Mendelian randomization analyses reveal causal relationships between brain functional networks and risk of psychiatric disorders.

Dysfunction of brain resting-state functional networks has been widely reported in psychiatric disorders. However, the causal relationships between brain resting-state functional networks and psychiatric disorders remain largely unclear. Here we perform bidirectional two-sample Mendelian randomization (MR) analyses to investigate the causalities between 191 resting-state functional magnetic resonance imaging (rsfMRI) phenotypes (n = 34,691 individuals) and 12 psychiatric disorders (n = 14,307 to 698,672 individuals). Forward MR identified 8 rsfMRI phenotypes causally associated with the risk of psychiatric disorders. For example, the increase in the connectivity of motor, subcortical-cerebellum and limbic network was associated with lower risk of autism spectrum disorder. In adddition, increased connectivity in the default mode and central executive network was associated with lower risk of post-traumatic stress disorder and depression. Reverse MR analysis revealed significant associations between 4 psychiatric disorders and 6 rsfMRI phenotypes. For instance, the risk of attention-deficit/hyperactivity disorder increases the connectivity of the attention, salience, motor and subcortical-cerebellum network. The risk of schizophrenia mainly increases the connectivity of the default mode and central executive network and decreases the connectivity of the attention network. In summary, our findings reveal causal relationships between brain functional networks and psychiatric disorders, providing important interventional and therapeutic targets for psychiatric disorders at the brain functional network level.

Genome-wide meta-analysis, functional genomics and integrative analyses implicate new risk genes and therapeutic targets for anxiety disorders.

Anxiety disorders are the most prevalent mental disorders. However, the genetic etiology of anxiety disorders remains largely unknown. Here we conducted a genome-wide meta-analysis on anxiety disorders by including 74,973 (28,392 proxy) cases and 400,243 (146,771 proxy) controls. We identified 14 risk loci, including 10 new associations near CNTNAP5, MAP2, RAB9BP1, BTN1A1, PRR16, PCLO, PTPRD, FARP1, CDH2 and RAB27B. Functional genomics and fine-mapping pinpointed the potential causal variants, and expression quantitative trait loci analysis revealed the potential target genes regulated by the risk variants. Integrative analyses, including transcriptome-wide association study, proteome-wide association study and colocalization analyses, prioritized potential causal genes (including CTNND1 and RAB27B). Evidence from multiple analyses revealed possibly causal genes, including RAB27B, BTN3A2, PCLO and CTNND1. Finally, we showed that Ctnnd1 knockdown affected dendritic spine density and resulted in anxiety-like behaviours in mice, revealing the potential role of CTNND1 in anxiety disorders. Our study identified new risk loci, potential causal variants and genes for anxiety disorders, providing insights into the genetic architecture of anxiety disorders and potential therapeutic targets.

Coexistence of Multiple Functional Variants and Genes Underlies Genetic Risk Locus 11p11.2 of Alzheimer's Disease.

BACKGROUND: Genome-wide association studies have identified dozens of genetic risk loci for Alzheimer's disease (AD), yet the underlying causal variants and biological mechanisms remain elusive, especially for loci with complex linkage disequilibrium and regulation. METHODS: To fully untangle the causal signal at a single locus, we performed a functional genomic study of 11p11.2 (the CELF1/SPI1 locus). Genome-wide association study signals at 11p11.2 were integrated with datasets of histone modification, open chromatin, and transcription factor binding to distill potentially functional variants (fVars). Their allelic regulatory activities were confirmed by allele imbalance, reporter assays, and base editing. Expressional quantitative trait loci and chromatin interaction data were incorporated to assign target genes to fVars. The relevance of these genes to AD was assessed by convergent functional genomics using bulk brain and single-cell transcriptomic, epigenomic, and proteomic datasets of patients with AD and control individuals, followed by cellular assays. RESULTS: We found that 24 potential fVars, rather than a single variant, were responsible for the risk of 11p11.2. These fVars modulated transcription factor binding and regulated multiple genes by long-range chromatin interactions. Besides SPI1, convergent evidence indicated that 6 target genes (MTCH2, ACP2, NDUFS3, PSMC3, C1QTNF4, and MADD) of fVars were likely to be involved in AD development. Disruption of each gene led to cellular amyloid-ß and phosphorylated tau changes, supporting the existence of multiple likely causal genes at 11p11.2. CONCLUSIONS: Multiple variants and genes at 11p11.2 may contribute to AD risk. This finding provides new insights into the mechanistic and therapeutic challenges of AD.

Mendelian randomization reveals the causal links between microRNA and schizophrenia.

MicroRNAs have pivotal roles in gene regulation. However, microRNAs that have causal effects on schizophrenia remain largely unknown. To investigate the causal relationships between microRNAs and schizophrenia, here we conduct a Mendelian randomization (MR) study. The genome-wide association study (GWAS) of schizophrenia (67,390 cases and 94,015 controls) from PGC3 were used as the outcome. Genetic variants associated with microRNAs were used as exposure in MR analysis. We identified 6 microRNAs that showed causality on schizophrenia. These microRNAs include hsa-miR-570-3p (OR = 1.03, 95% confidence interval (CI): 1.02 to 1.05, P = 5.45 × 10-5), hsa-miR-550a-3p (OR = 1.12, 95% CI: 1.06 to 1.18, P = 5.99 × 10-5), hsa-miR-130a-3p (OR = 1.10, 95% CI: 1.05 to 1.15, P = 1.58 × 10-4), hsa-miR-210 (OR = 0.87, 95% CI: 0.82 to 0.93, P = 3.09 × 10-5), hsa-miR-337-3p (OR = 1.01, 95% CI: 1.01 to 1.02, P = 3.39 × 10-4), and hsa-miR-130b-3p (OR = 0.89, 95% CI: 0.84 to 0.94, P = 1.50 × 10-5). Differential expression analysis showed dysregulation of hsa-miR-130b-3p in schizophrenia cases compared with controls. Gene Ontology (GO) analysis showed that the targets of these causal microRNAs were significantly enriched in RNA splicing pathways. This MR study identified six microRNAs whose genetically regulated expression might have a causal role in schizophrenia, indicating the causality of these microRNAs in schizophrenia. Our findings also indicate that these microRNAs may be used as potential biomarkers for schizophrenia.

Whole transcriptome analysis reveals dysregulation of molecular networks in schizophrenia.

To characterize the regulatory relationships between different types of transcripts and the altered molecular networks in schizophrenia (SCZ), we performed a whole transcriptome study by quantifying mRNAs, long noncoding RNAs (lncRNAs), miRNAs, and circular RNAs (circRNAs) in the same individuals simultaneously. A total of 807 dysregulated genes showed differential expression in SCZ cases compared with controls. Network-based analysis revealed dysregulation of molecular networks in SCZ. Finally, integration of the transcriptome data with published data identified promising SCZ candidate genes. Our study reveals that dysregulated molecular networks and regulatory relationships between different types of transcript may have a role in SCZ.

A missense mutation in RRM1 contributes to animal tameness.

The increased tameness to reduce avoidance of human in wild animals has been long proposed as the key step of animal domestication. The tameness is a complex behavior trait and largely determined by genetic factors. However, the underlying genetic mutations remain vague and how they influence the animal behaviors is yet to be explored. Behavior tests of a wild-domestic hybrid goat population indicate the locus under strongest artificial selection during domestication may exert a huge effect on the flight distance. Within this locus, only one missense mutation RRM1I241V which was present in the early domestic goat ~6500 years ago. Genome editing of RRM1I241V in mice showed increased tameness and sociability and reduced anxiety. These behavioral changes induced by RRM1I241V were modulated by the alternation of activity of glutamatergic synapse and some other synapse-related pathways. This study established a link between RRM1I241V and tameness, demonstrating that the complex behavioral change can be achieved by mutations under strong selection during animal domestication.

Proteome-wide Mendelian randomization reveals the causal effects of immune-related plasma proteins on psychiatric disorders.

Immune dysregulation has been consistently reported in psychiatric disorders, however, the causes and mechanisms underlying immune dysregulation in psychiatric disorders remain largely unclear. Here we conduct a Mendelian randomization study by integrating plasma proteome and GWASs of schizophrenia, bipolar disorder and depression. The primate-specific immune-related protein BTN3A3 showed the most significant associations with all three psychiatric disorders. In addition, other immune-related proteins, including AIF1, FOXO3, IRF3, CFHR4, IGLON5, FKBP2, and PI3, also showed significant associations with psychiatric disorders. Our study showed that a proportion of psychiatric risk variants may contribute to disease risk by regulating immune-related plasma proteins, providing direct evidence that connect the genetic risk of psychiatric disorders to immune system.

Mendelian Randomization Study Using Dopaminergic Neuron-Specific eQTL Identifies Novel Risk Genes for Schizophrenia.

Multiple integrative studies have been performed to identify the potential target genes of the non-coding schizophrenia (SCZ) risk variants. However, all the integrative studies used expression quantitative trait loci (eQTL) data from bulk tissues. Considering the cell type-specific regulatory effect of many genetic variants, it is important to conduct integrative studies using cell type-specific eQTL data. Here, we conduct a Mendelian randomization (MR) study by integrating genome-wide associations of SCZ (74,776 cases and 101,023 controls) and eQTL data (N = 215) from dopaminergic neurons, which were differentiated from human-induced pluripotent stem cell (iPSC) lines. For eQTL from young post-mitotic dopaminergic neurons (differentiation of iPSC for 30 days, D30), we identified 34 genes whose genetically regulated expression in dopaminergic neurons may have a causal role in SCZ. Among which, ARL3 showed the most significant associations with SCZ. For eQTL from more mature dopaminergic neurons (D52), we identified 37 potential SCZ causal genes, and ARL3 and GNL3 showed the most significant associations. Only 12 genes showed significant associations with SCZ in both D30 and D52 eQTL datasets, indicating the time point-specific genetic regulatory effects in young post-mitotic dopaminergic neurons and more mature dopaminergic neurons. Comparing the results from dopaminergic neurons with bulk brain tissues prioritized 2 high-confidence risk genes, including DDHD2 and GALNT10. Our study identifies multiple risk genes whose genetically regulated expression in dopaminergic neurons may have a causal role in SCZ. Further mechanistic investigation will provide pivotal insights into SCZ pathophysiology.

Genetic regulatory and biological implications of the 10q24.32 schizophrenia risk locus.

Genome-wide association studies have identified 10q24.32 as a robust schizophrenia risk locus. Here we identify a regulatory variant (rs10786700) that disrupts binding of transcription factors at 10q24.32. We independently confirmed the association between rs10786700 and schizophrenia in a large Chinese cohort (n = 11 547) and uncovered the biological mechanism underlying this association. We found that rs10786700 resides in a super-enhancer element that exhibits dynamic activity change during the development process and that the risk allele (C) of rs10786700 conferred significant lower enhancer activity through enhancing binding affinity to repressor element-1 silencing transcription factor (REST). CRISPR-Cas9-mediated genome editing identified SUFU as a potential target gene by which rs10786700 might exert its risk effect on schizophrenia, as deletion of rs10786700 downregulated SUFU expression. We further investigated the role of Sufu in neurodevelopment and found that Sufu knockdown inhibited proliferation of neural stem cells and neurogenesis, affected molecular pathways (including neurodevelopment-related pathways, PI3K-Akt and ECM-receptor interaction signalling pathways) associated with schizophrenia and altered the density of dendritic spines. These results reveal that the functional risk single nucleotide polymorphism rs10786700 at 10q24.32 interacts with REST synergistically to regulate expression of SUFU, a novel schizophrenia risk gene which is involved in schizophrenia pathogenesis by affecting neurodevelopment and spine morphogenesis.

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.

The schizophrenia-associated missense variant rs13107325 regulates dendritic spine density.

The missense variant rs13107325 (C/T, p.Ala391Thr) in SLC39A8 consistently showed robust association with schizophrenia in recent genome-wide association studies (GWASs), suggesting the potential pathogenicity of this non-synonymous risk variant. Nevertheless, how this missense variant confers schizophrenia risk remains unknown. Here we constructed a knock-in mouse model (by introducing a threonine at the 393th amino acid of mouse SLC39A8 (SLC39A8-p.393T), which corresponds to rs13107325 (p.Ala391Thr) of human SLC39A8) to explore the potential roles and biological effects of this missense variant in schizophrenia pathogenesis. We assessed multiple phenotypes and traits (associated with rs13107325) of the knock-in mice, including body and brain weight, concentrations of metal ions (including cadmium, zinc, manganese, and iron) transported by SLC39A8, blood lipids, proliferation and migration of neural stem cells (NSCs), cortical development, behaviors and cognition, transcriptome, dendritic spine density, and synaptic transmission. Many of the tested phenotypes did not show differences in SLC39A8-p.393T knock-in and wild-type mice. However, we found that zinc concentration in brain and blood of SLC39A8-p.393T knock-in mice was dysregulated compared with wild-types, validating the functionality of rs13107325. Further analysis indicated that cortical dendritic spine density of the SLC39A8-p.393T knock-in mice was significantly decreased compared with wild-types, indicating the important role of SLC39A8-p.393T in dendritic spine morphogenesis. These results indicated that SLC39A8-p.393T knock-in resulted in decreased dendritic spine density, thus mimicking the dendritic spine pathology observed in schizophrenia. Our study indicates that rs13107325 might confer schizophrenia risk by regulating zinc concentration and dendritic spine density, a featured characteristic that was frequently reported to be decreased in schizophrenia.

Mendelian Randomization Study Using Dopaminergic Neuron-Specific eQTL Nominates Potential Causal Genes for Parkinson's Disease.

BACKGROUND: Large-scale genome-wide association studies (GWASs) have reported multiple risk variants for Parkinson's disease (PD). However, little is known about how these reported risk variants confer risk of PD. OBJECTIVE: To nominate genes whose genetically regulated expression in dopaminergic neurons may have a causal role in PD. METHODS: We conducted a two-sample Mendelian randomization (MR) study by integrating large-scale genome-wide associations and expression quantitative trait loci (eQTL) data from dopaminergic neurons. RESULTS: MR analysis nominated 10 risk genes whose genetically regulated expression in dopaminergic neurons may have a causal role in PD. These MR significant genes include FAM200B, NDUFAF2, NUP42, SH3GL2, STX1B, CCDC189, KAT8, PRSS36, VAMP4, and ZSWIM7. CONCLUSIONS: We report the first MR study of PD by using dopaminergic neuron-specific eQTL and nominate novel risk genes for PD. Further functional characterization of the nominated risk genes will provide mechanistic insights into PD pathogenesis and potential therapeutic targets. © 2022 International Parkinson and Movement Disorder Society.

Functional genomic analysis delineates regulatory mechanisms of GWAS-identified bipolar disorder risk variants.

BACKGROUND: Genome-wide association studies (GWASs) have identified multiple risk loci for bipolar disorder (BD). However, pinpointing functional (or causal) variants in the reported risk loci and elucidating their regulatory mechanisms remain challenging. METHODS: We first integrated chromatin immunoprecipitation sequencing (ChIP-Seq) data from human brain tissues (or neuronal cell lines) and position weight matrix (PWM) data to identify functional single-nucleotide polymorphisms (SNPs). Then, we verified the regulatory effects of these transcription factor (TF) binding-disrupting SNPs (hereafter referred to as "functional SNPs") through a series of experiments, including reporter gene assays, allele-specific expression (ASE) analysis, TF knockdown, CRISPR/Cas9-mediated genome editing, and expression quantitative trait loci (eQTL) analysis. Finally, we overexpressed PACS1 (whose expression was most significantly associated with the identified functional SNPs rs10896081 and rs3862386) in mouse primary cortical neurons to investigate if PACS1 affects dendritic spine density. RESULTS: We identified 16 functional SNPs (in 9 risk loci); these functional SNPs disrupted the binding of 7 TFs, for example, CTCF and REST binding was frequently disrupted. We then identified the potential target genes whose expression in the human brain was regulated by these functional SNPs through eQTL analysis. Of note, we showed dysregulation of some target genes of the identified TF binding-disrupting SNPs in BD patients compared with controls, and overexpression of PACS1 reduced the density of dendritic spines, revealing the possible biological mechanisms of these functional SNPs in BD. CONCLUSIONS: Our study identifies functional SNPs in some reported risk loci and sheds light on the regulatory mechanisms of BD risk variants. Further functional characterization and mechanistic studies of these functional SNPs and candidate genes will help to elucidate BD pathogenesis and develop new therapeutic approaches and drugs.

Functional genomics elucidates regulatory mechanisms of Parkinson's disease-associated variants.

BACKGROUND: Genome-wide association studies (GWASs) have identified multiple risk loci for Parkinson's disease (PD). However, identifying the functional (or potential causal) variants in the reported risk loci and elucidating their roles in PD pathogenesis remain major challenges. To identify the potential causal (or functional) variants in the reported PD risk loci and to elucidate their regulatory mechanisms, we report a functional genomics study of PD. METHODS: We first integrated chromatin immunoprecipitation sequencing (ChIP-Seq) (from neuronal cells and human brain tissues) data and GWAS-identified single-nucleotide polymorphisms (SNPs) in PD risk loci. We then conducted a series of experiments and analyses to validate the regulatory effects of these (i.e., functional) SNPs, including reporter gene assays, allele-specific expression (ASE), transcription factor (TF) knockdown, CRISPR-Cas9-mediated genome editing, and expression quantitative trait loci (eQTL) analysis. RESULTS: We identified 44 SNPs (from 11 risk loci) affecting the binding of 12 TFs and we validated the regulatory effects of 15 TF binding-disrupting SNPs. In addition, we also identified the potential target genes regulated by these TF binding-disrupting SNPs through eQTL analysis. Finally, we showed that 4 eQTL genes of these TF binding-disrupting SNPs were dysregulated in PD cases compared with controls. CONCLUSION: Our study systematically reveals the gene regulatory mechanisms of PD risk variants (including widespread disruption of CTCF binding), generates the landscape of potential PD causal variants, and pinpoints promising candidate genes for further functional characterization and drug development.

Functional variant rs2270363 on 16p13.3 confers schizophrenia risk by regulating NMRAL1.

Recent genome-wide association studies have reported multiple schizophrenia risk loci, yet the functional variants and their roles in schizophrenia remain to be characterized. Here we identify a functional single nucleotide polymorphism (rs2270363: G>A) at the schizophrenia risk locus 16p13.3. rs2270363 lies in the E-box element of the promoter of NMRAL1 and disrupts binding of the basic helix-loop-helix leucine zipper family proteins, including USF1, MAX and MXI1. We validated the regulatory effects of rs2270363 using reporter gene assays and electrophoretic mobility shift assay. Besides, expression quantitative trait loci analysis showed that the risk allele (A) of rs2270363 was significantly associated with elevated NMRAL1 expression in the human brain. Transcription factors knockdown and CRISPR-Cas9-mediated editing further confirmed the regulatory effects of the genomic region containing rs2270363 on NMRAL1. Intriguingly, NMRAL1 was significantly downregulated in the brain of schizophrenia patients compared with healthy subjects, and knockdown of Nmral1 expression affected proliferation and differentiation of mouse neural stem cells, as well as genes and pathways associated with brain development and synaptic transmission. Of note, Nmral1 knockdown resulted in significant decrease of dendritic spine density, revealing the potential pathophysiological mechanisms of NMRAL1 in schizophrenia. Finally, we independently confirmed the association between rs2270363 and schizophrenia in the Chinese population and found that the risk allele of rs2270363 was the same in European and Chinese populations. These lines of evidence suggest that rs2270363 may confer schizophrenia risk by regulating NMRAL1, a gene whose expression dysregulation might be involved in the pathogenesis of schizophrenia by affecting neurodevelopment and synaptic plasticity.

Regulatory Variant rs2535629 in ITIH3 Intron Confers Schizophrenia Risk By Regulating CTCF Binding and SFMBT1 Expression.

Genome-wide association studies have identified 3p21.1 as a robust risk locus for schizophrenia. However, the underlying molecular mechanisms remain elusive. Here a functional regulatory variant (rs2535629) is identified that disrupts CTCF binding at 3p21.1. It is confirmed that rs2535629 is also significantly associated with schizophrenia in Chinese population and the regulatory effect of rs2535629 is validated. Expression quantitative trait loci analysis indicates that rs2535629 is associated with the expression of three distal genes (GLT8D1, SFMBT1, and NEK4) in the human brain, and CRISPR-Cas9-mediated genome editing confirmed the regulatory effect of rs2535629 on GLT8D1, SFMBT1, and NEK4. Interestingly, differential expression analysis of GLT8D1, SFMBT1, and NEK4 suggested that rs2535629 may confer schizophrenia risk by regulating SFMBT1 expression. It is further demonstrated that Sfmbt1 regulates neurodevelopment and dendritic spine density, two key pathological characteristics of schizophrenia. Transcriptome analysis also support the potential role of Sfmbt1 in schizophrenia pathogenesis. The study identifies rs2535629 as a plausibly causal regulatory variant at the 3p21.1 risk locus and demonstrates the regulatory mechanism and biological effect of this functional variant, indicating that this functional variant confers schizophrenia risk by altering CTCF binding and regulating expression of SFMBT1, a distal gene which plays important roles in neurodevelopment and synaptic morphogenesis.

Regulatory variants at 2q33.1 confer schizophrenia risk by modulating distal gene TYW5 expression.

Genome-wide association studies have shown that genetic variants at 2q33.1 are strongly associated with schizophrenia. However, potential causal variants in this locus and their roles in schizophrenia remain unknown. Here, we identified two functional variants (rs796364 and rs281759) that disrupt CTCF, RAD21 and FOXP2 binding at 2q33.1. We systematically investigated the regulatory mechanisms of these two variants with serial experiments, including reporter gene assays and electrophoretic mobility shift assay. Intriguingly, these two single nucleotide polymorphisms physically interacted with TYW5 and showed the most significant associations with TYW5 expression in human brain. Consistently, CRISPR-Cas9-mediated genome editing confirmed the regulatory effect of the two single nucleotide polymorphisms on TYW5 expression. Additionally, expression analysis indicated that TYW5 was significantly upregulated in brains of schizophrenia cases compared with controls, suggesting that rs796364 and rs281759 might confer schizophrenia risk by modulating TYW5 expression. We over-expressed TYW5 in mouse neural stem cells and rat primary neurons to mimic its upregulation in schizophrenia and found significant alterations in the proliferation and differentiation of neural stem cells, as well as dendritic spine density following TYW5 overexpression, indicating its important roles in neurodevelopment and spine morphogenesis. Furthermore, we independently confirmed the association between rs796364 and schizophrenia in a Chinese cohort of 8202 subjects. Finally, transcriptome analysis revealed that TYW5 affected schizophrenia-associated pathways. These lines of evidence consistently revealed that rs796364 and rs281759 might contribute to schizophrenia risk by regulating the expression of TYW5, a gene whose expression dysregulation affects two important schizophrenia pathophysiological processes (i.e. neurodevelopment and dendritic spine formation).

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.