Transcriptome-wide association study of attention deficit hyperactivity disorder identifies associated genes and phenotypes

Proteome-wide association studies have predicted that the protein abundance of LSM6, GMPPB, ICA1L, and CISD2 is associated with attention-deficit/hyperactivity disorder

Identification of changes in protein abundance for attention-deficit/hyperactivity disorder (ADHD) is important for potential disease mechanisms and therapeutic study for ADHD. In order to identify candidate proteins that confer risk for ADHD, a proteome-wide association study (PWAS) for ADHD was conducted by integrating two human brain proteome datasets and the ADHD genome-wide association study (GWAS) summary statistics released by the Psychiatric Genomics Consortium (PGC). A total of 11 risk proteins were identified as significant candidates that passed the bonferroni corrected proteome-wide significant (PWS) level. The predicted protein abundance level of LSM6, GMPPB, ICA1L and CISD2 are shown significantly associated with ADHD in both proteome datasets, highlighting their potential role in ADHD pathogenesis. A transcriptome-wide association study (TWAS) of ADHD was also conducted, and 13 genes with predicted expression changes related to ADHD were identified. GMPPB, ICA1L and NAT6 were supported by both TWAS and PWASs analysis. This study uncovers the predicted protein abundance changes that confer risk for ADHD and pinpoints a number of high-confidence protein candidates (e.g. LSM6, GMPPB, ICA1L, CISD2) for further functional exploration studies and drug development targeting these proteins.

A cross-tissue transcriptome-wide association study reveals novel susceptibility genes for migraine

BACKGROUND

Migraine is a common neurological disorder with a strong genetic component. Despite the identification of over 100 loci associated with migraine susceptibility through genome-wide association studies (GWAS), the underlying causative genes and biological mechanisms remain predominantly elusive.

METHODS

The FinnGen R10 dataset, consisting of 333,711 subjects (20,908 cases and 312,803 controls), was utilized in conjunction with the Genotype-Tissue Expression Project (GTEx) v8 EQTls files to conduct cross-tissue transcriptome association studies (TWAS). Functional Summary-based Imputation (FUSION) was employed to validate these findings in single tissues. Additionally, candidate susceptibility genes were screened using Gene Analysis combined with Multi-marker Analysis of Genomic Annotation (MAGMA). Subsequent Mendelian randomization (MR) and colocalization analyses were conducted. Furthermore, GeneMANIA analysis was employed to enhance our understanding of the functional implications of these susceptibility genes.

RESULTS

We identified a total of 19 susceptibility genes associated with migraine in the cross-tissue TWAS analysis. Two novel susceptibility genes, REV1 and SREBF2, were validated through both single tissue TWAS and MAGMA analysis. Mendelian randomization and colocalization analyses further confirmed these findings. REV1 may reduce the migraine risk by regulating DNA damage repair, while SREBF2 may increase the risk of migraine by regulating cholesterol metabolism.

CONCLUSION

Our study identified two novel genes whose predicted expression was associated with the risk of migraine, providing new insights into the genetic framework of migraine.

Integrating human endogenous retroviruses into transcriptome-wide association studies highlights novel risk factors for major psychiatric conditions

Human endogenous retroviruses (HERVs) are repetitive elements previously implicated in major psychiatric conditions, but their role in aetiology remains unclear. Here, we perform specialised transcriptome-wide association studies that consider HERV expression quantified to precise genomic locations, using RNA sequencing and genetic data from 792 post-mortem brain samples. In Europeans, we identify 1238 HERVs with expression regulated in cis, of which 26 represent expression signals associated with psychiatric disorders, with ten being conditionally independent from neighbouring expression signals. Of these, five are additionally significant in fine-mapping analyses and thus are considered high confidence risk HERVs. These include two HERV expression signatures specific to schizophrenia risk, one shared between schizophrenia and bipolar disorder, and one specific to major depressive disorder. No robust signatures are identified for autism spectrum conditions or attention deficit hyperactivity disorder in Europeans, or for any psychiatric trait in other ancestries, although this is likely a result of relatively limited statistical power. Ultimately, our study highlights extensive HERV expression and regulation in the adult cortex, including in association with psychiatric disorder risk, therefore providing a rationale for exploring neurological HERV expression in complex neuropsychiatric traits.

Examining Differences in the Genetic and Functional Architecture of Attention-Deficit/Hyperactivity Disorder Diagnosed in Childhood and Adulthood

Background

Attention-deficit/hyperactivity disorder (ADHD) is a neurodevelopmental disorder with diagnostic criteria requiring symptoms to begin in childhood. We investigated whether individuals diagnosed as children differ from those diagnosed in adulthood with respect to shared and unique architecture at the genome-wide and gene expression level of analysis.

Methods

We used genomic structural equation modeling (SEM) to investigate differences in genetic correlations (rg) of childhood-diagnosed (ncases = 14,878) and adulthood-diagnosed (ncases = 6961) ADHD with 98 behavioral, psychiatric, cognitive, and health outcomes. We went on to apply transcriptome-wide SEM to identify functional annotations and patterns of gene expression associated with genetic risk sharing or divergence across the ADHD subgroups.

Results

Compared with the childhood subgroup, adulthood-diagnosed ADHD exhibited a significantly larger negative rg with educational attainment, the noncognitive skills of educational attainment, and age at first sexual intercourse. We observed a larger positive rg for adulthood-diagnosed ADHD with major depression, suicidal ideation, and a latent internalizing factor. At the gene expression level, transcriptome-wide SEM analyses revealed 22 genes that were significantly associated with shared genetic risk across the subtypes that reflected a mixture of coding and noncoding genes and included 15 novel genes relative to the ADHD subgroups.

Conclusions

This study demonstrated that ADHD diagnosed later in life shows much stronger genetic overlap with internalizing disorders and related traits. This may indicate the potential clinical relevance of distinguishing these subgroups or increased misdiagnosis for those diagnosed later in life. Top transcriptome-wide SEM results implicated genes related to neuronal function and clinical characteristics (e.g., sleep).

Cerebrospinal and Brain Proteins Implicated in Neuropsychiatric and Risk Factor Traits: Evidence from Mendelian Randomization

Neuropsychiatric disorders present a global health challenge, necessitating an understanding of their molecular mechanisms for therapeutic development. Using Mendelian randomization (MR) analysis, this study explored associations between genetically predicted levels of 173 proteins in cerebrospinal fluid (CSF) and 25 in the brain with 14 neuropsychiatric disorders and risk factors. Follow-up analyses assessed consistency across plasma protein levels and gene expression in various brain regions. Proteins were instrumented using tissue-specific genetic variants, and colocalization analysis confirmed unbiased gene variants. Consistent MR and colocalization evidence revealed that lower cortical expression of low-density lipoprotein receptor-related protein 8, coupled higher abundance in the CSF and plasma, associated with lower fluid intelligence scores and decreased bipolar disorder risk. Additionally, elevated apolipoprotein-E2 and hepatocyte growth factor-like protein in the CSF and brain were related to reduced leisure screen time and lower odds of physical activity, respectively. Furthermore, elevated CSF soluble tyrosine-protein kinase receptor 1 level increased liability to attention deficit hyperactivity disorder and schizophrenia alongside lower fluid intelligence scores. This research provides genetic evidence supporting novel tissue-specific proteomic targets for neuropsychiatric disorders and their risk factors. Further exploration is necessary to understand the underlying biological mechanisms and assess their potential for therapeutic intervention.

A statistical method for image-mediated association studies discovers genes and pathways associated with four brain disorders

Brain imaging and genomics are critical tools enabling characterization of the genetic basis of brain disorders. However, imaging large cohorts is expensive and may be unavailable for legacy datasets used for genome-wide association studies (GWASs). Using an integrated feature selection/aggregation model, we developed an image-mediated association study (IMAS), which utilizes borrowed imaging/genomics data to conduct association mapping in legacy GWAS cohorts. By leveraging the UK Biobank image-derived phenotypes (IDPs), the IMAS discovered genetic bases underlying four neuropsychiatric disorders and verified them by analyzing annotations, pathways, and expression quantitative trait loci (eQTLs). A cerebellar-mediated mechanism was identified to be common to the four disorders. Simulations show that, if the goal is identifying genetic risk, our IMAS is more powerful than a hypothetical protocol in which the imaging results were available in the GWAS dataset. This implies the feasibility of reanalyzing legacy GWAS datasets without conducting additional imaging, yielding cost savings for integrated analysis of genetics and imaging.

Transcriptome-wide association study identifies new susceptibility genes and pathways for spondyloarthritis

BACKGROUND

Spondyloarthritis (SpA) is a group of multifactorial bone diseases influenced by genetic factors, the environment and lifestyle. However, current studies have found a limited number of SpA-related genes, and the genetic and pathogenic mechanisms of SpA are still unclear.

METHODS

A tissue-specific transcriptome-wide association study (TWAS) of SpA was performed using GWAS (including 3966 SpA patients and 448,298 controls) summary data and gene expression weights of whole blood and skeletal muscle. The SpA-associated genes identified by TWAS were further compared with the differentially expressed genes (DEGs) identified in the SpA gene expression profile acquired from the Gene Expression Omnibus database (GEO, GSE58667). Finally, functional enrichment and annotation analyses of the identified genes were performed.

RESULTS

The TWAS detected 499 suggestive genes associated with SpA in whole blood and skeletal muscle, such as CTNNAL1 (PSM = 3.04 × 10-2, PWB = 9.58 × 10-3). The gene expression profile of SpA identified 20 candidate genes that overlapped in the TWAS data, such as MCM4 (PTWAS = 1.32 × 10-2, PDEG = 2.75 × 10-2) and KIAA1109 (PTWAS = 3.71 × 10-2, PDEG = 4.67 × 10-2). Enrichment analysis of the genes identified by TWAS identified 93 significant GO terms and 33 KEGG pathways, such as mitochondrion organization (GO: 0007005) and axon guidance (hsa04360).

CONCLUSION

We identified multiple candidate genes that were genetically related to SpA. Our study may provide novel clues regarding the genetic mechanism, diagnosis, and treatment of SpA.

Transcriptome-Wide Structural Equation Modeling of 13 Major Psychiatric Disorders for Cross-Disorder Risk and Drug Repurposing

Importance

Psychiatric disorders display high levels of comorbidity and genetic overlap, necessitating multivariate approaches for parsing convergent and divergent psychiatric risk pathways. Identifying gene expression patterns underlying cross-disorder risk also stands to propel drug discovery and repurposing in the face of rising levels of polypharmacy.

Objective

To identify gene expression patterns underlying genetic convergence and divergence across psychiatric disorders along with existing pharmacological interventions that target these genes.

Design, Setting, and Participants

This genomic study applied a multivariate transcriptomic method, transcriptome-wide structural equation modeling (T-SEM), to investigate gene expression patterns associated with 5 genomic factors indexing shared risk across 13 major psychiatric disorders. Follow-up tests, including overlap with gene sets for other outcomes and phenome-wide association studies, were conducted to better characterize T-SEM results. The Broad Institute Connectivity Map Drug Repurposing Database and Drug-Gene Interaction Database public databases of drug-gene pairs were used to identify drugs that could be repurposed to target genes found to be associated with cross-disorder risk. Data were collected from database inception up to February 20, 2023.

Main Outcomes and Measures

Gene expression patterns associated with genomic factors or disorder-specific risk and existing drugs that target these genes.

Results

In total, T-SEM identified 466 genes whose expression was significantly associated (z ≥ 5.02) with genomic factors and 36 genes with disorder-specific effects. Most associated genes were found for a thought disorders factor, defined by bipolar disorder and schizophrenia. Several existing pharmacological interventions were identified that could be repurposed to target genes whose expression was associated with the thought disorders factor or a transdiagnostic p factor defined by all 13 disorders.

Conclusions and Relevance

The findings from this study shed light on patterns of gene expression associated with genetic overlap and uniqueness across psychiatric disorders. Future versions of the multivariate drug repurposing framework outlined here have the potential to identify novel pharmacological interventions for increasingly common, comorbid psychiatric presentations.

Transcriptomic risk scores for attention deficit/hyperactivity disorder

Attention deficit/hyperactivity disorder (ADHD) is a highly heritable neurodevelopmental disorder. We performed a transcriptome-wide association study (TWAS) using the latest genome-wide association study (GWAS) meta-analysis, in 38,691 individuals with ADHD and 186,843 controls, and 14 gene-expression reference panels across multiple brain tissues and whole blood. Based on TWAS results, we selected subsets of genes and constructed transcriptomic risk scores (TRSs) for the disorder in peripheral blood mononuclear cells of individuals with ADHD and controls. We found evidence of association between ADHD and TRSs constructed using expression profiles from multiple brain areas, with individuals with ADHD carrying a higher burden of TRSs than controls. TRSs were uncorrelated with the polygenic risk score (PRS) for ADHD and, in combination with PRS, improved significantly the proportion of variance explained over the PRS-only model. These results support the complementary predictive potential of genetic and transcriptomic profiles in blood and underscore the potential utility of gene expression for risk prediction and deeper insight in molecular mechanisms underlying ADHD.

A Transcriptome-Wide Analysis of Psoriasis: Identifying the Potential Causal Genes and Drug Candidates

Psoriasis is a chronic inflammatory skin disease characterized by cutaneous eruptions and pruritus. Because the genetic backgrounds of psoriasis are only partially revealed, an integrative and rigorous study is necessary. We conducted a transcriptome-wide association study (TWAS) with the new Genotype-Tissue Expression version 8 reference panels, including some tissue and multi-tissue panels that were not used previously. We performed tissue-specific heritability analyses on genome-wide association study data to prioritize the tissue panels for TWAS analysis. TWAS and colocalization (COLOC) analyses were performed with eight tissues from the single-tissue panels and the multi-tissue panels of context-specific genetics (CONTENT) to increase tissue specificity and statistical power. From TWAS, we identified the significant associations of 101 genes in the single-tissue panels and 64 genes in the multi-tissue panels, of which 26 genes were replicated in the COLOC. Functional annotation and network analyses identified that the genes were associated with psoriasis and/or immune responses. We also suggested drug candidates that interact with jointly significant genes through a conditional and joint analysis. Together, our findings may contribute to revealing the underlying genetic mechanisms and provide new insights into treatments for psoriasis.

Identifying potential risk genes and pathways for neuropsychiatric and substance use disorders using intermediate molecular mediator information

Neuropsychiatric and substance use disorders (NPSUDs) have a complex etiology that includes environmental and polygenic risk factors with significant cross-trait genetic correlations. Genome-wide association studies (GWAS) of NPSUDs yield numerous association signals. However, for most of these regions, we do not yet have a firm understanding of either the specific risk variants or the effects of these variants. Post-GWAS methods allow researchers to use GWAS summary statistics and molecular mediators (transcript, protein, and methylation abundances) infer the effect of these mediators on risk for disorders. One group of post-GWAS approaches is commonly referred to as transcriptome/proteome/methylome-wide association studies, which are abbreviated as T/P/MWAS (or collectively as XWAS). Since these approaches use biological mediators, the multiple testing burden is reduced to the number of genes (∼20,000) instead of millions of GWAS SNPs, which leads to increased signal detection. In this work, our aim is to uncover likely risk genes for NPSUDs by performing XWAS analyses in two tissues-blood and brain. First, to identify putative causal risk genes, we performed an XWAS using the Summary-data-based Mendelian randomization, which uses GWAS summary statistics, reference xQTL data, and a reference LD panel. Second, given the large comorbidities among NPSUDs and the shared cis-xQTLs between blood and the brain, we improved XWAS signal detection for underpowered analyses by performing joint concordance analyses between XWAS results i) across the two tissues and ii) across NPSUDs. All XWAS signals i) were adjusted for heterogeneity in dependent instruments (HEIDI) (non-causality) p-values and ii) used to test for pathway enrichment. The results suggest that there were widely shared gene/protein signals within the major histocompatibility complex region on chromosome 6 (BTN3A2 and C4A) and elsewhere in the genome (FURIN, NEK4, RERE, and ZDHHC5). The identification of putative molecular genes and pathways underlying risk may offer new targets for therapeutic development. Our study revealed an enrichment of XWAS signals in vitamin D and omega-3 gene sets. So, including vitamin D and omega-3 in treatment plans may have a modest but beneficial effect on patients with bipolar disorder.

Fins, fur, and wings: the study of Tmem161b across species, and what it tells us about its function in the heart

Transmembrane protein 161b (Tmem161b) was recently identified in multiple high-through-put phenotypic screens, including in fly, zebrafish, and mouse. In zebrafish, Tmem161b was identified as an essential regulator of cardiac rhythm. In mouse, Tmem161b shows conserved function in regulating cardiac rhythm but has also been shown to impact cardiac morphology. Homozygous or heterozygous missense mutations have also recently been reported for TMEM161B in patients with structural brain malformations, although its significance in the human heart remains to be determined. Across the three model organisms studied to date (fly, fish, and mouse), Tmem161b loss of function is implicated in intracellular calcium ion handling, which may explain the diverse phenotypes observed. This review summarises the current knowledge of this conserved and functionally essential protein in the context of cardiac biology.

BrainGENIE: The Brain Gene Expression and Network Imputation Engine

In vivo experimental analysis of human brain tissue poses substantial challenges and ethical concerns. To address this problem, we developed a computational method called the Brain Gene Expression and Network-Imputation Engine (BrainGENIE) that leverages peripheral-blood transcriptomes to predict brain tissue-specific gene-expression levels. Paired blood-brain transcriptomic data collected by the Genotype-Tissue Expression (GTEx) Project was used to train BrainGENIE models to predict gene-expression levels in ten distinct brain regions using whole-blood gene-expression profiles. The performance of BrainGENIE was compared to PrediXcan, a popular method for imputing gene expression levels from genotypes. BrainGENIE significantly predicted brain tissue-specific expression levels for 2947-11,816 genes (false-discovery rate-adjusted p < 0.05), including many transcripts that cannot be predicted significantly by a transcriptome-imputation method such as PrediXcan. BrainGENIE recapitulated measured diagnosis-related gene-expression changes in the brain for autism, bipolar disorder, and schizophrenia better than direct correlations from blood and predictions from PrediXcan. We developed a convenient software toolset for deploying BrainGENIE, and provide recommendations for how best to implement models. BrainGENIE complements and, in some ways, outperforms existing transcriptome-imputation tools, providing biologically meaningful predictions and opening new research avenues.

Telencephalon Organoids Derived from an Individual with ADHD Show Altered Neurodevelopment of Early Cortical Layer Structure

Attention-deficit/hyperactivity disorder (ADHD) is a neurodevelopmental disorder that occurs in early childhood and can persist to adulthood. It can affect many aspects of a patient's daily life, so it is necessary to explore the mechanism and pathological alterations. For this purpose, we applied induced pluripotent stem cell (iPSC)-derived telencephalon organoids to recapitulate the alterations occurring in the early cerebral cortex of ADHD patients. We found that telencephalon organoids of ADHD showed less growth of layer structures than control-derived organoids. On day 35 of differentiation, the thinner cortex layer structures of ADHD-derived organoids contained more neurons than those of control-derived organoids. Furthermore, ADHD-derived organoids showed a decrease in cell proliferation during development from day 35 to 56. On day 56 of differentiation, there was a significant difference in the proportion of symmetric and asymmetric cell division between the ADHD and control groups. In addition, we observed increased cell apoptosis in ADHD during early development. These results show alterations in the characteristics of neural stem cells and the formation of layer structures, which might indicate key roles in the pathogenesis of ADHD. Our organoids exhibit the cortical developmental alterations observed in neuroimaging studies, providing an experimental foundation for understanding the pathological mechanisms of ADHD.

A cross-tissue transcriptome association study identifies key genes in essential hypertension

Genome-wide association study (GWAS) have identified over 1,000 loci associated with blood pressure. However, these loci only explain 6% of heritability. Transcriptome-wide association studies (TWAS) combine GWAS summary data with expression quantitative trait loci (eQTL) to provide a better approach to finding genes associated with complex traits. GWAS summary data (N = 450,584) for essential hypertension originating from European samples were subjected to Post-GWAS analysis using FUMA software and then combined with eQTL data from Genotype-Tissues Expression Project (GTEx) v8 for TWAS analysis using UTMOST, FUSION software, and then validated the results with SMR. FUMA identified 346 significant genes associated with hypertension, FUSION identified 461, and UTMOST cross-tissue analysis identified 34, of which 5 were common. SMR validation identified 3 key genes: ENPEP, USP38, and KCNK3. In previous GWAS studies on blood pressure regulation, the association of ENPEP and KCNK3 with hypertension has been established, and the association between USP38 and blood pressure regulation still needs further validation.

TTLL11 gene is associated with sustained attention performance and brain networks: A genome-wide association study of a healthy Chinese sample

Genetic studies on attention have mainly focused on children with attention-deficit/hyperactivity disorder (ADHD), so little systematic research has been conducted on genetic correlates of attention performance and their potential brain mechanisms among healthy individuals. The current study included a genome-wide association study (GWAS, N = 1145 healthy young adults) aimed to identify genes associated with sustained attention and an imaging genetics study (an independent sample of 483 healthy young adults) to examine any identified genes' influences on brain function. The GWAS found that TTLL11 showed genome-wide significant associations with sustained attention, with rs13298112 as the most significant SNP and the GG homozygotes showing more impulsive but also more focused responses than the A allele carriers. A retrospective examination of previously published ADHD GWAS results confirmed an un-reported, small but statistically significant effect of TTLL11 on ADHD. The imaging genetics study replicated this association and showed that the TTLL11 gene was associated with resting state activity and connectivity of the somatomoter network, and can be predicted by dorsal attention network connectivity. Specifically, the GG homozygotes showed lower brain activity, weaker brain network connectivity, and non-significant brain-attention association compared to the A allele carriers. Expression database showed that expression of this gene is enriched in the brain and that the G allele is associated with lower expression level than the A allele. These results suggest that TTLL11 may play a major role in healthy individuals' attention performance and may also contribute to the etiology of ADHD.

Multi-omics data integration methods and their applications in psychiatric disorders

To study mental illness and health, in the past researchers have often broken down their complexity into individual subsystems (e.g., genomics, transcriptomics, proteomics, clinical data) and explored the components independently. Technological advancements and decreasing costs of high throughput sequencing has led to an unprecedented increase in data generation. Furthermore, over the years it has become increasingly clear that these subsystems do not act in isolation but instead interact with each other to drive mental illness and health. Consequently, individual subsystems are now analysed jointly to promote a holistic understanding of the underlying biological complexity of health and disease. Complementing the increasing data availability, current research is geared towards developing novel methods that can efficiently combine the information rich multi-omics data to discover biologically meaningful biomarkers for diagnosis, treatment, and prognosis. However, clinical translation of the research is still challenging. In this review, we summarise conventional and state-of-the-art statistical and machine learning approaches for discovery of biomarker, diagnosis, as well as outcome and treatment response prediction through integrating multi-omics and clinical data. In addition, we describe the role of biological model systems and in silico multi-omics model designs in clinical translation of psychiatric research from bench to bedside. Finally, we discuss the current challenges and explore the application of multi-omics integration in future psychiatric research. The review provides a structured overview and latest updates in the field of multi-omics in psychiatry.

Genome-wide Mendelian randomization identifies actionable novel drug targets for psychiatric disorders

Psychiatric disorders impose tremendous economic burden on society and are leading causes of disability worldwide. However, only limited drugs are available for psychiatric disorders and the efficacy of most currently used drugs is poor for many patients. To identify novel therapeutic targets for psychiatric disorders, we performed genome-wide Mendelian randomization analyses by integrating brain-derived molecular quantitative trait loci (mRNA expression and protein abundance quantitative trait loci) of 1263 actionable proteins (targeted by approved drugs or drugs in clinical phase of development) and genetic findings from large-scale genome-wide association studies (GWASs). Using transcriptome data, we identified 25 potential drug targets for psychiatric disorders, including 12 genes for schizophrenia, 7 for bipolar disorder, 7 for depression, and 1 (TIE1) for attention deficit and hyperactivity. We also identified 10 actionable drug targets by using brain proteome data, including 4 (HLA-DRB1, CAMKK2, P2RX7, and MAPK3) for schizophrenia, 1 (PRKCB) for bipolar disorder, 6 (PSMB4, IMPDH2, SERPINC1, GRIA1, P2RX7 and TAOK3) for depression. Of note, MAPK3 and HLA-DRB1 were supported by both transcriptome and proteome-wide MR analyses, suggesting that these two proteins are promising therapeutic targets for schizophrenia. Our study shows the power of integrating large-scale GWAS findings and transcriptomic and proteomic data in identifying actionable drug targets. Besides, our findings prioritize actionable novel drug targets for development of new therapeutics and provide critical drug-repurposing opportunities for psychiatric disorders.

TWAS Atlas: a curated knowledgebase of transcriptome-wide association studies

Transcriptome-wide association studies (TWASs), as a practical and prevalent approach for detecting the associations between genetically regulated genes and traits, are now leading to a better understanding of the complex mechanisms of genetic variants in regulating various diseases and traits. Despite the ever-increasing TWAS outputs, there is still a lack of databases curating massive public TWAS information and knowledge. To fill this gap, here we present TWAS Atlas (https://ngdc.cncb.ac.cn/twas/), an integrated knowledgebase of TWAS findings manually curated from extensive literature. In the current implementation, TWAS Atlas collects 401,266 high-quality human gene-trait associations from 200 publications, covering 22,247 genes and 257 traits across 135 tissue types. In particular, an interactive knowledge graph of the collected gene-trait associations is constructed together with single nucleotide polymorphism (SNP)-gene associations to build up comprehensive regulatory networks at multi-omics levels. In addition, TWAS Atlas, as a user-friendly web interface, efficiently enables users to browse, search and download all association information, relevant research metadata and annotation information of interest. Taken together, TWAS Atlas is of great value for promoting the utility and availability of TWAS results in explaining the complex genetic basis as well as providing new insights for human health and disease research.

A transcriptome-wide association study provides new insights into the etiology of osteoarthritis

Background

Osteoarthritis (OA) is a common clinical disease caused by a variety of factors, including genetic variants. Although genome-wide association studies (GWAS) have been performed to elucidate the genetic basis of OA, some loci of risk located in noncoding regions of the genome have been neglected. Therefore, we integrated multiple data types to detect the genetic component of gene expression in OA patients through transcriptome-wide association studies (TWAS) and summary-data-based Mendelian randomization (SMR) analysis.

Methods

TWAS was performed by integrating the larger GWAS summary-data for OA (n=30,727 cases, n=297,191 controls) and 2 expression weight sets (muscle-skeletal tissue and whole blood). Colocalization analysis, conditional analysis, and fine-mapping analysis were also conducted. A broad description of the identified associations was obtained. In addition, a causal relationship between certain risk genes and OA was identified with SMR.

Results

New significant genome-wide associations were found, including on chromosome 1q36.12 (rs1555024, P=4.24E-07) near the ASAP3 and TCEA3 genes, on chromosome 17q24.2 (rs2521348, P=1.01E-06) near the ABCA9 gene, on chromosome 20q11.22 (rs224331, P=8.17E-09) near the UQCC1 and MYH7B genes, and on chromosome 21q21.3 (rs2832155, P=5.39E-08) near the RWDD2B gene. In addition, SMR results exhibited that upregulated UQCC1 and downregulated ASAP3 were associated with OA development and both had a significant causal relationship with OA.

Conclusions

We revealed some novel OA-associated genes and risk loci by integrating multiple data types and analysis methods, thus providing new clues for the study of genetic mechanisms of OA.

Stratification of rheumatoid arthritis cohort using Ayurveda based deep phenotyping approach identifies novel genes in a GWAS

Background and aim

Genome wide association studies have scaled up both in terms of sample size and range of complex disorders investigated, but these have explained relatively little phenotypic variance. Of the several reasons, phenotypic heterogeneity seems to be a likely contributor for missing out genetic associations of large effects. Ayurveda, the traditional Indian system of medicine is one such tool which adopts a holistic deep phenotyping approach and classifies individuals based on their body constitution/prakriti. We hypothesized that Ayurveda based phenotypic stratification of healthy and diseased individuals will allow us to achieve much desired homogeneous cohorts which would facilitate detection of genetic association of large effects. In this proof of concept study, we performed a genome wide association testing of clinically diagnosed rheumatoid arthritis patients and healthy controls, who were re-phenotyped into Vata, Pitta and Kapha predominant prakriti sub-groups.

Experimental procedure

Genotypes of rheumatoid arthritis cases (Vata = 49; Pitta = 117; Kapha = 78) and controls (Vata = 33; Pitta = 175; Kapha = 85) were retrieved from the total genotype data, used in a recent genome-wide association study performed in our laboratory. A total of 528461 SNPs were included after quality control. Prakriti-wise genome-wide association analysis was employed.

Results and conclusion

This study identified (i) prakriti-specific novel disease risk genes of high effect sizes; (ii) putative candidates of novel therapeutic potential; and (iii) a good correlation between genetic findings and clinical knowledge in Ayurveda. Adopting Ayurveda based deep phenotyping may facilitate explaining hitherto undiscovered heritability in complex traits and may propel much needed progress in personalized medicine.

Genome-Wide Association and Transcriptome-Wide Association Studies Identify Novel Susceptibility Genes Contributing to Colorectal Cancer

Background

Colorectal cancer (CRC) is among the most common cancers diagnosed worldwide. Although genome-wide association studies have effectively identified the genetic basis of CRC, there is still unexplained variability in genetic risk. Transcriptome-wide association studies (TWAS) integrate summary statistics from CRC genome-wide association studies (GWAS) with gene expression data to prioritize these GWAS findings and uncover additional gene-trait correlations.

Methods

First, we carried out a post-GWAS analysis using summary statistics from a large-scale GWAS of CRC (n = 4,562 cases, n = 382,756 controls). Second, combined with the expression weight sets from GTEx (v7), susceptibility genes were identified with the FUSION software. Colocalization, conditional and fine-mapping analyses, phenome-wide association study (pheWAS), and Mendelian randomization were employed to further characterize the observed correlations.

Results

In the post-GWAS analyses, we first identified new genome-wide significant associations: three genomic risk loci were identified at 8q24.21 (rs6983267, P = 6.98 × 10⁻¹²), 15q13.3 (rs58658771, P = 1.40 × 10⁻¹⁰), and 18q21.1 (rs6507874, P = 1.91 × 10⁻¹⁴). In addition, the TWAS also identified four loci statistically significantly associated with CRC risk, largely explained by expression regulation, including six candidate genes (DUSP10, POU5F1B, C11orf53, COLCA1, COLCA2, and GREM1-AS1). We further discovered evidence that low expression of COLCA2 is correlated with CRC risk with Mendelian randomization.

Conclusions

We discovered novel CRC risk loci and candidate functional genes by merging gene expression and GWAS summary data, offering new insight into the molecular processes underlying CRC development. This makes it easier to prioritize potential genes for follow-up functional research in CRC.

Is genetic risk of ADHD mediated via dopaminergic mechanism? A study of functional connectivity in ADHD and pharmacologically challenged healthy volunteers with a genetic risk profile

Recent GWAS allow us to calculate polygenic risk scores for ADHD. At the imaging level, resting-state fMRI analyses have given us valuable insights into changes in connectivity patterns in ADHD patients. However, no study has yet attempted to combine these two different levels of investigation. For this endeavor, we used a dopaminergic challenge fMRI study (L-DOPA) in healthy participants who were genotyped for their ADHD, MDD, schizophrenia, and body height polygenic risk score (PRS) and compared results with a study comparing ADHD patients and healthy controls. Our objective was to evaluate how L-DOPA-induced changes of reward-system-related FC are dependent on the individual polygenic risk score. FMRI imaging was used to evaluate resting-state functional connectivity (FC) of targeted subcortical structures in 27 ADHD patients and matched controls. In a second study, we evaluated the effect of ADHD and non-ADHD PRS in a L-DOPA-based pharmaco-fMRI-challenge in 34 healthy volunteers. The functional connectivity between the putamen and parietal lobe was decreased in ADHD patients. In healthy volunteers, the FC between putamen and parietal lobe was lower in ADHD high genetic risk participants. This direction of connectivity was reversed during L-DOPA challenge. Further findings are described for other dopaminergic subcortical structures. The FC between the putamen and the attention network showed the most consistent change in patients as well as in high-risk participants. Our results suggest that FC of the dorsal attention network is altered in adult ADHD as well as in healthy controls with higher genetic risk.

Transcriptome-wide association study reveals increased neuronal FLT3 expression is associated with Tourette's syndrome

Tourette's Syndrome (TS) is a neurodevelopmental disorder that is characterized by motor and phonic tics. A recent TS genome-wide association study (GWAS) identified a genome-wide significant locus. However, determining the biological mechanism of GWAS signals remains difficult. To characterize effects of expression quantitative trait loci (eQTLs) in TS and understand biological underpinnings of the disease. Here, we conduct a TS transcriptome-wide association study (TWAS) consisting of 4819 cases and 9488 controls. We demonstrate that increased expression of FLT3 in the dorsolateral prefrontal cortex (DLPFC) is associated with TS. We further show that there is global dysregulation of FLT3 across several brain regions and probabilistic causal fine-mapping of the TWAS signal prioritizes FLT3 with a posterior inclusion probability of 0.849. After, we proxy the expression with 100 lymphoblastoid cell lines, and demonstrate that TS cells has a 1.72 increased fold change compared to controls. A phenome-wide association study also points toward FLT3 having links with immune-related pathways such as monocyte count. We further identify several splicing events in MPHOSPH9, CSGALNACT2 and FIP1L1 associated with TS, which are also implicated in immune function. This analysis of expression and splicing begins to explore the biology of TS GWAS signals.

A novel cis-regulatory variant modulating TIE1 expression associated with attention deficit hyperactivity disorder in Han Chinese children

BACKGROUND

The genetic factors of attention deficit hyperactivity disorder (ADHD) are far from fully elucidated. This study aims to get additional insight into the genetic structure of ADHD.

METHODS

First, a transcriptome-wide association study and summary data-based Mendelian randomization analysis were performed to identify ADHD susceptibility genes. Then, genetic variants influencing the expression of the identified susceptibility genes were tested for association with ADHD risk in a sample of Han Chinese children (543 cases and 560 controls). Dual-luciferase reporter gene assays and electrophoretic mobility shift assays were performed to verify the transcriptional regulatory functions of the identified ADHD-associated variants. Additionally, real-time quantitative polymerase chain reaction was applied to quantify the expression levels of target genes in blood samples.

RESULTS

Both TIE1 and MED8 were identified as ADHD susceptibility genes. Furthermore, we first found the G allele of rs3768046 was significantly associated with an increased risk of ADHD (recessive model: GG vs AA+AG, OR= 1.659, 95% CI= (1.262, 2.181); additive model: GG vs GA vs AA, OR= 1.493, 95% CI= (1.179, 1.890)). Additionally, in vitro functional experiments revealed that rs3768046 might alter TIE1 expression by affecting the binding sites of transcription factors. Moreover, the expression level of TIE1 in the blood samples of patients was significantly higher than that of controls.

LIMITATIONS

Given the moderate statistical power of this study, it is necessary to verify our findings in other larger samples.

CONCLUSIONS

Together, this study presents the first systematic evidence of TIE1 with potential implications for the genetic basis of ADHD.

Correlation research of susceptibility single nucleotide polymorphisms and the severity of clinical symptoms in attention deficit hyperactivity disorder

OBJECTIVE

To analyze the correlation between susceptibility single nucleotide polymorphisms (SNPs) and the severity of clinical symptoms in children with attention deficit hyperactivity disorder (ADHD), so as to supplement the clinical significance of gene polymorphism and increase our understanding of the association between genetic mutations and ADHD phenotypes.

METHODS

193 children with ADHD were included in our study from February 2017 to February 2020 in the Children's ADHD Clinic of the author's medical institution. 23 ADHD susceptibility SNPs were selected based on the literature, and multiple polymerase chain reaction (PCR) targeted capture sequencing technology was used for gene analysis. A series of ADHD-related questionnaires were used to reflect the severity of the disease, and the correlation between the SNPs of specific sites and the severity of clinical symptoms was evaluated. R software was used to search for independent risk factors by multivariate logistic regression and the "corplot" package was used for correlation analysis.

RESULTS

Among the 23 SNP loci of ADHD children, no mutation was detected in 6 loci, and 2 loci did not conform to Hardy-Weinberg equilibrium. Of the remaining 15 loci, there were 9 SNPs, rs2652511 (SLC6A3 locus), rs1410739 (OBI1-AS1 locus), rs3768046 (TIE1 locus), rs223508 (MANBA locus), rs2906457 (ST3GAL3 locus), rs4916723 (LINC00461 locus), rs9677504 (SPAG16 locus), rs1427829 (intron) and rs11210892 (intron), correlated with the severity of clinical symptoms of ADHD. Specifically, rs1410739 (OBI1-AS1 locus) was found to simultaneously affect conduct problems, control ability and abstract thinking ability of children with ADHD.

CONCLUSION

There were 9 SNPs significantly correlated with the severity of clinical symptoms in children with ADHD, and the rs1410739 (OBI1-AS1 locus) may provide a new direction for ADHD research. Our study builds on previous susceptibility research and further investigates the impact of a single SNP on the severity of clinical symptoms of ADHD. This can help improve the diagnosis, prognosis and treatment of ADHD.

Transcriptome-wide association study identified candidate genes associated with gut microbiota

Background

Gut microbiota is closely associated with host health and disease occurrence. Host genetic factor plays an important role in shaping gut microbial communities. The specific mechanism of host-regulated gene expression affecting gut microbiota has not been elucidated yet. Here we conducted a transcriptome-wide association study (TWAS) for gut microbiota by leveraging expression imputation from large-scale GWAS data sets.

Results

TWAS detected multiple tissue-specific candidate genes for gut microbiota, such as FUT2 for genus Bifidobacterium in transverse colon (P_PERM.ANL = 1.68 × 10^–3) and SFTPD for an unclassified genus of Proteobacteria in transverse colon (P_PERM.ANL = 5.69 × 10^–3). Fine mapping replicated 3 candidate genes in TWAS, such as HELLS for Streptococcus (PIP = 0.685) in sigmoid colon, ANO7 for Erysipelotrichaceae (PIP = 0.449) in sigmoid colon. Functional analyses detected 94 significant GO terms and 11 pathways for various taxa in total, such as GO_NUCLEOSIDE_DIPHOSPHATASE_ACTIVITY for Butyrivibrio (FDR P = 1.30 × 10^–4), KEGG_RENIN_ANGIOTENSIN_SYSTEM for Anaerostipes (FDR P = 3.16 × 10^–2). Literature search results showed 12 genes prioritized by TWAS were associated with 12 diseases. For instance, SFTPD for an unclassified genus of Proteobacteria was related to atherosclerosis, and FUT2 for Bifidobacterium was associated with Crohn’s disease.

Conclusions

Our study results provided novel insights for understanding the genetic mechanism of gut microbiota, and attempted to provide clues for revealing the influence of genetic factors on gut microbiota for the occurrence and development of diseases.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13099-021-00474-w.

Proteome-wide Association Study Provides Insights Into the Genetic Component of Protein Abundance in Psychiatric Disorders

BACKGROUND

Genome-wide association studies have identified multiple risk variants for psychiatric disorders. Nevertheless, how the risk variants confer risk of psychiatric disorders remains largely unknown.

METHODS

We performed proteome-wide association studies to identify genes whose cis-regulated protein abundance change in the human brain were associated with psychiatric disorders.

RESULTS

By integrating genome-wide associations of four common psychiatric disorders and two independent brain proteomes (n = 376 and n = 152, respectively) from the dorsolateral prefrontal cortex, we identified 61 genes (including 48 genes for schizophrenia, 12 genes for bipolar disorder, 5 genes for depression, and 2 genes for attention-deficit/hyperactivity disorder) whose genetically regulated protein abundance levels were associated with risk of psychiatric disorders. Comparison with transcriptome-wide association studies identified 18 overlapping genes that showed significant associations with psychiatric disorders at both proteome-wide and transcriptome-wide levels, suggesting that genetic risk variants likely confer risk of psychiatric disorders by regulating messenger RNA expression and protein abundance of these genes.

CONCLUSIONS

Our study not only provides new insights into the genetic component of protein abundance in psychiatric disorders but also highlights several high-confidence risk proteins (including CNNM2 and CTNND1) for schizophrenia and depression. These high-confidence risk proteins represent promising therapeutic targets for future drug development.

Transcriptome-Wide Association Study Provides Insights Into the Genetic Component of Gene Expression in Anxiety

Anxiety disorders are common mental disorders that often result in disability. Recently, large-scale genome-wide association studies (GWASs) have identified several novel risk variants and loci for anxiety disorders (or anxiety traits). Nevertheless, how the reported risk variants confer risk of anxiety remains unknown. To identify genes whose cis-regulated expression levels are associated with risk of anxiety traits, we conducted a transcriptome-wide association study (TWAS) by integrating genome-wide associations from a large-scale GWAS (N = 175,163) (which evaluated anxiety traits based on Generalized Anxiety Disorder 2-item scale (GAD-2) score) and brain expression quantitative trait loci (eQTL) data (from the PsychENCODE and GTEx). We identified 19 and 17 transcriptome-wide significant (TWS) genes in the PsychENCODE and GTEx, respectively. Intriguingly, 10 genes showed significant associations with anxiety in both datasets, strongly suggesting that genetic risk variants may confer risk of anxiety traits by regulating the expression of these genes. Top TWS genes included RNF123, KANSL1-AS1, GLYCTK, CRHR1, DND1P1, MAPT and ARHGAP27. Of note, 25 TWS genes were not implicated in the original GWAS. Our TWAS identified 26 risk genes whose cis-regulated expression were significantly associated with anxiety, providing important insights into the genetic component of gene expression in anxiety disorders/traits and new clues for future drug development.

Identification of EP300 as a Key Gene Involved in Antipsychotic-Induced Metabolic Dysregulation Based on Integrative Bioinformatics Analysis of Multi-Tissue Gene Expression Data

Antipsychotics (APs) are associated with weight gain and other metabolic abnormalities such as hyperglycemia, dyslipidemia and metabolic syndrome. This translational study aimed to uncover the underlying molecular mechanisms and identify the key genes involved in AP-induced metabolic effects. An integrative gene expression analysis was performed in four different mouse tissues (striatum, liver, pancreas and adipose) after risperidone or olanzapine treatment. The analytical approach combined the identification of the gene co-expression modules related to AP treatment, gene set enrichment analysis and protein-protein interaction network construction. We found several co-expression modules of genes involved in glucose and lipid homeostasis, hormone regulation and other processes related to metabolic impairment. Among these genes, EP300, which encodes an acetyltransferase involved in transcriptional regulation, was identified as the most important hub gene overlapping the networks of both APs. Then, we explored the genetically predicted EP300 expression levels in a cohort of 226 patients with first-episode psychosis who were being treated with APs to further assess the association of this gene with metabolic alterations. The EP300 expression levels were significantly associated with increases in body weight, body mass index, total cholesterol levels, low-density lipoprotein cholesterol levels and triglyceride concentrations after 6 months of AP treatment. Taken together, our analysis identified EP300 as a key gene in AP-induced metabolic abnormalities, indicating that the dysregulation of EP300 function could be important in the development of these side effects. However, more studies are needed to disentangle the role of this gene in the mechanism of action of APs.

A transcriptome-wide association study of Alzheimer's disease using prediction models of relevant tissues identifies novel candidate susceptibility genes

BACKGROUND

Genome-wide association studies (GWAS) have identified over 56 susceptibility loci associated with Alzheimer's disease (AD), but the genes responsible for these associations remain largely unknown.

METHODS

We performed a large transcriptome-wide association study (TWAS) leveraging modified UTMOST (Unified Test for MOlecular SignaTures) prediction models of ten brain tissues that are potentially related to AD to discover novel AD genetic loci and putative target genes in 71,880 (proxy) cases and 383,378 (proxy) controls of European ancestry.

RESULTS

We identified 53 genes with predicted expression associations with AD risk at Bonferroni correction threshold (P value < 3.38 × 10^-6). Based on fine-mapping analyses, 21 genes at nine loci showed strong support for being causal.

CONCLUSIONS

Our study provides new insights into the etiology and underlying genetic architecture of AD.

A transcriptome-wide association study identifies novel susceptibility genes for psoriasis

Although more than 80 psoriasis genetic risk loci have been reported through genome-wide association studies (GWASs), the genetic mechanism of psoriasis remains unclear. To identify novel candidate genes associated with psoriasis and reveal the potential effects of genetic factors in the development of psoriasis, we conducted a transcriptome-wide association study (TWAS) based on summary statistics from GWAS of psoriasis (5175 cases and 447 089 controls) and gene expression levels from six tissues datasets (blood and skin). We identified 11 conditionally independent genes for psoriasis after Bonferroni corrections, such as the most significant genes UBLCP1 (PYFS = 2.98 × 10-16), and LCE3C (PSNSE = 9.72 × 10-12, PSSE = 6.24 × 10-12). The omnibus test identified additional 5 genes associated with psoriasis via the joint association model from multiple reference tissues. Among the 16 identified genes, 5 genes (CTSW, E1F1AD, KLRC3, FIBP, and EFEMP2) were regarded as novel genes for psoriasis. We evaluated the 16 candidate genes by querying public databases and identified 11 differentially expressed genes and 8 genes proved by the knockout mice models. Through GO enrichment analyses, we found that TWAS genes were enriched in the known GO terms associated with skin development, such as cornified envelope (P = 4.80 × 10-8) and peptide cross-linking (P = 1.50 × 10-7). Taken together, our results detected multiple novel candidate genes for psoriasis, providing clues for understanding the genetic mechanism of psoriasis.

The zebrafish grime mutant uncovers an evolutionarily conserved role for Tmem161b in the control of cardiac rhythm

The establishment of cardiac function in the developing embryo is essential to ensure blood flow and, therefore, growth and survival of the animal. The molecular mechanisms controlling normal cardiac rhythm remain to be fully elucidated. From a forward genetic screen, we identified a unique mutant, grime, that displayed a specific cardiac arrhythmia phenotype. We show that loss-of-function mutations in tmem161b are responsible for the phenotype, identifying Tmem161b as a regulator of cardiac rhythm in zebrafish. To examine the evolutionary conservation of this function, we generated knockout mice for Tmem161b. Tmem161b knockout mice are neonatal lethal and cardiomyocytes exhibit arrhythmic calcium oscillations. Mechanistically, we find that Tmem161b is expressed at the cell membrane of excitable cells and live imaging shows it is required for action potential repolarization in the developing heart. Electrophysiology on isolated cardiomyocytes demonstrates that Tmem161b is essential to inhibit Ca²⁺ and K⁺ currents in cardiomyocytes. Importantly, Tmem161b haploinsufficiency leads to cardiac rhythm phenotypes, implicating it as a candidate gene in heritable cardiac arrhythmia. Overall, these data describe Tmem161b as a highly conserved regulator of cardiac rhythm that functions to modulate ion channel activity in zebrafish and mice.

Cis-effects on gene expression in the human prenatal brain associated with genetic risk for neuropsychiatric disorders

The majority of common risk alleles identified for neuropsychiatric disorders reside in noncoding regions of the genome and are therefore likely to impact gene regulation. However, the genes that are primarily affected and the nature and developmental timing of these effects remain unclear. Given the hypothesized role for early neurodevelopmental processes in these conditions, we here define genetic predictors of gene expression in the human fetal brain with which we perform transcriptome-wide association studies (TWASs) of attention deficit hyperactivity disorder (ADHD), autism spectrum disorder, bipolar disorder, major depressive disorder, and schizophrenia. We identify prenatal cis-regulatory effects on 63 genes and 166 individual transcripts associated with genetic risk for these conditions. We observe pleiotropic effects of expression predictors for a number of genes and transcripts, including those of decreased DDHD2 expression in association with risk for schizophrenia and bipolar disorder, increased expression of a ST3GAL3 transcript with risk for schizophrenia and ADHD, and increased expression of an XPNPEP3 transcript with risk for schizophrenia, bipolar disorder, and major depression. For the protocadherin alpha cluster genes PCDHA7 and PCDHA8, we find that predictors of low expression are associated with risk for major depressive disorder while those of higher expression are associated with risk for schizophrenia. Our findings support a role for altered gene regulation in the prenatal brain in susceptibility to various neuropsychiatric disorders and prioritize potential risk genes for further neurobiological investigation.

Multi-tissue neocortical transcriptome-wide association study implicates 8 genes across 6 genomic loci in Alzheimer's disease

BACKGROUND

Alzheimer's disease (AD) is an incurable neurodegenerative disease currently affecting 1.75% of the US population, with projected growth to 3.46% by 2050. Identifying common genetic variants driving differences in transcript expression that confer AD risk is necessary to elucidate AD mechanism and develop therapeutic interventions. We modify the FUSION transcriptome-wide association study (TWAS) pipeline to ingest gene expression values from multiple neocortical regions.

METHODS

A combined dataset of 2003 genotypes clustered to 1000 Genomes individuals from Utah with Northern and Western European ancestry (CEU) was used to construct a training set of 790 genotypes paired to 888 RNASeq profiles from temporal cortex (TCX = 248), prefrontal cortex (FP = 50), inferior frontal gyrus (IFG = 41), superior temporal gyrus (STG = 34), parahippocampal cortex (PHG = 34), and dorsolateral prefrontal cortex (DLPFC = 461). Following within-tissue normalization and covariate adjustment, predictive weights to impute expression components based on a gene's surrounding cis-variants were trained. The FUSION pipeline was modified to support input of pre-scaled expression values and support cross validation with a repeated measure design arising from the presence of multiple transcriptome samples from the same individual across different tissues.

RESULTS

Cis-variant architecture alone was informative to train weights and impute expression for 6780 (49.67%) autosomal genes, the majority of which significantly correlated with gene expression; FDR < 5%: N = 6775 (99.92%), Bonferroni: N = 6716 (99.06%). Validation of weights in 515 matched genotype to RNASeq profiles from the CommonMind Consortium (CMC) was (72.14%) in DLPFC profiles. Association of imputed expression components from all 2003 genotype profiles yielded 8 genes significantly associated with AD (FDR < 0.05): APOC1, EED, CD2AP, CEACAM19, CLPTM1, MTCH2, TREM2, and KNOP1.

CONCLUSIONS

We provide evidence of cis-genetic variation conferring AD risk through 8 genes across six distinct genomic loci. Moreover, we provide expression weights for 6780 genes as a valuable resource to the community, which can be abstracted across the neocortex and a wide range of neuronal phenotypes.

Delineating the Genetic Component of Gene Expression in Major Depression

BACKGROUND

Major depression (MD) is determined by a multitude of factors including genetic risk variants that regulate gene expression. We examined the genetic component of gene expression in MD by performing a transcriptome-wide association study (TWAS), inferring gene expression-trait relationships from genetic, transcriptomic, and phenotypic information.

METHODS

Genes differentially expressed in depression were identified with the TWAS FUSION method, based on summary statistics from the largest genome-wide association analysis of MD (n = 135,458 cases, n = 344,901 controls) and gene expression levels from 21 tissue datasets (brain; blood; thyroid, adrenal, and pituitary glands). Follow-up analyses were performed to extensively characterize the identified associations: colocalization, conditional, and fine-mapping analyses together with TWAS-based pathway investigations.

RESULTS

Transcriptome-wide significant differences between cases and controls were found at 94 genes, approximately half of which were novel. Of the 94 significant genes, 6 represented strong, colocalized, and potentially causal associations with depression. Such high-confidence associations include NEGR1, CTC-467M3.3, TMEM106B, LRFN5, ESR2, and PROX2. Lastly, TWAS-based enrichment analysis highlighted dysregulation of gene sets for, among others, neuronal and synaptic processes.

CONCLUSIONS

This study sheds further light on the genetic component of gene expression in depression by characterizing the identified associations, unraveling novel risk genes, and determining which associations are congruent with a causal model. These findings can be used as a resource for prioritizing and designing subsequent functional studies of MD.

A potential association of RNF219-AS1 with ADHD: Evidence from categorical analysis of clinical phenotypes and from quantitative exploration of executive function and white matter microstructure endophenotypes

Aims

Attention‐deficit/hyperactivity disorder (ADHD) is a neuropsychiatric disorder of substantial heritability, yet emerging evidence suggests that key risk variants might reside in the noncoding regions of the genome. Our study explored the association of lncRNAs (long noncoding RNAs) with ADHD as represented at three different phenotypic levels guided by the Research Domain Criteria (RDoC) framework: (i) ADHD caseness and symptom dimension, (ii) executive functions as functional endophenotype, and (iii) potential genetic influence on white matter architecture as brain structural endophenotype.

Methods

Genotype data of 107 tag single nucleotide polymorphisms (SNP) from 10 candidate lncRNAs were analyzed in 1040 children with ADHD and 630 controls of Chinese Han descent. Executive functions including inhibition and set‐shifting were assessed by STROOP and trail making tests, respectively. Imaging genetic analyses were performed in a subgroup of 33 children with ADHD and 55 controls using fractional anisotropy (FA).

Results

One SNP rs3908461 polymorphism in RNF219‐AS1 was found to be significantly associated with ADHD caseness: with C‐allele detected as the risk genotype in the allelic model (P = 8.607E‐05) and dominant genotypic model (P = 9.628E‐05). Nominal genotypic effects on inhibition (p = 0.020) and set‐shifting (p = 0.046) were detected. While no direct effect on ADHD core symptoms was detected, mediation analysis suggested that SNP rs3908461 potentially exerted an indirect effect through inhibition function [B = 0.21 (SE = 0.12), 95% CI = 0.02‐0.49]. Imaging genetic analyses detected significant associations between rs3908461 genotypes and FA values in corpus callosum, left superior longitudinal fasciculus, left posterior limb of internal capsule, left posterior thalamic radiate (include optic radiation), and the left anterior corona radiate (P_{FWE corrected} < 0.05).

Conclusion

Our present study examined the potential roles of lncRNA in genetic etiological of ADHD and provided preliminary evidence in support of the potential RNF219‐AS1 involvement in the pathophysiology of ADHD in line with the RDoC framework.

Non-genetic risk and protective factors and biomarkers for neurological disorders: a meta-umbrella systematic review of umbrella reviews

BACKGROUND

The etiologies of chronic neurological diseases, which heavily contribute to global disease burden, remain far from elucidated. Despite available umbrella reviews on single contributing factors or diseases, no study has systematically captured non-purely genetic risk and/or protective factors for chronic neurological diseases.

METHODS

We performed a systematic analysis of umbrella reviews (meta-umbrella) published until September 20th, 2018, using broad search terms in MEDLINE, SCOPUS, Web of Science, Cochrane Database of Systematic Reviews, Cumulative Index to Nursing and Allied Health Literature, ProQuest Dissertations & Theses, JBI Database of Systematic Reviews and Implementation Reports, DARE, and PROSPERO. The PRISMA guidelines were followed for this study. Reference lists of the identified umbrella reviews were also screened, and the methodological details were assessed using the AMSTAR tool. For each non-purely genetic factor association, random effects summary effect size, 95% confidence and prediction intervals, and significance and heterogeneity levels facilitated the assessment of the credibility of the epidemiological evidence identified.

RESULTS

We identified 2797 potentially relevant reviews, and 14 umbrella reviews (203 unique meta-analyses) were eligible. The median number of primary studies per meta-analysis was 7 (interquartile range (IQR) 7) and that of participants was 8873 (IQR 36,394). The search yielded 115 distinctly named non-genetic risk and protective factors with a significant association, with various strengths of evidence. Mediterranean diet was associated with lower risk of dementia, Alzheimer disease (AD), cognitive impairment, stroke, and neurodegenerative diseases in general. In Parkinson disease (PD) and AD/dementia, coffee consumption, and physical activity were protective factors. Low serum uric acid levels were associated with increased risk of PD. Smoking was associated with elevated risk of multiple sclerosis and dementia but lower risk of PD, while hypertension was associated with lower risk of PD but higher risk of dementia. Chronic occupational exposure to lead was associated with higher risk of amyotrophic lateral sclerosis. Late-life depression was associated with higher risk of AD and any form of dementia.

CONCLUSIONS

We identified several non-genetic risk and protective factors for various neurological diseases relevant to preventive clinical neurology, health policy, and lifestyle counseling. Our findings could offer new perspectives in secondary research (meta-research).

Heritability Enrichment of Immunoglobulin G N-Glycosylation in Specific Tissues

Genome-wide association studies (GWAS) have identified over 60 genetic loci associated with immunoglobulin G (IgG) N-glycosylation; however, the causal genes and their abundance in relevant tissues are uncertain. Leveraging data from GWAS summary statistics for 8,090 Europeans, and large-scale expression quantitative trait loci (eQTL) data from the genotype-tissue expression of 53 types of tissues (GTEx v7), we derived a linkage disequilibrium score for the specific expression of genes (LDSC-SEG) and conducted a transcriptome-wide association study (TWAS). We identified 55 gene associations whose predicted levels of expression were significantly associated with IgG N-glycosylation in 14 tissues. Three working scenarios, i.e., tissue-specific, pleiotropic, and coassociated, were observed for candidate genetic predisposition affecting IgG N-glycosylation traits. Furthermore, pathway enrichment showed several IgG N-glycosylation-related pathways, such as asparagine N-linked glycosylation, N-glycan biosynthesis and transport to the Golgi and subsequent modification. Through phenome-wide association studies (PheWAS), most genetic variants underlying TWAS hits were found to be correlated with health measures (height, waist-hip ratio, systolic blood pressure) and diseases, such as systemic lupus erythematosus, inflammatory bowel disease, and Parkinson's disease, which are related to IgG N-glycosylation. Our study provides an atlas of genetic regulatory loci and their target genes within functionally relevant tissues, for further studies on the mechanisms of IgG N-glycosylation and its related diseases.

Transcriptome profiling in adult attention-deficit hyperactivity disorder

Attention-deficit/hyperactivity disorder (ADHD) is a neurodevelopmental disorder with an estimated heritability of around 70%. Although the largest genome-wide association study (GWAS) meta-analysis on ADHD identified independent loci conferring risk to the disorder, the molecular mechanisms underlying the genetic basis of the disorder remain to be elucidated. To explore ADHD biology, we ran a two-step transcriptome profiling in peripheral blood mononuclear cells (PBMCs) of 143 ADHD subjects and 169 healthy controls. Through this exploratory study we found eight differentially expressed genes in ADHD. These results highlight promising candidate genes and gene pathways for ADHD and support the use of peripheral tissues to assess gene expression signatures for ADHD.

Differential attentional control mechanisms by two distinct noradrenergic coeruleo-frontal cortical pathways

The attentional control of behavior is a higher-order cognitive function that operates through attention and response inhibition. The locus coeruleus (LC), the main source of norepinephrine in the brain, is considered to be involved in attentional control by modulating the neuronal activity of the prefrontal cortex (PFC). However, evidence for the causal role of LC activity in attentional control remains elusive. Here, by using behavioral and optogenetic techniques, we investigate the effect of LC neuron activation or inhibition in operant tests measuring attention and response inhibition (i.e., a measure of impulsive behavior). We show that LC neuron stimulation increases goal-directed attention and decreases impulsivity, while its suppression exacerbates distractibility and increases impulsive responding. Remarkably, we found that attention and response inhibition are under the control of two divergent projections emanating from the LC: one to the dorso-medial PFC and the other to the ventro-lateral orbitofrontal cortex, respectively. These findings are especially relevant for those pathological conditions characterized by attention deficits and elevated impulsivity.

Biomarker discovery in attention deficit hyperactivity disorder: RNA sequencing of whole blood in discordant twin and case-controlled cohorts

Background

A variety of DNA-based methods have been applied to identify genetic markers of attention deficit hyperactivity disorder (ADHD), but the connection to RNA-based gene expression has not been fully exploited.

Methods

Using well defined cohorts of discordant, monozygotic twins from the Michigan State University Twin Registry, and case-controlled ADHD cases in adolescents, the present studies utilized advanced single molecule RNA sequencing to identify expressed changes in whole blood RNA in ADHD. Multiple analytical strategies were employed to narrow differentially expressed RNA targets to a small set of potential biomarkers of ADHD.

Results

RNA markers common to both the discordant twin study and case-controlled subjects further narrowed the putative targets, some of which had been previously associated with ADHD at the DNA level. The potential role of several differentially expressed genes, including ABCB5, RGS2, GAK, GIT1 and 3 members of the galactose metabolism pathway (GALE, GALT, GALK1) are substantiated by prior associations to ADHD and by established mechanistic connections to molecular pathways relevant to ADHD and behavioral control.

Conclusions

The convergence of DNA, RNA, and metabolic data suggests these may be promising targets for diagnostics and therapeutics in ADHD.

Gene co-expression networks in peripheral blood capture dimensional measures of emotional and behavioral problems from the Child Behavior Checklist (CBCL)

The U.S. National Institute of Mental Health (NIMH) introduced the research domain criteria (RDoC) initiative to promote the integration of information across multiple units of analysis (i.e., brain circuits, physiology, behavior, self-reports) to better understand the basic dimensions of behavior and cognitive functioning underlying normal and abnormal mental conditions. Along those lines, this study examined the association between peripheral blood gene expression levels and emotional and behavioral problems in school-age children. Children were chosen from two age- and sex-matched groups: those with or without parental reports of any prior or current psychiatric diagnosis. RNA-sequencing was performed on whole blood from 96 probands aged 6-12 years who were medication-free at the time of assessment. Module eigengenes were derived using weighted gene co-expression network analysis (WGCNA). Associations were tested between module eigengene expression levels and eight syndrome scales from parent ratings on the Child Behavior Checklist (CBCL). Nine out of the 36 modules were significantly associated with at least one syndrome scale measured by the CBCL (i.e., aggression, social problems, attention problems, and/or thought problems) after accounting for covariates and correcting for multiple testing. Our study demonstrates that variation in peripheral blood gene expression relates to emotional and behavioral profiles in children. If replicated and validated, our results may help in identifying problem or at-risk behavior in pediatric populations, and in elucidating the biological pathways that modulate complex human behavior.

Refining Attention-Deficit/Hyperactivity Disorder and Autism Spectrum Disorder Genetic Loci by Integrating Summary Data From Genome-wide Association, Gene Expression, and DNA Methylation Studies

BACKGROUND

Recent genome-wide association studies (GWASs) identified the first genetic loci associated with attention-deficit/hyperactivity disorder (ADHD) and autism spectrum disorder (ASD). The next step is to use these results to increase our understanding of the biological mechanisms involved. Most of the identified variants likely influence gene regulation. The aim of the current study is to shed light on the mechanisms underlying the genetic signals and prioritize genes by integrating GWAS results with gene expression and DNA methylation (DNAm) levels.

METHODS

We applied summary-data-based Mendelian randomization to integrate ADHD and ASD GWAS data with fetal brain expression and methylation quantitative trait loci, given the early onset of these disorders. We also analyzed expression and methylation quantitative trait loci datasets of adult brain and blood, as these provide increased statistical power. We subsequently used summary-data-based Mendelian randomization to investigate if the same variant influences both DNAm and gene expression levels.

RESULTS

We identified multiple gene expression and DNAm levels in fetal brain at chromosomes 1 and 17 that were associated with ADHD and ASD, respectively, through pleiotropy at shared genetic variants. The analyses in brain and blood showed additional associated gene expression and DNAm levels at the same and additional loci, likely because of increased statistical power. Several of the associated genes have not been identified in ADHD and ASD GWASs before.

CONCLUSIONS

Our findings identified the genetic variants associated with ADHD and ASD that likely act through gene regulation. This facilitates prioritization of candidate genes for functional follow-up studies.

Different effects of methylphenidate and atomoxetine on the behavior and brain transcriptome of zebrafish

Attention deficit-hyperactivity disorder (ADHD) is a prevalent neuropsychiatric disorder found in children. It is characterized by inattention, hyperactivity, and impulsivity. Methylphenidate (MPH) and atomoxetine (ATX) are commonly prescribed for the treatment of ADHD. In the present study, we examined the behavioral and brain transcriptome changes in MPH-treated and ATX-treated zebrafish. In behavioral analysis, zebrafish showed opposite response to each treatment. MPH-treated fish showed higher anxiety-like behavior while ATX-treated fish showed lower anxiety-like behavior. Further, we performed RNA sequencing analysis of zebrafish brain to elucidate the underlying biological pathways associated with MPH and ATX treatment. Interestingly, we found that shared differentially expressed genes in MPH-treated and ATX-treated fish were instrumental in cholesterol biosynthesis pathway and were regulated in opposite manner. Our findings highlight the contrast between MTH and ATX, and may suggest the alterations in clinical practice for these medications and drug development for ADHD.

Multiomics Analyses Identify Genes and Pathways Relevant to Essential Tremor

INTRODUCTION

The genetic factors and molecular mechanisms predisposing to essential tremor (ET) remains largely unknown.

OBJECTIVE

The objective of this study was to identify pathways and genes relevant to ET by integrating multiomics approaches.

METHODS

Case-control RNA sequencing of 2 cerebellar regions was done for 64 samples. A phenome-wide association study (pheWAS) of the differentially expressed genes was conducted, and a genome-wide gene association study (GWGAS) was done to identify pathways overlapping with the transcriptomic data. Finally, a transcriptome-wide association study (TWAS) was done to identify novel risk genes for ET.

RESULTS

We identified several novel dysregulated genes, including CACNA1A and SHF. Pathways including axon guidance, olfactory loss, and calcium channel activity were significantly enriched. The ET GWGAS data found calcium ion-regulated exocytosis of neurotransmitters to be significantly enriched. The TWAS also found calcium and olfactory pathways enriched. The pheWAS identified that the underexpressed differentially expressed gene, SHF, is associated with a blood pressure medication (P = 9.3E-08), which is used to reduce tremor in ET patients. Treatment of cerebellar DAOY cells with the ET drug propranolol identified increases in SHF when treated, suggesting it may rescue the underexpression.

CONCLUSION

We found that calcium-related pathways were enriched across the GWGAS, TWAS, and transcriptome. SHF was shown to have significantly decreased expression, and the pheWAS showed it was associated with blood pressure medication. The treatment of cells with propranolol showed that the drug restored levels of SHF. Overall, our findings highlight the power of integrating multiple different approaches to prioritize ET pathways and genes. © 2020 International Parkinson and Movement Disorder Society.