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Aims: Anxiety disorders are prevalent and anxiety symptoms (ANX) co‐occur with many psychiatric disorders. We aimed to identify genomic loci associated with ANX, characterize its genetic architecture, and genetic overlap with psychiatric disorders. Methods: We included a genome‐wide association study of ANX (meta‐analysis of UK Biobank and Million Veterans Program, n = 301,732), schizophrenia (SCZ), bipolar disorder (BIP), major depression (MD), attention‐deficit/hyperactivity disorder (ADHD), and autism spectrum disorder (ASD), and validated the findings in the Norwegian Mother, Father, and Child Cohort (n = 95,841). We employed the bivariate causal mixture model and local analysis of covariant association to characterize the genetic architecture including overlap between the phenotypes. Conditional and conjunctional false discovery rate analyses were performed to boost the identification of loci associated with anxiety and shared with psychiatric disorders. Results: Anxiety was polygenic with 12.9k genetic variants and overlapped extensively with psychiatric disorders (4.1k–11.4k variants) with predominantly positive genetic correlations between anxiety and psychiatric disorders. We identified 119 novel loci for anxiety by conditioning on the psychiatric disorders, and loci shared between anxiety and MD n=47, BIP n=33, SCZ n=71, ADHD n=20, and ASD n=5. Genes annotated to anxiety loci exhibit enrichment for a broader range of biological pathways including cell adhesion and neurofibrillary tangle compared with genes annotated to the shared loci. Conclusions: Anxiety is highly polygenic phenotype with extensive genetic overlap with psychiatric disorders, and we identified novel loci for anxiety implicating new molecular pathways. The shared genetic architecture may underlie the extensive cross‐disorder comorbidity of anxiety, and the identified molecular underpinnings may lead to potential drug targets. [ABSTRACT FROM AUTHOR]

Background: Multiple Sclerosis (MS), an autoimmune disorder causing demyelination and neurological damage, has been linked to 25-hydroxyvitamin D (25OHD) levels, suggesting its role in immune response and MS onset. This study used GWAS datasets to investigate genetic associations between 25OHD and MS. Methods: We utilized a large-scale prospective cohort to evaluate serum 25OHD levels and MS risk. Linkage Disequilibrium Score Regression (LDSC) assessed genetic correlations between 25OHD levels and MS. Cross-trait genome-wide pleiotropy analysis revealed shared genetic loci. MAGMA analysis identified pleiotropic genes, enriched tissues, and gene sets. Stratified LDSC estimated tissue-specific and cell-specific heritability enrichment, and multi-trait co-localization analysis identified shared immune cell subsets. Bidirectional Mendelian Randomization (MR) assessed the causal association between 25OHD and MS risk. Results: The observational study found a nonlinear relationship between 25OHD levels and MS risk, with the lowest quartile showing significant risk elevation. Our findings revealed shared genetic structure between 25OHD levels and MS, suggesting a common biological pathway involving immune function and CNS integrity. We found 24 independent loci shared between 25OHD levels and MS risk, enriched in brain tissues and involved in pathways like LDL, HDL, and TG metabolism. Four loci (6p24.3, 6p22.2, 12q14.1, and 19p13.2) had strong co-localization evidence, with mapped genes as potential drug targets. Bidirectional MR analysis supported a causal effect of 25OHD levels on MS risk, suggesting 25OHD supplementation could modulate MS risk. Conclusion: This study reveals the complex relationship between 25OHD levels and MS, indicating that higher levels are not always advantageous and recommending moderation in supplementation. We identified SMARCA4 as a potential therapeutic target and detailed key pathways influencing this interaction. [ABSTRACT FROM AUTHOR]

Background: The genetic association between psychiatric disorders and hemorrhoidal disease (HEM) is still not well known. The work aims to investigate their comorbidity at a genetic level. Methods: Utilizing recent large-scale genome-wide association studies (GWAS), we investigated the genetic overlap at the single nucleotide polymorphism (SNP), gene, and molecular level between depression and HEM, bipolar disorder (BD) and HEM, neuroticism and HEM, as well as schizophrenia (SCZ) and HEM. The cross-trait genes were validated through the utilization of transcriptome and proteome methodologies. The causal link was assessed using bidirectional two-sample Mendelian randomization analysis (MR) analysis. MRlap corrects for the potential bias in estimation caused by sample overlap. Results: We discovered significant positive genetic associations between these four types of psychiatric disorders and HEM. Cross-phenotypic association analyses identified shared SNPs along with 17 specific loci between psychiatric disorders and HEM. MAGMA identified a total of 2304 pleiotropic genes, several of which showed significant expression in the results of transcriptome and proteome analyses. We observed that these genes are mostly associated with the regulation of transcription factors and particular DNA binding activities. Lastly, MR analysis provided evidence supporting a correlation between these conditions. Conclusion: This study revealed a genetic correlation between four psychiatric disorders and HEM, identified pleiotropic loci, found multiple candidate genes, and confirmed causal relationships. This has enhanced our comprehension of the common genetic mechanisms of psychiatric disorders and HEM. [ABSTRACT FROM AUTHOR]

Objective: Observational studies have frequently shown a co-occurrence of psychiatric disorders and Obstructive sleep apnea (OSA), with major depressive disorder (MDD) being a prevalent psychiatric disorder. This study aims to investigate the genetic overlap between MDD and OSA to explore their underlying pathological mechanisms. Methods: Leveraging the extensive and recent GWAS for OSA and MDD, we conducted genetic correlation analyses utilizing Linkage disequilibrium score regression (LDSC), re-evaluated their pleiotropic Single-nucleotide polymorphisms (SNP) with Cross-Phenotype Association (CPASSOC) and Colocalization (COLOC), investigated the overlap at the gene level using physical annotations and Multi-marker Analysis of GenoMic Annotation (MAGMA), and finally employed Mendelian randomization (MR) to assess potential causal relationships between the two disorders. Results: Upon our investigation, we established that MDD and OSA exhibit high heritability (h2MDD=0.02, h2OSA=0.04) alongside a significant genetic correlation (rg=0.31, P= 1.42E-23). Utilizing CPASSOC, we identified 397 pleiotropic SNPs, associable with 45 loci, two of which share common genetic fragments with a pleiotropic role. Furthermore, the MAGMA study uncovered a total of 154 pleiotropic genes capable of influencing multiple brain regions. Lastly, leveraging MR analysis, we concluded that MDD heightens the risk of developing OSA (P=3. 10E-04, OR (95%CI):1.28(1.12~ 1.47)). Conclusion: In summary, our study identified PCLO as a common gene between OSA and MDD and provided evidence that MDD causally contributes to the development of OSA. These insights enhance our understanding of the shared mechanisms underlying the comorbidity of these conditions. [ABSTRACT FROM AUTHOR]

Background and Hypothesis The synaptic pruning hypothesis posits that schizophrenia (SCZ) and autism spectrum disorder (ASD) may represent opposite ends of neurodevelopmental disorders: individuals with ASD exhibit an overabundance of synapses and connections while SCZ was characterized by excessive pruning of synapses and a reduction. Given the strong genetic predisposition of both disorders, we propose a shared genetic component, with certain loci having differential regulatory impacts. Study Design Genome-Wide single nucleotide polymorphism (SNP) data of European descent from SCZ (N cases = 53 386, N controls = 77 258) and ASD (N cases = 18 381, N controls = 27 969) were analyzed. We used genetic correlation, bivariate causal mixture model, conditional false discovery rate method, colocalization, Transcriptome-Wide Association Study (TWAS), and Phenome-Wide Association Study (PheWAS) to investigate the genetic overlap and gene expression pattern. Study Results We found a positive genetic correlation between SCZ and ASD (r g = .26, SE = 0.01, P  = 7.87e−14), with 11 genomic loci jointly influencing both conditions (conjFDR <0.05). Functional analysis highlights a significant enrichment of shared genes during early to mid-fetal developmental stages. A notable genetic region on chromosome 17q21.31 (lead SNP rs2696609) showed strong evidence of colocalization (PP.H4.abf = 0.85). This SNP rs2696609 is linked to many imaging-derived brain phenotypes. TWAS indicated opposing gene expression patterns (primarily pseudogenes and long noncoding RNAs [lncRNAs]) for ASD and SCZ in the 17q21.31 region and some genes (LRRC37A4P , LINC02210 , and DND1P1) exhibit considerable variation in the cerebellum across the lifespan. Conclusions Our findings support a shared genetic basis for SCZ and ASD. A common genetic variant, rs2696609, located in the Chr17q21.31 locus, may exert differential risk regulation on SCZ and ASD by altering brain structure. Future studies should focus on the role of pseudogenes, lncRNAs, and cerebellum in synaptic pruning and neurodevelopmental disorders. [ABSTRACT FROM AUTHOR]

Abstract Background Multiple Sclerosis (MS), an autoimmune disorder causing demyelination and neurological damage, has been linked to 25-hydroxyvitamin D (25OHD) levels, suggesting its role in immune response and MS onset. This study used GWAS datasets to investigate genetic associations between 25OHD and MS. Methods We utilized a large-scale prospective cohort to evaluate serum 25OHD levels and MS risk. Linkage Disequilibrium Score Regression (LDSC) assessed genetic correlations between 25OHD levels and MS. Cross-trait genome-wide pleiotropy analysis revealed shared genetic loci. MAGMA analysis identified pleiotropic genes, enriched tissues, and gene sets. Stratified LDSC estimated tissue-specific and cell-specific heritability enrichment, and multi-trait co-localization analysis identified shared immune cell subsets. Bidirectional Mendelian Randomization (MR) assessed the causal association between 25OHD and MS risk. Results The observational study found a nonlinear relationship between 25OHD levels and MS risk, with the lowest quartile showing significant risk elevation. Our findings revealed shared genetic structure between 25OHD levels and MS, suggesting a common biological pathway involving immune function and CNS integrity. We found 24 independent loci shared between 25OHD levels and MS risk, enriched in brain tissues and involved in pathways like LDL, HDL, and TG metabolism. Four loci (6p24.3, 6p22.2, 12q14.1, and 19p13.2) had strong co-localization evidence, with mapped genes as potential drug targets. Bidirectional MR analysis supported a causal effect of 25OHD levels on MS risk, suggesting 25OHD supplementation could modulate MS risk. Conclusion This study reveals the complex relationship between 25OHD levels and MS, indicating that higher levels are not always advantageous and recommending moderation in supplementation. We identified SMARCA4 as a potential therapeutic target and detailed key pathways influencing this interaction. Graphical Abstract

Abstract Background Inflammatory bowel disease (IBD) and systemic lupus erythematosus (SLE) are autoimmune diseases that often coexist clinically. This phenomenon might be due to shared genetic components. Methods Genome-wide association study (GWAS) data for IBD and SLE were analyzed to determine both global and local genetic correlations using three methodologies: linkage disequilibrium score regression (LDSC), genetic covariance analyzer (GNOVA), and SUPERGNOVA. The genetic overlap and risk loci were subsequently examined using the conditional/conjunctional false discovery rate (cond/conjFDR) statistical framework. Furthermore, a multi-trait analysis of MTAG was employed to validate the loci, followed by an LDSC analysis focusing on tissue-specific gene expression. Results GWAS findings demonstrated a marked global genetic correlation between IBD (including Crohn’s disease and ulcerative colitis) and SLE. Locally, SLE showed a strong association with IBD and Crohn’s disease on chromosomes 10, 19, and 22. ConjFDR analysis confirmed the genetic overlap and identified relevant genetic risk loci. MTAG further validated several shared susceptibility genes. Additionally, the LDSC-SEG analysis results indicate that IBD (including CD and UC) and SLE are jointly enriched in the tissues of Spleen and Whole Blood. Conclusion This study confirms a genetic overlap between IBD and SLE, identifying marked comorbid genes and offering new insights for treating these diseases.

Abstract Hypertension is a disease associated with epigenetic aging. However, the pathogenic mechanism underlying this relationship remains unclear. We aimed to characterize the shared genetic architecture of hypertension and epigenetic aging, and identify novel risk loci. Leveraging genome-wide association studies (GWAS) summary statistics of hypertension (129,909 cases and 354,689 controls) and four epigenetic clocks (N = 34,710), we investigated genetic architectures and genetic overlap using bivariate casual mixture model and conditional/conjunctional false discovery rate methods. Functional gene-sets pathway analyses were performed by functional mapping and gene annotation (FUMA) protocol. Hypertension was polygenic with 2.8 K trait-influencing genetic variants. We observed cross-trait genetic enrichment and genetic overlap between hypertension and all four measures of epigenetic aging. Further, we identified 32 distinct genomic loci jointly associated with hypertension and epigenetic aging. Notably, rs1849209 was shared between hypertension and three epigenetic clocks (HannumAge, IEAA, and PhenoAge). The shared loci exhibited a combination of concordant and discordant allelic effects. Functional gene-set analyses revealed significant enrichment in biological pathways related to sensory perception of smell and nervous system processes. We observed genetic overlaps with mixed effect directions between hypertension and all four epigenetic aging measures, and identified 32 shared distinct loci with mixed effect directions, 25 of which were novel for hypertension. Shared genes enriched in biological pathways related to olfaction.

Background: Inflammatory bowel disease (IBD) and systemic lupus erythematosus (SLE) are autoimmune diseases that often coexist clinically. This phenomenon might be due to shared genetic components. Methods: Genome-wide association study (GWAS) data for IBD and SLE were analyzed to determine both global and local genetic correlations using three methodologies: linkage disequilibrium score regression (LDSC), genetic covariance analyzer (GNOVA), and SUPERGNOVA. The genetic overlap and risk loci were subsequently examined using the conditional/conjunctional false discovery rate (cond/conjFDR) statistical framework. Furthermore, a multi-trait analysis of MTAG was employed to validate the loci, followed by an LDSC analysis focusing on tissue-specific gene expression. Results: GWAS findings demonstrated a marked global genetic correlation between IBD (including Crohn's disease and ulcerative colitis) and SLE. Locally, SLE showed a strong association with IBD and Crohn's disease on chromosomes 10, 19, and 22. ConjFDR analysis confirmed the genetic overlap and identified relevant genetic risk loci. MTAG further validated several shared susceptibility genes. Additionally, the LDSC-SEG analysis results indicate that IBD (including CD and UC) and SLE are jointly enriched in the tissues of Spleen and Whole Blood. Conclusion: This study confirms a genetic overlap between IBD and SLE, identifying marked comorbid genes and offering new insights for treating these diseases. [ABSTRACT FROM AUTHOR]

Background Psychiatric disorders and type 2 diabetes mellitus (T2DM) are heritable, polygenic, and often comorbid conditions, yet knowledge about their potential shared familial risk is lacking. We used family designs and T2DM polygenic risk score (T2DM-PRS) to investigate the genetic associations between psychiatric disorders and T2DM. Methods We linked 659 906 individuals born in Denmark 1990–2000 to their parents, grandparents, and aunts/uncles using population-based registers. We compared rates of T2DM in relatives of children with and without a diagnosis of any or one of 11 specific psychiatric disorders, including neuropsychiatric and neurodevelopmental disorders, using Cox regression. In a genotyped sample (iPSYCH2015) of individuals born 1981–2008 (n = 134 403), we used logistic regression to estimate associations between a T2DM-PRS and these psychiatric disorders. Results Among 5 235 300 relative pairs, relatives of individuals with a psychiatric disorder had an increased risk for T2DM with stronger associations for closer relatives (parents:hazard ratio = 1.38, 95% confidence interval 1.35–1.42; grandparents: 1.14, 1.13–1.15; and aunts/uncles: 1.19, 1.16–1.22). In the genetic sample, one standard deviation increase in T2DM-PRS was associated with an increased risk for any psychiatric disorder (odds ratio = 1.11, 1.08–1.14). Both familial T2DM and T2DM-PRS were significantly associated with seven of 11 psychiatric disorders, most strongly with attention-deficit/hyperactivity disorder and conduct disorder, and inversely with anorexia nervosa. Conclusions Our findings of familial co-aggregation and higher T2DM polygenic liability associated with psychiatric disorders point toward shared familial risk. This suggests that part of the comorbidity is explained by shared familial risks. The underlying mechanisms still remain largely unknown and the contributions of genetics and environment need further investigation. [ABSTRACT FROM AUTHOR]

Numerous loci have been identified to be associated with brain morphology. Several genomic regions are associated with multiple neuroimaging traits, potentially playing a critical role during brain development and diseases. Genetic evidence suggests correlative, causal, and pleiotropic relationships between brain morphology and neuropsychiatric diseases. Neuropsychiatric disorders exhibit similar global neuroimaging patterns alongside diverse regional patterns. Exploring the genetics underlying brain morphology holds promise for diagnosing, predicting, and treating neuropsychiatric disorders. Uncovering the genetic architectures of brain morphology offers valuable insights into brain development and disease. Genetic association studies of brain morphological phenotypes have discovered thousands of loci. However, interpretation of these loci presents a significant challenge. One potential solution is exploring the genetic overlap between brain morphology and disorders, which can improve our understanding of their complex relationships, ultimately aiding in clinical applications. In this review, we examine current evidence on the genetic associations between brain morphology and neuropsychiatric traits. We discuss the impact of these associations on the diagnosis, prediction, and treatment of neuropsychiatric diseases, along with suggestions for future research directions. [ABSTRACT FROM AUTHOR]

This study aims to explore the genetic architecture shared between Attention-Deficit/Hyperactivity Disorder (ADHD) and risk behavior. Based 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. We 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. The majority of our data sources were of European origin, which may limit the generalizability of our findings to other ethnic populations. This 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. • ADHD has a significant positive genetic correlation with risk-taking behavior. • ADHD and risk-taking behavior have pleiotropic loci. • GRIN2A and FES potential are genes newly discovered shared between ADHD and risk-taking behavior. • Bi-directional Mendelian randomization suggests a causal relationship between ADHD and risk-taking behavior. [ABSTRACT FROM AUTHOR]

BackgroundThe genetic association between psychiatric disorders and hemorrhoidal disease (HEM) is still not well known. The work aims to investigate their comorbidity at a genetic level.MethodsUtilizing recent large-scale genome-wide association studies (GWAS), we investigated the genetic overlap at the single nucleotide polymorphism (SNP), gene, and molecular level between depression and HEM, bipolar disorder (BD) and HEM, neuroticism and HEM, as well as schizophrenia (SCZ) and HEM. The cross-trait genes were validated through the utilization of transcriptome and proteome methodologies. The causal link was assessed using bidirectional two-sample Mendelian randomization analysis (MR) analysis. MRlap corrects for the potential bias in estimation caused by sample overlap.ResultsWe discovered significant positive genetic associations between these four types of psychiatric disorders and HEM. Cross-phenotypic association analyses identified shared SNPs along with 17 specific loci between psychiatric disorders and HEM. MAGMA identified a total of 2304 pleiotropic genes, several of which showed significant expression in the results of transcriptome and proteome analyses. We observed that these genes are mostly associated with the regulation of transcription factors and particular DNA binding activities. Lastly, MR analysis provided evidence supporting a correlation between these conditions.ConclusionThis study revealed a genetic correlation between four psychiatric disorders and HEM, identified pleiotropic loci, found multiple candidate genes, and confirmed causal relationships. This has enhanced our comprehension of the common genetic mechanisms of psychiatric disorders and HEM.

ObjectiveObservational studies have frequently shown a co-occurrence of psychiatric disorders and Obstructive sleep apnea (OSA), with major depressive disorder (MDD) being a prevalent psychiatric disorder. This study aims to investigate the genetic overlap between MDD and OSA to explore their underlying pathological mechanisms.MethodsLeveraging the extensive and recent GWAS for OSA and MDD, we conducted genetic correlation analyses utilizing Linkage disequilibrium score regression (LDSC), re-evaluated their pleiotropic Single-nucleotide polymorphisms (SNP) with Cross-Phenotype Association (CPASSOC) and Colocalization (COLOC), investigated the overlap at the gene level using physical annotations and Multi-marker Analysis of GenoMic Annotation (MAGMA), and finally employed Mendelian randomization (MR) to assess potential causal relationships between the two disorders.ResultsUpon our investigation, we established that MDD and OSA exhibit high heritability (h2MDD=0.02, h2OSA=0.04) alongside a significant genetic correlation (rg=0.31, P= 1.42E-23). Utilizing CPASSOC, we identified 397 pleiotropic SNPs, associable with 45 loci, two of which share common genetic fragments with a pleiotropic role. Furthermore, the MAGMA study uncovered a total of 154 pleiotropic genes capable of influencing multiple brain regions. Lastly, leveraging MR analysis, we concluded that MDD heightens the risk of developing OSA (P=3. 10E-04, OR (95%CI):1.28(1.12~ 1.47)).ConclusionIn summary, our study identified PCLO as a common gene between OSA and MDD and provided evidence that MDD causally contributes to the development of OSA. These insights enhance our understanding of the shared mechanisms underlying the comorbidity of these conditions.

Abstract Background To study the shared genetic structure between autoimmune diseases and B-cell acute lymphoblastic leukemia (B-ALL) and identify the shared risk loci and genes and genetic mechanisms involved. Methods Based on large-scale genome-wide association study (GWAS) summary-level data sets, we observed genetic overlaps between autoimmune diseases and B-ALL, and cross-trait pleiotropic analysis was performed to detect shared pleiotropic loci and genes. A series of functional annotation and tissue-specific analysis were performed to determine the influence of pleiotropic genes. The heritability enrichment analysis was used to detect crucial immune cells and tissues. Finally, bidirectional Mendelian randomization (MR) methods were utilized to investigate the casual associations. Results Our research highlighted shared genetic mechanisms between seven autoimmune disorders and B-ALL. A total of 73 pleiotropic loci were identified at the genome-wide significance level (P

Background: The existence of chronic pain increases susceptibility to virus and is now widely acknowledged as a prominent feature recognized as a major manifestation of long-term coronavirus disease 2019 (COVID-19) infection. Given the ongoing COVID-19 pandemic, it is imperative to explore the genetic associations between chronic pain and predisposition to COVID-19. Methods: We conducted genetic analysis at the single nucleotide polymorphism (SNP), gene, and molecular levels using summary statistics of genome-wide association study (GWAS) and analyzed the drug targets by summary data-based Mendelian randomization analysis (SMR) to alleviate the multi-site chronic pain in COVID-19. Additionally, we performed a latent causal variable (LCV) method to investigate the causal relationship between chronic pain and susceptibility to COVID-19. Results: The cross-trait meta-analysis identified 19 significant SNPs shared between COVID-19 and chronic pain. Coloc analysis indicated that the posterior probability of association (PPH4) for three loci was above 70% in both critical COVID-19 and COVID-19, with the corresponding top three SNPs being rs13135092, rs7588831, and rs13135092. A total of 482 significant overlapped genes were detected from MAGMA and CPASSOC results. Additionally, the gene ANAPC4 was identified as a potential drug target for treating chronic pain (P=7.66E-05) in COVID-19 (P=8.23E-03). Tissue enrichment analysis highlighted that the amygdala (P=7.81E-04) and prefrontal cortex (P=8.19E-05) as pivotal in regulating chronic pain of critical COVID-19. KEGG pathway enrichment further revealed the enrichment of pleiotropic genes in both COVID-19 (P=3.20E-03,Padjust=4.77E-02,hsa05171) and neurotrophic pathways (P=9.03E-04,Padjust =2.55E-02,hsa04621). Finally, the latent causal variable (LCV) model was applied to find the genetic component of critical COVID-19 was causal for multi-site chronic pain (P=0.015), with a genetic causality proportion (GCP) of was 0.60. Conclusions: In this study, we identified several functional genes and underscored the pivotal role of the inflammatory system in the correlation between the paired traits. Notably, heat shock proteins emerged as potential objective biomarkers for chronic pain symptoms in individuals with COVID-19. Additionally, the ubiquitin system might play a role in mediating the impact of COVID-19 on chronic pain. These findings contribute to a more comprehensive understanding of the pleiotropy between COVID-19 and chronic pain, offering insights for therapeutic trials. [ABSTRACT FROM AUTHOR]

Abstract Milling quality (MQ) and grain shape (GS) of rice (Oryza sativa L.) are correlated traits, both determine farmers’ final profit. More than one population under multiple environments may provide valuable information for breeding selection on these MQ-GS correlations. However, suitable analytical methods for reciprocal introgression lines with linkage map for this kind of correlation remains unclear. In this study, our major tasks were (1) to provide a set of reciprocal introgression lines (composed of two BC2RIL populations) suitable for mapping by linkage mapping using markers/bins with physical positions; (2) to test the mapping effects of different methods by using MQ-GS correlation dissection as sample case; (3) to perform genetic and breeding simulation on pyramiding favorite alleles of QTLs for representative MQ-GS traits. Finally, with four analysis methods and data collected under five environments, we identified about 28.4 loci on average for MQ-GS traits. Notably, 52.3% of these loci were commonly detected by different methods and eight loci were novel. There were also nine regions harboring loci for different MQ-GS traits which may be underlying the MQ-GS correlations. Background independent (BI) loci were also found for each MQ and GS trait. All these information may provide useful resources for rice molecular breeding.

Observational studies have reported high comorbidity between obesity and severe COVID-19. The aim of this study is to explore whether genetic factors are involved in the co-occurrence of the two traits. Based on the available genomewide association studies (GWAS) summary statistics, we explored the genetic correlation and performed cross-trait meta-analysis (CPASSOC) and colocalization analysis (COLOC) to detect pleiotropic single nucleotide polymorphisms (SNPs). At the genetic level, we obtained genes detected by Functional mapping and annotation (FUMA) and the Multi-marker Analysis of GenoMic Annotation (MAGMA). Potential functional genes were further investigated by summary-data-based Mendelian randomization (SMR). Finally, the casualty was identiied using the latent causal variable model (LCV). A significant positive genetic correlation was revealed between obesity and COVID-19. We found 331 shared genetic SNPs by CPASSOC and 13 shared risk loci by COLOC. At the genetic level, We obtained 3546 pleiotropic genes, among which 107 genes were found to be significantly expressed by SMR. Lastly, we observed these genes were mainly enriched in immune pathways and signaling transduction. These indings could provide new insights into the etiology of comorbidity and have implications for future therapeutic trial. [ABSTRACT FROM AUTHOR]

Abstract Background Irritable bowel syndrome (IBS) often co-occurs with psychiatric and gastrointestinal disorders. A recent genome-wide association study (GWAS) identified several genetic risk variants for IBS. However, most of the heritability remains unidentified, and the genetic overlap with psychiatric and somatic disorders is not quantified beyond genome-wide genetic correlations. Here, we characterize the genetic architecture of IBS, further, investigate its genetic overlap with psychiatric and gastrointestinal phenotypes, and identify novel genomic risk loci. Methods Using GWAS summary statistics of IBS (53,400 cases and 433,201 controls), and psychiatric and gastrointestinal phenotypes, we performed bivariate casual mixture model analysis to characterize the genetic architecture and genetic overlap between these phenotypes. We leveraged identified genetic overlap to boost the discovery of genomic loci associated with IBS, and to identify specific shared loci associated with both IBS and psychiatric and gastrointestinal phenotypes, using the conditional/conjunctional false discovery rate (condFDR/conjFDR) framework. We used functional mapping and gene annotation (FUMA) for functional analyses. Results IBS was highly polygenic with 12k trait-influencing variants. We found extensive polygenic overlap between IBS and psychiatric disorders and to a lesser extent with gastrointestinal diseases. We identified 132 independent IBS-associated loci (condFDR

Schizophrenia (SZ) is a complex disorder with a highly polygenic inheritance. It can be conceived as the extreme expression of a continuum of traits that are present in the general population often broadly referred to as schizotypy. However, it is still poorly understood how these traits overlap genetically with the disorder. We investigated whether polygenic risk for SZ is associated with these disorder-related phenotypes (schizotypy, psychotic-like experiences, and subclinical psychopathology) in a sample of 253 non-clinically identified participants. Polygenic risk scores (PRSs) were constructed based on the latest SZ genome-wide association study using the PRS-CS method. Their association with self-report and interview measures of SZ-related traits was tested. No association with either schizotypy or psychotic-like experiences was found. However, we identified a significant association with the Motor Change subscale of the Comprehensive Assessment of At-Risk Mental States (CAARMS) interview. Our results indicate that the genetic overlap of SZ with schizotypy and psychotic-like experiences is less robust than previously hypothesized. The relationship between high PRS for SZ and motor abnormalities could reflect neurodevelopmental processes associated with psychosis proneness and SZ. [ABSTRACT FROM AUTHOR]

Schizophrenia is associated with increased risk of cardiovascular disease (CVD), although there is variation in risk among individuals. There are indications of shared genetic etiology between schizophrenia and CVD, but the nature of the overlap remains unclear. The aim of this study was to fill this gap in knowledge. Overlapping genetic architectures between schizophrenia and CVD risk factors were assessed by analyzing recent genome-wide association study (GWAS) results. The bivariate causal mixture model (MiXeR) was applied to estimate the number of shared variants and the conjunctional false discovery rate (conjFDR) approach was used to pinpoint specific shared loci. Extensive genetic overlap was found between schizophrenia and CVD risk factors, particularly smoking initiation (N=8.6K variants) and body mass index (BMI) (N=8.1K variants). Several specific shared loci were detected between schizophrenia and BMI (N=304), waist-to-hip ratio (N=193), smoking initiation (N=293), systolic (N=294) and diastolic (N=259) blood pressure, type 2 diabetes (N=147), lipids (N=471), and coronary artery disease (N=35). The schizophrenia risk loci shared with smoking initiation had mainly concordant effect directions, and the risk loci shared with BMI had mainly opposite effect directions. The overlapping loci with lipids, blood pressure, waist-to-hip ratio, type 2 diabetes, and coronary artery disease had mixed effect directions. Functional analyses implicated mapped genes that are expressed in brain tissue and immune cells. These findings indicate a genetic propensity to smoking and a reduced genetic risk of obesity among individuals with schizophrenia. The bidirectional effects of the shared loci with the other CVD risk factors may imply differences in genetic liability to CVD across schizophrenia subgroups, possibly underlying the variation in CVD comorbidity. [ABSTRACT FROM AUTHOR]

Low vitamin D (vitD) levels have been consistently reported in schizophrenia (SCZ) suggesting a role in the etiopathology. However, little is known about the role of underlying shared genetic mechanisms. We applied a conditional/conjunctional false discovery rate approach (FDR) on large, nonoverlapping genome-wide association studies for SCZ (N cases = 53 386, N controls = 77 258) and vitD serum concentration (N  = 417 580) to evaluate shared common genetic variants. The identified genomic loci were characterized using functional analyses and biological repositories. We observed cross-trait SNP enrichment in SCZ conditioned on vitD and vice versa, demonstrating shared genetic architecture. Applying the conjunctional FDR approach, we identified 72 loci jointly associated with SCZ and vitD at conjunctional FDR < 0.05. Among the 72 shared loci, 40 loci have not previously been reported for vitD, and 9 were novel for SCZ. Further, 64% had discordant effects on SCZ-risk and vitD levels. A mixture of shared variants with concordant and discordant effects with a predominance of discordant effects was in line with weak negative genetic correlation (rg = −0.085). Our results displayed shared genetic architecture between SCZ and vitD with mixed effect directions, suggesting overlapping biological pathways. Shared genetic variants with complex overlapping mechanisms may contribute to the coexistence of SCZ and vitD deficiency and influence the clinical picture. [ABSTRACT FROM AUTHOR]

Background: Irritable bowel syndrome (IBS) often co-occurs with psychiatric and gastrointestinal disorders. A recent genome-wide association study (GWAS) identified several genetic risk variants for IBS. However, most of the heritability remains unidentified, and the genetic overlap with psychiatric and somatic disorders is not quantified beyond genome-wide genetic correlations. Here, we characterize the genetic architecture of IBS, further, investigate its genetic overlap with psychiatric and gastrointestinal phenotypes, and identify novel genomic risk loci. Methods: Using GWAS summary statistics of IBS (53,400 cases and 433,201 controls), and psychiatric and gastrointestinal phenotypes, we performed bivariate casual mixture model analysis to characterize the genetic architecture and genetic overlap between these phenotypes. We leveraged identified genetic overlap to boost the discovery of genomic loci associated with IBS, and to identify specific shared loci associated with both IBS and psychiatric and gastrointestinal phenotypes, using the conditional/conjunctional false discovery rate (condFDR/conjFDR) framework. We used functional mapping and gene annotation (FUMA) for functional analyses. Results: IBS was highly polygenic with 12k trait-influencing variants. We found extensive polygenic overlap between IBS and psychiatric disorders and to a lesser extent with gastrointestinal diseases. We identified 132 independent IBS-associated loci (condFDR < 0.05) by conditioning on psychiatric disorders (n = 127) and gastrointestinal diseases (n = 24). Using conjFDR, 70 unique loci were shared between IBS and psychiatric disorders. Functional analyses of shared loci revealed enrichment for biological pathways of the nervous and immune systems. Genetic correlations and shared loci between psychiatric disorders and IBS subtypes were different. Conclusions: We found extensive polygenic overlap of IBS and psychiatric and gastrointestinal phenotypes beyond what was revealed with genetic correlations. Leveraging the overlap, we discovered genetic loci associated with IBS which implicate a wide range of biological pathways beyond the gut-brain axis. Genetic differences may underlie the clinical subtype of IBS. These results increase our understanding of the pathophysiology of IBS which may form the basis for the development of individualized interventions. [ABSTRACT FROM AUTHOR]

Neurodegenerative diseases are a group of disorders characterized by neuronal cell death causing a variety of physical and mental problems. While these disorders can be characterized by their phenotypic presentation within the nervous system, their aetiologies differ to varying degrees. The majority of previous genetic evidence for overlap between neurodegenerative diseases has been pairwise. In this study, we aimed to identify overlap between the 4 investigated neurodegenerative disorders (Alzheimer's disease, amyotrophic lateral sclerosis, Lewy body dementia, and Parkinson's disease) at the variant, gene, genomic locus, gene-set, cell, or tissue level, with specific interest in overlap between 3 or more diseases. Using local genetic correlation, we found 2 loci (TMEM175 and HLA) that were shared across 3 disorders. We also highlighted genes, genomic loci, gene sets, cell types, and tissue types which may be important to 2 or more disorders by analyzing the association of variants with a common factor estimated from the 4 disorders. Our study successfully highlighted genetic loci and tissues associated with 2 or more neurodegenerative diseases. [ABSTRACT FROM AUTHOR]

Opioid use disorder (OUD) and mental disorders are often comorbid, with increased morbidity and mortality. The causes underlying this relationship are poorly understood. Although these conditions are highly heritable, their shared genetic vulnerabilities remain unaccounted for. We applied the conditional/conjunctional false discovery rate (cond/conjFDR) approach to analyse summary statistics from independent genome wide association studies of OUD, schizophrenia (SCZ), bipolar disorder (BD) and major depression (MD) of European ancestry. Next, we characterized the identified shared loci using biological annotation resources. OUD data were obtained from the Million Veteran Program, Yale‐Penn and Study of Addiction: Genetics and Environment (SAGE) (15 756 cases, 99 039 controls). SCZ (53 386 cases, 77 258 controls), BD (41 917 cases, 371 549 controls) and MD (170 756 cases, 329 443 controls) data were provided by the Psychiatric Genomics Consortium. We discovered genetic enrichment for OUD conditional on associations with SCZ, BD, MD and vice versa, indicating polygenic overlap with identification of 14 novel OUD loci at condFDR < 0.05 and 7 unique loci shared between OUD and SCZ (n = 2), BD (n = 2) and MD (n = 7) at conjFDR < 0.05 with concordant effect directions, in line with estimated positive genetic correlations. Two loci were novel for OUD, one for BD and one for MD. Three OUD risk loci were shared with more than one psychiatric disorder, at DRD2 on chromosome 11 (BD and MD), at FURIN on chromosome 15 (SCZ, BD and MD) and at the major histocompatibility complex region (SCZ and MD). Our findings provide new insights into the shared genetic architecture between OUD and SCZ, BD and MD, indicating a complex genetic relationship, suggesting overlapping neurobiological pathways. [ABSTRACT FROM AUTHOR]

Background: Neuroinflammation is involved in the pathophysiology of Alzheimer's disease (AD), including immune-linked genetic variants and molecular pathways, microglia and astrocytes. Multiple Sclerosis (MS) is a chronic, immune-mediated disease with genetic and environmental risk factors and neuropathological features. There are clinical and pathobiological similarities between AD and MS. Here, we investigated shared genetic susceptibility between AD and MS to identify putative pathological mechanisms shared between neurodegeneration and the immune system. Methods: We analysed GWAS data for late-onset AD (N cases = 64,549, N controls = 634,442) and MS (N cases = 14,802, N controls = 26,703). Gaussian causal mixture modelling (MiXeR) was applied to characterise the genetic architecture and overlap between AD and MS. Local genetic correlation was investigated with Local Analysis of [co]Variant Association (LAVA). The conjunctional false discovery rate (conjFDR) framework was used to identify the specific shared genetic loci, for which functional annotation was conducted with FUMA and Open Targets. Results: MiXeR analysis showed comparable polygenicities for AD and MS (approximately 1800 trait-influencing variants) and genetic overlap with 20% of shared trait-influencing variants despite negligible genetic correlation (rg = 0.03), suggesting mixed directions of genetic effects across shared variants. conjFDR analysis identified 16 shared genetic loci, with 8 having concordant direction of effects in AD and MS. Annotated genes in shared loci were enriched in molecular signalling pathways involved in inflammation and the structural organisation of neurons. Conclusions: Despite low global genetic correlation, the current results provide evidence for polygenic overlap between AD and MS. The shared loci between AD and MS were enriched in pathways involved in inflammation and neurodegeneration, highlighting new opportunities for future investigation.

Background: Alcohol use disorder (AUD) and schizophrenia (SCZ) frequently co-occur, and large-scale genome-wide association studies (GWAS) have identified significant genetic correlations between these disorders. Methods: We used the largest published GWAS for AUD (total cases = 77 822) and SCZ (total cases = 46 827) to identify genetic variants that influence both disorders (with either the same or opposite direction of effect) and those that are disorder specific. Results: We identified 55 independent genome-wide significant single nucleotide polymorphisms with the same direction of effect on AUD and SCZ, 8 with robust effects in opposite directions, and 98 with disorder-specific effects. We also found evidence for 12 genes whose pleiotropic associations with AUD and SCZ are consistent with mediation via gene expression in the prefrontal cortex. The genetic covariance between AUD and SCZ was concentrated in genomic regions functional in brain tissues (p = 0.001). Conclusions: Our findings provide further evidence that SCZ shares meaningful genetic overlap with AUD. [ABSTRACT FROM AUTHOR]

The phenotypic and genetic links between body fat phenotypes and primary open-angle glaucoma (POAG) are unclear. We conducted a meta-analysis of relevant longitudinal epidemiological studies to evaluate the phenotypic link. To identify genetic links, we performed genetic correlation analysis and pleiotropy analysis of genome-wide association study summary statistics datasets of POAG, intraocular pressure (IOP), vertical cup-to-disc ratio, obesity, body mass index (BMI), and waist-to-hip ratio. In the meta-analysis, we first established that obese and underweight populations have a significantly higher risk of POAG using longitudinal data. We also discovered positive genetic correlations between POAG and BMI and obesity phenotypes. Finally, we identified over 20 genomic loci jointly associated with POAG/IOP and BMI. Among them, the genes loci CADM2, RP3-335N17.2, RP11-793K1.1, RPS17P5, and CASC20 showed the lowest false discovery rate. These findings support the connection between body fat phenotypes and POAG. The newly identified genomic loci and genes render further functional investigation. [ABSTRACT FROM AUTHOR]

• The phenotypes associated with Sarcopenia share a common genetic architecture. • There exists a strong genetic correlation between muscle strength and gait speed. • Thirteen pleiotropic loci were identified for pairs of Sarcopenia subphenotypes. • Novel candidate genes and molecular markers were proposed for Sarcopenia risk. Sarcopenia is a progressive age-related muscle disease characterized by low muscle strength, quantity and quality, and low physical performance. The clinical overlap between these subphenotypes (reduction in muscle strength, quantity and quality, and physical performance) was evidenced, but the genetic overlap is still poorly investigated. Herein, we investigated whether there is a genetic overlap amongst sarcopenia subphenotypes in the search for more effective molecular markers for this disease. For that, a Bioinformatics approach was used to identify and characterize pleiotropic effects at the genome, loci and gene levels using Genome-wide association study results. As a result, a high genetic correlation was identified between gait speed and muscle strength (rG=0.5358, p=3.39 × 10-8). Using a Pleiotropy-informed conditional and conjunctional false discovery rate method we identified two pleiotropic loci for muscle strength and gait speed, one of them was nearby the gene PHACTR1. Moreover, 11 pleiotropic loci and 25 genes were identified for muscle mass and muscle strength. Lastly, using a gene-based GWAS approach three candidate genes were identified in the overlap of the three Sarcopenia subphenotypes: FTO, RPS10 and CALCR. The current study provides evidence of genetic overlap and pleiotropy among sarcopenia subphenotypes and highlights novel candidate genes and molecular markers associated with the risk of sarcopenia. [Display omitted] [ABSTRACT FROM AUTHOR]

Migraine and headache frequently co-occur with type 2 diabetes (T2D), suggesting a shared aetiology between the two conditions. We used genome-wide association study (GWAS) data to investigate the genetic overlap and causal relationship between migraine and headache with T2D. Using linkage disequilibrium score regression (LDSC), we found a significant genetic correlation between migraine and T2D (rg = 0.06, p = 1.37 × 10−5) and between headache and T2D (rg = 0.07, p = 3.0 × 10−4). Using pairwise GWAS (GWAS-PW) analysis, we identified 11 pleiotropic regions between migraine and T2D and 5 pleiotropic regions between headache and T2D. Cross-trait SNP meta-analysis identified 23 novel SNP loci (Pmeta < 5 × 10−8) associated with migraine and T2D, and three novel SNP loci associated with headache and T2D. Cross-trait gene-based overlap analysis identified 33 genes significantly associated (Pgene-based < 3.85 × 10−6) with migraine and T2D, and 11 genes associated with headache and T2D, with 7 genes (EHMT2, SLC44A4, PLEKHA1, CFDP1, TMEM170A, CHST6, and BCAR1) common between them. There was also a significant overlap of genes nominally associated (Pgene-based < 0.05) with both migraine and T2D (Pbinomial-test = 2.83 × 10−46) and headache and T2D (Pbinomial-test = 4.08 × 10−29). Mendelian randomisation (MR) analyses did not provide consistent evidence for a causal relationship between migraine and T2D. However, we found headache was causally associated (inverse-variance weighted, ORIVW = 0.90, Pivw = 7 × 10−3) with T2D. Our findings robustly confirm the comorbidity of migraine and headache with T2D, with shared genetically controlled biological mechanisms contributing to their co-occurrence, and evidence for a causal relationship between headache and T2D. [ABSTRACT FROM AUTHOR]

Schizophrenia is a complex polygenic disorder with subtle, distributed abnormalities in brain morphology. There are indications of shared genetic architecture between schizophrenia and brain measures despite low genetic correlations. Through the use of analytical methods that allow for mixed directions of effects, this overlap may be leveraged to improve our understanding of underlying mechanisms of schizophrenia and enrich polygenic risk prediction outcome. We ran a multivariate genome-wide analysis of 175 brain morphology measures using data from 33,735 participants of the UK Biobank and analyzed the results in a conditional false discovery rate together with schizophrenia genome-wide association study summary statistics of the Psychiatric Genomics Consortium (PGC) Wave 3. We subsequently created a pleiotropy-enriched polygenic score based on the loci identified through the conditional false discovery rate approach and used this to predict schizophrenia in a nonoverlapping sample of 743 individuals with schizophrenia and 1074 healthy controls. We found that 20% of the loci and 50% of the genes significantly associated with schizophrenia were also associated with brain morphology. The conditional false discovery rate analysis identified 428 loci, including 267 novel loci, significantly associated with brain-linked schizophrenia risk, with functional annotation indicating high relevance for brain tissue. The pleiotropy-enriched polygenic score explained more variance in liability than conventional polygenic scores across several scenarios. Our results indicate strong genetic overlap between schizophrenia and brain morphology with mixed directions of effect. The results also illustrate the potential of exploiting polygenetic overlap between brain morphology and mental disorders to boost discovery of brain tissue–specific genetic variants and its use in polygenic risk frameworks. [ABSTRACT FROM AUTHOR]

Recent studies have indicated that heterozygous loss-of-function variants in fibroblast growth factor receptor 1 (FGFR1) are involved in the development of congenital hypogonadotropic hypogonadism and combined pituitary hormone deficiency (CPHD). We encountered a Japanese boy with short stature and pubertal failure. Endocrine studies showed GH, TSH, and LH/FSH deficiencies, and brain magnetic resonance imaging delineated hypoplastic anterior pituitary and ectopic posterior pituitary. The patient was treated with GH, l-thyroxine, and hCG/rFSH. Next-generation sequencing panel for pituitary dysfunction identified a probably weak disease-associated heterozygous missense variant in FGFR1 (NM_023110.3:c.176A>T:p.(Asp59Val)), together with a probably nondeleterious heterozygous missense variant in KISS1R (NM_032551.5:c.769G>C:p.(Val257Leu)). We also review six previously reported CHPD patients with probably deleterious FGFR1 variants. The data, in conjunction with the previously reported cases, argue for the relevance of FGFR1 variants to the development of CPHD. [ABSTRACT FROM AUTHOR]

The comorbidity among vascular diseases has been widely reported, however, the contribution of shared genetic components remains ambiguous. Based on genome-wide association study summary statistics, we employed statistical genetics methodologies to explore the shared genetic basis of eight vascular diseases: coronary artery disease, abdominal aortic aneurysm, ischemic stroke, peripheral artery disease, thoracic aortic aneurysm, phlebitis, varicose veins, and venous thromboembolism. We assessed global and local genetic correlations among these disorders by linkage disequilibrium score regression, high-definition likelihood, and local analysis of variant association. Cross-trait analyses conducted with CPASSOC identified pleiotropic variants and loci. Further, biological pathways at the multi-omics level were explored using multimarker analysis of genomic annotation, transcriptome-wide and proteome-wide association studies. Causal associations among the vascular diseases were evaluated by mendelian randomization and latent causal variable to assess vertical pleiotropic effects. We found significant global genetic associations in 18 pairs of vascular diseases. Additionally, we discovered 317 unique genomic regions where at least one pair of traits demonstrated significant correlation. Multi-trait association analysis identified 19,361 significant potential pleiotropic variants in 274 independent pleiotropic loci. Multi-trait colocalization analysis revealed 56 colocalized loci in specific disease sets. Gene-based analysis identified 700 potential pleiotropic genes, which were subsequently validated at both transcriptome and protein levels. Gene-set enrichment analysis supports the role of biological pathways such as vessel wall structure, coagulation and lipid transport in vascular disease. Additionally, 7 pairs of vascular diseases have a causal relationship. Our study indicates a shared genetic basis and the presence of common risk genes among vascular diseases. These findings offer novel insights into potential mechanisms underlying the association between vascular diseases, as well as provide guidance for interventions and treatments of multi-vascular conditions. • The first comprehensive exploration of the shared genetic etiology of vascular-related diseases. • Multiple mechanisms such as thrombosis and vascular biological behavior are shared across multiple vascular diseases through statistical genetics approaches revealed at the multi-omics level. [ABSTRACT FROM AUTHOR]

Background and aim: Schizophrenia (SCZ) and bipolar disorder (BD) have a high comorbidity of alcohol use disorder (AUD), and both comorbid AUD and excessive alcohol consumption (AC) have been linked to greater illness severity. We aimed to identify genomic loci jointly associated with SCZ, BD, AUD and AC to gain further insights into their shared genetic architecture. Design: We analysed summary data (P values and Z scores) from genome-wide association studies (GWAS) using conjunctional false discovery rate (conjFDR) analysis, which increases power to discover shared genomic loci. We functionally characterized the identified loci using publicly available biological resources. Setting: AUD and AC data provided by the Million Veteran Program, derived from the United States Department of Veterans Affairs Healthcare System. SCZ and BD data provided by the Psychiatric Genomics Consortium, based on cohorts from countries in Europe, North America and Australia. Participants: AUD (34 658 cases, 167 346 controls), AC (n = 200 680), SCZ (31 013 cases and 38 918 controls), BD (20 352 cases and 31 358 controls). All participants were of European ancestry. Measurements: Genomic loci shared between alcohol traits, SCZ and BD at conjFDR <0.05. Findings: Conditional Q-Q plots showed single-nucleotide polymorphism (SNP) enrichment for both alcohol traits across different levels of significance with SCZ and BD, and vice versa. Using conjFDR analysis we leveraged this genetic enrichment and identified several loci shared between SCZ and AUD (n = 28) and AC (n = 24), BD and AUD (n = 2) and AC (n = 8) at conjFDR <0.05. Among these loci, 24 are novel for AUD, 15 are novel for AC, three are novel for SCZ and one is novel for BD. There was a mixture of same and opposite effect directions among the shared loci. Conclusions: Alcohol use disorder and alcohol consumption share genomic loci with the psychiatric disorders schizophrenia and bipolar disorder with a mixed pattern of effect directions, indicating a complex genetic relationship between the phenotypes. [ABSTRACT FROM AUTHOR]

Background: Mitochondrial participation in tumorigenesis and metastasis has been studied for many years, but several aspects of this mechanism remain unclear, such as the association of mitochondrial DNA (mtDNA) with different cancers. Here, based on two independent datasets, we modelled an mtDNA mutation-cancer network by systematic integrative analysis including 37 cancer types to identify the mitochondrial variants found in common among them. Results: Our network showed mtDNA associations between gastric cancer and other cancer types, particularly kidney, liver, and prostate cancers, which is suggestive of a potential role of such variants in the metastatic processes among these cancer types. A graph-based interactive web tool was made available at www..lghm.ufpa.br/mtdna. We also highlighted that most shared variants were in the MT-ND4, MT-ND5 and D-loop, and that some of these variants were nonsynonymous, indicating a special importance of these variants and regions regarding cancer progression, involving genomic and epigenomic alterations. Conclusions: This study reinforces the importance of studying mtDNA in cancer and offers new perspectives on the potential involvement of different mitochondrial variants in cancer development and metastasis. [ABSTRACT FROM AUTHOR]

Risk factors and long-term consequences of COVID-19 infection are unclear but can be investigated with large-scale genomic data. To distinguish correlation from causation, we performed in-silico analyses of three COVID-19 outcomes (N > 1,000,000). We show genetic correlation and putative causality with depressive symptoms, metformin use (genetic causality proportion (gĉp) with severe respiratory COVID-19 = 0.576, p = 1.07 × 10−5 and hospitalized COVID-19 = 0.713, p = 0.003), and alcohol drinking status (gĉp with severe respiratory COVID-19 = 0.633, p = 7.04 × 10−5 and hospitalized COVID-19 = 0.848, p = 4.13 × 10−13). COVID-19 risk loci associated with several hematologic biomarkers. Comprehensive findings inform genetic contributions to COVID-19 epidemiology, molecular mechanisms, and risk factors and potential long-term health effects of severe response to infection. [ABSTRACT FROM AUTHOR]

A range of sleep disturbances are commonly experienced by patients with psychiatric disorders, and genome-wide genetic analyses have shown some significant genetic correlations between these traits. Here, we applied novel statistical genetic methodologies to better characterize the potential shared genetic architecture between sleep-related phenotypes and psychiatric disorders. Using the MiXeR method, which can estimate polygenic overlap beyond genetic correlation, the shared genetic architecture between major psychiatric disorders (bipolar disorder [ N = 51,710], depression [ N = 480,359], and schizophrenia [ N = 77,096]) and sleep-related phenotypes (chronotype [ N = 449,734], insomnia [ N = 386,533] and sleep duration [ N = 446,118]) were quantified on the basis of genetic summary statistics. Furthermore, the conditional/conjunctional false discovery rate framework was used to identify specific shared loci between these phenotypes, for which positional and functional annotation were conducted with FUMA. Extensive genetic overlap between the sleep-related phenotypes and bipolar disorder (63%–77%), depression (76%–79%), and schizophrenia (64%–79%) was identified, with moderate levels of congruence between most investigated traits (47%–58%). Specific shared loci were identified for all bivariate analyses, and a subset of 70 credible genes were mapped to these shared loci. The current results provide evidence for substantial polygenic overlap between psychiatric disorders and sleep-related phenotypes, beyond genetic correlation (| r g | = 0.02 to 0.42). Moderate congruency within the shared genetic components suggests a complex genetic relationship and potential subgroups with higher or lower genetic concordance. This work provides new insights and understanding of the shared genetic etiology of sleep-related phenotypes and psychiatric disorders and highlights new opportunities and avenues for future investigation. [ABSTRACT FROM AUTHOR]

Risk factors and long-term consequences of COVID-19 infection are unclear but can be investigated with large-scale genomic data. To distinguish correlation from causation, we performed in-silico analyses of three COVID-19 outcomes (N > 1,000,000). We show genetic correlation and putative causality with depressive symptoms, metformin use (genetic causality proportion (gĉp) with severe respiratory COVID-19 = 0.576, p = 1.07 × 10−5 and hospitalized COVID-19 = 0.713, p = 0.003), and alcohol drinking status (gĉp with severe respiratory COVID-19 = 0.633, p = 7.04 × 10−5 and hospitalized COVID-19 = 0.848, p = 4.13 × 10−13). COVID-19 risk loci associated with several hematologic biomarkers. Comprehensive findings inform genetic contributions to COVID-19 epidemiology, molecular mechanisms, and risk factors and potential long-term health effects of severe response to infection.

Background: Alzheimer’s disease (AD) and depression are debilitating brain disorders that are often comorbid. Shared brain mechanisms have been implicated, yet findings are inconsistent, reflecting the complexity of the underlying pathophysiology. As both disorders are (partly) heritable, characterising their genetic overlap may provide aetiological clues. While previous studies have indicated negligible genetic correlations, this study aims to expose the genetic overlap that may remain hidden due to mixed directions of effects.Methods: We applied Gaussian mixture modelling, through MiXeR, and conjunctional false discovery rate (cFDR) analysis, through pleioFDR, to genome-wide association study (GWAS) summary statistics of AD (n = 79,145) and depression (n = 450,619). The effects of identified overlapping loci on AD and depression were tested in 403,029 participants of the UK Biobank (UKB) (mean age 57.21, 52.0% female), and mapped onto brain morphology in 30,699 individuals with brain MRI data.Results: MiXer estimated 98 causal genetic variants overlapping between the 2 disorders, with 0.44 concordant directions of effects. Through pleioFDR, we identified a SNP in the TMEM106B gene, which was significantly associated with AD (B = −0.002, p = 9.1 × 10–4) and depression (B = 0.007, p = 3.2 × 10–9) in the UKB. This SNP was also associated with several regions of the corpus callosum volume anterior (B > 0.024, p < 8.6 × 10–4), third ventricle volume ventricle (B = −0.025, p = 5.0 × 10–6), and inferior temporal gyrus surface area (B = 0.017, p = 5.3 × 10–4).Discussion: Our results indicate there is substantial genetic overlap, with mixed directions of effects, between AD and depression. These findings illustrate the value of biostatistical tools that capture such overlap, providing insight into the genetic architectures of these disorders.

Background: Alzheimer's disease (AD) and depression are debilitating brain disorders that are often comorbid. Shared brain mechanisms have been implicated, yet findings are inconsistent, reflecting the complexity of the underlying pathophysiology. As both disorders are (partly) heritable, characterising their genetic overlap may provide aetiological clues. While previous studies have indicated negligible genetic correlations, this study aims to expose the genetic overlap that may remain hidden due to mixed directions of effects. Methods: We applied Gaussian mixture modelling, through MiXeR, and conjunctional false discovery rate (cFDR) analysis, through pleioFDR, to genome-wide association study (GWAS) summary statistics of AD (n = 79,145) and depression (n = 450,619). The effects of identified overlapping loci on AD and depression were tested in 403,029 participants of the UK Biobank (UKB) (mean age 57.21, 52.0% female), and mapped onto brain morphology in 30,699 individuals with brain MRI data. Results: MiXer estimated 98 causal genetic variants overlapping between the 2 disorders, with 0.44 concordant directions of effects. Through pleioFDR, we identified a SNP in the TMEM106B gene, which was significantly associated with AD (B = −0.002, p = 9.1 × 10–4) and depression (B = 0.007, p = 3.2 × 10–9) in the UKB. This SNP was also associated with several regions of the corpus callosum volume anterior (B > 0.024, p < 8.6 × 10–4), third ventricle volume ventricle (B = −0.025, p = 5.0 × 10–6), and inferior temporal gyrus surface area (B = 0.017, p = 5.3 × 10–4). Discussion: Our results indicate there is substantial genetic overlap, with mixed directions of effects, between AD and depression. These findings illustrate the value of biostatistical tools that capture such overlap, providing insight into the genetic architectures of these disorders. [ABSTRACT FROM AUTHOR]

Personality and subjective well-being (SWB) have been suggested to be strongly related in previous studies. This study was intended to confirm the relationship between personality and SWB and tried to seek out the genetic variants which underlie both personality and SWB. The subjects were 890 participants from Chinese Han population. We evaluated their personality using the Big Five Inventory (BFI) and used the Satisfaction With Life Scale (SWLS) to reflect their SWB. Five single nucleotide polymorphisms (SNPs) were selected from the literature (rs1426371, rs2164273, rs322931, rs3756290, rs490647) and genotyped for genetic association study. We found negative correlations between neuroticism and SWB. On the contrary, extraversion and agreeableness were positively associated with SWB. Three SNPs (rs2164273, rs3756290, rs490647) out of the five were found to connect with personality (extraversion, neuroticism, conscientiousness and openness to experience) and rs490647 variants of GRIK3 was also associated with SWB. Individuals carrying G allele at this site were predisposed to have lower risk to be neuroticism and greater chance to be extraverted, open and satisfied with their life. In summary, our study revealed that rs490647 might be a good candidate genetic variant for personality and SWB in Chinese Han population.

Abstract Background A growing number of studies clearly demonstrate a substantial association between chronic obstructive pulmonary disease (COPD) and cardiovascular diseases (CVD), although little is known about the shared genetics that contribute to this association. Methods We conducted a large-scale cross-trait genome-wide association study to investigate genetic overlap between COPD (Ncase = 12,550, Ncontrol = 46,368) from the International COPD Genetics Consortium and four primary cardiac traits: resting heart rate (RHR) (N = 458,969), high blood pressure (HBP) (Ncase = 144,793, Ncontrol = 313,761), coronary artery disease (CAD)(Ncase = 60,801, Ncontrol = 123,504), and stroke (Ncase = 40,585, Ncontrol = 406,111) from UK Biobank, CARDIoGRAMplusC4D Consortium, and International Stroke Genetics Consortium data. Results RHR and HBP had modest genetic correlation, and CAD had borderline evidence with COPD at a genome-wide level. We found evidence of local genetic correlation with particular regions of the genome. Cross-trait meta-analysis of COPD identified 21 loci jointly associated with RHR, 22 loci with HBP, and 3 loci with CAD. Functional analysis revealed that shared genes were enriched in smoking-related pathways and in cardiovascular, nervous, and immune system tissues. An examination of smoking-related genetic variants identified SNPs located in 15q25.1 region associated with cigarettes per day, with effects on RHR and CAD. A Mendelian randomization analysis showed a significant positive causal effect of COPD on RHR (causal estimate = 0.1374, P = 0.008). Conclusion In a set of large-scale GWAS, we identify evidence of shared genetics between COPD and cardiac traits.

Background: A considerable proportion of patients with bipolar disorder (BD) have psychotic symptoms during the illness. This subset of BD due to its genetic susceptibility and family segregation has considerable overlap with schizophrenia. However, the extent to which BD patients with psychotic symptoms and without psychotic symptoms differ on neurocognitive functions is still not completely clear. Aim: The aim of this study was to examine the neurocognitive functions in BD patients with psychotic symptoms and BD without psychotic symptoms in comparison with healthy volunteers (HVs). Materials and Methods: Thirty patients with Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition BD (16 with psychotic symptoms) and thirty age- and sex-matched HVs were recruited in the study. Clinical severity was assessed using structured rating scales. The presence of psychotic symptoms was assessed using the Lifetime Dimensions of Psychosis Scale (LDPS). All patients underwent tests, namely continuous performance test, Stroop Word-Color interference test, and Wisconsin Card Sorting Test, to measure executive functions. Differences between groups were examined using analysis of covariance with age and sex as covariates. Results: There was a significant difference between groups on the performance of all the three tests, with patients performing poorer than HVs. While the HVs differed from both BD with psychotic symptoms and without psychotic symptoms, there was no difference between BD patients with and without psychotic symptoms. There was no significant correlation between LDPS score and scores on neurocognitive tests. Conclusion: The study findings, at least with respect to cognitive function, suggest that BD with psychotic symptoms may not be a categorically distinct subtype of BD. Cognitive functions need to be assessed in all patients with BD, regardless of psychotic symptoms, and remediation interventions need to be provided.

Background: Recent findings indicated a high comorbidity between attention-deficit/hyperactivity disorder (ADHD) and autism spectrum disorder (ASD), as well as shared genetic influences on them. The latter might contribute at least partly to the former clinical scenario. This study aimed at investigating whether SHANK genes were potential pleiotropic genes to the two said disorders, underlying their genetic overlap.Methods: This study recruited 298 boys with ADHD (including 256 family trios of 1 ADHD boy and his 2 biological parents), 134 boys with ASD, 109 boys with both ADHD and ASD, and 232 typically developing boys as community controls. They were aged between 6 and 11 years old.Results: There was no significant difference in allele frequency of a number of single nucleotide polymorphisms (SNPs) in SHANK2/SHANK3 between the three clinical groups (ADHD, ASD, and ADHD + ASD) and between the two control groups (community controls and pseudo-controls), respectively. The three clinical groups and the two control groups were thus, respectively, combined. A comparison between the two aggregated samples identified significant evidence of disease association for three SHANK2 SNPs with both ADHD and ASD, even after multiple testing correction: rs11236616 (OR = 0.762, permuted p = 0.0376), rs7106631 (OR = 0.720, permuted p = 0.0034), and rs9888288 (OR = 0.770, permuted p = 0.0407). Comparisons among individual groups pointed to a similar trend of findings.Conclusion:SHANK2 could be considered a potential pleiotropic gene underlying the genetic overlap between ADHD and ASD. This might contribute partly to their high comorbidity in the afflicted children.

Background: Recent findings indicated a high comorbidity between attention-deficit/hyperactivity disorder (ADHD) and autism spectrum disorder (ASD), as well as shared genetic influences on them. The latter might contribute at least partly to the former clinical scenario. This study aimed at investigating whether SHANK genes were potential pleiotropic genes to the two said disorders, underlying their genetic overlap. Methods: This study recruited 298 boys with ADHD (including 256 family trios of 1 ADHD boy and his 2 biological parents), 134 boys with ASD, 109 boys with both ADHD and ASD, and 232 typically developing boys as community controls. They were aged between 6 and 11 years old. Results: There was no significant difference in allele frequency of a number of single nucleotide polymorphisms (SNPs) in SHANK2 / SHANK3 between the three clinical groups (ADHD, ASD, and ADHD + ASD) and between the two control groups (community controls and pseudo-controls), respectively. The three clinical groups and the two control groups were thus, respectively, combined. A comparison between the two aggregated samples identified significant evidence of disease association for three SHANK2 SNPs with both ADHD and ASD, even after multiple testing correction: rs11236616 (OR = 0.762, permuted p = 0.0376), rs7106631 (OR = 0.720, permuted p = 0.0034), and rs9888288 (OR = 0.770, permuted p = 0.0407). Comparisons among individual groups pointed to a similar trend of findings. Conclusion: SHANK2 could be considered a potential pleiotropic gene underlying the genetic overlap between ADHD and ASD. This might contribute partly to their high comorbidity in the afflicted children. [ABSTRACT FROM AUTHOR]