An Atlas of Genetic Correlations and Genetically Informed Associations Linking Psychiatric and Immune-Related Phenotypes

Shared molecular mechanisms and transdiagnostic potential of neurodevelopmental disorders and immune disorders

The co-occurrence and familial clustering of neurodevelopmental disorders and immune disorders suggest shared genetic risk factors. Based on genome-wide association summary statistics from five neurodevelopmental disorders and four immune disorders, we conducted genome-wide, local genetic correlation and polygenic overlap analysis. We further performed a cross-trait GWAS meta-analysis. Pleotropic loci shared between the two categories of diseases were mapped to candidate genes using multiple algorithms and approaches. Significant genetic correlations were observed between neurodevelopmental disorders and immune disorders, including both positive and negative correlations. Neurodevelopmental disorders exhibited higher polygenicity compared to immune disorders. Around 50%-90% of genetic variants of the immune disorders were shared with neurodevelopmental disorders. The cross-trait meta-analysis revealed 154 genome-wide significant loci, including 8 novel pleiotropic loci. Significant associations were observed for 30 loci with both types of diseases. Pathway analysis on the candidate genes at these loci revealed common pathways shared by the two types of diseases, including neural signaling, inflammatory. Response, and PI3K-Akt signaling pathway. In addition, 26 of the 30 lead SNPs were associated with blood cell traits. Neurodevelopmental disorders exhibit complex polygenic architecture, with a subset of individuals being at a heightened genetic risk for both neurodevelopmental and immune disorders. The identification of pleiotropic loci has important implications for exploring opportunities for drug repurposing, enabling more accurate patient stratification, and advancing genomics-informed precision in the medical field of neurodevelopmental disorders.

Shared genetic basis and causality between schizophrenia and inflammatory bowel disease: evidence from a comprehensive genetic analysis

BACKGROUND

The comorbidity between schizophrenia (SCZ) and inflammatory bowel disease (IBD) observed in epidemiological studies is partially attributed to genetic overlap, but the magnitude of shared genetic components and the causality relationship between them remains unclear.

METHODS

By leveraging large-scale genome-wide association study (GWAS) summary statistics for SCZ, IBD, ulcerative colitis (UC), and Crohn's disease (CD), we conducted a comprehensive genetic pleiotropic analysis to uncover shared loci, genes, or biological processes between SCZ and each of IBD, UC, and CD, independently. Univariable and multivariable Mendelian randomization (MR) analyses were applied to assess the causality across these two disorders.

RESULTS

SCZ genetically correlated with IBD (rg = 0.14, p = 3.65 × 10−9), UC (rg = 0.15, p = 4.88 × 10−8), and CD (rg = 0.12, p = 2.27 × 10−6), all surpassed the Bonferroni correction. Cross-trait meta-analysis identified 64, 52, and 66 significantly independent loci associated with SCZ and IBD, UC, and CD, respectively. Follow-up gene-based analysis found 11 novel pleiotropic genes (KAT5, RABEP1, ELP5, CSNK1G1, etc) in all joint phenotypes. Co-expression and pathway enrichment analysis illustrated those novel genes were mainly involved in core immune-related signal transduction and cerebral disorder-related pathways. In univariable MR, genetic predisposition to SCZ was associated with an increased risk of IBD (OR 1.11, 95% CI 1.07–1.15, p = 1.85 × 10−6). Multivariable MR indicated a causal effect of genetic liability to SCZ on IBD risk independent of Actinobacteria (OR 1.11, 95% CI 1.06–1.16, p = 1.34 × 10−6) or BMI (OR 1.11, 95% CI 1.04–1.18, p = 1.84 × 10−3).

CONCLUSIONS

We confirmed a shared genetic basis, pleiotropic loci/genes, and causal relationship between SCZ and IBD, providing novel insights into the biological mechanism and therapeutic targets underlying these two disorders.

Effects of genetically predicted posttraumatic stress disorder on autoimmune phenotypes

Observational studies suggest that posttraumatic stress disorder (PTSD) increases risk for various autoimmune diseases. Insights into shared biology and causal relationships between these diseases may inform intervention approaches to PTSD and co-morbid autoimmune conditions. We investigated the shared genetic contributions and causal relationships between PTSD, 18 autoimmune diseases, and 3 immune/inflammatory biomarkers. Univariate MiXeR was used to contrast the genetic architectures of phenotypes. Genetic correlations were estimated using linkage disequilibrium score regression. Bi-directional, two-sample Mendelian randomization (MR) was performed using independent, genome-wide significant single nucleotide polymorphisms; inverse variance weighted and weighted median MR estimates were evaluated. Sensitivity analyses for uncorrelated (MR PRESSO) and correlated horizontal pleiotropy (CAUSE) were also performed. PTSD was considerably more polygenic (10,863 influential variants) than autoimmune diseases (median 255 influential variants). However, PTSD evidenced significant genetic correlation with nine autoimmune diseases and three inflammatory biomarkers. PTSD had putative causal effects on autoimmune thyroid disease (p = 0.00009) and C-reactive protein (CRP) (p = 4.3 × 10-7). Inferences were not substantially altered by sensitivity analyses. Additionally, the PTSD-autoimmune thyroid disease association remained significant in multivariable MR analysis adjusted for genetically predicted inflammatory biomarkers as potential mechanistic pathway variables. No autoimmune disease had a significant causal effect on PTSD (all p values > 0.05). Although causal effect models were supported for associations of PTSD with CRP, shared pleiotropy was adequate to explain a putative causal effect of CRP on PTSD (p = 0.18). In summary, our results suggest a significant genetic overlap between PTSD, autoimmune diseases, and biomarkers of inflammation. PTSD has a putative causal effect on autoimmune thyroid disease, consistent with existing epidemiologic evidence. A previously reported causal effect of CRP on PTSD is potentially confounded by shared genetics. Together, results highlight the nuanced links between PTSD, autoimmune disorders, and associated inflammatory signatures, and suggest the importance of targeting related pathways to protect against disease and disability.

Genetic evidence for T-wave area from 12-lead electrocardiograms to monitor cardiovascular diseases in patients taking diabetes medications

Aims Many studies indicated use of diabetes medications can influence the electrocardiogram (ECG), which remains the simplest and fastest tool for assessing cardiac functions. However, few studies have explored the role of genetic factors in determining the relationship between the use of diabetes medications and ECG trace characteristics (ETC). Methods Genome-wide association studies (GWAS) were performed for 168 ETCs extracted from the 12-lead ECGs of 42,340 Europeans in the UK Biobank. The genetic correlations, causal relationships, and phenotypic relationships of these ETCs with medication usage, as well as the risk of cardiovascular diseases (CVDs), were estimated by linkage disequilibrium score regression (LDSC), Mendelian randomization (MR), and regression model, respectively. Results The GWAS identified 124 independent single nucleotide polymorphisms (SNPs) that were study-wise and genome-wide significantly associated with at least one ETC. Regression model and LDSC identified significant phenotypic and genetic correlations of T-wave area in lead aVR (aVR_T-area) with usage of diabetes medications (ATC code: A10 drugs, and metformin), and the risks of ischemic heart disease (IHD) and coronary atherosclerosis (CA). MR analyses support a putative causal effect of the use of diabetes medications on decreasing aVR_T-area, and on increasing risk of IHD and CA. ConclusionPatients taking diabetes medications are prone to have decreased aVR_T-area and an increased risk of IHD and CA. The aVR_T-area is therefore a potential ECG marker for pre-clinical prediction of IHD and CA in patients taking diabetes medications.

Estimating the direct effects of the genetic liabilities to bipolar disorder, schizophrenia, and behavioral traits on suicide attempt using a multivariable Mendelian randomization approach

Bipolar disorder (BD) and schizophrenia (SZ) are associated with higher odds of suicide attempt (SA). In this study, we aimed to explore the effect of BD and SZ genetic liabilities on SA, also considering the contribution of behavioral traits, socioeconomic factors, and substance use disorders. Leveraging large-scale genome-wide association data from the Psychiatric Genomics Consortium (PGC) and the UK Biobank (UKB), we conducted a two-sample Mendelian randomization (MR) analysis to evaluate the putative causal effect of BD (41,917 cases, 371,549 controls) and SZ (53,386 cases, 77,258 controls) on SA (26,590 cases, 492,022 controls). Then, we assessed the putative causal effect of BD and SZ on behavioral traits, socioeconomic factors, and substance use disorders. Considering the associations identified, we evaluated the direct causal effect of behavioral traits, socioeconomic factors, and substance use disorders on SA using a multivariable MR approach. The genetic liabilities to BD and SZ were associated with higher odds of SA (BD odds ratio (OR) = 1.24, p = 3.88 × 10-12; SZ OR = 1.09, p = 2.44 × 10-20). However, while the effect of mental distress (OR = 1.17, p = 1.02 × 10-4) and risk-taking (OR = 1.52, p = 0.028) on SA was independent of SZ genetic liability, the BD-SA relationship appeared to account for the effect of these risk factors. Similarly, the association with loneliness on SA was null after accounting for the effect of SZ genetic liability. These findings highlight the complex interplay between genetic risk of psychiatric disorders and behavioral traits in the context of SA, suggesting the need for a comprehensive mental health assessment for high-risk individuals.

The Association between Glucose 6-Phosphate Dehydrogenase Deficiency and Attention Deficit/Hyperactivity Disorder

BACKGROUND

Glucose-6-phosphate dehydrogenase (G6PD) deficiency, impacting 4.9% of the population and more prevalent in Mediterranean communities, is a common enzymopathy with potential relevance to Attention Deficit/Hyperactivity Disorder (ADHD). This study investigated this association.

METHODS

The clinical characteristics of 7473 G6PD-deficient patients and 29,892 matched case-controls (selected at a 1:4 ratio) from a cohort of 1,031,354 within the Leumit Health Services database were analyzed using Fisher's exact test for categorical variables and the Mann-Whitney U test for continuous variables.

RESULTS

In total, 68.7% were male. The mean duration of follow-up was 14.3 ± 6.2 years at a mean age of 29.2 ± 22.3 years. G6PD deficiency was associated with an increased risk of being diagnosed with ADHD (Odds Ratio (OR) = 1.16 [95% CI, 1.08-1.25], p < 0.001), seeking care from adult neurologists (OR = 1.30 [95% CI, 1.22-1.38], p < 0.001), and consulting adult psychiatrists (OR = 1.12 [95% CI, 1.01-1.24], p = 0.048). The use of stimulant medications among G6PD-deficient individuals was 17% higher for the methylphenidate class of drugs (OR = 1.17 [95% CI, 1.08, 1.27], p < 0.001), and there was a 16% elevated risk for amphetamine use (OR = 1.16 [95% CI, 1.03, 1.37], p = 0.047).

CONCLUSIONS

G6PD deficiency signals an increased risk of ADHD diagnosis, more severe presentations of ADHD and a greater need for psychiatric medications to treat ADHD.

Blood-borne extracellular vesicles of bacteria and intestinal cells in patients with psychotic disorders

BACKGROUND

Human cells and bacteria secrete extracellular vesicles (EV) which play a role in intercellular communication. EV from the host intestinal epithelium are involved in the regulation of bacterial gene expression and growth. Bacterial EV (bactEV) produced in the intestine can pass to various tissues where they deliver biomolecules to many kinds of cells, including neurons. Emerging data indicate that gut microbiota is altered in patients with psychotic disorders. We hypothesized that the amount and content of blood-borne EV from intestinal cells and bactEV in psychotic patients would differ from healthy controls.

METHODS

We analyzed for human intestinal proteins by proteomics, for bactEV by metaproteomic analysis, and by measuring the level of lipopolysaccharide (LPS) in blood-borne EV from patients with psychotic disorders (n = 25), tested twice, in the acute phase of psychosis and after improvement, with age- and sex-matched healthy controls (n = 25).

RESULTS

Patients with psychotic disorders had lower LPS levels in their EV compared to healthy controls (p = .027). Metaproteome analyses confirmed LPS finding and identified Firmicutes and Bacteroidetes as dominating phyla. Total amounts of human intestine proteins in EV isolated from blood was lower in patients compared to controls (p = .02).

CONCLUSIONS

Our results suggest that bactEV and host intestinal EV are decreased in patients with psychosis and that this topic is worthy of further investigation given potential pathophysiological implications. Possible mechanisms involve dysregulation of the gut microbiota by host EV, altered translocation of bactEV to systemic circulation where bactEV can interact with both the brain and the immune system.

Comorbidity between major depressive disorder and physical diseases: a comprehensive review of epidemiology, mechanisms and management

Populations with common physical diseases - such as cardiovascular diseases, cancer and neurodegenerative disorders - experience substantially higher rates of major depressive disorder (MDD) than the general population. On the other hand, people living with MDD have a greater risk for many physical diseases. This high level of comorbidity is associated with worse outcomes, reduced adherence to treatment, increased mortality, and greater health care utilization and costs. Comorbidity can also result in a range of clinical challenges, such as a more complicated therapeutic alliance, issues pertaining to adaptive health behaviors, drug-drug interactions and adverse events induced by medications used for physical and mental disorders. Potential explanations for the high prevalence of the above comorbidity involve shared genetic and biological pathways. These latter include inflammation, the gut microbiome, mitochondrial function and energy metabolism, hypothalamic-pituitary-adrenal axis dysregulation, and brain structure and function. Furthermore, MDD and physical diseases have in common several antecedents related to social factors (e.g., socioeconomic status), lifestyle variables (e.g., physical activity, diet, sleep), and stressful live events (e.g., childhood trauma). Pharmacotherapies and psychotherapies are effective treatments for comorbid MDD, and the introduction of lifestyle interventions as well as collaborative care models and digital technologies provide promising strategies for improving management. This paper aims to provide a detailed overview of the epidemiology of the comorbidity of MDD and specific physical diseases, including prevalence and bidirectional risk; of shared biological pathways potentially implicated in the pathogenesis of MDD and common physical diseases; of socio-environmental factors that serve as both shared risk and protective factors; and of management of MDD and physical diseases, including prevention and treatment. We conclude with future directions and emerging research related to optimal care of people with comorbid MDD and physical diseases.

Household income does not affect the pleiotropy of schizophrenia genetic liability with mental and physical health outcomes

Background and Hypothesis

Individuals with schizophrenia (SCZ) suffer from comorbidities that substantially reduce their life expectancy. Socioeconomic inequalities could contribute to many of the negative health outcomes associated with SCZ.

Study Design

We investigated genome-wide datasets related to SCZ (52,017 cases and 75,889 controls) from the Psychiatric Genomics Consortium, household income (HI; N=361,687) from UK Biobank, and 2,202 medical endpoints assessed in up to 342,499 FinnGen participants. A phenome-wide genetic correlation analysis of SCZ and HI was performed, also assessing whether SCZ genetic correlations were influenced by HI effect on SCZ. Additionally, SCZ and HI direct effects on medical endpoints were estimated using multivariable Mendelian randomization (MR).

Study Results

SCZ and HI showed overlapping genetic correlations with 70 traits (p<2.89×10 -5 ), including mental health, substance use, gastrointestinal illnesses, reproductive outcomes, liver diseases, respiratory problems, and musculoskeletal phenotypes. SCZ genetic correlations with these traits were not affected by HI effect on SCZ. Considering Bonferroni multiple testing correction (p<7.14×10 -4 ), MR analysis indicated that SCZ and HI may affect medical abortion (SCZ odds ratio, OR=1.07; HI OR=0.78), panic disorder (SCZ OR=1.20; HI OR=0.60), personality disorders (SCZ OR=1.31; HI OR=0.67), substance use (SCZ OR=1.2; HI OR=0.68), and adjustment disorders (SCZ OR=1.18; HI OR=0.78). Multivariable MR analysis confirmed that SCZ effects on these outcomes were independent of HI.

Conclusions

The effect of SCZ genetic liability on mental and physical health may not be strongly affected by socioeconomic differences. This suggests that SCZ-specific strategies are needed to reduce negative health outcomes affecting patients and high-risk individuals.

Polygenic risk scores analyses of psychiatric and metabolic traits with antipsychotic-induced weight gain in schizophrenia: an exploratory study

Given the polygenic nature of antipsychotic-induced weight gain (AIWG), we investigated whether polygenic risk scores (PRS) for various psychiatric and metabolic traits were associated with AIWG. We included individuals with schizophrenia (SCZ) of European ancestry from two cohorts (N = 151, age = 40.3 ± 11.8 and N = 138, age = 36.5 ± 10.8). We investigated associations of AIWG defined as binary and continuous variables with PRS calculated from genome-wide association studies of body mass index (BMI), coronary artery disease (CAD), fasting glucose, fasting insulin, high-density lipoprotein cholesterol, low-density lipoprotein cholesterol (LDL-C), triglycerides, type 1 and 2 diabetes mellitus, and SCZ, using regression models. We observed nominal associations (uncorrected p < 0.05) between PRSs for BMI, CAD, and LDL-C, type 1 diabetes, and SCZ with AIWG. While results became non-significant after correction for multiple testing, these preliminary results suggest that PRS analyses might contribute to identifying risk factors of AIWG and might help to elucidate mechanisms at play in AIWG.

Phenome-wide genetic-correlation analysis and genetically informed causal inference of amyotrophic lateral sclerosis

Leveraging genome-wide association statistics generated from a large study of amyotrophic lateral sclerosis (ALS; 29,612 cases and 122,656 controls) and UK Biobank (UKB; 4,024 phenotypes, up to 361,194 participants), we conducted a phenome-wide analysis of ALS genetic liability and identified 46 genetically correlated traits, such as fluid intelligence score (rg = - 0.21, p = 1.74 × 10-6), "spending time in pub or social club" (rg = 0.24, p = 2.77 × 10-6), non-work related walking (rg = - 0.25, p = 1.95 × 10-6), college education (rg = - 0.15, p = 7.08 × 10-5), "ever diagnosed with panic attacks (rg = 0.39, p = 4.24 × 10-5), and "self-reported other gastritis including duodenitis" (rg = 0.28, p = 1.4 × 10-3). To assess the putative directionality of these genetic correlations, we conducted a latent causal variable analysis, identifying significant genetic causality proportions (gĉp) linking ALS genetic liability to seven traits. While the genetic component of "self-reported other gastritis including duodenitis" showed a causal effect on ALS (gĉp = 0.50, p = 1.26 × 10-29), the genetic liability to ALS is potentially causal for multiple traits, also including an effect on "ever being diagnosed with panic attacks" (gĉp = 0.79, p = 5.011 × 10-15) and inverse effects on "other leisure/social group activities" (gĉp = 0.66, p = 1 × 10-4) and prospective memory result (gĉp = 0.35, p = 0.005). Our subsequent Mendelian randomization analysis indicated that some of these associations may be due to bidirectional effects. In conclusion, this phenome-wide investigation of ALS polygenic architecture highlights the widespread pleiotropy linking this disorder with several health domains.

Evaluation of Brain-Body Health in Individuals With Common Neuropsychiatric Disorders

Importance

Physical health and chronic medical comorbidities are underestimated, inadequately treated, and often overlooked in psychiatry. A multiorgan, systemwide characterization of brain and body health in neuropsychiatric disorders may enable systematic evaluation of brain-body health status in patients and potentially identify new therapeutic targets.

Objective

To evaluate the health status of the brain and 7 body systems across common neuropsychiatric disorders.

Design, Setting, and Participants

Brain imaging phenotypes, physiological measures, and blood- and urine-based markers were harmonized across multiple population-based neuroimaging biobanks in the US, UK, and Australia, including UK Biobank; Australian Schizophrenia Research Bank; Australian Imaging, Biomarkers, and Lifestyle Flagship Study of Ageing; Alzheimer's Disease Neuroimaging Initiative; Prospective Imaging Study of Ageing; Human Connectome Project-Young Adult; and Human Connectome Project-Aging. Cross-sectional data acquired between March 2006 and December 2020 were used to study organ health. Data were analyzed from October 18, 2021, to July 21, 2022. Adults aged 18 to 95 years with a lifetime diagnosis of 1 or more common neuropsychiatric disorders, including schizophrenia, bipolar disorder, depression, generalized anxiety disorder, and a healthy comparison group were included.

Main Outcomes and Measures

Deviations from normative reference ranges for composite health scores indexing the health and function of the brain and 7 body systems. Secondary outcomes included accuracy of classifying diagnoses (disease vs control) and differentiating between diagnoses (disease vs disease), measured using the area under the receiver operating characteristic curve (AUC).

Results

There were 85 748 participants with preselected neuropsychiatric disorders (36 324 male) and 87 420 healthy control individuals (40 560 male) included in this study. Body health, especially scores indexing metabolic, hepatic, and immune health, deviated from normative reference ranges for all 4 neuropsychiatric disorders studied. Poor body health was a more pronounced illness manifestation compared to brain changes in schizophrenia (AUC for body = 0.81 [95% CI, 0.79-0.82]; AUC for brain = 0.79 [95% CI, 0.79-0.79]), bipolar disorder (AUC for body = 0.67 [95% CI, 0.67-0.68]; AUC for brain = 0.58 [95% CI, 0.57-0.58]), depression (AUC for body = 0.67 [95% CI, 0.67-0.68]; AUC for brain = 0.58 [95% CI, 0.58-0.58]), and anxiety (AUC for body = 0.63 [95% CI, 0.63-0.63]; AUC for brain = 0.57 [95% CI, 0.57-0.58]). However, brain health enabled more accurate differentiation between distinct neuropsychiatric diagnoses than body health (schizophrenia-other: mean AUC for body = 0.70 [95% CI, 0.70-0.71] and mean AUC for brain = 0.79 [95% CI, 0.79-0.80]; bipolar disorder-other: mean AUC for body = 0.60 [95% CI, 0.59-0.60] and mean AUC for brain = 0.65 [95% CI, 0.65-0.65]; depression-other: mean AUC for body = 0.61 [95% CI, 0.60-0.63] and mean AUC for brain = 0.65 [95% CI, 0.65-0.66]; anxiety-other: mean AUC for body = 0.63 [95% CI, 0.62-0.63] and mean AUC for brain = 0.66 [95% CI, 0.65-0.66).

Conclusions and Relevance

In this cross-sectional study, neuropsychiatric disorders shared a substantial and largely overlapping imprint of poor body health. Routinely monitoring body health and integrated physical and mental health care may help reduce the adverse effect of physical comorbidity in people with mental illness.

Genome-wide association studies reveal shared genetic haplotypes of autoimmune rheumatic and endocrine diseases with psychiatric disorders

BACKGROUND

Several studies have shown that autoimmune diseases are associated with psychiatric diseases like depression and psychosis. Genetic evidence supports this association. The aim of this study was to investigate if genetic variants predisposing to autoimmune diseases and psychiatric disorders are genetically linked, constructing the common haplotypes.

METHODS

All registered single nucleotide polymorphisms (SNPs) in the Genome-wide association studies ("GWAS catalog") having been associated with autoimmune rheumatic and endocrine diseases were investigated for being in linkage disequilibrium with any psychiatric disorders' associated SNPs. Analysis was performed by the LDtrait and LDhap bioinformatics tools.

RESULTS

Multiple chromosomal regions have been detected containing rheumatic/endocrine diseases' predisposing SNPs and psychiatric disorders' predisposing SNPs. The genetic haplotypes have been constructed for some of these genetic regions. Six of the autoimmune rheumatic and endocrine diseases examined here share a common haplotype with psychiatric diseases at the HLA locus 6p21-22.

CONCLUSION

Our study shows that autoimmune diseases and psychiatric diseases are genetically linked. Genetic haplotypes have been constructed, showing in detail this genetic linkage.

Role of the Gut-Brain Axis in the Shared Genetic Etiology Between Gastrointestinal Tract Diseases and Psychiatric Disorders: A Genome-Wide Pleiotropic Analysis

IMPORTANCE

Comorbidities and genetic correlations between gastrointestinal tract diseases and psychiatric disorders have been widely reported, with the gut-brain axis (GBA) hypothesized as a potential biological basis. However, the degree to which the shared genetic determinants are involved in these associations underlying the GBA is unclear.

OBJECTIVE

To investigate the shared genetic etiology between gastrointestinal tract diseases and psychiatric disorders and to identify shared genomic loci, genes, and pathways.

DESIGN, SETTING, AND PARTICIPANTS

This genome-wide pleiotropic association study using genome-wide association summary statistics from publicly available data sources was performed with various statistical genetic approaches to sequentially investigate the pleiotropic associations from genome-wide single-nucleotide variation (SNV; formerly single-nucleotide polymorphism [SNP]), and gene levels and biological pathways to disentangle the underlying shared genetic etiology between 4 gastrointestinal tract diseases (inflammatory bowel disease, irritable bowel syndrome, peptic ulcer disease, and gastroesophageal reflux disease) and 6 psychiatric disorders (schizophrenia, bipolar disorder, major depressive disorder, attention-deficit/hyperactivity disorder, posttraumatic stress disorder, and anorexia nervosa). Data were collected from March 10, 2021, to August 25, 2021, and analysis was performed from January 8 through May 30, 2022.

MAIN OUTCOMES AND MEASURES

The primary outcomes consisted of a list of genetic loci, genes, and pathways shared between gastrointestinal tract diseases and psychiatric disorders.

RESULTS

Extensive genetic correlations and genetic overlaps were found among 22 of 24 trait pairs. Pleiotropic analysis under a composite null hypothesis identified 2910 significant potential pleiotropic SNVs in 19 trait pairs, with 83 pleiotropic loci and 24 colocalized loci detected. Gene-based analysis found 158 unique candidate pleiotropic genes, which were highly enriched in certain GBA-related phenotypes and tissues, whereas pathway enrichment analysis further highlighted biological pathways primarily involving cell adhesion, synaptic structure and function, and immune cell differentiation. Several identified pleiotropic loci also shared causal variants with gut microbiomes. Mendelian randomization analysis further illustrated vertical pleiotropy across 8 pairwise traits. Notably, many pleiotropic loci were identified for multiple pairwise traits, such as 1q32.1 (INAVA), 19q13.33 (FUT2), 11q23.2 (NCAM1), and 1p32.3 (LRP8).

CONCLUSIONS AND RELEVANCE

These findings suggest that the pleiotropic genetic determinants between gastrointestinal tract diseases and psychiatric disorders are extensively distributed across the genome. These findings not only support the shared genetic basis underlying the GBA but also have important implications for intervention and treatment targets of these diseases simultaneously.

New insights from the last decade of research in psychiatric genetics: discoveries, challenges and clinical implications

Psychiatric genetics has made substantial progress in the last decade, providing new insights into the genetic etiology of psychiatric disorders, and paving the way for precision psychiatry, in which individual genetic profiles may be used to personalize risk assessment and inform clinical decision-making. Long recognized to be heritable, recent evidence shows that psychiatric disorders are influenced by thousands of genetic variants acting together. Most of these variants are commonly occurring, meaning that every individual has a genetic risk to each psychiatric disorder, from low to high. A series of large-scale genetic studies have discovered an increasing number of common and rare genetic variants robustly associated with major psychiatric disorders. The most convincing biological interpretation of the genetic findings implicates altered synaptic function in autism spectrum disorder and schizophrenia. However, the mechanistic understanding is still incomplete. In line with their extensive clinical and epidemiological overlap, psychiatric disorders appear to exist on genetic continua and share a large degree of genetic risk with one another. This provides further support to the notion that current psychiatric diagnoses do not represent distinct pathogenic entities, which may inform ongoing attempts to reconceptualize psychiatric nosology. Psychiatric disorders also share genetic influences with a range of behavioral and somatic traits and diseases, including brain structures, cognitive function, immunological phenotypes and cardiovascular disease, suggesting shared genetic etiology of potential clinical importance. Current polygenic risk score tools, which predict individual genetic susceptibility to illness, do not yet provide clinically actionable information. However, their precision is likely to improve in the coming years, and they may eventually become part of clinical practice, stressing the need to educate clinicians and patients about their potential use and misuse. This review discusses key recent insights from psychiatric genetics and their possible clinical applications, and suggests future directions.