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.

Lanthanide Complex for Single-Molecule Fluorescent in Situ Hybridization and Background-Free Imaging.

Traditional single-molecule fluorescence in situ hybridization (smFISH) methods for RNA detection often face sensitivity challenges due to the low fluorescence intensity of the probe. Also, short-lived autofluorescence complicates obtaining clear signals from tissue sections. In response, we have developed an smFISH probe using highly grafted lanthanide complexes to address both concentration quenching and autofluorescence background. Our approach involves an oligo PCR incorporating azide-dUTP, enabling conjugation with lanthanide complexes. This method has proven to be stable, convenient, and cost-effective. Notably, for the mRNA detection in SKBR3 cells, the lanthanide probe group exhibited 2.5 times higher luminescence intensity and detected 3 times more signal points in cells compared with the Cy3 group. Furthermore, we successfully applied the probe to image HER2 mRNA molecules in breast cancer FFPE tissue sections, achieving a 2.7-fold improvement in sensitivity compared to Cy3-based probes. These results emphasize the potential of time-resolved smFISH as a highly sensitive method for nucleic acid detection, free of background fluorescence interference.

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.

Brain transcriptome-wide association study implicates novel risk genes underlying schizophrenia risk.

BACKGROUND: To identify risk genes whose expression are regulated by the reported risk variants and to explore the potential regulatory mechanism in schizophrenia (SCZ). METHODS: We systematically integrated three independent brain expression quantitative traits (eQTLs) (CommonMind, GTEx, and BrainSeq Phase 2, a total of 1039 individuals) and GWAS data (56 418 cases and 78 818 controls), with the use of transcriptome-wide association study (TWAS). Diffusion magnetic resonance imaging was utilized to quantify the integrity of white matter bundles and determine whether polygenic risk of novel genes linked to brain structure was present in patients with first-episode antipsychotic SCZ. RESULTS: TWAS showed that eight risk genes (CORO7, DDAH2, DDHD2, ELAC2, GLT8D1, PCDHA8, THOC7, and TYW5) reached transcriptome-wide significance (TWS) level. These findings were confirmed by an independent integrative approach (i.e. Sherlock). We further conducted conditional analyses and identified the potential risk genes that driven the TWAS association signal in each locus. Gene expression analysis showed that several TWS genes (including CORO7, DDAH2, DDHD2, ELAC2, GLT8D1, THOC7 and TYW5) were dysregulated in the dorsolateral prefrontal cortex of SCZ cases compared with controls. TWS genes were mainly expressed on the surface of glutamatergic neurons, GABAergic neurons, and microglia. Finally, SCZ cases had a substantially greater TWS genes-based polygenic risk (PRS) compared to controls, and we showed that fractional anisotropy of the cingulum-hippocampus mediates the influence of TWS genes PRS on SCZ. CONCLUSIONS: Our findings identified novel SCZ risk genes and highlighted the importance of the TWS genes in frontal-limbic dysfunctions in SCZ, indicating possible therapeutic targets.

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.

High-Contrast Luminescent Immunohistochemistry Using PEGylated Lanthanide Complexes.

Immunohistochemistry (IHC) using fluorescent probes provides high resolution with multiplexing capability, but the imaging contrast is limited by the brightness of the fluorescent probe and the intrinsic autofluorescence background from tissues. Herein, we improved the contrast by high-density labeling of long-lifetime lanthanide complexes and time-gated imaging. As the large (∼280 nm) Stokes shift of lanthanide complexes effectively prevents the issue of concentration quenching, we succeeded in conjugating seven europium complexes to an eight-arm hydrophilic poly(ethylene glycol) (PEG) linker for signal amplification with improved water solubility to the level of up to 10 mg/mL. Moreover, we demonstrated that both human epidermal growth factor receptor 2 (HER2) in a formalin-fixed paraffin-embedded (FFPE) tissue section and cytokeratin 18 (CK18) in a frozen section can be resolved with the enhanced contrast by 2-fold and 3-fold, respectively. Furthermore, we show that the PEGylation of multiple lanthanide complexes is compatible with tyramide signal amplification (TSA). This work suggests new opportunities for sensitive imaging of low-abundance biomarkers in a tissue matrix.

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.

dbBIP: a comprehensive bipolar disorder database for genetic research.

Bipolar disorder (BIP) is one of the most common hereditary psychiatric disorders worldwide. Elucidating the genetic basis of BIP will play a pivotal role in mechanistic delineation. Genome-wide association studies (GWAS) have successfully reported multiple susceptibility loci conferring BIP risk, thus providing insight into the effects of its underlying pathobiology. However, difficulties remain in the extrication of important and biologically relevant data from genetic discoveries related to psychiatric disorders such as BIP. There is an urgent need for an integrated and comprehensive online database with unified access to genetic and multi-omics data for in-depth data mining. Here, we developed the dbBIP, a database for BIP genetic research based on published data. The dbBIP consists of several modules, i.e.: (i) single nucleotide polymorphism (SNP) module, containing large-scale GWAS genetic summary statistics and functional annotation information relevant to risk variants; (ii) gene module, containing BIP-related candidate risk genes from various sources and (iii) analysis module, providing a simple and user-friendly interface to analyze one's own data. We also conducted extensive analyses, including functional SNP annotation, integration (including summary-data-based Mendelian randomization and transcriptome-wide association studies), co-expression, gene expression, tissue expression, protein-protein interaction and brain expression quantitative trait loci analyses, thus shedding light on the genetic causes of BIP. Finally, we developed a graphical browser with powerful search tools to facilitate data navigation and access. The dbBIP provides a comprehensive resource for BIP genetic research as well as an integrated analysis platform for researchers and can be accessed online at http://dbbip.xialab.info. Database URL:  http://dbbip.xialab.info.

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.

Comprehensive and integrative analyses identify TYW5 as a schizophrenia risk gene.

BACKGROUND: Identifying the causal genes at the risk loci and elucidating their roles in schizophrenia (SCZ) pathogenesis remain significant challenges. To explore risk variants associated with gene expression in the human brain and to identify genes whose expression change may contribute to the susceptibility of SCZ, here we report a comprehensive integrative study on SCZ. METHODS: We systematically integrated the genetic associations from a large-scale SCZ GWAS (N = 56,418) and brain expression quantitative trait loci (eQTL) data (N = 175) using a Bayesian statistical framework (Sherlock) and Summary data-based Mendelian Randomization (SMR). We also measured brain structure of 86 first-episode antipsychotic-naive schizophrenia patients and 152 healthy controls with the structural MRI. RESULTS: Both Sherlock (P = 3. 38 × 10-6) and SMR (P = 1. 90 × 10-8) analyses showed that TYW5 mRNA expression was significantly associated with risk of SCZ. Brain-based studies also identified a significant association between TYW5 protein abundance and SCZ. The single-nucleotide polymorphism rs203772 showed significant association with SCZ and the risk allele is associated with higher transcriptional level of TYW5 in the prefrontal cortex. We further found that TYW5 was significantly upregulated in the brain tissues of SCZ cases compared with controls. In addition, TYW5 expression was also significantly higher in neurons induced from pluripotent stem cells of schizophrenia cases compared with controls. Finally, combining analysis of genotyping and MRI data showed that rs203772 was significantly associated with gray matter volume of the right middle frontal gyrus and left precuneus. CONCLUSIONS: We confirmed that TYW5 is a risk gene for SCZ. Our results provide useful information toward a better understanding of the genetic mechanism of TYW5 in risk of SCZ.

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.