8, 17, and 19. Completing a three-way analysis, we confirm a strong genetic correlation between lipids and CAD traits-HDL and sphingomyelin demonstrate negative correlations, while LDL, triglycerides, and total cholesterol show positive correlations. These findings support genetic overlap between AD, specific lipids, and CAD traits, implicating shared but non-causal genetic susceptibility. The identified shared genes and pleiotropic hotspots are valuable targets for further investigation into AD and, potentially, its comorbidity with CAD traits.

Shared and unique 3D genomic features of substance use disorders across multiple cell types.

Recent genome-wide association studies (GWAS) have revealed shared genetic components among alcohol, opioid, tobacco and cannabis use disorders. However, the extent of the underlying shared causal variants and effector genes, along with their cellular context, remain unclear. We leveraged our existing 3D genomic datasets comprising high-resolution promoter-focused Capture-C/Hi-C, ATAC-seq and RNA-seq across >50 diverse human cell types to focus on genomic regions that coincide with GWAS loci. Using stratified LD regression, we determined the proportion of genomewide SNP heritability attributable to the features assayed across our cell types by integrating recent GWAS summary statistics for the relevant traits: alcohol use disorder (AUD), tobacco use disorder (TUD), opioid use disorder (OUD) and cannabis use disorder (CanUD). Statistically significant enrichments (P<0.05) were observed in 14 specific cell types, with heritability reaching 9.2-fold for iPSC-derived cortical neurons and neural progenitors, confirming that they are crucial cell types for further functional exploration. Additionally, several pancreatic cell types, notably pancreatic beta cells, showed enrichment for TUD, with heritability enrichments up to 4.8-fold, suggesting genomic overlap with metabolic processes. Further investigation revealed significant positive genetic correlations between T2D with both TUD and CanUD (FDR<0.05) and a significant negative genetic correlation with AUD. Interestingly, after partitioning the heritability for each cell type's cis-regulatory elements, the correlation between T2D and TUD for pancreatic beta cells was greater (r=0.2) than the global genetic correlation value. Our study provides new genomic insights into substance use disorders and implicates cell types where functional follow-up studies could reveal causal variant-gene mechanisms underpinning these disorders.

Genome-wide cross-disease analyses highlight causality and shared biological pathways of type 2 diabetes with gastrointestinal disorders.

Studies suggest links between diabetes and gastrointestinal (GI) traits; however, their underlying biological mechanisms remain unclear. Here, we comprehensively assess the genetic relationship between type 2 diabetes (T2D) and GI disorders. Our study demonstrates a significant positive global genetic correlation of T2D with peptic ulcer disease (PUD), irritable bowel syndrome (IBS), gastritis-duodenitis, gastroesophageal reflux disease (GERD), and diverticular disease, but not inflammatory bowel disease (IBD). We identify several positive local genetic correlations (negative for T2D - IBD) contributing to T2D's relationship with GI disorders. Univariable and multivariable Mendelian randomisation analyses suggest causal effects of T2D on PUD and gastritis-duodenitis and bidirectionally with GERD. Gene-based analyses reveal a gene-level genetic overlap between T2D and GI disorders and identify several shared genes reaching genome-wide significance. Pathway-based study implicates leptin (T2D - IBD), thyroid, interferon, and notch signalling (T2D - IBS), abnormal circulating calcium (T2D - PUD), cardiovascular, viral, proinflammatory and (auto)immune-mediated mechanisms in T2D and GI disorders. These findings support a risk-increasing genetic overlap between T2D and GI disorders (except IBD), implicate shared biological pathways with putative causality for certain T2D - GI pairs, and identify targets for further investigation.

Association between migraine and venous thromboembolism: a Mendelian randomization and genetic correlation study.

Previous observational studies have reported an increased risk of venous thromboembolism (VTE) among individuals with migraine. This study aimed to investigate the causal effect of migraine on the development of VTE, as well as explore the genetic correlation between them. We conducted a two-sample Mendelian randomization (MR) study using publicly available summary statistics from large-scale genome-wide association studies for migraine and VTE. Linkage disequilibrium score regression analysis was performed to estimate the genetic correlation between migraine and VTE. There were several shared risk variants (p-value < 5 × 10-8) between migraine and VTE. Linkage disequilibrium score regression analysis found a significant positive genetic correlation between migraine and VTE. The genetic correlations based on two migraine datasets were 0.208 (se = 0.031, p-value = 2.91 × 10-11) and 0.264 (se = 0.040, p-value = 4.82 × 10-11), respectively. Although main MR analysis showed that migraine was associated with an increased risk of VTE (odds ratio = 1.069, 95% confidence interval = 1.022-1.118, p-value = 0.004), the association attenuated to non-significance when using several other MR methods and using another set of genetic instruments. In addition, evidence of heterogeneity was found. Reverse MR analysis showed VTE was associated with increased risk of migraine with aura (odds ratio = 1.137, 95% confidence interval = 1.062-1.218, p-value = 2.47 × 10-4) with no evidence of pleiotropy and heterogeneity. We showed suggestive evidence indicating an association between migraine and increased risk of VTE. Additionally, we found robust evidence suggesting that VTE is associated with an increased risk of migraine. The positive genetic correlation indicates that migraine and VTE has shared genetic basis. Further investigations will be necessary to address potential sex-specific effects in the analysis.

OA01 Cluster medicine: the role of genetics for identifying shared biological pathways between rheumatoid arthritis and common comorbidities for targeting treatments

Abstract Background/Aims Rheumatoid arthritis (RA) is a chronic inflammatory disorder associated with significant pain and disability, as well as increased risk of comorbidities. These comorbidities, such as coronary artery disease, stroke, heart failure and type 2 diabetes, often form predictable clusters highlighting the importance of common disease mechanisms. Identifying these clusters, and the underlying shared mechanisms, is key to the concept of cluster medicine which aims to take a more systemic approach to treating comorbidity. It is hypothesised that inflammatory processes in RA promote the pathogenesis of these comorbid diseases, which typically occur at an earlier stage of life than in the general population. However, few studies have investigated the degree of shared genetic susceptibility implicated across these traits. The present study aimed to identify and characterise pleiotropic loci and shared biological pathways involved in the pathogenesis of RA and cardiometabolic disorders. Methods European-only GWAS summary statistics were collected for RA (seropositive, seronegative, and overall) and seven cardiometabolic traits, including ischemic stroke, any stroke, heart failure, coronary artery disease, hypertension, atrial fibrillation, and type 2 diabetes. Cross-trait linkage disequilibrium score regression was employed to estimate the degree of genetic correlation (rg) between all pairs of traits. Subset-based meta-analysis was performed using the R package ASSET to identify pleiotropic single nucleotide polymorphisms (SNPs). Pleiotropic SNPs were assigned to genes based on positional and eQTL mapping. Prioritised genes were tested for over-representation in functional categories and biological pathways in gene sets obtained from MsigDB and WikiPathways using the hypergeometric test loci. Gene mapping and enrichment analyses were conducted in FUMA. Results RA showed significant positive genetic correlation with all cardiometabolic traits, with the seronegative subtype showing greater correlation than the seropositive subtype. Correlations between RA and cardiometabolic phenotypes ranged from 0.11 - 0.38, the strongest of which was between seronegative RA and heart failure (rg = 0.38, P = 2.6e-07). A total of 67 lead SNPs were identified as potentially pleiotropic. Pleiotropic SNPs were mapped to genes including IL6R, PTPN11, ATXN2, PLCL1 and SOX6. Pathway enrichment analyses revealed that mapped genes were primarily involved in inflammatory signalling pathways, involving interleukins, TNF-α and interferon (gamma and alpha) response. Conclusion This study provides evidence for pleiotropy across RA and cardiometabolic traits, whereby inherited genetic variants predispose to aberrant cytokine signalling, thus conferring risk to multiple diseases where inflammation is a key driver of pathogenesis. Disclosure M. Stoves: None. M. Soomro: None. S. Zhao: None. D. Plant: None. A. Barton: None. J. Bowes: None.

Investigating the shared genetic architecture between attention-deficit/hyperactivity disorder and risk taking behavior: A large-scale genomewide cross-trait analysis

BackgroundThis study aims to explore the genetic architecture shared between Attention-Deficit/Hyperactivity Disorder (ADHD) and risk behavior. MethodsBased on the latest large-scale Genome-wide association studies (GWAS), we firstly employed Linkage disequilibrium score regression (LDSC) and Local Analysis of Variant Association (LAVA) to investigate the genetic correlation between risk behavior and ADHD. Then, we conducted cross-trait analysis to identified the Pleiotropic loci. Finally, bidirectional Mendelian randomization analysis (MR) was applied to examine the causal relationship. ResultsWe found a significant positive genetic correlation between ADHD and risk-taking behavior (rg = 0.351, p = 6.50E-37). The cross-trait meta-analysis identified 27 significant SNPs shared between ADHD and risk behavior. The most significant locus, located near the CADM2 gene on chromosome 3, had been identified associated with this two trait (pADHD = 3.07E-05 and prisk-taking behavior = 2.47E-30). The same situation can also be observed near the FOXP2 gene on chromosome 7 (rs8180817, pmeta = 5.72E-21). We found CCDC171 gene and other genes played a significant role in ADHD and risk behavior in mRNA level. Bidirectional MR analysis found a causal relationship between them. LimitationThe majority of our data sources were of European origin, which may limit the generalizability of our findings to other ethnic populations. ConclusionThis article reveals in depth the shared genetic structure between ADHD and risk-taking behavior, finding a significant positive genetic correlation between ADHD and risk-taking behavior. Providing insights for the future treatment and management of these two traits.

Genetic parameter estimation and molecular foundation of chicken beak shape

The bird beak is mainly functioned as feeding and attacking, and its shape has extremely important significance for survival and reproduction. In chickens, since beak shape could lead to some disadvantages including pecking and waste of feed, it is important to understand the inheritance of chicken beak shape. In the present study, we firstly established 4 indicators to describe the chicken beak shapes, including upper beak length (UL), lower beak length (LL), distance between upper and lower beak tips (DB) and upper beak curvature (BC). And then, we measured the 4 beak shape indicators as well as some production traits including body weight (BW), shank length (SL), egg weight (EW), eggshell strength (ES) of a layer breed, Rhode Island Red (RIR), in order to estimate genetic parameters of chicken beak shape. The heritabilities of UL and LL were 0.41 and 0.37, and the heritabilities of DB and BC were 0.22 and 0.21, indicating that beak shape was a highly or mediumly heritable. There were significant positive genetic and phenotypic correlations among UL, LL, and DB. And UL was positively correlated with body weight (BW18) and shank length (SL18) at 18 weeks of age in genetics, and DB was positively correlated with BC in terms of genetics and phenotype. We also found that layers of chicken cages played a role on beak shape, which could be attributed to the difference of lightness in different cage layers. By a genome-wide association study (GWAS) for the chicken UL, we identified 9 significant candidate genes associated with UL in RIR. For the variants with low minor allele frequencies (MAF <0.01) and outside of high linkage disequilibrium (LD) regions, we also conducted rare variant association studies (RVA) and GWAS to find the association between genotype and phenotype. We also analyzed transcriptomic data from multiple tissues of chicken embryos and revealed that all of the 9 genes were highly expressed in beak of chicken embryos, indicating their potential function for beak development. Our results provided the genetic foundation of chicken beak shape, which could help chicken breeding on beak related traits.

Shared genetic architecture between periodontal disease and type 2 diabetes: a large scale genome-wide cross-trait analysis

PurposeTo investigate the relationship between abnormal glucose metabolism, type 2 diabetes (T2D), and periodontal disease (PER) independent of Body Mass Index (BMI), we employed a genome-wide cross-trait approach to clarify the association.MethodsOur study utilized the most extensive genome-wide association studies conducted for populations of European ancestry, including PER, T2D, fasting glucose, fasting insulin, 2-hour glucose after an oral glucose challenge, HOMA-β, HOMA-IR (unadjusted or adjusted for BMI) and HbA1c.ResultsWith this approach, we were able to identify pleiotropic loci, establish expression-trait associations, and quantify global and local genetic correlations. There was a significant positive global genetic correlation between T2D (rg = 0.261, p = 2.65 × 10−13), HbA1c (rg = 0.182, p = 4.14 × 10−6) and PER, as well as for T2D independent of BMI (rg = 0.158, p = 2.34 × 10−6). A significant local genetic correlation was also observed between PER and glycemic traits or T2D. We also identified 62 independent pleiotropic loci that impact both PER and glycemic traits, including T2D. Nine significant pathways were identified between the shared genes between T2D, glycemic traits and PER. Genetically liability of HOMA-βadjBMI was causally associated with the risk of PER.ConclusionOur research has revealed a genetic link between T2D, glycemic traits, and PER that is influenced by biological pleiotropy. Notably, some of these links are not related to BMI. Our research highlights an underlying link between patients with T2D and PER, regardless of their BMI.

Genetic correlation and causal associations between circulating C-reactive protein levels and lung cancer risk.

We aimed to characterize genetic correlations and causal associations between circulating C-reactive protein (CRP) levels and the risk of lung cancer (LC). Leveraging summary statistics from genome-wide association studies of circulating CRP levels among 575,531 individuals of European ancestry, and LC risk among 29,266 cases and 56,450 controls, we investigated genetic associations of circulating CRP levels with the risk of overall lung cancer and its histological subtypes, by using linkage disequilibrium score (LDSC) regression and Mendelian randomization (MR) analyses. Significant positive genetic correlations between circulating CRP levels and the risk of LC and its histological subtypes were identified from LDSC regression, with correlation coefficients ranging from 0.12 to 0.26, and all false discovery adjusted p < 0.05. Univariable MR demonstrated a nominal association between CRP levels and an increased risk of lung squamous cell carcinoma (SCC) (inverse variance-weighted OR = 1.15, 95% CI 1.01-1.30). However, this association disappeared when multivariable MR included cigarettes per day and/or body mass index. By using our recently developed constrained maximum likelihood-based MR method, we identified significant associations of CRP levels with the risk of overall LC (OR 1.06, 95% CI 1.03-1.09), SCC (OR 1.06, 95% CI 1.02-1.09), and small cell lung cancer (SCLC, OR 1.09, 95% CI 1.03-1.15). Moreover, most univariable and multivariable MR analyses also revealed consistent CRP-SCLC associations. There may be a genetic and causal association between circulating CRP levels and the risk of SCLC, which is in line with previous population-based observational studies.

Patients with periodontitis might increase the risk of urologic cancers: a bidirectional two-sample Mendelian randomization study

BackgroundNumerous observational epidemiological studies have reported a bidirectional relationship between periodontitis and urological cancers. However, the causal link between these two phenotypes remains uncertain. This study aimed to examine the bidirectional causal association between periodontitis and four types of urological tumors, specifically kidney cancer (KC), prostate cancer (PC), bladder cancer (BC), and testis cancer (TC).MethodsBased on large-scale genome-wide association study (GWAS) data, we utilized the two-sample Mendelian randomization (MR) approach to evaluate causal relationships between periodontitis and urological cancers. Several MR methods covering various consistency assumptions were applied in this study, including contamination mixture and Robust Adjusted Profile Score to obtain robust results. Summary-level data of individuals with European ancestry were extracted from the UK Biobank, the Kaiser GERA cohorts, and the FinnGen consortium.ResultsOur findings revealed significant positive genetic correlations between periodontitis and kidney cancer (OR 1.287; 95% CI 1.04, 1.594; P = 0.020). We did not find a significant association of periodontitis on prostate cancer, bladder cancer, and testis cancer. In reverse MR, no significant results were observed supporting the effect of urologic cancers on periodontitis (all P > 0.05).ConclusionOur study provides the evidence of a potential causal relationship between periodontitis and kidney cancer. However, large-scale studies are warranted to confirm and elucidate the underlying mechanisms of this association.

Genetic overlap for ten cardiovascular diseases: A comprehensive gene-centric pleiotropic association analysis and Mendelian randomization study

Recent studies suggest that pleiotropic effects may explain the genetic architecture of cardiovascular diseases (CVDs). We conducted a comprehensive gene-centric pleiotropic association analysis for ten CVDs using genome-wide association study (GWAS) summary statistics to identify pleiotropic genes and pathways that may underlie multiple CVDs. We found shared genetic mechanisms underlying the pathophysiology of CVDs, with over two-thirds of the diseases exhibiting common genes and single-nucleotide polymorphisms (SNPs). Significant positive genetic correlations were observed in more than half of paired CVDs. Additionally, we investigated the pleiotropic genes shared between different CVDs, as well as their functional pathways and distribution in different tissues. Moreover, six hub genes, including ALDH2, XPO1, HSPA1L, ESR2, WDR12, and RAB1A, as well as 26 targeted potential drugs, were identified. Our study provides further evidence for the pleiotropic effects of genetic variants on CVDs and highlights the importance of considering pleiotropy in genetic association studies.

Susceptibility and severity of COVID-19 and risk of psychiatric disorders in European populations: a Mendelian randomization study.

Observational studies have suggested that COVID-19 increases the prevalence of psychiatric disorders, but the results of such studies are inconsistent. This study aims to investigate the association between COVID-19 and the risk of psychiatric disorders using Mendelian randomization (MR) analysis. We used summary statistics from COVID-19 Host Genetics Initiative genome-wide association study (GWAS) of COVID-19 involving 2,586,691 participants from European ancestry. Genetic variations of five psychiatric disorders including autism spectrum disorder (ASD) (N = 46,351), bipolar disorder (BID) (N = 51,710), major depressive disorder (MDD) (N = 480,359), anxiety disorder (N = 83,566), and schizophrenia (SCZ) (N = 77,096) were extracted from several GWAS of European ancestry. The inverse-variance weighted (IVW) method as the main MR analysis conducted. We further performed sensitivity analyzes and heterogeneity analyzes as validation of primary MR results. The IVW analysis found that COVID-19 hospitalization phenotype was the risk factor for BID (OR = 1.320, 95% CI = 1.106-1.576, p = 0.002) and SCZ (OR = 1.096, 95% CI = 1.031-1.164, p = 0.002). Moreover, we detected a significant positive genetic correlation between COVID-19 severity and two psychiatric traits, BID (OR = 1.139, 95% CI = 1.033-1.256, p = 0.008) and SCZ (OR = 1.043, 95% CI = 1.005-1.082, p = 0.024). There was no evidence supporting the causal relationship between COVID-19 susceptibility and psychiatric disorders. Our results found that the COVID-19 hospitalization phenotype and COVID-19 severity phenotype might be the potential risks of BID and SCZ in European populations. Therefore, patients infected with SARS-CoV-2 should have enhanced monitoring of their mental status.

Genetic Correlations between Migraine and Carpal Tunnel Syndrome.

Surgical deactivation of extracranial nerve trigger sites is now well established as an effective treatment for migraine headache. Parallels have been drawn to median nerve decompression for carpal tunnel syndrome (CTS), and 2 previous studies have demonstrated an association between migraine and CTS. The authors sought to (1) substantiate these findings in a considerably larger UK cohort, and (2) investigate potential genetic associations between the 2 disorders. Nested case-control studies were conducted in the UK Biobank cohort of 401,656 individuals. Odds ratios were calculated for the association between migraine and CTS in the overall cohort and sex-stratified subsets. Genetic correlation between migraine and CTS was interrogated by linkage disequilibrium score regression, leveraging data from published genomewide association studies. Regions of genetic overlap were identified by multitrait analysis of genomewide association studies and cross-phenotype association. Migraine and CTS show a significant epidemiologic association within UK Biobank (OR, 1.14, 95% CI, 1.04 to 1.25; P = 0.0058), which is specific to women (OR, 1.15; 95% CI, 1.04 to 1.28; P = 0.0057) and not men (OR, 1.07; 95% CI, 0.82 to 1.40; P = 0.61). Genetic analysis demonstrated a significant positive genetic correlation between the 2 disorders ( rg = 0.13; P = 0.0039), and implicated the TRIM32 locus on chromosome 9 as a region of genetic overlap. This study replicates past reports of an epidemiologic association between CTS and migraine, albeit in women only. This association is underpinned by a genetic correlation, with shared genetic susceptibility at the TRIM32 locus. The authors' data add credibility to the notion that an element of entrapment neuropathy underlies migraine pathophysiology. Risk, III.

Genetic correlations between suicide attempts and psychiatric and intermediate phenotypes adjusting for mental disorders.

Suicide attempts are a moderately heritable trait, and genetic correlations with psychiatric and related intermediate phenotypes have been reported. However, as several mental disorders as well as major depressive disorder (MDD) are strongly associated with suicide attempts, these genetic correlations could be mediated by psychiatric disorders. Here, we investigated genetic correlations of suicide attempts with psychiatric and related intermediate phenotypes, with and without adjusting for mental disorders. To investigate the genetic correlations, we utilized large-scale genome-wide association study summary statistics for suicide attempts (with and without adjusting for mental disorders), nine psychiatric disorders, and 15 intermediate phenotypes. Without adjusting for mental disorders, suicide attempts had significant positive genetic correlations with risks of attention-deficit/hyperactivity disorder, schizophrenia, bipolar disorder, MDD, anxiety disorders and posttraumatic stress disorder; higher risk tolerance; earlier age at first sexual intercourse, at first birth and at menopause; higher parity; lower childhood IQ, educational attainment and cognitive ability; and lower smoking cessation. After adjusting for mental disorders, suicide attempts had significant positive genetic correlations with the risk of MDD; earlier age at first sexual intercourse, at first birth and at menopause; and lower educational attainment. After adjusting for mental disorders, most of the genetic correlations with psychiatric disorders were decreased, while several genetic correlations with intermediate phenotypes were increased. These findings highlight the importance of considering mental disorders in the analysis of genetic correlations related to suicide attempts and suggest that susceptibility to MDD, reproductive behaviors, and lower educational levels share a genetic basis with suicide attempts after adjusting for mental disorders.

A shared genetic contribution to osteoarthritis and COVID-19 outcomes: a large-scale genome-wide cross-trait analysis.

Patients with osteoarthritis (OA) are exposed to an increased risk of adverse outcomes of COVID-19, and they tend to experience disruption in access to healthcare services and exercise facilities. However, a deep understanding of this comorbidity phenomenon and the underlying genetic architecture of the two diseases is still unclear. In this study, we aimed to untangle the relationship between OA and COVID-19 outcomes by conducting a large-scale genome-wide cross-trait analysis. Genetic correlation and causal relationships between OA and COVID-19 outcomes (critical COVID-19, COVID-19 hospitalization, and COVID-19 infection) were estimated by linkage disequilibrium score regression and Mendelian Randomization approaches. We further applied Multi-Trait Analysis of GWAS and colocalization analysis to identify putative functional genes associated with both OA and COVID-19 outcomes. Significant positive genetic correlations between OA susceptibility and both critical COVID-19 (rg=0.266, P=0.0097) and COVID-19 hospitalization (rg=0.361, P=0.0006) were detected. However, there was no evidence to support causal genetic relationships between OA and critical COVID-19 (OR=1.17[1.00-1.36], P=0.049) or OA and COVID-19 hospitalization OR=1.08[0.97-1.20], P=0.143). These results were robustly consistent after the removal of obesity-related single nucleotide polymorphisms (SNPs). Moreover, we identified a strong association signal located near the FYCO1 gene (lead SNPs: rs71325101 for critical COVID-19, Pmeta=1.02×10-34; rs13079478 for COVID-19 hospitalization, Pmeta=1.09×10-25). Our findings further confirmed the comorbidity of OA and COVID-19 severity, but indicate a non-causal impact of OA on COVID-19 outcomes. The study offers an instructive perspective that OA patients did not generate negative COVID-19 outcomes during the pandemic in a causal way. Further clinical guidance can be formulated to enhance the quality of self-management in vulnerable OA patients.

Shared Genetic Loci Between Schizophrenia and White Blood Cell Counts Suggest Genetically Determined Systemic Immune Abnormalities.

Immune mechanisms are indicated in schizophrenia (SCZ). Recent genome-wide association studies (GWAS) have identified genetic variants associated with SCZ and immune-related phenotypes. Here, we use cutting edge statistical tools to identify shared genetic variants between SCZ and white blood cell (WBC) counts and further understand the role of the immune system in SCZ. GWAS results from SCZ (patients, n = 53 386; controls, n = 77 258) and WBC counts (n = 56 3085) were analyzed. We applied linkage disequilibrium score regression, the conditional false discovery rate method and the bivariate causal mixture model for analyses of genetic associations and overlap, and 2 sample Mendelian randomization to estimate causal effects. The polygenicity for SCZ was 7.5 times higher than for WBC count and constituted 32%-59% of WBC count genetic loci. While there was a significant but weak positive genetic correlation between SCZ and lymphocytes (rg = 0.05), the conditional false discovery rate method identified 383 shared genetic loci (53% concordant effect directions), with shared variants encompassing all investigated WBC subtypes: lymphocytes, n = 215 (56% concordant); neutrophils, n = 158 (49% concordant); monocytes, n = 146 (47% concordant); eosinophils, n = 135 (56% concordant); and basophils, n = 64 (53% concordant). A few causal effects were suggested, but consensus was lacking across different Mendelian randomization methods. Functional analyses indicated cellular functioning and regulation of translation as overlapping mechanisms. Our results suggest that genetic factors involved in WBC counts are associated with the risk of SCZ, indicating a role of immune mechanisms in subgroups of SCZ with potential for stratification of patients for immune targeted treatment.