Gene-based analyses reveal novel genetic overlap and allelic heterogeneity across five major psychiatric disorders

DNA methylation profiles of transgenerational rat hyperactivity primed by silver nanoparticles: Comparison with valproate model rats of autism

There is an increasing body of evidence suggesting that a single exposure to certain chemicals can have transgenerational effects, with the underlying mechanism believed to be epigenetic. However, it remains largely unknown whether psychiatric conditions like ADHD or autism, induced by environmental chemicals, can be inherited across generations. Pregnant rats were purchased from a commercial breeder. On the 7th day of gestation (E7), they were divided into two groups: one group was orally exposed to silver nanoparticles (AgNP; 4 mg/kg), while the control group received vehicle alone. The subsequent generation (F1) underwent spontaneous motor activity (SMA) measurements at 8-11 weeks of age. For breeding at 26 weeks of age, rats with higher SMA were selected from hyperactive litters, while untreated rats were randomly selected. This process was continued for four generations in both groups. The AgNP-primed rats at 4th generation displayed significantly higher SMA, 1.8 times greater than that of untreated rats. Intraperitoneal injection of valproic acid (150 mg/kg), an epigenetic modifier to 5-day-old rats causes adult hyperactivity (1.4-fold), suggesting that epigenetic modification contributes to rat hyperactivity. Global DNA methylation profiles in the mesencephalon were positively correlated in both groups of hyperactive rats. Furthermore, there were 7-8 common genes showing both hypermethylation and hypomethylation, which are involved in neuronal development, neuronal function, transcriptional activity, DNA binding activity, cell differentiation, ubiquitination processes, or histone modification, including Pax 6 and Mecp 2. Thus, it is most likely that rats retain hyperactivity through mesencephalic DNA methylation status across transgeneration.

Micronutrients and Major Depression: A Mendelian Randomisation Study

BACKGROUND

Various vitamins and minerals have been implicated in the aetiology of depression.

OBJECTIVE

To estimate the effects of micronutrient exposures on major depressive disorder (MDD) and recurrent depression (rMDD) using Mendelian randomisation (MR), a method using genetic data to estimate causal effects given certain assumptions.

METHODS

We undertook a comprehensive bidirectional MR study of multiple micronutrient exposures on MDD and rMDD. Summary statistics were obtained from the Psychiatric Genomics Consortium (PGC) genome-wide association studies (GWASs) of MDD (cases = 116,209; controls = 314,566) and rMDD (cases = 17,451; controls = 62,482).

RESULTS

None of the micronutrients with available genetic instruments were strongly associated with MDD or rMDD using traditional MR methods. However, using methods to increase analytical power by accounting for genetically correlated variants (e.g., cIVW) highlighted five micronutrients with possible causal effects. Point estimates for rMDD were the largest magnitude, with three micronutrients suggestive of a protective effect: serum iron (ORcIVW 0.90 per SD increase; 95% CI 0.85-0.95; p = 0.0003); erythrocyte copper (ORcIVW 0.97; 95% CI 0.95-0.99; p = 0.0004); and 25(OH) vitamin D (ORcIVW 0.81; 0.66-0.99; p = 0.04). Apparent adverse effects of increased selenium on the risk of MDD (ORcIVW 1.03; 95% CI 1.02-1.05; p = 0.0003) and rMDD (ORcIVW 1.08; 95% CI 1.00-1.08; p = 0.06), and serum magnesium on rMDD (ORcIVW 1.21; 1.01-1.44; p = 0.04); were less consistent between methods and may be driven by pleiotropy.

CONCLUSIONS

Our results suggest weak evidence for a protective effect of iron, copper and 25(OH)D on major depressive outcomes, with mixed evidence for selenium and magnesium. There was no evidence to support a causal effect of any other micronutrients on MDD or rMDD, although genetic instruments were lacking, with insufficient power to detect small but important effects. Future micronutrient supplementation trials should ensure ample statistical power given modest causal effect estimates and consider potential risks of supplementation, as some micronutrient effect estimates suggested potential harm in excess.

Codes between Poles: Linking Transcriptomic Insights into the Neurobiology of Bipolar Disorder

Bipolar disorder (BPD) is a serious psychiatric condition that is characterized by the frequent shifting of mood patterns, ranging from manic to depressive episodes. Although there are already treatment strategies that aim at regulating the manifestations of this disorder, its etiology remains unclear and continues to be a question of interest within the scientific community. The development of RNA sequencing techniques has provided newer and better approaches to studying disorders at the transcriptomic level. Hence, using RNA-seq data, we employed intramodular connectivity analysis and network pharmacology assessment of disease-associated variants to elucidate the biological pathways underlying the complex nature of BPD. This study was intended to characterize the expression profiles obtained from three regions in the brain, which are the nucleus accumbens (nAcc), the anterior cingulate cortex (AnCg), and the dorsolateral prefrontal cortex (DLPFC), provide insights into the specific roles of these regions in the onset of the disorder, and present potential targets for drug design and development. The nAcc was found to be highly associated with genes responsible for the deregulated transcription of neurotransmitters, while the DLPFC was greatly correlated with genes involved in the impairment of components crucial in neurotransmission. The AnCg did show association with some of the expressions, but the relationship was not as strong as the other two regions. Furthermore, disease-associated variants or single nucleotide polymorphisms (SNPs) were identified among the significant genes in BPD, which suggests the genetic interrelatedness of such a disorder and other mental illnesses. DRD2, GFRA2, and DCBLD1 were the genes with disease-associated variants expressed in the nAcc; ST8SIA2 and ADAMTS16 were the genes with disease-associated variants expressed in the AnCg; and FOXO3, ITGA9, CUBN, PLCB4, and RORB were the genes with disease-associated variants expressed in the DLPFC. Aside from unraveling the molecular and cellular mechanisms behind the expression of BPD, this investigation was envisioned to propose a new research pipeline in studying the transcriptome of psychiatric disorders to support and improve existing studies.

Accurate identification of genes associated with brain disorders by integrating heterogeneous genomic data into a Bayesian framework

BACKGROUND

Genome-wide association studies (GWAS) have revealed many brain disorder-associated SNPs residing in the noncoding genome, rendering it a challenge to decipher the underlying pathogenic mechanisms.

METHODS

Here, we present an unsupervised Bayesian framework to identify disease-associated genes by integrating risk SNPs with long-range chromatin interactions (iGOAT), including SNP-SNP interactions extracted from ∼500,000 patients and controls from the UK Biobank, and enhancer-promoter interactions derived from multiple brain cell types at different developmental stages.

FINDINGS

The application of iGOAT to three psychiatric disorders and three neurodegenerative/neurological diseases predicted sets of high-risk (HRGs) and low-risk (LRGs) genes for each disorder. The HRGs were enriched in drug targets, and exhibited higher expression during prenatal brain developmental stages than postnatal stages, indicating their potential to affect brain development at an early stage. The HRGs associated with Alzheimer's disease were found to share genetic architecture with schizophrenia, bipolar disorder and major depressive disorder according to gene co-expression module analysis and rare variants analysis. Comparisons of this method to the eQTL-based method, the TWAS-based method, and the gene-level GWAS method indicated that the genes identified by our method are more enriched in known brain disorder-related genes, and exhibited higher precision. Finally, the method predicted 205 risk genes not previously reported to be associated with any brain disorder, of which one top-risk gene, MLH1, was experimentally validated as being schizophrenia-associated.

INTERPRETATION

iGOAT can successfully leverage epigenomic data, phenotype-genotype associations, and protein-protein interactions to advance our understanding of brain disorders, thereby facilitating the development of new therapeutic approaches.

FUNDING

The work was funded by the National Key Research and Development Program of China (2024YFF1204902), the Natural Science Foundation of China (82371482), Guangzhou Science and Technology Research Plan (2023A03J0659) and Natural Science Foundation of Guangdong (2024A1515011363).

Identification of a Predictive Model for Schizophrenia Based on SNPs in a Chinese Population

Background

Schizophrenia is a devastating mental disease with high heritability. A growing number of susceptibility genes associated with schizophrenia, as well as their corresponding SNPs loci, have been revealed by genome-wide association studies. However, using SNPs as predictors of disease and diagnosis remains difficult. Here, we aimed to uncover susceptibility SNPs in a Chinese population and to construct a prediction model for schizophrenia.

Methods

A total of 210 participants, including 70 patients with schizophrenia, 70 patients with bipolar disorder, and 70 healthy controls, were enrolled in this study. We estimated 14 SNPs using published risk loci of schizophrenia, and used these SNPs to build a model for predicting schizophrenia via comparison of genotype frequencies and regression. We evaluated the efficacy of the diagnostic model in schizophrenia and control patients using ROC curves and then used the 70 patients with bipolar disorder to evaluate the model's differential diagnostic efficacy.

Results

5 SNPs were selected to construct the model: rs148415900, rs71428218, rs4666990, rs112222723 and rs1716180. Correlation analysis results suggested that, compared with the risk SNP of 0, the risk SNP of 3 was associated with an increased risk of schizophrenia (OR = 13.00, 95% CI: 2.35-71.84, p = 0.003). The ROC-AUC of this prediction model for schizophrenia was 0.719 (95% CI: 0.634-0.804), with the greatest sensitivity and specificity being 60% and 80%, respectively. The ROC-AUC of the model in distinguishing between schizophrenia and bipolar disorder was 0.591 (95% CI: 0.497-0.686), with the greatest sensitivity and specificity being 60% and 55.7%, respectively.

Conclusion

The SNP risk score prediction model had good performance in predicting schizophrenia. To the best of our knowledge, previous studies have not applied SNP-based models to differentiate between cases of schizophrenia and other mental illnesses. It could have several potential clinical applications, including shaping disease diagnosis, treatment, and outcomes.

Graph Self-Supervised Learning With Application to Brain Networks Analysis

The less training data and insufficient supervision limit the performance of the deep supervised models for brain disease diagnosis. It is significant to construct a learning framework that can capture more information in limited data and insufficient supervision. To address these issues, we focus on self-supervised learning and aim to generalize the self-supervised learning to the brain networks, which are non-Euclidean graph data. More specifically, we propose an ensemble masked graph self-supervised framework named BrainGSLs, which incorporates 1) a local topological-aware encoder that takes the partially visible nodes as input and learns these latent representations, 2) a node-edge bi-decoder that reconstructs the masked edges by the representations of both the masked and visible nodes, 3) a signal representation learning module for capturing temporal representations from BOLD signals and 4) a classifier used for the classification. We evaluate our model on three real medical clinical applications: diagnosis of Autism Spectrum Disorder (ASD), diagnosis of Bipolar Disorder (BD) and diagnosis of Major Depressive Disorder (MDD). The results suggest that the proposed self-supervised training has led to remarkable improvement and outperforms state-of-the-art methods. Moreover, our method is able to identify the biomarkers associated with the diseases, which is consistent with the previous studies. We also explore the correlation of these three diseases and find the strong association between ASD and BD. To the best of our knowledge, our work is the first attempt of applying the idea of self-supervised learning with masked autoencoder on the brain network analysis.

Cross-trait analyses identify shared genetics between migraine, headache, and glycemic traits, and a causal relationship with fasting proinsulin

The co-occurrence of migraine and glycemic traits has long been reported in observational epidemiological studies, but it has remained unknown how they are linked genetically. We used large-scale GWAS summary statistics on migraine, headache, and nine glycemic traits in European populations to perform cross-trait analyses to estimate genetic correlation, identify shared genomic regions, loci, genes, and pathways, and test for causal relationships. Out of the nine glycemic traits, significant genetic correlation was observed for fasting insulin (FI) and glycated haemoglobin (HbA1c) with both migraine and headache, while 2-h glucose was genetically correlated only with migraine. Among 1703 linkage disequilibrium (LD) independent regions of the genome, we found pleiotropic regions between migraine and FI, fasting glucose (FG), and HbA1c, and pleiotropic regions between headache and glucose, FI, HbA1c, and fasting proinsulin. Cross-trait GWAS meta-analysis with glycemic traits, identified six novel genome-wide significant lead SNPs with migraine, and six novel lead SNPs with headache (Pmeta < 5.0 × 10-8 and Psingle-trait < 1 × 10-4), all of which were LD-independent. Genes with a nominal gene-based association (Pgene ≤ 0.05) were significantly enriched (overlapping) across the migraine, headache, and glycemic traits. Mendelian randomisation analyses produced intriguing, but inconsistent, evidence for a causal relationship between migraine and headache with multiple glycemic traits; and consistent evidence suggesting increased fasting proinsulin levels may causally decrease the risk of headache. Our findings indicate that migraine, headache, and glycemic traits share a common genetic etiology and provide genetic insights into the molecular mechanisms contributing to their comorbid relationship.

Parents' depression and anxiety associated with hyperactivity-inattention and emotional symptoms in children during school closure due to COVID-19 in France

Several risk factors of children's mental health issues have been identified during the pandemic of COronaVIrus Disease first appeared in 2019 (COVID-19). This study aims to fill the knowledge gap regarding the association between parents' and children's mental health issues during the COVID-19 school closure in France. We conducted a cross-sectional analysis of data collected in the SAPRIS-ELFE study during the COVID-19 pandemic in France. Using multinomial logistic regressions, we estimated associations between parents' and children's mental health issues. Symptoms of anxiety were assessed by the General Anxiety Disorder-7 (GAD-7) and depression by the Patient Health Questionnaire-9 (PHQ-9) for the parents. Hyperactivity/inattention and emotional symptoms in children were assessed by the Strengths and Difficulties Questionnaire (SDQ). The sample included 3496 children aged 8 to 9 years, of whom 50.0% were girls. During the school closure, 7.1% of responding parents had moderate to severe levels of anxiety and 6.7% had moderate to severe levels of depression. A total of 11.8% of the children had an abnormal hyperactivity/inattention score and 6.6% had an abnormal emotional symptoms score. In multivariate regression models, parental moderate to severe level of anxiety and moderate to severe level of depression were associated with abnormal hyperactivity-inattention score (adjusted Odds Ratio (aOR) 3.31; 95% Confidence Interval (CI) 2.33-4.70 and aOR 4.65; 95% CI 3.27-6.59, respectively) and abnormal emotional symptoms score in children (aOR 3.58; 95% CI 2.33-5.49 and aOR 3.78; 95 CI 2.47-5.78 respectively). Children whose parents have symptoms of anxiety and/or depression have an increased likelihood of symptoms of hyperactivity/inattention and emotional symptoms during school closures in France due to COVID-19. Our findings suggest that public health initiatives should target parents and children to limit the impact of such crises on their mental health issues.

Third-generation genome sequencing implicates medium-sized structural variants in chronic schizophrenia

Background

Schizophrenia (SCZ) is a heterogeneous psychiatric disorder, with significant contribution from genetic factors particularly for chronic cases with negative symptoms and cognitive deficits. To date, Genome Wide Association Studies (GWAS) and exome sequencing have associated SCZ with a number of single nucleotide polymorphisms (SNPs) and copy number variants (CNVs), but there is still missing heritability. Medium-sized structural variants (SVs) are difficult to detect using SNP arrays or second generation sequencing, and may account for part of the missing heritability of SCZ.

Aims and objectives

To identify SVs associated with severe chronic SCZ across the whole genome.

Study design

10 multiplex families with probands suffering from chronic SCZ with negative symptoms and cognitive deficits were recruited, with all their affected members demonstrating uni-lineal inheritance. Control subjects comprised one affected member from the affected lineage, and unaffected members from each paternal and maternal lineage.

Methods

Third generation sequencing was applied to peripheral blood samples from 10 probands and 5 unaffected controls. Bioinformatic tools were used to identify SVs from the long sequencing reads, with confirmation of findings in probands by short-read Illumina sequencing, Sanger sequencing and visual manual validation with Integrated Genome Browser.

Results

In the 10 probands, we identified and validated 88 SVs (mostly in introns and medium-sized), within 79 genes, which were absent in the 5 unaffected control subjects. These 79 genes were enriched in 20 biological pathways which were related to brain development, neuronal migration, neurogenesis, neuronal/synaptic function, learning/memory, and hearing. These identified SVs also showed evidence for enrichment of genes that are highly expressed in the adolescent striatum.

Conclusion

A substantial part of the missing heritability in SCZ may be explained by medium-sized SVs detectable only by third generation sequencing. We have identified a number of such SVs potentially conferring risk for SCZ, which implicate multiple brain-related genes and pathways. In addition to previously-identified pathways involved in SCZ such as neurodevelopment and neuronal/synaptic functioning, we also found novel evidence for enrichment in hearing-related pathways and genes expressed in the adolescent striatum.

Neurodevelopmental toxicity induced by PM2.5 Exposure and its possible role in Neurodegenerative and mental disorders

Recent extensive evidence suggests that ambient fine particulate matter (PM2.5, with an aerodynamic diameter ≤2.5 μm) may be neurotoxic to the brain and cause central nervous system damage, contributing to neurodevelopmental disorders, such as autism spectrum disorders, neurodegenerative diseases, such as Alzheimer's disease and Parkinson's disease, and mental disorders, such as schizophrenia, depression, and bipolar disorder. PM2.5 can enter the brain via various pathways, including the blood-brain barrier, olfactory system, and gut-brain axis, leading to adverse effects on the CNS. Studies in humans and animals have revealed that PM2.5-mediated mechanisms, including neuroinflammation, oxidative stress, systemic inflammation, and gut flora dysbiosis, play a crucial role in CNS damage. Additionally, PM2.5 exposure can induce epigenetic alterations, such as hypomethylation of DNA, which may contribute to the pathogenesis of some CNS damage. Through literature analysis, we suggest that promising therapeutic targets for alleviating PM2.5-induced neurological damage include inhibiting microglia overactivation, regulating gut microbiota with antibiotics, and targeting signaling pathways, such as PKA/CREB/BDNF and WNT/β-catenin. Additionally, several studies have observed an association between PM2.5 exposure and epigenetic changes in neuropsychiatric disorders. This review summarizes and discusses the association between PM2.5 exposure and CNS damage, including the possible mechanisms by which PM2.5 causes neurotoxicity.

Relationship of Cognition and Alzheimer's Disease with Gastrointestinal Tract Disorders: A Large-Scale Genetic Overlap and Mendelian Randomisation Analysis

Emerging observational evidence suggests links between cognitive impairment and a range of gastrointestinal tract (GIT) disorders; however, the mechanisms underlying their relationships remain unclear. Leveraging large-scale genome-wide association studies’ summary statistics, we comprehensively assessed genetic overlap and potential causality of cognitive traits and Alzheimer’s disease (AD) with several GIT disorders. We demonstrate a strong and highly significant inverse global genetic correlation between cognitive traits and GIT disorders—peptic ulcer disease (PUD), gastritis-duodenitis, diverticulosis, irritable bowel syndrome, and gastroesophageal reflux disease (GERD), but not inflammatory bowel disease (IBD). Further analysis detects 35 significant (p < 4.37 × 10−5) bivariate local genetic correlations between cognitive traits, AD, and GIT disorders (including IBD). Mendelian randomisation analysis suggests a risk-decreasing causality of educational attainment, intelligence, and other cognitive traits on PUD and GERD, but not IBD, and a putative association of GERD with cognitive function decline. Gene-based analysis reveals a significant gene-level genetic overlap of cognitive traits with AD and GIT disorders (IBD inclusive, pbinomial-test = 1.18 × 10−3−2.20 × 10−16). Our study supports the protective roles of genetically-influenced educational attainments and other cognitive traits on the risk of GIT disorders and highlights a putative association of GERD with cognitive function decline. Findings from local genetic correlation analysis provide novel insights, indicating that the relationship of IBD with cognitive traits (and AD) will depend largely on their local effects across the genome.

Exploring the genetic overlap between twelve psychiatric disorders

The widespread comorbidity among psychiatric disorders demonstrated in epidemiological studies1-5 is mirrored by non-zero, positive genetic correlations from large-scale genetic studies6-10. To identify shared biological processes underpinning this observed phenotypic and genetic covariance and enhance molecular characterization of general psychiatric disorder liability11-13, we used several strategies aimed at uncovering pleiotropic, that is, cross-trait-associated, single-nucleotide polymorphisms (SNPs), genes and biological pathways. We conducted cross-trait meta-analysis on 12 psychiatric disorders to identify pleiotropic SNPs. The meta-analytic signal was driven by schizophrenia, hampering interpretation and joint biological characterization of the cross-trait meta-analytic signal. Subsequent pairwise comparisons of psychiatric disorders identified substantial pleiotropic overlap, but mainly among pairs of psychiatric disorders, and mainly at less stringent P-value thresholds. Only annotations related to evolutionarily conserved genomic regions were significant for multiple (9 out of 12) psychiatric disorders. Overall, identification of shared biological mechanisms remains challenging due to variation in power and genetic architecture between psychiatric disorders.

Genetic Overlap Analysis Identifies a Shared Etiology between Migraine and Headache with Type 2 Diabetes

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

A comprehensive comparison of multilocus association methods with summary statistics in genome-wide association studies

BACKGROUND

Multilocus analysis on a set of single nucleotide polymorphisms (SNPs) pre-assigned within a gene constitutes a valuable complement to single-marker analysis by aggregating data on complex traits in a biologically meaningful way. However, despite the existence of a wide variety of SNP-set methods, few comprehensive comparison studies have been previously performed to evaluate the effectiveness of these methods.

RESULTS

We herein sought to fill this knowledge gap by conducting a comprehensive empirical comparison for 22 commonly-used summary-statistics based SNP-set methods. We showed that only seven methods could effectively control the type I error, and that these well-calibrated approaches had varying power performance under the simulation scenarios. Overall, we confirmed that the burden test was generally underpowered and score-based variance component tests (e.g., sequence kernel association test) were much powerful under the polygenic genetic architecture in both common and rare variant association analyses. We further revealed that two linkage-disequilibrium-free P value combination methods (e.g., harmonic mean P value method and aggregated Cauchy association test) behaved very well under the sparse genetic architecture in simulations and real-data applications to common and rare variant association analyses as well as in expression quantitative trait loci weighted integrative analysis. We also assessed the scalability of these approaches by recording computational time and found that all these methods can be scalable to biobank-scale data although some might be relatively slow.

CONCLUSION

In conclusion, we hope that our findings can offer an important guidance on how to choose appropriate multilocus association analysis methods in post-GWAS era. All the SNP-set methods are implemented in the R package called MCA, which is freely available at https://github.com/biostatpzeng/ .

Genetic overlap analysis of endometriosis and asthma identifies shared loci implicating sex hormones and thyroid signalling pathways

STUDY QUESTION

Is there a shared genetic or causal association of endometriosis with asthma or what biological mechanisms may underlie their potential relationships?

SUMMARY ANSWER

Our results confirm a significant but non-causal association of endometriosis with asthma implicating shared genetic susceptibility and biological pathways in the mechanisms of the disorders, and potentially, their co-occurrence.

WHAT IS KNOWN ALREADY

Some observational studies have reported a pattern of co-occurring relationship between endometriosis and asthma; however, there is conflicting evidence and the aetiology, as well as the underlying mechanisms of the relationship, remain unclear.

STUDY DESIGN, SIZE, DURATION

We applied multiple statistical genetic approaches in the analysis of well-powered, genome-wide association study (GWAS) summary data to comprehensively assess the relationship of endometriosis with asthma. Endometriosis GWAS from the International Endogene Consortium (IEC, 17 054 cases and 191 858 controls) and asthma GWAS from the United Kingdom Biobank (UKB, 26 332 cases and 375 505 controls) were analysed. Additional asthma data from the Trans-National Asthma Genetic Consortium (TAGC, 19 954 cases and 107 715 controls) were utilized for replication testing.

PARTICIPANTS/MATERIALS, SETTING, METHODS

We assessed single-nucleotide polymorphism (SNP)-level genetic overlap and correlation between endometriosis and asthma using SNP effect concordance analysis (SECA) and linkage disequilibrium score regression analysis (LDSC) methods, respectively. GWAS meta-analysis, colocalization (GWAS-PW), gene-based and pathway-based functional enrichment analysis methods were applied, respectively, to identify SNP loci, genomic regions, genes and biological pathways shared by endometriosis and asthma. Potential causal associations between endometriosis and asthma were assessed using Mendelian randomization (MR) methods.

MAIN RESULTS AND THE ROLE OF CHANCE

SECA revealed significant concordance of SNP risk effects across the IEC endometriosis and the UKB asthma GWAS. Also, LDSC analysis found a positive and significant genetic correlation (rG = 0.16, P = 2.01 × 10-6) between the two traits. GWAS meta-analysis of the IEC endometriosis and UKB asthma GWAS identified 14 genome-wide significant (Pmeta-analysis < 5.0 × 10-8) independent loci, five of which are putatively novel. Three of these loci were consistently replicated using TAGC asthma GWAS and reinforced in colocalization and gene-based analyses. Additional shared genomic regions were identified in the colocalization analysis. MR found no evidence of a significant causal association between endometriosis and asthma. However, combining gene-based association results across the GWAS for endometriosis and asthma, we identified 17 shared genes with a genome-wide significant Fisher's combined P-value (FCPgene) <2.73 × 10-6. Additional analyses (independent gene-based analysis) replicated evidence of gene-level genetic overlap between endometriosis and asthma. Biological mechanisms including 'thyroid hormone signalling', 'abnormality of immune system physiology', 'androgen biosynthetic process' and 'brain-derived neurotrophic factor signalling pathway', among others, were significantly enriched for endometriosis and asthma in a pathway-based analysis.

LARGE SCALE DATA

The GWAS for endometriosis data were sourced from the International Endogen Consortium (IEC) and can be accessed by contacting the consortium. The GWAS data for asthma are freely available online at Lee Lab (https://www.leelabsg.org/resources) and from the Trans-National Asthma Genetic Consortium (TAGC).

LIMITATIONS, REASONS FOR CAUTION

Given we analysed GWAS datasets from mainly European populations, our results may not be generalizable to other ancestries.

WIDER IMPLICATIONS OF THE FINDINGS

This study provides novel insights into mechanisms underpinning endometriosis and asthma, and potentially their observed relationship. Findings support a co-occurring relationship of endometriosis with asthma largely due to shared genetic components. Agents targeting 'selective androgen receptor modulators' may be therapeutically relevant in both disorders. Moreover, SNPs, loci, genes and biological pathways identified in our study provide potential targets for further investigation in endometriosis and asthma.

STUDY FUNDING/COMPETING INTEREST(S)

National Health and Medical Research Council (NHMRC) of Australia (241,944, 339,462, 389,927, 389,875, 389,891, 389,892, 389,938, 443,036, 442,915, 442,981, 496,610, 496,739, 552,485, 552,498, 1,026,033 and 1,050,208), Wellcome Trust (awards 076113 and 085475) and the Lundbeck Foundation (R102-A9118 and R155-2014-1724). All researchers had full independence from the funders. Authors do not have any conflict of interest.

Sleep disturbances in ADHD: investigating the contribution of polygenic liability for ADHD and sleep-related phenotypes

Sleep disturbances are common in attention deficit hyperactivity disorder (ADHD) and associated with poor outcomes. We tested whether, in children with ADHD, (1) polygenic liability for sleep phenotypes is over- or under-transmitted from parents, (2) this liability is linked to comorbid sleep disturbances, and (3) ADHD genetic risk is associated with comorbid sleep disturbances. We derived polygenic scores (PGS) for insomnia, chronotype, sleep duration, and ADHD, in 758 children (5-18 years old) diagnosed with ADHD and their parents. We conducted polygenic transmission disequilibrium tests for each sleep PGS in complete parent-offspring ADHD trios (N = 328) and an independent replication sample of ADHD trios (N = 844). Next, we tested whether insomnia, sleep duration, and ADHD PGS were associated with co-occurring sleep phenotypes (hypersomnia, insomnia, restless sleep, poor sleep quality, and nightmares) in children with ADHD. Children's insomnia and chronotype PGS did not differ from mid-parent average PGS but long sleep duration PGS were significantly over-transmitted to children with ADHD. This was supported by a combined analysis using the replication sample. Insomnia, sleep duration, and ADHD PGS were not associated with comorbid sleep disturbances. There is weak evidence that children with ADHD over-inherit polygenic liability for longer sleep duration and do not differentially inherit polygenic liability for insomnia or chronotype. There was insufficient evidence that childhood sleep disturbances were driven by polygenic liability for ADHD or sleep traits, suggesting that sleep disturbances in ADHD may be aetiologically different to general population sleep phenotypes and do not index greater ADHD genetic risk burden.

Subtyping Schizophrenia Patients Based on Patterns of Structural Brain Alterations

Schizophrenia is a complex and heterogeneous syndrome. Whether quantitative imaging biomarkers can identify discrete subgroups of patients as might be used to foster personalized medicine approaches for patient care remains unclear. Cross-sectional structural MR images of 163 never-treated first-episode schizophrenia patients (FES) and 133 chronically ill patients with midcourse schizophrenia from the Bipolar and Schizophrenia Network for Intermediate Phenotypes (B-SNIP) consortium and a total of 403 healthy controls were recruited. Morphometric measures (cortical thickness, surface area, and subcortical structures) were extracted for each subject and then the optimized subtyping results were obtained with nonsupervised cluster analysis. Three subgroups of patients defined by distinct patterns of regional cortical and subcortical morphometric features were identified in FES. A similar three subgroup pattern was identified in the independent dataset of patients from the multi-site B-SNIP consortium. Similarities of classification patterns across these two patient cohorts suggest that the 3-group typology is relatively stable over the course of illness. Cognitive functions were worse in subgroup 1 with midcourse schizophrenia than those in subgroup 3. These findings provide novel insight into distinct subgroups of patients with schizophrenia based on structural brain features. Findings of different cognitive functions among the subgroups support clinical differences in the MRI-defined illness subtypes. Regardless of clinical presentation and stage of illness, anatomic MR subgrouping biomarkers can separate neurobiologically distinct subgroups of schizophrenia patients, which represent an important and meaningful step forward in differentiating subtypes of patients for studies of illness neurobiology and potentially for clinical trials.

Patterns of cilia gene dysregulations in major psychiatric disorders

Primary cilia function as cells' antennas to detect and transduce external stimuli and play crucial roles in cell signaling and communication. The vast majority of cilia genes that are causally linked with ciliopathies are also associated with neurological deficits, such as cognitive impairments. Yet, the roles of cilia dysfunctions in the pathogenesis of psychiatric disorders have not been studied. Our aim is to identify patterns of cilia gene dysregulation in the four major psychiatric disorders: schizophrenia (SCZ), autism spectrum disorder (ASD), bipolar disorder (BP), and major depressive disorder (MDD). For this purpose, we acquired differentially expressed genes (DEGs) from the largest and most recent publicly available databases. We found that 42%, 24%, 17%, and 15% of brain-expressed cilia genes were significantly differentially expressed in SCZ, ASD, BP, and MDD, respectively. Several genes exhibited cross-disorder overlap, suggesting that typical cilia signaling pathways' dysfunctions determine susceptibility to more than one psychiatric disorder or may partially underlie their pathophysiology. Our study revealed that genes encoding proteins of almost all sub-cilia structural and functional compartments were dysregulated in the four psychiatric disorders. Strikingly, the genes of 75% of cilia GPCRs and 50% of the transition zone proteins were differentially expressed in SCZ. The present study is the first to draw associations between cilia and major psychiatric disorders, and is the first step toward understanding the role that cilia components play in their pathophysiological processes, which may lead to novel therapeutic targets for these disorders.

Transdiagnostic neuroimaging of reward system phenotypes in ADHD and comorbid disorders

ADHD is a disorder characterized by changes in the reward system and which is highly comorbid with other mental disorders, suggesting common neurobiological pathways. Transdiagnostic neuroimaging findings could help to understand whether a dysregulated reward pathway might be the actual link between ADHD and its comorbidities. We here synthesize ADHD neuroimaging findings on the reward system with findings in obesity, depression, and substance use disorder including their comorbid appearance regarding neuroanatomical features (structural MRI) and activation patterns (resting-state and functional MRI). We focus on findings from monetary-incentive-delay (MID) and delay-discounting (DD) tasks and then review data on striatal connectivity and volumetry. Next, for better understanding of comorbidity in adult ADHD, we discuss these neuroimaging features in ADHD, obesity, depression and substance use disorder and ask whether ADHD heterogeneity and comorbidity are reflected by a common dysregulation in the reward system. Finally, we highlight conceptual issues related to heterogeneous paradigms, different phenotyping, longitudinal prediction and highlight some promising future directions for using striatal reward functioning as a clinical biomarker.

Genetic and morphological estimates of androgen exposure predict social deficits in multiple neurodevelopmental disorder cohorts

BACKGROUND

Neurodevelopmental disorders (NDDs) such as autism spectrum disorder (ASD) display a strong male bias. Androgen exposure is profoundly increased in typical male development, but it also varies within the sexes, and previous work has sought to connect morphological proxies of androgen exposure, including digit ratio and facial morphology, to neurodevelopmental outcomes. The results of these studies have been mixed, and the relationships between androgen exposure and behavior remain unclear.

METHODS

Here, we measured both digit ratio masculinity (DRM) and facial landmark masculinity (FLM) in the same neurodevelopmental cohort (N = 763) and compared these proxies of androgen exposure to clinical and parent-reported features as well as polygenic risk scores.

RESULTS

We found that FLM was significantly associated with NDD diagnosis (ASD, ADHD, ID; all [Formula: see text]), while DRM was not. When testing for association with parent-reported problems, we found that both FLM and DRM were positively associated with concerns about social behavior ([Formula: see text], [Formula: see text]; [Formula: see text], [Formula: see text], respectively). Furthermore, we found evidence via polygenic risk scores (PRS) that DRM indexes masculinity via testosterone levels ([Formula: see text], [Formula: see text]), while FLM indexes masculinity through a negative relationship with sex hormone binding globulin (SHBG) levels ([Formula: see text], [Formula: see text]). Finally, using the SPARK cohort (N = 9419) we replicated the observed relationship between polygenic estimates of testosterone, SHBG, and social functioning ([Formula: see text], [Formula: see text], and [Formula: see text], [Formula: see text] for testosterone and SHBG, respectively). Remarkably, when considered over the extremes of each variable, these quantitative sex effects on social functioning were comparable to the effect of binary sex itself (binary male: [Formula: see text]; testosterone: [Formula: see text] from 0.1%-ile to 99.9%-ile; SHBG: [Formula: see text] from 0.1%-ile to 99.9%-ile).

LIMITATIONS

In the devGenes and SPARK cohorts, our analyses rely on indirect, rather than direct measurement of androgens and related molecules.

CONCLUSIONS

These findings and their replication in the large SPARK cohort lend support to the hypothesis that increasing net androgen exposure diminishes capacity for social functioning in both males and females.

Candidate risk genes for bipolar disorder are highly conserved during evolution and highly interconnected

OBJECTIVES

Bipolar disorder (BPD) is a highly heritable psychiatric disorder whose genetic complexity and pathogenetic mechanisms are still being unraveled. The main goal of this work was to characterize BPD risk-gene candidates (identified by Nurnberger et al., JAMA Psychiatry 71:657, 2014, and Stahl et al., Nat. Genet. 51:793, 2019) with respect to their evolutionary conservation, associated phenotypes, and extent of gene-gene interactions.

METHODS

Database searches and BLAST were used to identify homologous counterparts of human BPD risk genes in C. elegans, zebrafish, and Drosophila. Phenotypes associated with the C. elegans genes were annotated and searched. With GeneMANIA, we characterized and quantified gene-gene interactions among members of the BPD gene set in comparison to randomly chosen gene sets of the same size.

RESULTS

BPD risk genes are highly conserved across species and are enriched for essential genes and genes associated with lethality and altered life span. They are significantly more interactive with each other in comparison to random genes. We identified syntenic blocks of risk genes, which provided potential insights into molecular pathways and co-morbidities associated with BPD including coronary disease, obesity, and decreased life expectancy.

CONCLUSIONS

BPD risk genes appear to be special in terms of their degree of conservation, interconnectedness, and pleiotropic effects that extend beyond a role in brain function. Key hub genes or pleiotropic regulatory components may represent attractive targets for future drug discovery.

Genetic Overlap Between Attention Deficit/Hyperactivity Disorder and Autism Spectrum Disorder in SHANK2 Gene

Background: Recent findings indicated a high comorbidity between attention-deficit/hyperactivity disorder (ADHD) and autism spectrum disorder (ASD), as well as shared genetic influences on them. The latter might contribute at least partly to the former clinical scenario. This study aimed at investigating whether SHANK genes were potential pleiotropic genes to the two said disorders, underlying their genetic overlap.

Methods: This study recruited 298 boys with ADHD (including 256 family trios of 1 ADHD boy and his 2 biological parents), 134 boys with ASD, 109 boys with both ADHD and ASD, and 232 typically developing boys as community controls. They were aged between 6 and 11 years old.

Results: There was no significant difference in allele frequency of a number of single nucleotide polymorphisms (SNPs) in SHANK2/SHANK3 between the three clinical groups (ADHD, ASD, and ADHD + ASD) and between the two control groups (community controls and pseudo-controls), respectively. The three clinical groups and the two control groups were thus, respectively, combined. A comparison between the two aggregated samples identified significant evidence of disease association for three SHANK2 SNPs with both ADHD and ASD, even after multiple testing correction: rs11236616 (OR = 0.762, permuted p = 0.0376), rs7106631 (OR = 0.720, permuted p = 0.0034), and rs9888288 (OR = 0.770, permuted p = 0.0407). Comparisons among individual groups pointed to a similar trend of findings.

Conclusion:SHANK2 could be considered a potential pleiotropic gene underlying the genetic overlap between ADHD and ASD. This might contribute partly to their high comorbidity in the afflicted children.

Family-based association study identifies SNAP25 as a susceptibility gene for autism in the Han Chinese population

Autism is a neurodevelopmental disorder with high heritability. Synaptosome associated protein 25 (SNAP25) encodes a presynaptic membrane-binding protein. It plays a crucial role in neurotransmission and may be involved in the pathogenesis of autism. However, the association between SNAP25 and autism in the Han Chinese population remains unclear. To investigate whether single nucleotide polymorphisms (SNPs) in SNAP25 contribute to the risk of autism, we performed a family-based association study of 14 tagSNPs in SNAP25 in 640 Han Chinese autism trios. Our results demonstrated that rs363018 in SNAP25 was significantly associated with autism under both additive (A > G, Z = 3.144, P = .0017) and recessive models (A > G, Z = 3.055, P = .0023) after Bonferroni correction (P < .0036). An additional SNP, rs8636, was nominally associated with autism under the recessive model (C > T, Z = 1.972, P = .0487). Haplotype-based association test revealed that haplotypes A-T (Z = 2.038, P = .0415) and G-T (Z = -3.114, P = .0018) of rs363018-rs362582 were significantly associated with autism after the permutation test (P = .0158). These findings suggest that SNAP25 may represent a susceptibility gene for autism in the Han Chinese population.

Association of parental depression with offspring attention deficit hyperactivity disorder and autism spectrum disorder: A nationwide birth cohort study

BACKGROUND

Studies have indicated that parental depression was slightly related to the increased risk of offspring attention deficit hyperactivity disorder (ADHD) and autism spectrum disorder (ASD). However, the association between exposure to parental depression at different neurodevelopmental stages (i.e., perinatal or postnatal period) and subsequent ADHD and ASD development remained uncertain.

METHOD

708,515 children born between 2001 and 2008 were screened for ADHD and ASD based on ICD-9-CM codes of 314 and 299 given by psychiatrists from their birth to the end of 2011. Paternal and maternal depression was separately assessed during five periods, namely those before pregnancy (pre-pregnancy), during pregnancy (perinatal), and <1, 1-3, and >3 years after childbirth (postnatal). Cox regression analyses were performed.

RESULTS

Both paternal and maternal depression occurring in the pre-pregnancy, perinatal and postnatal periods were significantly associated with subsequent ADHD and ASD in the offspring, with hazard ratios between 1.42 (95% confidence interval [CI]: 1.35-1.49) and 2.25 (2.09-2.41). The chronicity and additive effect of paternal and maternal depression were related to increased risks of offspring ADHD and ASD. The effects of maternal depression were stronger than the effects of paternal depression for offspring ADHD (HR: 1.35, 95% CI: 1.27-1.45) and ASD (HR: 1.23, 95% CI: 1.05-1.46) risks.

CONCLUSION

Both paternal depression and maternal depression in the pre-pregnancy, perinatal and postnatal periods increases offspring ADHD and ASD risks, and these risks increase further with increases in the duration of parental depression and with the additive effect of parental and maternal depression.

Integrative analyses prioritize GNL3 as a risk gene for bipolar disorder

Genome-wide association studies (GWASs) have identified numerous single nucleotide polymorphisms (SNPs) associated with bipolar disorder (BD), but what the causal variants are and how they contribute to BD is largely unknown. In this study, we used FUMA, a GWAS annotation tool, to pinpoint potential causal variants and genes from the latest BD GWAS findings, and performed integrative analyses, including brain expression quantitative trait loci (eQTL), gene coexpression network, differential gene expression, protein-protein interaction, and brain intermediate phenotype association analysis to identify the functions of a prioritized gene and its connection to BD. Convergent lines of evidence prioritized protein-coding gene G Protein Nucleolar 3 (GNL3) as a BD risk gene, with integrative analyses revealing GNL3's roles in cell proliferation, neuronal functions, and brain phenotypes. We experimentally revealed that BD-related eQTL SNPs rs10865973, rs12635140, and rs4687644 regulate GNL3 expression using dual luciferase reporter assay and CRISPR interference experiment in human neural progenitor cells. We further identified that GNL3 knockdown and overexpression led to aberrant neuronal proliferation and differentiation, using two-dimensional human neural cell cultures and three-dimensional forebrain organoid model. This study gathers evidence that BD-related genetic variants regulate GNL3 expression which subsequently affects neuronal proliferation and differentiation.

Genetic and environmental factors of schizophrenia and autism spectrum disorder: insights from twin studies

Twin studies of psychiatric disorders such as schizophrenia and autism spectrum disorder have employed epidemiological approaches that determine heritability by comparing the concordance rate between monozygotic twins (MZs) and dizygotic twins. The basis for these studies is that MZs share 100% of their genetic information. Recently, biological studies based on molecular methods are now being increasingly applied to examine the differences between MZs discordance for psychiatric disorders to unravel their possible causes. Although recent advances in next-generation sequencing have increased the accuracy of this line of research, there has been greater emphasis placed on epigenetic changes versus DNA sequence changes as the probable cause of discordant psychiatric disorders in MZs. Since the epigenetic status differs in each tissue type, in addition to the DNA from the peripheral blood, studies using DNA from nerve cells induced from postmortem brains or induced pluripotent stem cells are being carried out. Although it was originally thought that epigenetic changes occurred as a result of environmental factors, and thus were not transmittable, it is now known that such changes might possibly be transmitted between generations. Therefore, the potential possible effects of intestinal flora inside the body are currently being investigated as a cause of discordance in MZs. As a result, twin studies of psychiatric disorders are greatly contributing to the elucidation of genetic and environmental factors in the etiology of psychiatric conditions.

The influence of common polygenic risk and gene sets on social skills group training response in autism spectrum disorder

Social skills group training (SSGT) is a frequently used behavioral intervention in autism spectrum disorder (ASD), but the effects are moderate and heterogeneous. Here, we analyzed the effect of polygenic risk score (PRS) and common variants in gene sets on the intervention outcome. Participants from the largest randomized clinical trial of SSGT in ASD to date were selected (N = 188, 99 from SSGT, 89 from standard care) to calculate association between the outcomes in the SSGT trial and PRSs for ASD, attention-deficit hyperactivity disorder (ADHD), and educational attainment. In addition, specific gene sets were selected to evaluate their role on intervention outcomes. Among all participants in the trial, higher PRS for ADHD was associated with significant improvement in the outcome measure, the parental-rated Social Responsiveness Scale. The significant association was due to better outcomes in the standard care group for individuals with higher PRS for ADHD (post-intervention: β = −4.747, P = 0.0129; follow-up: β = −5.309, P = 0.0083). However, when contrasting the SSGT and standard care group, an inferior outcome in the SSGT group was associated with higher ADHD PRS at follow-up (β = 6.67, P = 0.016). Five gene sets within the synaptic category showed a nominal association with reduced response to interventions. We provide preliminary evidence that genetic liability calculated from common variants could influence the intervention outcomes. In the future, larger cohorts should be used to investigate how genetic contribution affects individual response to ASD interventions.

Vascular endothelial growth factor in major depressive disorder, schizophrenia, and bipolar disorder: A network meta-analysis

The peripheral levels of vascular endothelial growth factor (VEGF) have been studied in major psychiatric diseases compared with healthy controls (HCs), but the results were inconsistent. Moreover, few studies have compared VEGF levels between these psychiatric diseases. The aim of the present study was to compare blood VEGF levels in major depressive disorder (MDD), schizophrenia (SCZ), bipolar disorder either in a manic episode, a depressive episode, or a euthymic state, and HC. We supposed that VEGF levels may be elevated in some of these diseases as a potential biomarker. In this study, forty-four studies with 6343 participants were included, and network meta-analysis was used to synthesize evidence from both direct and indirect comparisons. The main analysis showed that no significant differences were found between these groups. Subgroup analysis found that patients with MDD may have higher blood VEGF levels than patients with SCZ when the levels were measured through ELISA, and VEGF levels were increased in medication-treated MDD patients compared with HCs. Taken together, blood VEGF levels may be unaltered in these psychiatric disorders, while detection of VEGF in blood by ELISA may a feasible way to distinguish MDD and SCZ. Further replicated studies with larger samples are needed.

Genetic analysis of endometriosis and depression identifies shared loci and implicates causal links with gastric mucosa abnormality

Evidence from observational studies indicates that endometriosis and depression often co-occur. However, conflicting evidence exists, and the etiology as well as biological mechanisms underlying their comorbidity remain unknown. Utilizing genome-wide association study (GWAS) data, we comprehensively assessed the relationship between endometriosis and depression. Single nucleotide polymorphism effect concordance analysis (SECA) found a significant genetic overlap between endometriosis and depression (P_{Fsig-permuted} = 9.99 × 10^-4). Linkage disequilibrium score regression (LDSC) analysis estimated a positive and highly significant genetic correlation between the two traits (r_G = 0.27, P = 8.85 × 10^-27). A meta-analysis of endometriosis and depression GWAS (sample size = 709,111), identified 20 independent genome-wide significant loci (P < 5 × 10^-8), of which eight are novel. Mendelian randomization analysis (MR) suggests a causal effect of depression on endometriosis. Combining gene-based association results across endometriosis and depression GWAS, we identified 22 genes with a genome-wide significant Fisher's combined P value (FCP_gene < 2.75 × 10^-6). Genes with a nominal gene-based association (P_gene < 0.05) were significantly enriched across endometriosis and depression (P_{binomial-test} = 2.90 × 10^-4). Also, genes overlapping the two traits at P_gene < 0.1 (P_{binomial-test} = 1.31 × 10^-5) were significantly enriched for the biological pathways 'cell-cell adhesion', 'inositol phosphate metabolism', 'Hippo-Merlin signaling dysregulation' and 'gastric mucosa abnormality'. These results reveal a shared genetic etiology for endometriosis and depression. Indeed, additional analyses found evidence of a causal association between each of endometriosis and depression and at least one abnormal condition of gastric mucosa. Our study confirms the comorbidity of endometriosis and depression, implicates links with gastric mucosa abnormalities in their causal pathways and reveals potential therapeutic targets for further investigation.

Changes in Non-Coding RNA in Depression and Bipolar Disorder: Can They Be Used as Diagnostic or Theranostic Biomarkers?

The similarities between the depressive symptoms of Major Depressive Disorders (MDD) and Bipolar Disorders (BD) suggest these disorders have some commonality in their molecular pathophysiologies, which is not apparent from the risk genes shared between MDD and BD. This is significant, given the growing literature suggesting that changes in non-coding RNA may be important in both MDD and BD, because they are causing dysfunctions in the control of biochemical pathways that are affected in both disorders. Therefore, understanding the changes in non-coding RNA in MDD and BD will lead to a better understanding of how and why these disorders develop. Furthermore, as a significant number of individuals suffering with MDD and BD do not respond to medication, identifying non-coding RNA that are altered by the drugs used to treat these disorders offer the potential to identify biomarkers that could predict medication response. Such biomarkers offer the potential to quickly identify patients who are unlikely to respond to traditional medications so clinicians can refocus treatment strategies to ensure more effective outcomes for the patient. This review will focus on the evidence supporting the involvement of non-coding RNA in MDD and BD and their potential use as biomarkers for treatment response.

Attention Deficit/Hyperactivity Disorder and risk for non-affective psychotic disorder: The role of ADHD medication and comorbidity, and sibling comparison

Attention Deficit/Hyperactivity Disorder (ADHD) is the most common psychiatric disorder in childhood. It is unclear whether ADHD increases the risk of non-affective psychotic disorder (NAPD). The study included a matched cohort, drawn from all born in Sweden 1987-1991 (n = 548,852). ADHD was defined as ICD diagnosis and/or prescription of ADHD medication. We distinguished between stimulants and non-stimulants, and usage duration (<1 year, 1-2 years and ≥2 years). We calculated odds ratios (OR) with 95% confidence intervals (CI) for NAPD, adjusted for confounders, comorbid autism spectrum disorder (ASD) and substance abuse. ADHD cases were also compared to their unaffected full siblings. We analyzed 18,139 ADHD cases and 72,437 sex and birth year matched controls. NAPD was more common in cases than controls (2.7 and 0.4%, respectively). After adjustment for confounders, ADHD cases had markedly high risk for NAPD (OR: 6.99; 95% CI 6.03-8.10), which attenuated further after adjustment for ASD and substance abuse (OR: 2.57; 95% CI 2.09-3.16). Utilization of ADHD medication increased the risk for NAPD (ORs for change in odds of NAPD for every 5 extra prescriptions of stimulants 1.06 (95% CI 1.02-1.10) and, non-stimulants 1.15 (95% CI 1.01-1.30)). There was no association between usage length of medication and risk for NAPD. The risk was higher in individuals with ADHD than their unaffected siblings (OR: 2.95 (95% CI 2.07-4.20)). Overall, ADHD was associated with elevated risk for NAPD, which is not entirely explained by shared familial factors. The clinical severity leading to medical treatment may also increase NAPD risk. Ethics approval: Approved by the ethical committee in Stockholm, Sweden (dnrs: 2010-1185-31/5 and 2013/1118-32).

Integrative analyses indicate an association between ITIH3 polymorphisms with autism spectrum disorder

It is challenge to pinpoint the functional variants among numerous genetic variants. Investigating the spatial dynamics of the human brain transcriptome for genes and exploring the expression quantitative trait loci data may provide the potential direction to identify the functional variants among autism spectrum disorders (ASD) patients. In order to explore the association of ITIH3 with ASD, the present study included three components: identifying the spatial-temporal expression of ITIH3 in the developing human brain using the expression data from the Allen Institute for Brain Science; examining the cis-acting regulatory effect of SNPs on the ITIH3 expression using UK Brain Expression Consortium database; validating the effect of identified SNPs using a case-control study with samples of 602 cases and 604 controls. The public expression data showed that ITIH3 may have a role in the development of human brain and suggested a cis-eQTL effect for rs2535629 and rs3617 on ITIH3 in the hippocampus. Genetic analysis of the above two SNPs suggested that the over-dominant model of rs2535629 was significantly associated with decreased risk of ASD. Convergent lines of evidence supported ITIH3 rs25352629 as a susceptibility variant for ASD.

Shared Molecular Genetic Mechanisms Underlie Endometriosis and Migraine Comorbidity

Observational epidemiological studies indicate that endometriosis and migraine co-occur within individuals more than expected by chance. However, the aetiology and biological mechanisms underlying their comorbidity remain unknown. Here we examined the relationship between endometriosis and migraine using genome-wide association study (GWAS) data. Single nucleotide polymorphism (SNP) effect concordance analysis found a significant concordance of SNP risk effects across endometriosis and migraine GWAS. Linkage disequilibrium score regression analysis found a positive and highly significant genetic correlation (rG = 0.38, P = 2.30 × 10-25) between endometriosis and migraine. A meta-analysis of endometriosis and migraine GWAS data did not reveal novel genome-wide significant SNPs, and Mendelian randomisation analysis found no evidence for a causal relationship between the two traits. However, gene-based analyses identified two novel loci for migraine. Also, we found significant enrichment of genes nominally associated (Pgene < 0.05) with both traits (Pbinomial-test = 9.83 × 10-6). Combining gene-based p-values across endometriosis and migraine, three genes, two (TRIM32 and SLC35G6) of which are at novel loci, were genome-wide significant. Genes having Pgene < 0.1 for both endometriosis and migraine (Pbinomial-test = 1.85 ×10-°3) were significantly enriched for biological pathways, including interleukin-1 receptor binding, focal adhesion-PI3K-Akt-mTOR-signaling, MAPK and TNF-α signalling. Our findings further confirm the comorbidity of endometriosis and migraine and indicate a non-causal relationship between the two traits, with shared genetically-controlled biological mechanisms underlying the co-occurrence of the two disorders.

CK1δ over-expressing mice display ADHD-like behaviors, frontostriatal neuronal abnormalities and altered expressions of ADHD-candidate genes

The cognitive mechanisms underlying attention-deficit hyperactivity disorder (ADHD), a highly heritable disorder with an array of candidate genes and unclear genetic architecture, remain poorly understood. We previously demonstrated that mice overexpressing CK1δ (CK1δ OE) in the forebrain show hyperactivity and ADHD-like pharmacological responses to D-amphetamine. Here, we demonstrate that CK1δ OE mice exhibit impaired visual attention and a lack of D-amphetamine-induced place preference, indicating a disruption of the dopamine-dependent reward pathway. We also demonstrate the presence of abnormalities in the frontostriatal circuitry, differences in synaptic ultra-structures by electron microscopy, as well as electrophysiological perturbations of both glutamatergic and GABAergic transmission, as observed by altered frequency and amplitude of mEPSCs and mIPSCs. Furthermore, gene expression profiling by next-generation sequencing alone, or in combination with bacTRAP technology to study specifically Drd1a versus Drd2 medium spiny neurons, revealed that developmental CK1δ OE alters transcriptional homeostasis in the striatum, including specific alterations in Drd1a versus Drd2 neurons. These results led us to perform a fine molecular characterization of targeted gene networks and pathway analysis. Importantly, a large fraction of 92 genes identified by GWAS studies as associated with ADHD in humans are significantly altered in our mouse model. The multiple abnormalities described here might be responsible for synaptic alterations and lead to complex behavioral abnormalities. Collectively, CK1δ OE mice share characteristics typically associated with ADHD and should represent a valuable model to investigate the disease in vivo.

The involvement of the canonical Wnt-signaling receptor LRP5 and LRP6 gene variants with ADHD and sexual dimorphism: Association study and meta-analysis

Wnt-signaling is one of the most abundant pathways involved in processes such as cell-proliferation, -polarity, and -differentiation. Altered Wnt-signaling has been linked with several neurodevelopmental disorders including attention-deficit/hyperactivity disorder (ADHD) as well as with cognitive functions, learning and memory. Particularly, lipoprotein receptor-related protein 5 (LRP5) or LRP6 coreceptors, responsible in the activation of the canonical Wnt-pathway, were associated with cognitive alterations in psychiatric disorders. Following the hypothesis of Wnt involvement in ADHD, we investigated the association of genetic variations in LRP5 and LRP6 genes with three independent child and adolescent ADHD (cADHD) samples (total 2,917 participants), followed by a meta-analysis including previously published data. As ADHD is more prevalent in males, we stratified the analysis according to sex and compared the results with the recent ADHD Psychiatric Genomic Consortium (PGC) GWAS. Meta-analyzing our data including previously published cADHD studies, association of LRP5 intronic rs4988319 and rs3736228 (Ala1330Val) with cADHD was observed among girls (OR = 1.80 with 95% CI = 1.07-3.02, p = .0259; and OR = 2.08 with 95% CI = 1.01-4.46, p = .0026, respectively), whereas in boys association between LRP6 rs2302685 (Val1062Ile) and cADHD was present (OR = 1.66, CI = 1.20-2.31, p = .0024). In the PGC-ADHD dataset (using pooled data of cADHD and adults) tendency of associations were observed only among females with OR = 1.09 (1.02-1.17) for LRP5 rs3736228 and OR = 1.18 (1.09-1.25) for LRP6 rs2302685. Together, our findings suggest a potential sex-specific link of cADHD with LRP5 and LRP6 gene variants, which could contribute to the differences in brain maturation alterations in ADHD affected boys and girls, and suggest possible therapy targets.

The Functional Brain Organization of an Individual Allows Prediction of Measures of Social Abilities Transdiagnostically in Autism and Attention-Deficit/Hyperactivity Disorder

BACKGROUND

Autism spectrum disorder and attention-deficit/hyperactivity disorder (ADHD) are associated with complex changes as revealed by functional magnetic resonance imaging. To date, neuroimaging-based models are not able to characterize individuals with sufficient sensitivity and specificity. Further, although evidence shows that ADHD traits occur in individuals with autism spectrum disorder, and autism spectrum disorder traits in individuals with ADHD, the neurofunctional basis of the overlap is undefined.

METHODS

Using individuals from the Autism Brain Imaging Data Exchange and ADHD-200, we apply a data-driven, subject-level approach, connectome-based predictive modeling, to resting-state functional magnetic resonance imaging data to identify brain-behavior associations that are predictive of symptom severity. We examine cross-diagnostic commonalities and differences.

RESULTS

Using leave-one-subject-out and split-half analyses, we define networks that predict Social Responsiveness Scale, Autism Diagnostic Observation Schedule, and ADHD Rating Scale scores and confirm that these networks generalize to novel subjects. Networks share minimal overlap of edges (<2%) but some common regions of high hubness (Brodmann areas 10, 11, and 21, cerebellum, and thalamus). Further, predicted Social Responsiveness Scale scores for individuals with ADHD are linked to ADHD symptoms, supporting the hypothesis that brain organization relevant to autism spectrum disorder severity shares a component associated with attention in ADHD. Predictive connections and high-hubness regions are found within a wide range of brain areas and across conventional networks.

CONCLUSIONS

An individual's functional connectivity profile contains information that supports dimensional, nonbinary classification in autism spectrum disorder and ADHD. Furthermore, we can determine disorder-specific and shared neurofunctional pathology using our method.

Wnt/β-catenin signaling in brain development and mental disorders: keeping TCF7L2 in mind

Canonical Wnt signaling, which is transduced by β-catenin and lymphoid enhancer factor 1/T cell-specific transcription factors (LEF1/TCFs), regulates many aspects of metazoan development and tissue renewal. Although much evidence has associated canonical Wnt/β-catenin signaling with mood disorders, the mechanistic links are still unknown. Many components of the canonical Wnt pathway are involved in cellular processes that are unrelated to classical canonical Wnt signaling, thus further blurring the picture. The present review critically evaluates the involvement of classical Wnt/β-catenin signaling in developmental processes that putatively underlie the pathology of mental illnesses. Particular attention is given to the roles of LEF1/TCFs, which have been discussed surprisingly rarely in this context. Highlighting recent discoveries, we propose that alterations in the activity of LEF1/TCFs, and particularly of transcription factor 7-like 2 (TCF7L2), result in defects previously associated with neuropsychiatric disorders, including imbalances in neurogenesis and oligodendrogenesis, the functional disruption of thalamocortical circuitry and dysfunction of the habenula.

Pharmacological treatment of adult bipolar disorder

We summarize evidence supporting contemporary pharmacological treatment of phases of BD, including: mania, depression, and long-term recurrences, emphasizing findings from randomized, controlled trials (RCTs). Effective treatment of acute or dysphoric mania is provided by modern antipsychotics, some anticonvulsants (divalproex and carbamazepine), and lithium salts. Treatment of BD-depression remains unsatisfactory but includes some modern antipsychotics (particularly lurasidone, olanzapine + fluoxetine, and quetiapine) and the anticonvulsant lamotrigine; value and safety of antidepressants remain controversial. Long-term prophylactic treatment relies on lithium, off-label use of valproate, and growing use of modern antipsychotics. Lithium has unique evidence of antisuicide effects. Methods of evaluating treatments for BD rely heavily on meta-analysis, which is convenient but with important limitations. Underdeveloped treatment for BD-depression may reflect an assumption that effects of antidepressants are similar in BD as in unipolar major depressive disorder. Effective prophylaxis of BD is limited by the efficacy of available treatments and incomplete adherence owing to adverse effects, costs, and lack of ongoing symptoms. Long-term treatment of BD also is limited by access to, and support of expert, comprehensive clinical programs. Pursuit of improved, rationally designed pharmacological treatments for BD, as for most psychiatric disorders, is fundamentally limited by lack of coherent pathophysiology or etiology.

MeCP2 Dysfunction in Rett Syndrome and Neuropsychiatric Disorders

Elucidating the functions of a particular gene is paramount to the understanding of how its dysfunction contributes to disease. This is especially important when the gene is implicated in multiple different disorders. One such gene is methyl-CpG-binding protein 2 (MECP2), which has been most prominently associated with the neurodevelopmental disorder Rett syndrome, as well as major neuropsychiatric disorders such as autism and schizophrenia. Being initially identified as a transcriptional regulator that modulates gene expression and subsequently also shown to be involved in other molecular events, dysfunction of the MeCP2 protein has the potential to affect many cellular processes. In this chapter, we will briefly review the functions of the MeCP2 protein and how its mutations are implicated in Rett syndrome and other neuropsychiatric disorders. We will further discuss about the mouse models that have been generated to specifically dissect the function of MeCP2 in different cell types and brain regions. It is envisioned that such thorough and targeted examination of MeCP2 functions can aid in enlightening the role that it plays in normal and dysfunctional physiological systems.

Molecular genetic overlap between migraine and major depressive disorder

Migraine and major depressive disorder (MDD) are common brain disorders that frequently co-occur. Despite epidemiological evidence that migraine and MDD share a genetic basis, their overlap at the molecular genetic level has not been thoroughly investigated. Using single-nucleotide polymorphism (SNP) and gene-based analysis of genome-wide association study (GWAS) genotype data, we found significant genetic overlap across the two disorders. LD Score regression revealed a significant SNP-based heritability for both migraine (h² = 12%) and MDD (h² = 19%), and a significant cross-disorder genetic correlation (r_G = 0.25; P = 0.04). Meta-analysis of results for 8,045,569 SNPs from a migraine GWAS (comprising 30,465 migraine cases and 143,147 control samples) and the top 10,000 SNPs from a MDD GWAS (comprising 75,607 MDD cases and 231,747 healthy controls), implicated three SNPs (rs146377178, rs672931, and rs11858956) with novel genome-wide significant association (P_SNP ≤ 5 × 10^-8) to migraine and MDD. Moreover, gene-based association analyses revealed significant enrichment of genes nominally associated (P_gene-based ≤ 0.05) with both migraine and MDD (P_{binomial-test} = 0.001). Combining results across migraine and MDD, two genes, ANKDD1B and KCNK5, produced Fisher's combined gene-based P values that surpassed the genome-wide significance threshold (P_{Fisher's-combined} ≤ 3.6 × 10^-6). Pathway analysis of genes with P_{Fisher's-combined} ≤ 1 × 10^-3 suggested several pathways, foremost neural-related pathways of signalling and ion channel regulation, to be involved in migraine and MDD aetiology. In conclusion, our study provides strong molecular genetic support for shared genetically determined biological mechanisms underlying migraine and MDD.

nArgBP2-SAPAP-SHANK, the core postsynaptic triad associated with psychiatric disorders

Despite the complex genetic architecture, a broad spectrum of psychiatric disorders can still be caused by mutation(s) in the same gene. These disorders are interrelated with overlapping causative mechanisms including variations in the interaction among the risk-associated proteins that may give rise to the specific spectrum of each disorder. Additionally, multiple lines of evidence implicate an imbalance between excitatory and inhibitory neuronal activity (E/I imbalance) as the shared key etiology. Thus, understanding the molecular mechanisms underlying E/I imbalance provides essential insight into the etiology of these disorders. One important class of candidate risk genes is the postsynaptic scaffolding proteins, such as nArgBP2, SAPAP, and SHANK that regulate the actin cytoskeleton in dendritic spines of excitatory synapses. This review will cover and discuss recent studies that examined how these proteins, especially nArgBP2, are associated with psychiatric disorders. Next, we propose a possibility that variations in the interaction among these proteins in a specific brain region might contribute to the onset of diverse phenotypes of psychiatric disorders.

The assembly of scaffolding proteins, key regulators of many signaling pathways, found in the brain’s synapses underpin a diverse range of neuropsychiatric disorders. Sunghoe Chang and colleagues from Seoul National University, South Korea, review how these postsynaptic proteins regulate the cellular cytoskeleton in nerve cell protrusions to maintain the balance between excitatory and inhibitory inputs in the brain. They discuss how perturbations in three particular proteins can cause an imbalance in synaptic signals that leads to conditions such as bipolar disorder, schizophrenia and autism. The authors propose that these proteins form a “core scaffolding triad” and interact in different ways to cause different mental illnesses. Dysregulation of these proteins could explain how mutations in the same genes, depending on whether they boost or decrease gene expression, contribute to the onset of diverse psychiatric disorders.

Schizophrenia: What's Arc Got to Do with It?

Human studies of schizophrenia are now reporting a previously unidentified genetic convergence on postsynaptic signaling complexes such as the activity-regulated cytoskeletal-associated (Arc) gene. However, because this evidence is still very recent, the neurobiological implication of Arc in schizophrenia is still scattered and unrecognized. Here, we first review current and developing findings connecting Arc in schizophrenia. We then highlight recent and previous findings from preclinical mouse models that elucidate how Arc genetic modifications might recapitulate schizophrenia-relevant behavioral phenotypes following the novel Research Domain Criteria (RDoC) framework. Building on this, we finally compare and evaluate several lines of evidence demonstrating that Arc genetics can alter both glutamatergic and dopaminergic systems in a very selective way, again consistent with molecular alterations characteristic of schizophrenia. Despite being only initial, accumulating and compelling data are showing that Arc might be one of the primary biological players in schizophrenia. Synaptic plasticity alterations in the genetic architecture of psychiatric disorders might be a rule, not an exception. Thus, we anticipate that additional evidence will soon emerge to clarify the Arc-dependent mechanisms involved in the psychiatric-related dysfunctional behavior.