Pervasive pleiotropy between psychiatric disorders and immune disorders revealed by integrative analysis of multiple GWAS

Examining the Genetic Links between Clusters of Immune-mediated Diseases and Psychiatric Disorders

Importance

Autoimmune and autoinflammatory diseases have been linked to psychiatric disorders in the phenotypic and genetic literature. However, a comprehensive model that investigates the association between a broad range of psychiatric disorders and immune-mediated disease in a multivariate framework is lacking.

Objective

This study aims to establish a factor structure based on the genetic correlations of immune-mediated diseases and investigate their genetic relationships with clusters of psychiatric disorders.

Design Setting and Participants

We utilized Genomic Structural Equation Modeling (Genomic SEM) to establish a factor structure of 11 immune-mediated diseases. Genetic correlations between these immune factors were examined with five established factors across 13 psychiatric disorders representing compulsive, schizophrenia/bipolar, neurodevelopmental, internalizing, and substance use disorders. We included GWAS summary statistics of individuals of European ancestry with sample sizes from 1,223 cases for Addison's disease to 170,756 cases for major depressive disorder.

Main Outcomes and Measures

Genetic correlations between psychiatric and immune-mediated disease factors and traits to determine genetic overlap. We develop and validate a new heterogeneity metric, Q Factor , that quantifies the degree to which factor correlations are driven by more specific pairwise associations. We also estimate residual genetic correlations between pairs of psychiatric disorders and immune-mediated diseases.

Results

A four-factor model of immune-mediated diseases fit the data well and described a continuum from autoimmune to autoinflammatory diseases. The four factors reflected autoimmune, celiac, mixed pattern, and autoinflammatory diseases. Analyses revealed seven significant factor correlations between the immune and psychiatric factors, including autoimmune and mixed pattern diseases with the internalizing and substance use factors, and autoinflammatory diseases with the compulsive, schizophrenia/bipolar, and internalizing factors. Additionally, we find evidence of divergence in associations within factors as indicated by Q Factor . This is further supported by 14 significant residual genetic correlations between individual psychiatric disorders and immune-mediated diseases.

Conclusion and Relevance

Our results revealed genetic links between clusters of immune-mediated diseases and psychiatric disorders. Current analyses indicate that previously described relationships between specific psychiatric disorders and immune-mediated diseases often capture broader pathways of risk sharing indexed by our genomic factors, yet are more specific than a general association across all psychiatric disorders and immune-mediated diseases.

Causal role of immune cells in obstructive sleep apnea hypopnea syndrome: Mendelian randomization study

BACKGROUND

Despite being one of the most prevalent sleep disorders, obstructive sleep apnea hypoventilation syndrome (OSAHS) has limited information on its immunologic foundation. The immunological underpinnings of certain major psychiatric diseases have been uncovered in recent years thanks to the extensive use of genome-wide association studies (GWAS) and genotyping techniques using high-density genetic markers (e.g., SNP or CNVs). But this tactic hasn't yet been applied to OSAHS. Using a Mendelian randomization analysis, we analyzed the causal link between immune cells and the illness in order to comprehend the immunological bases of OSAHS.

AIM

To investigate the immune cells' association with OSAHS via genetic methods, guiding future clinical research.

METHODS

A comprehensive two-sample mendelian randomization study was conducted to investigate the causal relationship between immune cell characteristics and OSAHS. Summary statistics for each immune cell feature were obtained from the GWAS catalog. Information on 731 immune cell properties, such as morphologic parameters, median fluorescence intensity, absolute cellular, and relative cellular, was compiled using publicly available genetic databases. The results' robustness, heterogeneity, and horizontal pleiotropy were confirmed using extensive sensitivity examination.

RESULTS

Following false discovery rate (FDR) correction, no statistically significant effect of OSAHS on immunophenotypes was observed. However, two lymphocyte subsets were found to have a significant association with the risk of OSAHS: Basophil %CD33dim HLA DR- CD66b- (OR = 1.03, 95%CI = 1.01-1.03, P < 0.001); CD38 on IgD+ CD24- B cell (OR = 1.04, 95%CI = 1.02-1.04, P = 0.019).

CONCLUSION

This study shows a strong link between immune cells and OSAHS through a gene approach, thus offering direction for potential future medical research.

Genetic correlation, shared loci, but no causality between bipolar disorder and inflammatory bowel disease: A genome-wide pleiotropic analysis

BACKGROUND AND AIMS

The comorbidity between bipolar disorder (BD) and inflammatory bowel disease (IBD) has been widely reported in observational studies. However, unclear whether this comorbidity reflects a shared genetic architecture.

METHODS

Leveraging large-scale genome-wide association study (GWAS) summary statistics of BD, IBD and its subtypes, ulcerative colitis (UC) and Crohn's disease (CD), we performed a genome-wide pleiotropic analysis to estimate heritability and genetic correlation, identify pleiotropy loci/genes, and explore the shared biological pathway. Mendelian randomization (MR) studies were subsequently employed to infer whether the potential causal relationship is present.

RESULTS

We found a positive significant genetic correlation between BD and IBD (rg = 0.10, P = 7.00 × 10-4), UC (rg = 0.09, P = 2.90 × 10-3), CD (rg = 0.08, P = 6.10 × 10-3). In cross-trait meta-analysis, a total of 29, 24, and 23 independent SNPs passed the threshold for significant association between BD and IBD, UC, and CD, respectively. We identified five novel pleiotropy genes including ZDHHC2, SCRN1, INPP4B, C1orf123, and BRD3 in both BD and IBD, as well as in its subtypes UC and CD. Pathway enrichment analyses revealed that those pleiotropy genes were mainly enriched in several immune-related signal transduction pathways and cerebral disease-related pathways. MR analyses provided no evidence for a causal relationship between BD and IBD.

CONCLUSION

Our findings corroborated that shared genetic basis and common biological pathways may explain the comorbidity of BD and IBD. These findings further our understanding of shared genetic mechanisms underlying BD and IBD, and potentially provide points of intervention that may allow the development of new therapies for these co-occurrent disorders.

Shared Genetic Risk in the Association of Screen Time With Psychiatric Problems in Children

Importance

Children's exposure to screen time has been associated with poor mental health outcomes, yet the role of genetic factors remains largely unknown.

Objective

To assess the extent of genetic confounding in the associations between screen time and attention problems or internalizing problems in preadolescent children.

Design, Setting, and Participants

This cohort study analyzed data obtained between 2016 and 2019 from the Adolescent Brain Cognitive Development Study at 21 sites in the US. The sample included children aged 9 to 11 years of genetically assigned European ancestry with self-reported screen time. Data were analyzed between November 2021 and September 2023.

Exposure

Child-reported daily screen time (in hours) was ascertained from questionnaires completed by the children at baseline.

Main Outcomes and Measures

Child psychiatric problems, specifically attention and internalizing problems, were measured with the parent-completed Achenbach Child Behavior Checklist at the 1-year follow-up. Genetic sensitivity analyses model (Gsens) was used, which incorporated polygenic risk scores (PRSs) of both exposure and outcomes as well as either single-nucleotide variant (SNV; formerly single-nucleotide polymorphism)-based heritability or twin-based heritability to estimate genetic confounding.

Results

The 4262 children in the sample included 2269 males (53.2%) with a mean (SD) age of 9.9 (0.6) years. Child screen time was associated with attention problems (β = 0.10 SD; 95% CI, 0.07-0.13 SD) and internalizing problems (β = 0.03 SD; 95% CI, 0.003-0.06 SD). The television time PRS was associated with child screen time (β = 0.18 SD; 95% CI, 0.14-0.23 SD), the attention-deficit/hyperactivity disorder PRS was associated with attention problems (β = 0.13 SD; 95% CI, 0.10-0.16 SD), and the depression PRS was associated with internalizing problems (β = 0.10 SD; 95% CI, 0.07-0.13 SD). These PRSs were associated with cross-traits, suggesting genetic confounding. Estimates using PRSs and SNV-based heritability showed that genetic confounding accounted for most of the association between child screen time and attention problems and for 42.7% of the association between child screen time and internalizing problems. When PRSs and twin-based heritability estimates were used, genetic confounding fully explained both associations.

Conclusions and Relevance

Results of this study suggest that genetic confounding may explain a substantial part of the associations between child screen time and psychiatric problems. Genetic confounding should be considered in sociobehavioral studies of modifiable factors for youth mental health.

Beyond expectations: disease duration and psychological burden in psoriatic arthritis

This study aims to investigate the relationship between disease duration and psychological burden in PsA and to identify the risk factors associated with psychological distress. Patients with PsA who met CASPAR classification criteria enrolled by Turkish League Against Rheumatism (TLAR)-Network. Patients were categorized into three groups based on disease duration: early stage (< 5 years), middle stage (≥ 5, < 10 years), and late stage (≥ 10 years). All patients underwent clinical and laboratory assessment using standardized protocol and case report forms. The associations between psychological variables and clinical parameters were assessed by a multivariate analysis. Of the 1113 patients with PsA (63.9% female), 564 (%50.7) had high risk for depression and 263 (%23.6) for anxiety. The risk of psychological burden was similar across all PsA groups, and patients with a higher risk of depression and anxiety also experienced greater disease activity, poorer quality of life, and physical disability. Multivariate logistic regression revealed that female gender (OR = 1.52), PsAQoL (OR = 1.13), HAQ (OR = 1.99), FiRST score (OR = 1.14), unemployment/retired (OR = 1.48) and PASI head score (OR = 1.41) were factors that influenced the risk of depression, whereas the current or past enthesitis (OR = 1.45), PsAQoL (OR = 1.19), and FiRST score (OR = 1.26) were factors that influenced the risk of anxiety. PsA patients can experience a comparable level of psychological burden throughout the course of their disease. Several socio-demographic and disease-related factors may contribute to mental disorders in PsA. In the present era of personalized treatment for PsA, evaluating psychiatric distress can guide tailored interventions that improve overall well-being and reduce disease burden.

Risk factors of involuntary referral by police to ER psychiatric services for patients with a severe mental illness: A GEE analysis

This study aimed to identify risk factors for involuntary referral by police to emergency room (ER) psychiatric services for community-based patients with a mental illness via a generalized estimating equation (GEE) analysis. The analysis was based on data from the Management Information System of Psychiatric Care (MISPC) system for patients with a severe mental illness in Taipei, Taiwan and registered referral records of the police. Data on 6378 patients aged ≥20 years were used in this study, including 164 patients who were involuntarily referred to the ER by the police and 6214 patients who were not during the period of January 1, 2018 to December 31, 2020. GEEs were utilized to explore possible risk factors of repeated involuntary referral to ER psychiatric services for patients with a severe mental illness. The logistic regressions indicated that patients defined as "severe" according to the Mental Health Act of Taiwan (crude odds ratio (OR): 3.840, 95 % confidence interval (CI): 2.407-6.126), with a disability (crude OR: 3.567, 95 % CI: 1.339-9.501), with two or more family members with a psychiatric disorder (crude OR: 1.598, 95 % CI: 1.002-2.548), with a history of a suicide attempt (crude OR: 25.582, 95 % CI: 17.608-37.167), and with a history of domestic violence (crude OR: 16.141, 95 % CI: 11.539-22.579) were positively associated with involuntary referral to ER psychiatric services. However, age (crude OR: 0.971, 95 % CI: 0.960-0.983) and the MISPC score (crude OR: 0.834, 95 % CI: 0.800-0.869) were inversely associated with involuntary referral to ER psychiatric services. After adjusting for demographics and potential confounders, we found that patients defined as "severe" (Exp (β): 3.236), with a disability (Exp (β): 3.715), with a history of a suicide attempt (Exp (β): 8.706), and with a history of domestic violence (Exp (β): 8.826), as well as age (Exp (β): 0.986) and the MISPC score (Exp (β): 0.902) remained significantly associated with repeated involuntary referral to ER psychiatric services. In conclusion, community-based mentally ill patients with a history of a suicide attempt, with a history of domestic violence, with a severe illness, and with a profound level of disability were highly associated with involuntary referral to ER psychiatric services. We suggest that community mental health case managers identify significant factors associated with involuntary referral to ER psychiatric services to accordingly arrange case management plans.

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.

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

Importance

Certain psychiatric and immune-related disorders are reciprocal risk factors. However, the nature of these associations is unclear.

Objective

To characterize the pleiotropy between psychiatric and immune-related traits, as well as risk factors of hypothesized relevance.

Design, Setting, and Participants

This genetic association study was conducted from July 10, 2020, to January 15, 2022. Analyses used genome-wide association (GWA) statistics related to 14 psychiatric traits; 13 immune-related phenotypes, ie, allergic, autoimmune, and inflammatory disorders; and 15 risk factors related to health-related behaviors, social determinants of health, and stress response. Genetically correlated psychiatric-immune pairs were assessed using 2-sample mendelian randomization (MR) with sensitivity analyses and multivariable adjustment for genetic associations of third variables. False discovery rate correction (Q value < .05) was applied for each analysis.

Exposures

Genetic associations.

Main Outcomes and Measures

Genetic correlations and MR association estimates with SEs and P values. A data-driven approach was used that did not test a priori planned hypotheses.

Results

A total of 44 genetically correlated psychiatric-immune pairs were identified, including 31 positive correlations (most consistently involving asthma, Crohn disease, hypothyroidism, and ulcerative colitis) and 13 negative correlations (most consistently involving allergic rhinitis and type 1 diabetes). Correlations with third variables were especially strong for psychiatric phenotypes. MR identified 7 associations of psychiatric phenotypes on immune-related phenotypes that were robust to multivariable adjustment, including the positive association of (1) the psychiatric cross-disorder phenotype with asthma (odds ratio [OR], 1.04; 95% CI, 1.02-1.06), Crohn disease (OR, 1.09; 95% CI, 1.05-1.14), and ulcerative colitis (OR, 1.09; 95% CI, 1.05-1.14); (2) major depression with asthma (OR, 1.25; 95% CI, 1.13-1.37); (3) schizophrenia with Crohn disease (OR, 1.12; 95% CI, 1.05-1.18) and ulcerative colitis (OR, 1.14; 95% CI, 1.07-1.21); and a negative association of risk tolerance with allergic rhinitis (OR, 0.77; 95% CI, 0.67-0.92).

Conclusions and Relevance

Results of this genetic association study suggest that genetic liability for psychiatric disorders was associated with liability for several immune disorders, suggesting that vertical pleiotropy related to behavioral traits (or correlated third variables) contributes to clinical associations observed in population-scale data.

Limited association between infections, autoimmune disease and genetic risk and immune activation in severe mental disorders

BACKGROUND

Low-grade inflammation may be part of the underlying mechanism of schizophrenia and bipolar disorder. We investigated if genetic susceptibility, infections or autoimmunity could explain the immune activation.

METHODS

Seven immune markers were selected based on indicated associations to severe mental disorders (IL-1Ra, sIL-2R, IL-18, sgp130, sTNFR-1, APRIL, ICAM-1) and measured in plasma of patients with schizophrenia (SCZ, N = 732) and bipolar spectrum disorders (BD, N = 460) and healthy controls (HC, N = 938). Information on rate of infections and autoimmune diseases were obtained from Norwegian national health registries for a twelve-year period. Polygenic risk scores (PRS) of SCZ and BD were calculated from genome-wide association studies. Analysis of covariance were used to test effects of infection rate, autoimmune disease and PRS on differences in immune markers between patients and HC.

RESULTS

Infection rate differed between all groups (BD > HC > SCZ, all p < 0.001) whereas autoimmune disease was more frequent in BD compared to SCZ (p = 0.004) and HC (p = 0.003). sIL-2R was positively associated with autoimmune disease (p = 0.001) and negatively associated with PRS of SCZ (p = 0.006) across SCZ and HC; however, associations represented only small changes in the difference of sIL-2R levels between SCZ and HC.

CONCLUSION

There were few significant associations between rate of infections, autoimmune disease or PRS and altered immune markers in SCZ and BD, and the detected associations represented only small changes in the immune aberrations. The findings suggest that most of the low-grade inflammation in SCZ and BD is explained by other factors than the underlying PRS, autoimmunity and infection rates.

Quantifying concordant genetic effects of de novo mutations on multiple disorders

Exome sequencing on tens of thousands of parent-proband trios has identified numerous deleterious de novo mutations (DNMs) and implicated risk genes for many disorders. Recent studies have suggested shared genes and pathways are enriched for DNMs across multiple disorders. However, existing analytic strategies only focus on genes that reach statistical significance for multiple disorders and require large trio samples in each study. As a result, these methods are not able to characterize the full landscape of genetic sharing due to polygenicity and incomplete penetrance. In this work, we introduce EncoreDNM, a novel statistical framework to quantify shared genetic effects between two disorders characterized by concordant enrichment of DNMs in the exome. EncoreDNM makes use of exome-wide, summary-level DNM data, including genes that do not reach statistical significance in single-disorder analysis, to evaluate the overall and annotation-partitioned genetic sharing between two disorders. Applying EncoreDNM to DNM data of nine disorders, we identified abundant pairwise enrichment correlations, especially in genes intolerant to pathogenic mutations and genes highly expressed in fetal tissues. These results suggest that EncoreDNM improves current analytic approaches and may have broad applications in DNM studies.

Abnormal RasGRP1 Expression in the Post-Mortem Brain and Blood Serum of Schizophrenia Patients

Schizophrenia (SCZ) is a polygenic severe mental illness. Genome-wide association studies (GWAS) have detected genomic variants associated with this psychiatric disorder and pathway analyses have indicated immune system and dopamine signaling as core components of risk in dorsolateral-prefrontal cortex (DLPFC) and hippocampus, but the mechanistic links remain unknown. The RasGRP1 gene, encoding for a guanine nucleotide exchange factor, is implicated in dopamine signaling and immune response. RasGRP1 has been identified as a candidate risk gene for SCZ and autoimmune disease, therefore representing a possible point of convergence between mechanisms involving the nervous and the immune system. Here, we investigated RasGRP1 mRNA and protein expression in post-mortem DLPFC and hippocampus of SCZ patients and healthy controls, along with RasGRP1 protein content in the serum of an independent cohort of SCZ patients and control subjects. Differences in RasGRP1 expression between SCZ patients and controls were detected both in DLPFC and peripheral blood of samples analyzed. Our results indicate RasGRP1 may mediate risk for SCZ by involving DLPFC and peripheral blood, thus encouraging further studies to explore its possible role as a biomarker of the disease and/or a target for new medication.

The evolution of knowledge on genes associated with human diseases

Thousands of biomedical scientific articles, including those describing genes associated with human diseases, are published every week. Computational methods such as text mining and machine learning algorithms are now able to automatically detect these associations. In this study, we used a cognitive computing text-mining application to construct a knowledge network comprising 3,723 genes and 99 diseases. We then tracked the yearly changes on these networks to analyze how our knowledge has evolved in the past 30 years. Our systems approach helped to unravel the molecular bases of diseases and detect shared mechanisms between clinically distinct diseases. It also revealed that multi-purpose therapeutic drugs target genes that are commonly associated with several psychiatric, inflammatory, or infectious disorders. By navigating this knowledge tsunami, we were able to extract relevant biological information and insights about human diseases.

Plasma Levels of the Cytokines B Cell-Activating Factor (BAFF) and A Proliferation-Inducing Ligand (APRIL) in Schizophrenia, Bipolar, and Major Depressive Disorder: A Cross Sectional, Multisite Study

BACKGROUND

Immune dysfunction has been implicated in the pathogenesis of schizophrenia and other nonaffective psychosis (SCZ), bipolar spectrum disorder (BIP) and major depressive disorder (MDD). The cytokines B cell-activating factor (BAFF) and A proliferation-inducing ligand (APRIL) belong to the tumor necrosis factor (TNF) super family and are essential in orchestrating immune responses. Abnormal levels of BAFF and APRIL have been found in autoimmune diseases with CNS affection.

METHODS

We investigated if plasma levels of BAFF and APRIL differed between patients with SCZ, BIP, and MDD with psychotic symptoms (n = 2009) and healthy control subjects (HC, n = 1212), and tested for associations with psychotic symptom load, controlling for sociodemographic status, antipsychotic and other psychotropic medication, smoking, body-mass-index, and high sensitivity CRP.

RESULTS

Plasma APRIL level was significantly lower across all patient groups compared to HC (P < .001; Cohen's d = 0.33), and in SCZ compared to HC (P < .001; d = 0.28) and in BIP compared to HC (P < .001; d = 0.37). Lower plasma APRIL was associated with higher psychotic symptom load with nominal significance (P = .017), but not with any other clinical characteristics. Plasma BAFF was not significantly different across patient groups vs HC, but significantly higher in BIP compared to HC (P = .040; d = 0.12) and SCZ (P = .027; d = 0.10).

CONCLUSIONS

These results show aberrant levels of BAFF and APRIL and association with psychotic symptoms in patients with SCZ and BIP. This suggest that dysregulation of the TNF system, mediated by BAFF and APRIL, is involved in the pathophysiology of psychotic disorders.

Model checking via testing for direct effects in Mendelian Randomization and transcriptome-wide association studies

It is of great interest and potential to discover causal relationships between pairs of exposures and outcomes using genetic variants as instrumental variables (IVs) to deal with hidden confounding in observational studies. Two most popular approaches are Mendelian randomization (MR), which usually use independent genetic variants/SNPs across the genome, and transcriptome-wide association studies (TWAS) (or their generalizations) using cis-SNPs local to a gene (or some genome-wide and likely dependent SNPs), as IVs. In spite of their many promising applications, both approaches face a major challenge: the validity of their causal conclusions depends on three critical assumptions on valid IVs, and more generally on other modeling assumptions, which however may not hold in practice. The most likely as well as challenging situation is due to the wide-spread horizontal pleiotropy, leading to two of the three IV assumptions being violated and thus to biased statistical inference. More generally, we'd like to conduct a goodness-of-fit (GOF) test to check the model being used. Although some methods have been proposed as being robust to various degrees to the violation of some modeling assumptions, they often give different and even conflicting results due to their own modeling assumptions and possibly lower statistical efficiency, imposing difficulties to the practitioner in choosing and interpreting varying results across different methods. Hence, it would help to directly test whether any assumption is violated or not. In particular, there is a lack of such tests for TWAS. We propose a new and general GOF test, called TEDE (TEsting Direct Effects), applicable to both correlated and independent SNPs/IVs (as commonly used in TWAS and MR respectively). Through simulation studies and real data examples, we demonstrate high statistical power and advantages of our new method, while confirming the frequent violation of modeling (including valid IV) assumptions in practice and thus the importance of model checking by applying such a test in MR/TWAS analysis.

Identification of Novel Pleiotropic SNPs Associated with Osteoporosis and Rheumatoid Arthritis

Genome-wide association studies (GWASs) have identified hundreds of genetic loci for osteoporosis (OP) and rheumatoid arthritis (RA), individually, however, a large proportion of the total trait heritability remains unexplained. Previous studies demonstrated that these two diseases may share some common genetic determination and risk factors, but they were generally focused on individual trait and failed to identify the common variants that play key functional roles in the etiology of these two diseases. Here, we performed a conditional false discovery rate (cFDR) analysis to identify novel pleiotropic variants shared between them by integrating two independent GWASs with summary statistics for total body bone mineral density (TB-BMD, a major risk factor for osteoporosis) (n = 66,628) and RA (n = 58,284). A fine-mapping approach was also applied to identify the most probable causal variants with biological effects on both TB-BMD and RA. As a result, we found 47 independent pleiotropic SNPs shared between TB-BMD and RA, and 40 of them were validated in heel ultrasound estimated BMD (eBMD), femoral neck BMD (FN-BMD) or lumbar spine (LS-BMD). We detected one SNP (rs13299616) was novel and not identified by previous BMD or RA-related studies. Combined with fine-mapping and GWAS-eQTL colocalization analyses, our results suggested that locus 1p13.2 (including PTPN22, MAGI3, PHTF1, and RSBN1) was an important region to regulate TB-BMD and RA simultaneously. These findings provide new insights into the shared biological mechanisms and functional genetic determinants between OP and RA, and novel potential targets for treatment development.

Pathway analysis for genome-wide genetic variation data: Analytic principles, latest developments, and new opportunities

Pathway analysis, also known as gene-set enrichment analysis, is a multilocus analytic strategy that integrates a priori, biological knowledge into the statistical analysis of high-throughput genetics data. Originally developed for the studies of gene expression data, it has become a powerful analytic procedure for in-depth mining of genome-wide genetic variation data. Astonishing discoveries were made in the past years, uncovering genes and biological mechanisms underlying common and complex disorders. However, as massive amounts of diverse functional genomics data accrue, there is a pressing need for newer generations of pathway analysis methods that can utilize multiple layers of high-throughput genomics data. In this review, we provide an intellectual foundation of this powerful analytic strategy, as well as an update of the state-of-the-art in recent method developments. The goal of this review is threefold: (1) introduce the motivation and basic steps of pathway analysis for genome-wide genetic variation data; (2) review the merits and the shortcomings of classic and newly emerging integrative pathway analysis tools; and (3) discuss remaining challenges and future directions for further method developments.

Relevant Characteristics Analysis Using Natural Language Processing and Machine Learning Based on Phenotypes and T-Cell Subsets in Systemic Lupus Erythematosus Patients With Anxiety

Anxiety is frequently observed in patients with systemic lupus erythematosus (SLE) and the immune system could act as a trigger for anxiety. To recognize abnormal T-cell and B-cell subsets for SLE patients with anxiety, in this study, patient disease phenotypes data from electronic lupus symptom records were extracted by using natural language processing. The Hospital Anxiety and Depression Scale (HADS) was used to distinguish patients, and 107 patients were selected to meet research requirements. Then, peripheral blood was collected from two patient groups for multicolor flow cytometry experiments. The characteristics of 75 T-cell and 15 B-cell subsets were investigated between SLE patients with- (n = 23) and without-anxiety (n = 84) groups by four machine learning methods. The findings showed 13 T-cell subsets were significantly different between the two groups. Furthermore, BMI, fatigue, depression, unstable emotions, CD27⁺CD28⁺ Th/Treg, CD27^-CD28^- Th/Treg, CD45RA^-CD27^- Th, and CD45RA⁺HLADR⁺ Th cells may be important characteristics between SLE patients with- and without-anxiety groups. The findings not only point out the difference of T-cell subsets in SLE patients with or without anxiety, but also imply that T cells might play the important role in patients with anxiety disorder.

Depression in patients with spondyloarthritis: prevalence, incidence, risk factors, mechanisms and management

Depression is a major neuropsychiatric disorder common in patients with rheumatological conditions including spondyloarthritis (SpA). It is associated with higher disease activity, functional impairment, poor treatment response and quality of life in patients with musculoskeletal disorders. Using ankylosing spondylitis (AS) and psoriatic arthritis (PsA) as examples, we have reviewed the evidence regarding the burden, risk factors, potential mechanisms and clinical management of depression in spondyloarthritis. The prevalence of depression is higher in patients with AS and PsA compared with the general population, with evidence of moderate/severe depression in about 15% of patients with AS or PsA. Mild depression is even more common and estimated to be present in about 40% of patients with AS. In addition to conventional risk factors such as stressful life events and socioeconomic deprivation, increased risk of depression in SpA may be associated with disease-related factors, such as disease activity, poor quality of life, fatigue, and sleep disturbances. Emerging evidence implicates inflammation in the aetiology of depression, which could also be a shared mechanism for depression and chronic inflammatory conditions such as AS and PsA. It is imperative for clinicians to actively assess and treat depression in SpA, as this could improve treatment adherence, quality of life, and overall long-term clinical and occupational outcomes. The use of validated tools can aid recognition and management of depression in rheumatology clinics. Management of depression in SpA, especially when to refer to specialist mental health services, are discussed.

Pediatric Acute-Onset Neuropsychiatric Syndrome: A Data Mining Approach to a Very Specific Constellation of Clinical Variables

Objectives: Pediatric acute onset neuropsychiatric syndrome (PANS) is a clinically heterogeneous disorder presenting with: unusually abrupt onset of obsessive compulsive disorder (OCD) or severe eating restrictions, with at least two concomitant cognitive, behavioral, or affective symptoms such as anxiety, obsessive-compulsive behavior, and irritability/depression. This study describes the clinical and laboratory variables of 39 children (13 female and 26 male) with a mean age at recruitment of 8.6 years (standard deviation 3.1). Methods: Using a mathematical approach based on Artificial Neural Networks, the putative associations between PANS working criteria, as defined at the NIH in July 2010 (Swedo et al. 2012), were explored by the Auto Contractive Map (Auto-CM) system, a mapping method able to compute the multidimensional association of strength of each variable with all other variables in predefined dataset. Results: The PANS symptoms were strictly linked to one another on the semantic connectivity map, shaping a central "diamond" encompassing anxiety, irritability/oppositional defiant disorder symptoms, obsessive-compulsive symptoms, behavioral regression, sensory motor abnormalities, school performance deterioration, sleep disturbances, and emotional lability/depression. The semantic connectivity map also showed the aggregation between PANS symptoms and laboratory and clinical variables. In particular, the emotional lability/depression resulted as a highly connected hub linked to autoimmune disease in pregnancy, allergic and atopic disorders, and low Natural Killer percentage. Also anxiety symptoms were shown to be strongly related with recurrent infectious disease remarking the possible role of infections as a risk factor for PANS. Conclusion: Our data mining approach shows a very specific constellation of symptoms having strong links to laboratory and clinical variables consistent with PANS feature.

A Genetics Perspective on the Role of the (Neuro)Immune System in Schizophrenia

The immune system has long been hypothesized to play a role in schizophrenia pathogenesis based on data from diverse disciplines. Recent reports of the identification of schizophrenia-associated genetic variants and their initial biological characterization have renewed investigation of the role of the immune system in schizophrenia. In the current review, the plausibility of a role of the immune system in schizophrenia pathogenesis is examined, by revisiting epidemiology, neuroimaging, pharmacology, and developmental biology from a genetics perspective, as well as by synthesizing diverse findings from the emerging and dynamic schizophrenia genomics field. Genetic correlations between schizophrenia and immunological disorders are inconsistent and often contradictory, as are neuroimaging studies of microglia markers. Small therapeutic trials of anti-inflammatory agents targeting immune function have been consistently negative. Some gene expression analyses of post-mortem brains of patients with schizophrenia have reported an upregulation of genes of immune function though others report downregulation, and overall transcriptome profiling to date does not support an upregulation of immune pathways associated with schizophrenia genetic risk. The currently reviewed genetic data do not converge to reveal consistent evidence of the neuroimmune system in schizophrenia pathogenesis, and indeed, a substantive role for the neuroimmune system in schizophrenia has yet to be established.

Longitudinal epigenome-wide association studies of three male military cohorts reveal multiple CpG sites associated with post-traumatic stress disorder

BACKGROUND

Epigenetic mechanisms have been suggested to play a role in the development of post-traumatic stress disorder (PTSD). Here, blood-derived DNA methylation data (HumanMethylation450 BeadChip) collected prior to and following combat exposure in three cohorts of male military members were analyzed to assess whether DNA methylation profiles are associated with the development of PTSD. A total of 123 PTSD cases and 143 trauma-exposed controls were included in the analyses. The Psychiatric Genomics Consortium (PGC) PTSD EWAS QC pipeline was used on all cohorts, and results were combined using a sample size weighted meta-analysis in a two-stage design. In stage one, we jointly analyzed data of two new cohorts (N = 126 and 78) for gene discovery, and sought to replicate significant findings in a third, previously published cohort (N = 62) to assess the robustness of our results. In stage 2, we aimed at maximizing power for gene discovery by combining all three cohorts in a meta-analysis.

RESULTS

Stage 1 analyses identified four CpG sites in which, conditional on pre-deployment DNA methylation, post-deployment DNA methylation was significantly associated with PTSD status after epigenome-wide adjustment for multiple comparisons. The most significant (intergenic) CpG cg05656210 (p = 1.0 × 10-08) was located on 5q31 and significantly replicated in the third cohort. In addition, 19 differentially methylated regions (DMRs) were identified, but failed replication. Stage 2 analyses identified three epigenome-wide significant CpGs, the intergenic CpG cg05656210 and two additional CpGs located in MAD1L1 (cg12169700) and HEXDC (cg20756026). Interestingly, cg12169700 had an underlying single nucleotide polymorphism (SNP) which was located within the same LD block as a recently identified PTSD-associated SNP in MAD1L1. Stage 2 analyses further identified 12 significant differential methylated regions (DMRs), 1 of which was located in MAD1L1 and 4 were situated in the human leukocyte antigen (HLA) region.

CONCLUSIONS

This study suggests that the development of combat-related PTSD is associated with distinct methylation patterns in several genomic positions and regions. Our most prominent findings suggest the involvement of the immune system through the HLA region and HEXDC, and MAD1L1 which was previously associated with PTSD.

Social phobia in immune-mediated inflammatory diseases

OBJECTIVE

Immune-mediated inflammatory diseases (IMID) such as multiple sclerosis (MS), inflammatory bowel disease (IBD) and rheumatoid arthritis (RA) are associated with a high prevalence of psychiatric comorbidity but little is known about the prevalence of social phobia in IMID, or the factors associated with social phobia. We aimed to determine the prevalence of social phobia in MS, IBD and RA, and the factors associated with social phobia in these IMID.

METHODS

We obtained data from the enrollment visit of a cohort study in IMID of whom 654 participants were eligible for this analysis (MS: 254, IBD: 247, RA: 153). Each participant underwent a semi-structured psychiatric interview which identified depression and anxiety disorders including social phobia (lifetime and current), an assessment of disease activity, and reported sociodemographic information.

RESULTS

Overall, 12.8% of participants had a lifetime diagnosis of social phobia (MS: 10.2%, IBD: 13.0%, RA: 17.0%). Social phobia was associated with younger age (OR 0.98; 0.97-1.00), having a high school education or less (OR 1.78; 1.08-2.91), comorbid major depressive disorder (OR 2.79; 1.63-4.78) and comorbid generalized anxiety disorder (OR 2.56; 1.30-5.05). Persons with RA had increased odds of having social phobia as compared to persons with MS (OR 2.26; 1.14-4.48) but not IBD.

CONCLUSION

Persons with IMIDs have a relatively high lifetime prevalence of social phobia, exceeding that reported for the Canadian general population. Strategies aimed at early detection, and effective clinical management of social phobia in IMID are warranted.

Shared genetics of asthma and mental health disorders: a large-scale genome-wide cross-trait analysis

Epidemiological studies demonstrate an association between asthma and mental health disorders, although little is known about the shared genetics and causality of this association. Thus, we aimed to investigate shared genetics and the causal link between asthma and mental health disorders.We conducted a large-scale genome-wide cross-trait association study to investigate genetic overlap between asthma from the UK Biobank and eight mental health disorders from the Psychiatric Genomics Consortium: attention deficit hyperactivity disorder (ADHD), anxiety disorder (ANX), autism spectrum disorder, bipolar disorder, eating disorder, major depressive disorder (MDD), post-traumatic stress disorder and schizophrenia (sample size 9537-394 283).In the single-trait genome-wide association analysis, we replicated 130 previously reported loci and discovered 31 novel independent loci that are associated with asthma. We identified that ADHD, ANX and MDD have a strong genetic correlation with asthma at the genome-wide level. Cross-trait meta-analysis identified seven loci jointly associated with asthma and ADHD, one locus with asthma and ANX, and 10 loci with asthma and MDD. Functional analysis revealed that the identified variants regulated gene expression in major tissues belonging to the exocrine/endocrine, digestive, respiratory and haemic/immune systems. Mendelian randomisation analyses suggested that ADHD and MDD (including 6.7% sample overlap with asthma) might increase the risk of asthma.This large-scale genome-wide cross-trait analysis identified shared genetics and potential causal links between asthma and three mental health disorders (ADHD, ANX and MDD). Such shared genetics implicate potential new biological functions that are in common among them.

Nod-like receptors are critical for gut-brain axis signalling in mice

KEY POINTS

•Nucleotide binding oligomerization domain (Nod)-like receptors regulate cognition, anxiety and hypothalamic-pituitary-adrenal axis activation. •Nod-like receptors regulate central and peripheral serotonergic biology. •Nod-like receptors are important for maintenance of gastrointestinal physiology. •Intestinal epithelial cell expression of Nod1 receptors regulate behaviour.

ABSTRACT

Gut-brain axis signalling is critical for maintaining health and homeostasis. Stressful life events can impact gut-brain signalling, leading to altered mood, cognition and intestinal dysfunction. In the present study, we identified nucleotide binding oligomerization domain (Nod)-like receptors (NLR), Nod1 and Nod2, as novel regulators for gut-brain signalling. NLR are innate immune pattern recognition receptors expressed in the gut and brain, and are important in the regulation of gastrointestinal physiology. We found that mice deficient in both Nod1 and Nod2 (NodDKO) demonstrate signs of stress-induced anxiety, cognitive impairment and depression in the context of a hyperactive hypothalamic-pituitary-adrenal axis. These deficits were coupled with impairments in the serotonergic pathway in the brain, decreased hippocampal cell proliferation and immature neurons, as well as reduced neural activation. In addition, NodDKO mice had increased gastrointestinal permeability and altered serotonin signalling in the gut following exposure to acute stress. Administration of the selective serotonin reuptake inhibitor, fluoxetine, abrogated behavioural impairments and restored serotonin signalling. We also identified that intestinal epithelial cell-specific deletion of Nod1 (VilCre⁺ Nod1^f/f ), but not Nod2, increased susceptibility to stress-induced anxiety-like behaviour and cognitive impairment following exposure to stress. Together, these data suggest that intestinal epithelial NLR are novel modulators of gut-brain communication and may serve as potential novel therapeutic targets for the treatment of gut-brain disorders.

Anorexia Nervosa and the Immune System-A Narrative Review

The pathogenesis of an increasing number of chronic diseases is being attributed to effects of the immune system. However, its role in the development and maintenance of anorexia nervosa is seemingly under-appreciated. Yet, in examining the available research on the immune system and genetic studies in anorexia nervosa, one becomes increasingly suspicious of the immune system’s potential role in the pathophysiology of anorexia nervosa. Specifically, research is suggestive of increased levels of various pro-inflammatory cytokines as well as the spontaneous production of tumor necrosis factor in anorexia nervosa; genetic studies further support a dysregulated immune system in this disorder. Potential contributors to this dysregulated immune system are discussed including increased oxidative stress, chronic physiological/psychological stress, changes in the intestinal microbiota, and an abnormal bone marrow microenvironment, all of which are present in anorexia nervosa.

Cross-disorder analysis of schizophrenia and 19 immune-mediated diseases identifies shared genetic risk

Many immune diseases occur at different rates among people with schizophrenia compared to the general population. Here, we evaluated whether this phenomenon might be explained by shared genetic risk factors. We used data from large genome-wide association studies to compare the genetic architecture of schizophrenia to 19 immune diseases. First, we evaluated the association with schizophrenia of 581 variants previously reported to be associated with immune diseases at genome-wide significance. We identified five variants with potentially pleiotropic effects. While colocalization analyses were inconclusive, functional characterization of these variants provided the strongest evidence for a model in which genetic variation at rs1734907 modulates risk of schizophrenia and Crohn's disease via altered methylation and expression of EPHB4-a gene whose protein product guides the migration of neuronal axons in the brain and the migration of lymphocytes towards infected cells in the immune system. Next, we investigated genome-wide sharing of common variants between schizophrenia and immune diseases using cross-trait LD score regression. Of the 11 immune diseases with available genome-wide summary statistics, we observed genetic correlation between six immune diseases and schizophrenia: inflammatory bowel disease (rg = 0.12 ± 0.03, P = 2.49 × 10-4), Crohn's disease (rg = 0.097 ± 0.06, P = 3.27 × 10-3), ulcerative colitis (rg = 0.11 ± 0.04, P = 4.05 × 10-3), primary biliary cirrhosis (rg = 0.13 ± 0.05, P = 3.98 × 10-3), psoriasis (rg = 0.18 ± 0.07, P = 7.78 × 10-3) and systemic lupus erythematosus (rg = 0.13 ± 0.05, P = 3.76 × 10-3). With the exception of ulcerative colitis, the degree and direction of these genetic correlations were consistent with the expected phenotypic correlation based on epidemiological data. Our findings suggest shared genetic risk factors contribute to the epidemiological association of certain immune diseases and schizophrenia.

Bivariate logistic Bayesian LASSO for detecting rare haplotype association with two correlated phenotypes

In genetic association studies, joint modeling of related traits/phenotypes can utilize the correlation between them and thereby provide more power and uncover additional information about genetic etiology. Moreover, detecting rare genetic variants are of current scientific interest as a key to missing heritability. Logistic Bayesian LASSO (LBL) has been proposed recently to detect rare haplotype variants using case-control data, that is, a single binary phenotype. As there is currently no haplotype association method that can handle multiple binary phenotypes, we extend LBL to fill this gap. We develop a bivariate model by using a latent variable to induce correlation between the two outcomes. We carry out extensive simulations to investigate the bivariate LBL and compare with the univariate LBL. The bivariate LBL performs better or similar to the univariate LBL in most settings. It has the highest gain in power when a haplotype is associated with both traits and it affects at least one trait in a direction opposite to the direction of the correlation between the traits. We analyze two data sets-Genetic Analysis Workshop 19 sequence data on systolic and diastolic blood pressures and a genome-wide association data set on lung cancer and smoking and detect several associated rare haplotypes.

Rising incidence of psychiatric disorders before diagnosis of immune-mediated inflammatory disease

AIMS

After the diagnosis of immune-mediated inflammatory diseases (IMID) such as inflammatory bowel disease (IBD), multiple sclerosis (MS) and rheumatoid arthritis (RA), the incidence of psychiatric comorbidity is increased relative to the general population. We aimed to determine whether the incidence of psychiatric disorders is increased in the 5 years before the diagnosis of IMID as compared with the general population.

METHODS

Using population-based administrative health data from the Canadian province of Manitoba, we identified all persons with incident IBD, MS and RA between 1989 and 2012, and cohorts from the general population matched 5 : 1 on year of birth, sex and region to each disease cohort. We identified members of these groups with at least 5 years of residency before and after the IMID diagnosis date. We applied validated algorithms for depression, anxiety disorders, bipolar disorder, schizophrenia, and any psychiatric disorder to determine the annual incidence of these conditions in the 5-year periods before and after the diagnosis year.

RESULTS

We identified 12 141 incident cases of IMID (3766 IBD, 2190 MS, 6350 RA) and 65 424 matched individuals. As early as 5 years before diagnosis, the incidence of depression [incidence rate ratio (IRR) 1.54; 95% CI 1.30-1.84) and anxiety disorders (IRR 1.30; 95% CI 1.12-1.51) were elevated in the IMID cohort as compared with the matched cohort. Similar results were obtained for each of the IBD, MS and RA cohorts. The incidence of bipolar disorder was elevated beginning 3 years before IMID diagnosis (IRR 1.63; 95% CI 1.10-2.40).

CONCLUSION

The incidence of psychiatric comorbidity is elevated in the IMID population as compared with a matched population as early as 5 years before diagnosis. Future studies should elucidate whether this reflects shared risk factors for psychiatric disorders and IMID, a shared final common inflammatory pathway or other aetiology.

Genetic variants differentially associated with rheumatoid arthritis and systemic lupus erythematosus reveal the disease-specific biology

Two rheumatic autoimmune diseases, rheumatoid arthritis (RA) and systemic lupus erythematosus (SLE), have distinct clinical features despite their genetic similarities. We hypothesized that disease-specific variants exclusively associated with only one disease could contribute to disease-specific phenotypes. We calculated the strength of disease specificity for each variant in each disease against the other disease using summary association statistics reported in the largest genome-wide association studies of RA and SLE. Most of highly disease-specific associations were explained by non-coding variants that were significantly enriched within regulatory regions (enhancers or H3K4me3 histone modification marks) in specific cell or organ types. (e.g., In RA, regulatory T primary cells, CD4+ memory T primary cells, thymus and lung; In SLE, CD19+ B primary cells, mobilized CD34+ primary cells, regulatory T primary cells and monocytes). Consistently, genes in the disease-specific loci were significantly involved in T cell- and B cell-related gene sets in RA and SLE. In summary, this study identified disease-specific variants between RA and SLE, and provided statistical evidence for disease-specific cell types, organ and gene sets that may drive the disease-specific phenotypes.

Increased Burden of Psychiatric Disorders in Inflammatory Bowel Disease

BACKGROUND

Psychiatric comorbidity in inflammatory bowel disease (IBD) is well known; however, data from a truly representative sample are sparse. We aimed to estimate the incidence and prevalence of psychiatric disorders in an IBD cohort compared with a matched cohort without IBD.

METHODS

Using population-based administrative health data from Manitoba, Canada, we identified all persons with incident IBD from 1989 to 2012 and a general population matched cohort (5:1). We applied validated algorithms for IBD, depression, anxiety disorders, bipolar disorder, and schizophrenia to determine the annual incidence of these conditions post-IBD diagnosis and their lifetime and current prevalence.

RESULTS

There were 6119 incident cases of IBD and 30,573 matched individuals. After adjustment for age, sex, socioeconomic status, region of residence, and year, there was a higher incidence in the IBD cohort compared with controls for depression (incidence rate ratio [IRR], 1.58; 95% confidence interval [CI], 1.41-1.76), anxiety disorder (IRR, 1.39; 95% CI, 1.26-1.53), bipolar disorder (IRR, 1.82; 95% CI, 1.44-2.30), and schizophrenia (IRR, 1.64; 95% CI, 0.95-2.84). Incidence rate ratios were similar for Crohn's disease and ulcerative colitis between males and females and were stable over time. However, within the IBD cohort, the incidence rates of depression, anxiety, and bipolar disorders were higher among females, those aged 18-24 years vs those older than 44 years, urbanites, and those of lower socioeconomic status. The lifetime and current prevalence rates of psychiatric disorders were also higher in the IBD than the matched cohort.

CONCLUSIONS

The incidence and prevalence of psychiatric disorders are elevated in the IBD population.

SJ. Genetic correlations among psychiatric and immune-related phenotypes based on genome-wide association data

Individuals with psychiatric disorders have elevated rates of autoimmune comorbidity and altered immune signaling. It is unclear whether these altered immunological states have a shared genetic basis with those psychiatric disorders. The present study sought to use existing summary-level data from previous genome-wide association studies to determine if commonly varying single nucleotide polymorphisms are shared between psychiatric and immune-related phenotypes. We estimated heritability and examined pair-wise genetic correlations using the linkage disequilibrium score regression (LDSC) and heritability estimation from summary statistics methods. Using LDSC, we observed significant genetic correlations between immune-related disorders and several psychiatric disorders, including anorexia nervosa, attention deficit-hyperactivity disorder, bipolar disorder, major depression, obsessive compulsive disorder, schizophrenia, smoking behavior, and Tourette syndrome. Loci significantly mediating genetic correlations were identified for schizophrenia when analytically paired with Crohn's disease, primary biliary cirrhosis, systemic lupus erythematosus, and ulcerative colitis. We report significantly correlated loci and highlight those containing genome-wide associations and candidate genes for respective disorders. We also used the LDSC method to characterize genetic correlations among the immune-related phenotypes. We discuss our findings in the context of relevant genetic and epidemiological literature, as well as the limitations and caveats of the study.

The Emerging Immunogenetic Architecture of Schizophrenia

Schizophrenia is a severe psychiatric disorder of complex etiology. Immune processes have long been proposed to contribute to the development of schizophrenia, and accumulating evidence supports immune involvement in at least a subset of cases. In recent years, large-scale genetic studies have provided new insights into the role of the immune system in this disease. Here, we provide an overview of the immunogenetic architecture of schizophrenia based on findings from genome-wide association studies (GWAS). First, we review individual immune loci identified in secondary analyses of GWAS, which implicate over 30 genes expressed in both immune and brain cells. The function of the proteins encoded by these immune candidates highlight the role of the complement system, along with regulation of apoptosis in both immune and neuronal cells. Next, we review hypothesis-free pathway analyses which have so far been inconclusive with respect to identifying immune pathways involved in schizophrenia. Finally, we explore the genetic overlap between schizophrenia and immune-mediated diseases. Although there have been some inconsistencies across studies, genome-wide pleiotropy has been reported between schizophrenia and Crohn's disease, multiple sclerosis, rheumatoid arthritis, systemic lupus erythematosus, type 1 diabetes, and ulcerative colitis. Overall, there are multiple lines of evidence supporting the role of immune genes in schizophrenia. Current evidence suggests that specific immune pathways are involved-likely those with dual functions in the central nervous system. Future studies focused on further elucidating the relevant pathways hold the potential to identify novel biomarkers and therapeutic targets for schizophrenia.

LLR: a latent low-rank approach to colocalizing genetic risk variants in multiple GWAS

Motivation

Genome-wide association studies (GWAS), which genotype millions of single nucleotide polymorphisms (SNPs) in thousands of individuals, are widely used to identify the risk SNPs underlying complex human phenotypes (quantitative traits or diseases). Most conventional statistical methods in GWAS only investigate one phenotype at a time. However, an increasing number of reports suggest the ubiquity of pleiotropy, i.e. many complex phenotypes sharing common genetic bases. This motivated us to leverage pleiotropy to develop new statistical approaches to joint analysis of multiple GWAS.

Results

In this study, we propose a latent low-rank (LLR) approach to colocalizing genetic risk variants using summary statistics. In the presence of pleiotropy, there exist risk loci that affect multiple phenotypes. To leverage pleiotropy, we introduce a low-rank structure to modulate the probabilities of the latent association statuses between loci and phenotypes. Regarding the computational efficiency of LLR, a novel expectation-maximization-path (EM-path) algorithm has been developed to greatly reduce the computational cost and facilitate model selection and inference. We demonstrate the advantages of LLR over competing approaches through simulation studies and joint analysis of 18 GWAS datasets.

Availability and implementation

The LLR software is available on https://sites.google.com/site/liujin810822.

Contact

macyang@ust.hk.edu.

Supplementary information

Supplementary data are available at Bioinformatics online.

8q22.1 Microduplication Syndrome: Why the Brain Should Be Spared? A Literature Review and a Case Report

Microduplication of chromosome 8q22.1 is mainly associated to Leri's pleonosteosis syndrome phenotype, an extremely rare autosomal dominant disease encompassing the GDF6 and SDC2 genes. To date, most of the authors focus their attention only on skeletal symptoms of the disease, and they do not systematically research or describe the co-occurrence of psychiatric illnesses or mental disorders with these muscular-skeletal diseases. In this report, we provide a description of an 8-year-old girl, with a positive family history for both skeletal malformations and bipolar disorders (BD). We suggest a possible association between Leri's pleonosteosis features and psychiatric symptoms. Furthermore, our report could be added to the large amount of reports that describe the correlation between genetic regions and disease risk for both psychiatric and rheumatological disorders.

Increased Burden of Psychiatric Disorders in Rheumatoid Arthritis

OBJECTIVE

We estimated the incidence and prevalence of depression, anxiety disorder, bipolar disorder, and schizophrenia in a population-based cohort with rheumatoid arthritis (RA) as compared to an age-, sex-, and geographically matched cohort without RA.

METHODS

Using population-based administrative health data from Manitoba, Canada, we identified persons with incident RA between 1989 and 2012, and a cohort from the general population matched 5:1 on year of birth, sex, and region of residence. We applied validated algorithms for depression, anxiety disorder, bipolar disorder, and schizophrenia to determine the annual incidence of these conditions after the diagnosis of RA, and their lifetime and annual period prevalence. We compared findings between cohorts using negative binomial regression models.

RESULTS

We identified 10,206 incident cases of RA and 50,960 matched individuals. After adjustment for age, sex, socioeconomic status, region of residence, number of physician visits, and year, the incidence of depression was higher in the RA cohort over the study period (incidence rate ratio [IRR] 1.46 [95% confidence interval (95% CI) 1.35-1.58]), as was the incidence of anxiety disorder (IRR 1.24 [95% CI 1.15-1.34]) and bipolar disorder (IRR 1.21 [95% CI 1.00-1.47]). The incidence of schizophrenia did not differ between groups (IRR 0.96 [95% CI 0.61-1.50]). Incidence rates of psychiatric disorders declined minimally over time. The lifetime and annual period prevalence of depression and anxiety disorder were also higher in the RA than in the matched cohort over the study period.

CONCLUSION

The incidence and prevalence of depression, anxiety disorder, and bipolar disorder are elevated in the RA population as compared to a matched population.

LPG: A four-group probabilistic approach to leveraging pleiotropy in genome-wide association studies

Background

To date, genome-wide association studies (GWAS) have successfully identified tens of thousands of genetic variants among a variety of traits/diseases, shedding light on the genetic architecture of complex disease. The polygenicity of complex diseases is a widely accepted phenomenon through which a vast number of risk variants, each with a modest individual effect, collectively contribute to the heritability of complex diseases. This imposes a major challenge on fully characterizing the genetic bases of complex diseases. An immediate implication of polygenicity is that a much larger sample size is required to detect individual risk variants with weak/moderate effects. Meanwhile, accumulating evidence suggests that different complex diseases can share genetic risk variants, a phenomenon known as pleiotropy.

Results

In this study, we propose a statistical framework for Leveraging Pleiotropic effects in large-scale GWAS data (LPG). LPG utilizes a variational Bayesian expectation-maximization (VBEM) algorithm, making it computationally efficient and scalable for genome-wide-scale analysis. To demonstrate the advantages of LPG over existing methods that do not leverage pleiotropy, we conducted extensive simulation studies and applied LPG to analyze two pairs of disorders (Crohn’s disease and Type 1 diabetes, as well as rheumatoid arthritis and Type 1 diabetes). The results indicate that by levelaging pleiotropy, LPG can improve the power of prioritization of risk variants and the accuracy of risk prediction.

Conclusions

Our methodology provides a novel and efficient tool to detect pleiotropy among GWAS data for multiple traits/diseases collected from different studies. The software is available at https://github.com/Shufeyangyi2015310117/LPG.

Electronic supplementary material

The online version of this article (10.1186/s12864-018-4851-2) contains supplementary material, which is available to authorized users.

Associations between attention-deficit/hyperactivity disorder and autoimmune diseases are modified by sex: a population-based cross-sectional study

Several studies have demonstrated associations between neuropsychiatric disorders, such as attention-deficit/hyperactivity disorder (ADHD), and the immune system, including autoimmune diseases. Since ADHD and many autoimmune diseases show sex-specific properties, such associations may also differ by sex. Using Norwegian national registries, we performed a cross-sectional study based on a cohort of 2,500,118 individuals to investigate whether ADHD is associated with common autoimmune diseases. Associations between ADHD and autoimmune diseases in females and males were investigated with logistic regression and effect modification by sex was evaluated. Several subanalyses were performed. The strongest association was found between ADHD and psoriasis in females, adjusted odds ratio (adjOR) = 1.57 (95% confidence interval: 1.46-1.68) and males, adjOR = 1.31 (1.23-1.40); p value for interaction < 0.0001. Furthermore, among females, ADHD was associated with Crohn's disease, adjOR = 1.44 (1.16-1.79) and ulcerative colitis, adjOR = 1.28 (1.06-1.54). In contrast, males with ADHD had lower odds of Crohn's disease, adjOR = 0.71 (0.54-0.92), in addition to a trend for lower odds of ulcerative colitis, adjOR = 0.86 (0.71-1.03); p values for interaction < 0.0001 and 0.0023, respectively. In a group of females where information on smoking and body mass index was available, adjustment for these potential mediators did not substantially alter the associations. Our findings support previously reported associations between ADHD and diseases of the immune system. The associations differ by sex, suggesting that sex-specific immune-mediated neurodevelopmental processes may be involved in the etiology of ADHD.

Effect of Human Genetic Variability on Gene Expression in Dorsal Root Ganglia and Association with Pain Phenotypes

Dorsal root ganglia (DRG) relay sensory information to the brain, giving rise to the perception of pain, disorders of which are prevalent and burdensome. Here, we mapped expression quantitative trait loci (eQTLs) in a collection of human DRGs. DRG eQTLs were enriched within untranslated regions of coding genes of low abundance, with some overlapping with other brain regions and blood cell cis-eQTLs. We confirm functionality of identified eQTLs through their significant enrichment within open chromatin and highly deleterious SNPs, particularly at the exon level, suggesting substantial contribution of eQTLs to alternative splicing regulation. We illustrate pain-related genetic association results explained by DRG eQTLs, with the strongest evidence for contribution of the human leukocyte antigen (HLA) locus, confirmed using a mouse inflammatory pain model. Finally, we show that DRG eQTLs are found among hits in numerous genome-wide association studies, suggesting that this dataset will help address pain components of non-pain disorders.

Physical comorbidities increase the risk of psychiatric comorbidity in immune-mediated inflammatory disease

OBJECTIVE

We tested the association between physical comorbidity and incident depression, anxiety disorder and bipolar disorder in three immune-mediated inflammatory diseases (IMID): inflammatory bowel disease (IBD), multiple sclerosis (MS) and rheumatoid arthritis (RA) versus age-, sex- and geographically-matched controls.

METHODS

Using population-based administrative data we identified 6119 persons with IBD, 3514 persons with MS, 10,206 persons with RA and 97,727 matched controls. We identified incident cases of depression, anxiety disorder and bipolar disorder in these populations. We evaluated the association of physical comorbidities with incident psychiatric comorbidity using Cox regression, adjusting for sociodemographic factors and index year.

RESULTS

The risk of incident depression, anxiety disorders and bipolar disorder was higher in each IMID cohort versus their matched cohorts. The risk of incident psychiatric comorbidity increased with an increasing number of physical comorbidities for each psychiatric comorbidity evaluated, across all IMID. Adjustment for physical comorbidity did not attenuate the increased risk of psychiatric comorbidity in the IMID cohorts versus their matched cohorts.

CONCLUSION

The increased incidence of psychiatric comorbidity in IMID versus matched general population cohorts is not accounted for by their increased prevalence of physical comorbidities. However, within IMID cohorts, physical comorbidity increases the risk of psychiatric comorbidity.

Longitudinal association between mental disorders in childhood and subsequent depression - A nationwide prospective cohort study

BACKGROUND

Depression ranges among the most impairing mental disorders worldwide, and early detection is a global health priority. Little is known about the association between non-affective mental disorders in childhood/adolescence and later depression.

METHODS

Nationwide register-based prospective cohort study, estimating cumulative incidences and incidence rate ratios (IRR) for later depression in individuals with and without non-affective mental disorders in early life.

RESULTS

475,213 females and 484,813 males born 1990-2007 were followed for a mean of 9.14 years (contributing a total of 8778,331 person-years of observation). In the cohort, 7963 (5451 females) were diagnosed with depression. Depression was more common in individuals with prior non-affective mental disorders in adolescence (15.98% in females and 7.02% in males) and in childhood (4.98% in females and 1.6% in males), than in the background population (3.94% and 1.3% in females; 1.37% and 0.47% in males). Eating and anxiety disorders in childhood/adolescence carried the highest absolute risk of depression. The relative risk of depression was particularly high the first year after the first non-affective disorder (IRR = 15.5; 14.07-17.10), but remained highly elevated more than five years after the first non-affective diagnosis (IRR = 2.05; 1.84-2.28), when compared to young people without such disorders.

LIMITATIONS

This study only included diagnoses given at hospital departments, representing the more severe mental disorders.

CONCLUSIONS

Children and adolescents with non-affective mental disorders were at substantially increased absolute and relative risk of developing depression in young adulthood, especially females diagnosed with anxiety- or eating disorders in adolescence. These findings may help identify groups of children and adolescents at very high risk of developing depression.

Searching for ancient balanced polymorphisms shared between Neanderthals and Modern Humans

Hominin evolution is characterized by adaptive solutions often rooted in behavioral and cognitive changes. If balancing selection had an important and long-lasting impact on the evolution of these traits, it can be hypothesized that genes associated with them should carry an excess of shared polymorphisms (trans- SNPs) across recent Homo species. In this study, we investigate the role of balancing selection in human evolution using available exomes from modern (Homo sapiens) and archaic humans (H. neanderthalensis and Denisovan) for an excess of trans-SNP in two gene sets: one associated with the immune system (IMMS) and another one with behavioral system (BEHS). We identified a significant excess of trans-SNPs in IMMS (N=547), of which six of these located within genes previously associated with schizophrenia. No excess of trans-SNPs was found in BEHS, but five genes in this system harbor potential signals for balancing selection and are associated with psychiatric or neurodevelopmental disorders. Our approach evidenced recent Homo trans-SNPs that have been previously implicated in psychiatric diseases such as schizophrenia, suggesting that a genetic repertoire common to the immune and behavioral systems could have been maintained by balancing selection starting before the split between archaic and modern humans.

Testing Genetic Pleiotropy with GWAS Summary Statistics for Marginal and Conditional Analyses

There is growing interest in testing genetic pleiotropy, which is when a single genetic variant influences multiple traits. Several methods have been proposed; however, these methods have some limitations. First, all the proposed methods are based on the use of individual-level genotype and phenotype data; in contrast, for logistical, and other, reasons, summary statistics of univariate SNP-trait associations are typically only available based on meta- or mega-analyzed large genome-wide association study (GWAS) data. Second, existing tests are based on marginal pleiotropy, which cannot distinguish between direct and indirect associations of a single genetic variant with multiple traits due to correlations among the traits. Hence, it is useful to consider conditional analysis, in which a subset of traits is adjusted for another subset of traits. For example, in spite of substantial lowering of low-density lipoprotein cholesterol (LDL) with statin therapy, some patients still maintain high residual cardiovascular risk, and, for these patients, it might be helpful to reduce their triglyceride (TG) level. For this purpose, in order to identify new therapeutic targets, it would be useful to identify genetic variants with pleiotropic effects on LDL and TG after adjusting the latter for LDL; otherwise, a pleiotropic effect of a genetic variant detected by a marginal model could simply be due to its association with LDL only, given the well-known correlation between the two types of lipids. Here, we develop a new pleiotropy testing procedure based only on GWAS summary statistics that can be applied for both marginal analysis and conditional analysis. Although the main technical development is based on published union-intersection testing methods, care is needed in specifying conditional models to avoid invalid statistical estimation and inference. In addition to the previously used likelihood ratio test, we also propose using generalized estimating equations under the working independence model for robust inference. We provide numerical examples based on both simulated and real data, including two large lipid GWAS summary association datasets based on ∼100,000 and ∼189,000 samples, respectively, to demonstrate the difference between marginal and conditional analyses, as well as the effectiveness of our new approach.

Increased incidence of psychiatric disorders in immune-mediated inflammatory disease

OBJECTIVE

Although psychiatric comorbidity is known to be more prevalent in immune-mediated inflammatory diseases (IMID) than in the general population, the incidence of psychiatric comorbidity in IMID is less understood, yet incidence is more relevant for understanding etiology.

METHODS

Using population-based administrative (health) data, we conducted a retrospective cohort study over the period 1989-2012 in Manitoba, Canada. We identified 19,572 incident cases of IMID including 6119 persons with inflammatory bowel disease (IBD), 3514 persons with multiple sclerosis (MS), 10,206 persons with rheumatoid arthritis (RA), and 97,727 age-, sex- and geographically-matched controls. After applying validated case definitions, we estimated the incidence of depression, anxiety disorder, bipolar disorder and schizophrenia in each of the study cohorts. Using negative binomial regression models, we tested whether the incidence rate of psychiatric comorbidity was elevated in the individual and combined IMID cohorts versus the matched cohorts, adjusting for sex, age, region of residence, socioeconomic status and year.

RESULTS

The relative incidence of depression (incidence rate ratio [IRR] 1.71; 95%CI: 1.64-1.79), anxiety (IRR 1.34; 95%CI: 1.29-1.40), bipolar disorder (IRR 1.68; 95%CI: 1.52-1.85) and schizophrenia (IRR 1.32; 95%CI: 1.03-1.69) were elevated in the IMID cohort. Depression and anxiety affected the MS population more often than the IBD and RA populations.

CONCLUSIONS

Individuals with IMID, including IBD, MS and RA are at increased risk of psychiatric comorbidity. This increased risk appears non-specific as it is seen for all three IMIDs and for all psychiatric disorders studied, implying a common underlying biology for psychiatric comorbidity in those with IMID.

Significant Locus and Metabolic Genetic Correlations Revealed in Genome-Wide Association Study of Anorexia Nervosa

OBJECTIVE

The authors conducted a genome-wide association study of anorexia nervosa and calculated genetic correlations with a series of psychiatric, educational, and metabolic phenotypes.

METHOD

Following uniform quality control and imputation procedures using the 1000 Genomes Project (phase 3) in 12 case-control cohorts comprising 3,495 anorexia nervosa cases and 10,982 controls, the authors performed standard association analysis followed by a meta-analysis across cohorts. Linkage disequilibrium score regression was used to calculate genome-wide common variant heritability (single-nucleotide polymorphism [SNP]-based heritability [h2SNP]), partitioned heritability, and genetic correlations (rg) between anorexia nervosa and 159 other phenotypes.

RESULTS

Results were obtained for 10,641,224 SNPs and insertion-deletion variants with minor allele frequencies >1% and imputation quality scores >0.6. The h2SNP of anorexia nervosa was 0.20 (SE=0.02), suggesting that a substantial fraction of the twin-based heritability arises from common genetic variation. The authors identified one genome-wide significant locus on chromosome 12 (rs4622308) in a region harboring a previously reported type 1 diabetes and autoimmune disorder locus. Significant positive genetic correlations were observed between anorexia nervosa and schizophrenia, neuroticism, educational attainment, and high-density lipoprotein cholesterol, and significant negative genetic correlations were observed between anorexia nervosa and body mass index, insulin, glucose, and lipid phenotypes.

CONCLUSIONS

Anorexia nervosa is a complex heritable phenotype for which this study has uncovered the first genome-wide significant locus. Anorexia nervosa also has large and significant genetic correlations with both psychiatric phenotypes and metabolic traits. The study results encourage a reconceptualization of this frequently lethal disorder as one with both psychiatric and metabolic etiology.

Immune dysregulation in offspring of a bipolar parent. Altered serum levels of immune growth factors at adolescent age

Immune dysregulation plays a role in the vulnerability for mood disorders. Immune growth factors, such as Stem Cell Factor (SCF), Insulin-like Growth Factor-Binding Protein-2 (IGF-BP2), Epidermal Growth Factor (EGF), IL-7 and sCD25 have repeatedly been reported altered in patients with mood disorders. The aim of this study was to investigate levels of these factors in serum of adolescent bipolar offspring, who have a heightened risk for mood disorder development and to also analyze the data combined with previously published data. Growth factors were assessed by CBA/ELISA in adolescent bipolar offspring (n=96, mean age=16years) and in age- and gender-matched healthy controls (n=50). EGF belonged to a mutually correlating cluster of mainly neurotrophic compounds including S100B and BDNF, which were in general decreased in serum. IL-7, SCF, IGF-BP2 and sCD25, belonged to a different mutually correlating cluster of immune growth factors, which were in general increased: IGF-BP2 significantly in serum of offspring without a mood disorder, IL-7 and SCF in serum of offspring who had experienced a mood episode. This pattern of de- and increases was not different between bipolar offspring that developed or did not develop a mood disorder over time, apart from the IGF-BP2 level, which was near significantly higher in offspring later developing a mood disorder. Correlations with the previously published immune-cellular abnormalities were not found. In conclusion non-affected adolescents at familial mood disorder development risk were characterized by a distinct pattern of a series of compounds operating in a network of hematopoiesis, neurogenesis and inflammation.

Genetic variation in the exome: Associations with alcohol and tobacco co-use

Shared genetic factors represent one underlying mechanism thought to contribute to high rates of alcohol and tobacco co-use and dependence. Common variants identified by molecular genetic studies tend to confer only small disease risk, and rare protein-coding variants are posited to contribute to disease risk, as well. However, given that genotyping technologies allowing for their inclusion in association studies have only recently become available, the magnitude of their contribution is poorly understood. The current study examined genetic variation in protein-coding regions (i.e., the exome) for associations with measures of lifetime alcohol and tobacco co-use. Participants from the UCSF Family Alcoholism Study (N = 1,862) were genotyped using an exome-focused genotyping array, and assessed for DSM-IV diagnoses of alcohol and tobacco dependence and quantitative consumption measures using a modified version of the Semi-Structured Assessment for the Genetics of Alcoholism. Analyses included single variant, gene-based, and pathway-based tests of association. One EMR3 variant and a pathway related to genes upregulated in mesenchymal stem cells during the late phase of adipogenesis met criteria for statistical significance. Suggestive associations were consistent with previous findings from studies of substance use and dependence, including variants in the CHRNA5-CHRNA3-CHRNB4 gene cluster with cigarettes smoked per day. Further, several variants and genes demonstrated suggestive association across phenotypes, suggesting that shared genetic factors may underlie risk for increased levels of alcohol and tobacco use, as well as psychopathology more broadly, providing insight into our understanding of the genetic architecture underlying these traits. (PsycINFO Database Record

graph-GPA: A graphical model for prioritizing GWAS results and investigating pleiotropic architecture

Genome-wide association studies (GWAS) have identified tens of thousands of genetic variants associated with hundreds of phenotypes and diseases, which have provided clinical and medical benefits to patients with novel biomarkers and therapeutic targets. However, identification of risk variants associated with complex diseases remains challenging as they are often affected by many genetic variants with small or moderate effects. There has been accumulating evidence suggesting that different complex traits share common risk basis, namely pleiotropy. Recently, several statistical methods have been developed to improve statistical power to identify risk variants for complex traits through a joint analysis of multiple GWAS datasets by leveraging pleiotropy. While these methods were shown to improve statistical power for association mapping compared to separate analyses, they are still limited in the number of phenotypes that can be integrated. In order to address this challenge, in this paper, we propose a novel statistical framework, graph-GPA, to integrate a large number of GWAS datasets for multiple phenotypes using a hidden Markov random field approach. Application of graph-GPA to a joint analysis of GWAS datasets for 12 phenotypes shows that graph-GPA improves statistical power to identify risk variants compared to statistical methods based on smaller number of GWAS datasets. In addition, graph-GPA also promotes better understanding of genetic mechanisms shared among phenotypes, which can potentially be useful for the development of improved diagnosis and therapeutics. The R implementation of graph-GPA is currently available at https://dongjunchung.github.io/GGPA/.

Recently, there has been accumulating evidence suggesting pleiotropy, i.e., genetic components shared across multiple phenotypes. Incorporation of pleiotropy in genetic analysis might improve statistical power to identify risk associated genetic variants. Several statistical approaches have been proposed to utilize pleiotropy for association mapping but they are currently still limited to a relatively small number of phenotypes, e.g., a pair of phenotypes. This restricts potential gain in statistical power in association mapping and investigation of pleiotropic structure among a large number of phenotypes. In order to address this challenge, in this paper, we propose graph-GPA, a novel statistical framework to integrate a large number of phenotypes using a hidden Markov random field architecture. Application of the proposed statistical method to GWAS datasets for 12 phenotypes showed that graph-GPA does not only provide a parsimonious representation of genetic relationship among these phenotypes, but also identify significantly larger number of novel genetic variants that are potentially functional. We believe that this novel approach might help investigation of common etiology and improvement of diagnosis and therapeutics.