Shared genetic loci between depression and cardiometabolic traits.

Epidemiological and clinical studies have found associations between depression and cardiovascular disease risk factors, and coronary artery disease patients with depression have worse prognosis. The genetic relationship between depression and these cardiovascular phenotypes is not known. We here investigated overlap at the genome-wide level and in individual loci between depression, coronary artery disease and cardiovascular risk factors. We used the bivariate causal mixture model (MiXeR) to quantify genome-wide polygenic overlap and the conditional/conjunctional false discovery rate (pleioFDR) method to identify shared loci, based on genome-wide association study summary statistics on depression (n = 450,619), coronary artery disease (n = 502,713) and nine cardiovascular risk factors (n = 204,402-776,078). Genetic loci were functionally annotated using FUnctional Mapping and Annotation (FUMA). Of 13.9K variants influencing depression, 9.5K (SD 1.0K) were shared with body-mass index. Of 4.4K variants influencing systolic blood pressure, 2K were shared with depression. ConjFDR identified 79 unique loci associated with depression and coronary artery disease or cardiovascular risk factors. Six genomic loci were associated jointly with depression and coronary artery disease, 69 with blood pressure, 49 with lipids, 9 with type 2 diabetes and 8 with c-reactive protein at conjFDR < 0.05. Loci associated with increased risk for depression were also associated with increased risk of coronary artery disease and higher total cholesterol, low-density lipoprotein and c-reactive protein levels, while there was a mixed pattern of effect direction for the other risk factors. Functional analyses of the shared loci implicated metabolism of alpha-linolenic acid pathway for type 2 diabetes. Our results showed polygenic overlap between depression, coronary artery disease and several cardiovascular risk factors and suggest molecular mechanisms underlying the association between depression and increased cardiovascular disease risk.

Dissecting unique and common variance across body and brain health indicators using age prediction.

Ageing is a heterogeneous multisystem process involving different rates of decline in physiological integrity across biological systems. The current study dissects the unique and common variance across body and brain health indicators and parses inter-individual heterogeneity in the multisystem ageing process. Using machine-learning regression models on the UK Biobank data set (N = 32,593, age range 44.6-82.3, mean age 64.1 years), we first estimated tissue-specific brain age for white and gray matter based on diffusion and T1-weighted magnetic resonance imaging (MRI) data, respectively. Next, bodily health traits, including cardiometabolic, anthropometric, and body composition measures of adipose and muscle tissue from bioimpedance and body MRI, were combined to predict 'body age'. The results showed that the body age model demonstrated comparable age prediction accuracy to models trained solely on brain MRI data. The correlation between body age and brain age predictions was 0.62 for the T1 and 0.64 for the diffusion-based model, indicating a degree of unique variance in brain and bodily ageing processes. Bayesian multilevel modelling carried out to quantify the associations between health traits and predicted age discrepancies showed that higher systolic blood pressure and higher muscle-fat infiltration were related to older-appearing body age compared to brain age. Conversely, higher hand-grip strength and muscle volume were related to a younger-appearing body age. Our findings corroborate the common notion of a close connection between somatic and brain health. However, they also suggest that health traits may differentially influence age predictions beyond what is captured by the brain imaging data, potentially contributing to heterogeneous ageing rates across biological systems and individuals.

Identification of novel genomic risk loci shared between common epilepsies and psychiatric disorders.

Psychiatric disorders and common epilepsies are heritable disorders with a high comorbidity and overlapping symptoms. However, the causative mechanisms underlying this relationship are poorly understood. Here we aimed to identify overlapping genetic loci between epilepsy and psychiatric disorders to gain a better understanding of their comorbidity and shared clinical features. We analysed genome-wide association study data for all epilepsies (n = 44 889), genetic generalized epilepsy (n = 33 446), focal epilepsy (n = 39 348), schizophrenia (n = 77 096), bipolar disorder (n = 406 405), depression (n = 500 199), attention deficit hyperactivity disorder (n = 53 293) and autism spectrum disorder (n = 46 350). First, we applied the MiXeR tool to estimate the total number of causal variants influencing the disorders. Next, we used the conjunctional false discovery rate statistical framework to improve power to discover shared genomic loci. Additionally, we assessed the validity of the findings in independent cohorts, and functionally characterized the identified loci. The epilepsy phenotypes were considerably less polygenic (1.0 K to 3.4 K causal variants) than the psychiatric disorders (5.6 K to 13.9 K causal variants), with focal epilepsy being the least polygenic (1.0 K variants), and depression having the highest polygenicity (13.9 K variants). We observed cross-trait genetic enrichment between genetic generalized epilepsy and all psychiatric disorders and between all epilepsies and schizophrenia and depression. Using conjunctional false discovery rate analysis, we identified 40 distinct loci jointly associated with epilepsies and psychiatric disorders at conjunctional false discovery rate <0.05, four of which were associated with all epilepsies and 39 with genetic generalized epilepsy. Most epilepsy risk loci were shared with schizophrenia (n = 31). Among the identified loci, 32 were novel for genetic generalized epilepsy, and two were novel for all epilepsies. There was a mixture of concordant and discordant allelic effects in the shared loci. The sign concordance of the identified variants was highly consistent between the discovery and independent datasets for all disorders, supporting the validity of the findings. Gene-set analysis for the shared loci between schizophrenia and genetic generalized epilepsy implicated biological processes related to cell cycle regulation, protein phosphatase activity, and membrane and vesicle function; the gene-set analyses for the other loci were underpowered. The extensive genetic overlap with mixed effect directions between psychiatric disorders and common epilepsies demonstrates a complex genetic relationship between these disorders, in line with their bi-directional relationship, and indicates that overlapping genetic risk may contribute to shared pathophysiological and clinical features between epilepsy and psychiatric disorders.

The shared genetic basis of mood instability and psychiatric disorders: A cross-trait genome-wide association analysis.

Recent genome-wide association studies of mood instability (MOOD) have found significant positive genetic correlation with major depression (DEP) and weak correlations with other psychiatric disorders. We investigated the polygenic overlap between MOOD and psychiatric disorders beyond genetic correlation to better characterize putative shared genetic determinants. GWAS summary statistics for schizophrenia (SCZ, n = 105,318), bipolar disorder (BIP, n = 413,466), DEP (n = 450,619), attention-deficit hyperactivity disorder (ADHD, n = 53,293), and MOOD (n = 363,705) were analyzed using the bivariate causal mixture model and conjunctional false discovery rate methods. MOOD correlated positively with all psychiatric disorders, but with wide variation in strength (rg = 0.10-0.62). Of 10.4 K genomic variants influencing MOOD, 4 K-9.4 K influenced psychiatric disorders. Furthermore, MOOD was jointly associated with DEP at 163 loci, SCZ at 110, BIP at 60 and ADHD at 25. Fifty-three jointly associated loci were overlapping across two or more disorders, seven of which had discordant effect directions on psychiatric disorders. Genes mapped to loci associated with MOOD and all four disorders were enriched in a single gene-set, "synapse organization." The extensive polygenic overlap indicates shared molecular underpinnings across MOOD and psychiatric disorders. However, distinct patterns of genetic correlation and effect directions may relate to differences in the core clinical features of each disorder.

Effects of a Water, Sanitation, and Hygiene Mobile Health Program on Diarrhea and Child Growth in Bangladesh: A Cluster-randomized Controlled Trial of the Cholera Hospital-based Intervention for 7 Days (CHoBI7) Mobile Health Program.

BACKGROUND: The Cholera Hospital-Based Intervention for 7 Days (CHoBI7) mobile health (mHealth) program was a cluster-randomized controlled trial of diarrhea patient households conducted in Dhaka, Bangladesh. METHODS: Patients were block-randomized to 3 arms: standard message on oral rehydration solution use; health facility delivery of CHoBI7 plus mHealth (no home visits); and health facility delivery of CHoBI7 plus 2 home visits and mHealth. The primary outcome was reported diarrhea in the past 2 weeks collected monthly for 12 months. The secondary outcomes were stunting, underweight, and wasting at a 12-month follow-up. Analysis was intention-to-treat. RESULTS: Between 4 December 2016 and 26 April 2018, 2626 participants in 769 households were randomly allocated to 3 arms: 849 participants to the standard message arm, 886 to mHealth with no home visits arm, and 891 to the mHealth with 2 home visits. Children <5 years had significantly lower 12-month diarrhea prevalence in both the mHealth with 2 home visits arm (prevalence ratio [PR]: 0.73 [95% confidence interval {CI}, .61-.87]) and the mHealth with no home visits arm (PR: 0.82 [95% CI, .69-.97]). Children <2 years were significantly less likely to be stunted in both the mHealth with 2 home visits arm (33% vs 45%; odds ratio [OR]: 0.55 [95% CI, .31-.97]) and the mHealth with no home visits arm (32% vs 45%; OR: 0.54 [95% CI, .31-.96]) compared with children in the standard message arm. CONCLUSIONS: The CHoBI7 mHealth program lowered pediatric diarrhea and stunting among diarrhea patient households. CLINICAL TRIALS REGISTRATION: NCT04008134.

Child mouthing of soil and presence of animals in child sleeping spaces are associated with growth faltering among young children in Dhaka, Bangladesh (CHoBI7 Program).

OBJECTIVE: The objective of the study was to investigate potential risk factors for growth faltering among children under 5 years of age. METHOD: We conducted a prospective cohort study of 553 children under 5 years from diarrhoea patient households in urban Dhaka, Bangladesh. Height and weight measurements were obtained at baseline and at a 12-month follow-up. Caregivers of young children were administered a monthly questionnaire on household sociodemographic characteristics and hygiene practices. RESULTS: Children with caregiver reports of mouthing soil at the majority of household visits had a significant reduction in their height-for-age z-scores (HAZ) from baseline to the 12-month follow-up (ΔHAZ: -0.28 (95% confidence interval (CI): -0.51, -0.05)). A significant reduction in HAZ was also observed for children in households with animals in their sleeping space (ΔHAZ: -0.37 (95% CI: -0.71, -0.04)). CONCLUSION: These findings provide further evidence to support the hypothesis that child mouthing of soil and the presence of animals in the child's sleeping space are potential risk factors for growth faltering among young children. Interventions are urgently needed to provide clean play and sleeping spaces for young children to reduce exposure to faecal pathogens through child mouthing.

OBJECTIF: L'objectif de l'étude était d'examiner les facteurs de risque potentiels de retard de croissance chez les enfants de moins de 5 ans. MÉTHODE: Nous avons mené une étude de cohorte prospective sur 553 enfants de moins de 5 ans provenant de ménages avec des patients diarrhéiques dans la ville de Dhaka, au Bangladesh. Les mesures de taille et de poids ont été obtenues au départ et à 12 mois de suivi. Les personnes s'occupant de jeunes enfants (les gardiens) ont reçu un questionnaire mensuel sur les caractéristiques sociodémographiques des ménages et les pratiques d'hygiène. RÉSULTATS: Les enfants pour lesquels les gardiens ont déclaré qu'ils mâchouillaient de la terre lors de la majorité des visites à domicile présentaient une diminution du score Z de taille pour l'âge (TAZ) de manière significative de l'âge de référence au 12 mois de suivi (ΔTAZ −0,28 (intervalle de confiance (IC) à 95%: −0,51, −0,05)). Une réduction significative des TAZ a également été observée pour les enfants des ménages ayant des animaux dans leur espace de couchage (ΔTAZ −0,37 (IC95%: −0,71, −0,04)). CONCLUSION: Ces résultats apportent des données supplémentaires pour appuyer l'hypothèse selon laquelle le fait que l'enfant mâchouille de la terre et la présence d'animaux dans son espace de couchage sont des facteurs de risque potentiels de retard de croissance chez les jeunes enfants. Des interventions sont urgemment nécessaires pour fournir des espaces de jeu et de sommeil sains aux jeunes enfants afin de réduire l'exposition aux agents pathogènes fécaux par le mâchouillement des enfants.

Genetic relatedness of Vibrio cholerae isolates within and between households during outbreaks in Dhaka, Bangladesh.

BACKGROUND: Household contacts of cholera patients have a 100 times higher risk of developing a cholera infection than the general population. To compare the genetic relatedness of clinical and water source Vibrio cholerae isolates from cholera patients' households across three outbreaks, we analyzed these isolates using whole-genome-sequencing (WGS) and multilocus variable-number tandem-repeat analysis (MLVA). RESULTS: The WGS analyses revealed that 80% of households had source water isolates that were more closely related to clinical isolates from the same household than to any other isolates. While in another 20% of households an isolate from a person was more closely related to clinical isolates from another household than to source water isolates from their own household. The mean pairwise differences in single nucleotide-variant (SNV) counts for isolates from the same household were significantly lower than those for different households (2.4 vs. 7.7 p < 0.0001), and isolates from the same outbreak had significantly fewer mean pairwise differences compared to isolates from different outbreaks (mean: 6.2 vs. 8.0, p < 0.0001). Based on MLVA in outbreak 1, we observed that the majority of households had clinical isolates with MLVA genotypes related to other clinical isolates and unrelated to water source isolates from the same household. While in outbreak 3, there were different MLVA genotypes between households, however within the majority of households, the clinical and water source isolates had the same MLVA genotypes. The beginning of outbreak 2 resembled outbreak 1 and the latter part resembled outbreak 3. We validated our use of MLVA by comparing it to WGS. Isolates with the identical MLVA genotype had significantly fewer mean pairwise SNV differences than those isolates with different MLVA genotypes (mean: 4.8 vs. 7.7, p < 0.0001). Furthermore, consistent with WGS results, the number of pairwise differences in the five MLVA loci for isolates within the same household was significantly lower than isolates from different households (mean: 1.6 vs. 3.0, p < 0.0001). CONCLUSION: These results suggest that transmission patterns for cholera are a combination of person-to-person and water-to-person cholera transmission with the proportions of the two modes varying within and between outbreaks.

Rapid dipstick detection of Vibrio cholerae in household stored and municipal water in Dhaka, Bangladesh: CHoBI7 trial.

OBJECTIVE: In urban Dhaka, Bangladesh, 30% of source water samples collected from the households of patients with cholera had detectable Vibrio cholerae. These findings indicate an urgent need for a public health intervention for this population. The Crystal VC® dipstick test is a rapid method for detecting V. cholerae in stool and water. However, to date no study has investigated the use of the rapid dipstick test for household surveillance of stored drinking water. METHODS: The efficacy of the Crystal VC® dipstick test for detecting V. cholerae in the Dhaka city municipal water supply and stored household drinking water sources after enrichment for 18 h in alkaline peptone water (APW) was compared to bacterial culture as the gold standard. RESULTS: A total of 1648 water samples (824 stored household drinking water samples and 824 municipal water supply samples) were collected from households of patients with cholera. The overall specificity and sensitivity of the dipstick test compared to bacterial culture was 99.6% (95% confidence interval (CI): 99.2%, 99.9%) and 65.6% (95% CI: 55.2%, 75%), respectively. The specificities for stored household drinking water and Dhaka city municipal supply water compared to bacterial culture were 99.8% (95% CI: 99.1%, 100%) and 99.5% (95% CI: 98.6%, 99.9%), respectively (P = 0.138), and the sensitivities were 66.7% (95% CI: 43.0%, 85.4%) and 65.3% (95% CI: 53.5%, 76.0%), respectively (P = 0.891). CONCLUSION: The Crystal VC® dipstick is a promising screening tool for cholera outbreak surveillance in resource-limited settings where elimination of false-positive results is critical. The lower than expected sensitivity should be further investigated in future studies.

Randomized Controlled Trial of Hospital-Based Hygiene and Water Treatment Intervention (CHoBI7) to Reduce Cholera.

The risk for cholera infection is >100 times higher for household contacts of cholera patients during the week after the index patient seeks hospital care than it is for the general population. To initiate a standard of care for this high-risk population, we developed Cholera-Hospital-Based-Intervention-for-7-Days (CHoBI7), which promotes hand washing with soap and treatment of water. To test CHoBI7, we conducted a randomized controlled trial among 219 intervention household contacts of 82 cholera patients and 220 control contacts of 83 cholera patients in Dhaka, Bangladesh, during 2013-2014. Intervention contacts had significantly fewer symptomatic Vibrio cholerae infections than did control contacts and 47% fewer overall V. cholerae infections. Intervention households had no stored drinking water with V. cholerae and 14 times higher odds of hand washing with soap at key events during structured observation on surveillance days 5, 6, or 7. CHoBI7 presents a promising approach for controlling cholera among highly susceptible household contacts of cholera patients.

Genomic characterization of extended-spectrum beta-lactamase-producing and carbapenem-resistant Escherichia coli from urban wastewater in Australia.

This study investigates extended-spectrum beta-lactamase-producing and carbapenem-resistant Escherichia coli isolates from Sydney's wastewater. These isolates exhibit resistance to critical antibiotics and harbor novel resistance mechanisms. The findings highlight the importance of wastewater-based surveillance in monitoring resistance beyond the clinical setting.

Identification of Novel Genomic Loci for Anxiety and Extensive Genetic Overlap with Psychiatric Disorders.

Background: Anxiety disorders are prevalent and anxiety symptoms co-occur with many psychiatric disorders. We aimed to identify genomic risk loci associated with anxiety, characterize its genetic architecture, and genetic overlap with psychiatric disorders. Methods: We used the GWAS of anxiety symptoms, schizophrenia, bipolar disorder, major depression, and attention deficit hyperactivity disorder (ADHD). We employed MiXeR and LAVA to characterize the genetic architecture and genetic overlap between the phenotypes. Conditional and conjunctional false discovery rate analyses were performed to boost the identification of genomic loci associated with anxiety and those shared with psychiatric disorders. Gene annotation and gene set analyses were conducted using OpenTargets and FUMA, respectively. Results: Anxiety was polygenic with 12.9k estimated genetic risk variants and overlapped extensively with psychiatric disorders (4.1-11.4k variants). MiXeR and LAVA revealed predominantly positive genetic correlations between anxiety and psychiatric disorders. We identified 114 novel loci for anxiety by conditioning on the psychiatric disorders. We also identified loci shared between anxiety and major depression (n = 47), bipolar disorder (n = 33), schizophrenia (n = 71), and ADHD (n = 20). Genes annotated to anxiety loci exhibit enrichment for a broader range of biological pathways and differential tissue expression in more diverse tissues than those annotated to the shared loci. Conclusions: Anxiety is a highly polygenic phenotype with extensive genetic overlap with psychiatric disorders. These genetic overlaps enabled the identification of novel loci for anxiety. The shared genetic architecture may underlie the extensive cross-disorder comorbidity of anxiety, and the identified genetic loci implicate molecular pathways that may lead to potential drug targets.

Dissecting the genetic overlap between three complex phenotypes with trivariate MiXeR.

Comorbidities are an increasing global health challenge. Accumulating evidence suggests overlapping genetic architectures underlying comorbid complex human traits and disorders. The bivariate causal mixture model (MiXeR) can quantify the polygenic overlap between complex phenotypes beyond global genetic correlation. Still, the pattern of genetic overlap between three distinct phenotypes, which is important to better characterize multimorbidities, has previously not been possible to quantify. Here, we present and validate the trivariate MiXeR tool, which disentangles the pattern of genetic overlap between three phenotypes using summary statistics from genome-wide association studies (GWAS). Our simulations show that the trivariate MiXeR can reliably reconstruct different patterns of genetic overlap. We further demonstrate how the tool can be used to estimate the proportions of genetic overlap between three phenotypes using real GWAS data, providing examples of complex patterns of genetic overlap between diverse human traits and diseases that could not be deduced from bivariate analyses. This contributes to a better understanding of the etiology of complex phenotypes and the nature of their relationship, which may aid in dissecting comorbidity patterns and their biological underpinnings.

Dissecting the Shared Genetic Architecture of Common Epilepsies With Cortical Brain Morphology.

Background and Objectives: Epilepsies are associated with differences in cortical thickness (TH) and surface area (SA). However, the mechanisms underlying these relationships remain elusive. We investigated the extent to which these phenotypes share genetic influences. Methods: We analyzed genome-wide association study data on common epilepsies (n = 69,995) and TH and SA (n = 32,877) using Gaussian mixture modeling MiXeR and conjunctional false discovery rate (conjFDR) analysis to quantify their shared genetic architecture and identify overlapping loci. We biologically interrogated the loci using a variety of resources and validated in independent samples. Results: The epilepsies (2.4 k-2.9 k variants) were more polygenic than both SA (1.8 k variants) and TH (1.3 k variants). Despite absent genome-wide genetic correlations, there was a substantial genetic overlap between SA and genetic generalized epilepsy (GGE) (1.1 k), all epilepsies (1.1 k), and juvenile myoclonic epilepsy (JME) (0.7 k), as well as between TH and GGE (0.8 k), all epilepsies (0.7 k), and JME (0.8 k), estimated with MiXeR. Furthermore, conjFDR analysis identified 15 GGE loci jointly associated with SA and 15 with TH, 3 loci shared between SA and childhood absence epilepsy, and 6 loci overlapping between SA and JME. 23 loci were novel for epilepsies and 11 for cortical morphology. We observed a high degree of sign concordance in the independent samples. Discussion: Our findings show extensive genetic overlap between generalized epilepsies and cortical morphology, indicating a complex genetic relationship with mixed-effect directions. The results suggest that shared genetic influences may contribute to cortical abnormalities in epilepsies.

Unraveling the shared genetics of common epilepsies and general cognitive ability.

Objective: Cognitive impairment is prevalent among individuals with epilepsy, and it is possible that genetic factors can underlie this relationship. Here, we investigated the potential shared genetic basis of common epilepsies and general cognitive ability (COG). Methods: We applied linkage disequilibrium score (LDSC) regression, MiXeR and conjunctional false discovery rate (conjFDR) to analyze different aspects of genetic overlap between COG and epilepsies. We used the largest available genome-wide association study data on COG (n = 269,867) and common epilepsies (n = 27,559 cases, 42,436 controls), including the broad phenotypes 'all epilepsy', focal epilepsies and genetic generalized epilepsies (GGE), and as well as specific subtypes. We functionally annotated the identified loci using a variety of biological resources and validated the results in independent samples. Results: Using MiXeR, COG (11.2k variants) was estimated to be almost four times more polygenic than 'all epilepsy', GGE, juvenile myoclonic epilepsy (JME), and childhood absence epilepsy (CAE) (2.5k - 2.9k variants). The other epilepsy phenotypes were insufficiently powered for analysis. We show extensive genetic overlap between COG and epilepsies with significant negative genetic correlations (-0.23 to -0.04). COG was estimated to share 2.9k variants with both GGE and 'all epilepsy', and 2.3k variants with both JME and CAE. Using conjFDR, we identified 66 distinct loci shared between COG and epilepsies, including novel associations for GGE (27), 'all epilepsy' (5), JME (5) and CAE (5). The implicated genes were significantly expressed in multiple brain regions. The results were validated in independent samples (COG: p = 1.0 × 10-14; 'all epilepsy': p = 5.6 × 10-3). Significance: Our study demonstrates a substantial genetic basis shared between epilepsies and COG and identifies novel overlapping genomic loci. Enhancing our understanding of the relationship between epilepsies and COG may lead to the development of novel comorbidity-targeted epilepsy treatments.

Wastewater-based monitoring reveals geospatial-temporal trends for antibiotic-resistant pathogens in a large urban community.

Antimicrobial resistance (AMR) is one of the top ten global health threats, and current surveillance programs rarely monitor it outside healthcare settings. This limits our ability to understand and manage the spread of AMR. Wastewater testing has the potential to simply, reliably and continuously survey trends in AMR outside the healthcare settings, as it captures biological material from the entire community. To establish and evaluate such a surveillance, we monitored wastewater for four clinically significant pathogens across the urban area of Greater Sydney, Australia. Untreated wastewater from 25 wastewater treatment plants (WWTPs) covering distinct catchment regions of 5.2 million residents was sampled between 2017 and 2019. Isolates for extended-spectrum ß-lactamases-producing Enterobacteriaceae (ESBL-E) were consistently detected, suggesting its endemicity in the community. Isolates for carbapenem-resistant Enterobacteriaceae (CRE), vancomycin-resistant enterococci (VRE), and methicillin-resistant Staphylococcus aureus (MRSA) were only occasionally detected. The flow normalized relative (FNR) ESBL-E load was positively correlated with the proportion of the population between 19 and 50 years of age, completion of vocational education and the average length of hospital stay. Collectively, these variables explained only a third of the variance of the FNR ESBL-E load, indicating further, yet-unidentified factors as a contributor to the distribution. About half of the variation in the FNR CRE load was explained by the average length of hospital stay, showing healthcare-related drivers. Interestingly, variation in the FNR VRE load was not correlated to healthcare-related parameters but to the number of schools per 10,000 population. Our study provides insight into how routine wastewater surveillance can be used to understand the factors driving the distribution of AMR in an urban community. Such information can help to manage and mitigate the emergence and spread of AMR in important human pathogens.

Shared genetic architecture between irritable bowel syndrome and psychiatric disorders reveals molecular pathways of the gut-brain axis.

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.

Genome-wide analysis of anorexia nervosa and major psychiatric disorders and related traits reveals genetic overlap and identifies novel risk loci for anorexia nervosa.

Anorexia nervosa (AN) is a heritable eating disorder (50-60%) with an array of commonly comorbid psychiatric disorders and related traits. Although significant genetic correlations between AN and psychiatric disorders and related traits have been reported, their shared genetic architecture is largely understudied. We investigated the shared genetic architecture of AN and schizophrenia (SCZ), bipolar disorder (BIP), major depression (MD), mood instability (Mood), neuroticism (NEUR), and intelligence (INT). We applied the conditional false discovery rate (FDR) method to identify novel risk loci for AN, and conjunctional FDR to identify loci shared between AN and related phenotypes, to summarize statistics from relevant genome-wide association studies (GWAS). Individual GWAS samples varied from 72,517 to 420,879 participants. Using conditional FDR we identified 58 novel AN loci. Furthermore, we identified 38 unique loci shared between AN and major psychiatric disorders (SCZ, BIP, and MD) and 45 between AN and psychological traits (Mood, NEUR, and INT). In line with genetic correlations, the majority of shared loci showed concordant effect directions. Functional analyses revealed that the shared loci are involved in 65 unique pathways, several of which overlapped across analyses, including the "signal by MST1" pathway involved in Hippo signaling. In conclusion, we demonstrated genetic overlap between AN and major psychiatric disorders and related traits, and identified novel risk loci for AN by leveraging this overlap. Our results indicate that some shared characteristics between AN and related disorders and traits may have genetic underpinnings.

Genome-wide Association Analysis of Schizophrenia and Vitamin D Levels Shows Shared Genetic Architecture and Identifies Novel Risk Loci.

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.

Characterizing the Shared Genetic Underpinnings of Schizophrenia and Cardiovascular Disease Risk Factors.

OBJECTIVE: 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. METHODS: 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. RESULTS: 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. CONCLUSIONS: 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.

The relationship between cannabis use, schizophrenia, and bipolar disorder: a genetically informed study.

BACKGROUND: The relationship between psychotic disorders and cannabis use is heavily debated. Shared underlying genetic risk is one potential explanation. We investigated the genetic association between psychotic disorders (schizophrenia and bipolar disorder) and cannabis phenotypes (lifetime cannabis use and cannabis use disorder). METHODS: We used genome-wide association summary statistics from individuals with European ancestry from the Psychiatric Genomics Consortium, UK Biobank, and International Cannabis Consortium. We estimated heritability, polygenicity, and discoverability of each phenotype. We performed genome-wide and local genetic correlations. Shared loci were identified and mapped to genes, which were tested for functional enrichment. Shared genetic liabilities to psychotic disorders and cannabis phenotypes were explored using causal analyses and polygenic scores, using the Norwegian Thematically Organized Psychosis cohort. FINDINGS: Psychotic disorders were more heritable than cannabis phenotypes and more polygenic than cannabis use disorder. We observed positive genome-wide genetic correlations between psychotic disorders and cannabis phenotypes (range 0·22-0·35) with a mixture of positive and negative local genetic correlations. Three to 27 shared loci were identified for the psychotic disorder and cannabis phenotype pairs. Enrichment of mapped genes implicated neuronal and olfactory cells as well as drug-gene targets for nicotine, alcohol, and duloxetine. Psychotic disorders showed a causal effect on cannabis phenotypes, and lifetime cannabis use had a causal effect on bipolar disorder. Of 2181 European participants from the Norwegian Thematically Organized Psychosis cohort applied in polygenic risk score analyses, 1060 (48·6%) were females and 1121 (51·4%) were males (mean age 33·1 years [SD 11·8]). 400 participants had bipolar disorder, 697 had schizophrenia, and 1044 were healthy controls. Within this sample, polygenic scores for cannabis phenotypes predicted psychotic disorders independently and improved prediction beyond the polygenic score for the psychotic disorders. INTERPRETATION: A subgroup of individuals might have a high genetic risk of developing a psychotic disorder and using cannabis. This finding supports public health efforts to reduce cannabis use, particularly in individuals at high risk or patients with psychotic disorders. Identified shared loci and their functional implications could facilitate development of novel treatments. FUNDING: US National Institutes of Health, the Research Council Norway, the South-East Regional Health Authority, Stiftelsen Kristian Gerhard Jebsen, EEA-RO-NO-2018-0535, European Union's Horizon 2020 Research and Innovation Programme, the Marie Sklodowska-Curie Actions, and University of Oslo Life Science.