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).

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.

A missense mutation in 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.

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).

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.

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.

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.

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.

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.

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.

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).

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.

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).

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.

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.

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.

Identification of a Risk Locus at 7p22.3 for Schizophrenia and Bipolar Disorder in East Asian Populations.

Shared psychopathological features and mechanisms have been observed between schizophrenia (SZ) and bipolar disorder (BD), but their common risk genes and full genetic architectures remain to be fully characterized. The genome-wide association study (GWAS) datasets offer the opportunity to explore this scientific question using combined genetic data from enormous samples, ultimately allowing a better understanding of the onset and development of these illnesses. We have herein performed a genome-wide meta-analysis in two GWAS datasets of SZ and BD respectively (24,600 cases and 40,012 controls in total, discovery sample), followed by replication analyses in an independent sample of 4,918 SZ cases and 5,506 controls of Han Chinese origin (replication sample).

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.

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.

Genome-Wide Meta-Analysis Identifies Two Novel Risk Loci for Epilepsy.

Epilepsy (affects about 70 million people worldwide) is one of the most prevalent brain disorders and imposes a huge economic burden on society. Epilepsy has a strong genetic component. In this study, we perform the largest genome-wide meta-analysis of epilepsy ( = 8,00,869 subjects) by integrating four large-scale genome-wide association studies (GWASs) of epilepsy.

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.

Genome-wide association study followed by trans-ancestry meta-analysis identify 17 new risk loci for schizophrenia.

Background: Over 200 schizophrenia risk loci have been identified by genome-wide association studies (GWASs). However, the majority of risk loci were identified in populations of European ancestry (EUR), potentially missing important biological insights. It is important to perform 5 GWASs in non-European populations.