Integrating genome-wide association study and methylation functional annotation data identified candidate genes and pathways for schizophrenia

Whole-genome sequencing analysis of suicide deaths integrating brain-regulatory eQTLs data to identify risk loci and genes

Recent large-scale genome-wide association studies (GWAS) have started to identify potential genetic risk loci associated with risk of suicide; however, a large portion of suicide-associated genetic factors affecting gene expression remain elusive. Dysregulated gene expression, not assessed by GWAS, may play a significant role in increasing the risk of suicide death. We performed the first comprehensive genomic association analysis prioritizing brain expression quantitative trait loci (eQTLs) within regulatory regions in suicide deaths from the Utah Suicide Genetic Risk Study (USGRS). 440,324 brain-regulatory eQTLs were obtained by integrating brain eQTLs, histone modification ChIP-seq, ATAC-seq, DNase-seq, and Hi-C results from publicly available data. Subsequent genomic analyses were conducted in whole-genome sequencing (WGS) data from 986 suicide deaths of non-Finnish European (NFE) ancestry and 415 ancestrally matched controls. Additional independent USGRS suicide deaths with genotyping array data (n = 4657) and controls from the Genome Aggregation Database were explored for WGS result replication. One significant eQTL locus, rs926308 (p = 3.24e-06), was identified. The rs926308-T is associated with lower expression of RFPL3S, a gene important for neocortex development and implicated in arousal. Gene-based analyses performed using Sherlock Bayesian statistical integrative analysis also detected 20 genes with expression changes that may contribute to suicide risk. From analyzing publicly available transcriptomic data, ten of these genes have previous evidence of differential expression in suicide death or in psychiatric disorders that may be associated with suicide, including schizophrenia and autism (ZNF501, ZNF502, CNN3, IGF1R, KLHL36, NBL1, PDCD6IP, SNX19, BCAP29, and ARSA). Electronic health records (EHR) data was further merged to evaluate if there were clinically relevant subsets of suicide deaths associated with genetic variants. In summary, our study identified one risk locus and ten genes associated with suicide risk via gene expression, providing new insight into possible genetic and molecular mechanisms leading to suicide.

Research Progress on the Role of RNA m6A Modification in Glial Cells in the Regulation of Neurological Diseases

Glial cells are the most abundant and widely distributed cells that maintain cerebral homeostasis in the central nervous system. They mainly include microglia, astrocytes, and the oligodendrocyte lineage cells. Moreover, glial cells may induce pathological changes, such as inflammatory responses, demyelination, and disruption of the blood–brain barrier, to regulate the occurrence and development of neurological diseases through various molecular mechanisms. Furthermore, RNA m6A modifications are involved in various pathological processes associated with glial cells. In this review, the roles of glial cells in physiological and pathological states, as well as advances in understanding the mechanisms by which glial cells regulate neurological diseases under RNA m6A modification, are summarized, hoping to provide new perspectives on the deeper mechanisms and potential therapeutic targets for neurological diseases.

SNX19 restricts endolysosome motility through contacts with the endoplasmic reticulum

The ability of endolysosomal organelles to move within the cytoplasm is essential for the performance of their functions. Long-range movement involves coupling of the endolysosomes to motor proteins that carry them along microtubule tracks. This movement is influenced by interactions with other organelles, but the mechanisms involved are incompletely understood. Herein we show that the sorting nexin SNX19 tethers endolysosomes to the endoplasmic reticulum (ER), decreasing their motility and contributing to their concentration in the perinuclear area of the cell. Tethering depends on two N-terminal transmembrane domains that anchor SNX19 to the ER, and a PX domain that binds to phosphatidylinositol 3-phosphate on the endolysosomal membrane. Two other domains named PXA and PXC negatively regulate the interaction of SNX19 with endolysosomes. These studies thus identify a mechanism for controlling the motility and positioning of endolysosomes that involves tethering to the ER by a sorting nexin.

Recent advances in functional annotation and prediction of the epitranscriptome

RNA modifications, in particular N⁶-methyladenosine (m⁶A), participate in every stages of RNA metabolism and play diverse roles in essential biological processes and disease pathogenesis. Thanks to the advances in sequencing technology, tens of thousands of RNA modification sites can be identified in a typical high-throughput experiment; however, it remains a major challenge to decipher the functional relevance of these sites, such as, affecting alternative splicing, regulation circuit in essential biological processes or association to diseases. As the focus of RNA epigenetics gradually shifts from site discovery to functional studies, we review here recent progress in functional annotation and prediction of RNA modification sites from a bioinformatics perspective. The review covers naïve annotation with associated biological events, e.g., single nucleotide polymorphism (SNP), RNA binding protein (RBP) and alternative splicing, prediction of key sites and their regulatory functions, inference of disease association, and mining the diagnosis and prognosis value of RNA modification regulators. We further discussed the limitations of existing approaches and some future perspectives.

Genome-Wide Detection of m6A-Associated Genetic Polymorphisms Associated with Ischemic Stroke

N⁶-Methyladenosine (m⁶A) methylation is the most abundant post-transcription modification in eukaryotes and plays a vital role in many pathological conditions including cerebral ischemia-reperfusion injury and vascular inflammation. Moreover, recent studies have reported that single-nucleotide polymorphisms (SNPs) can affect the m⁶A modification. Therefore, we investigated the relationship between m⁶A-SNPs and ischemic stroke (IS) risk through integrative analysis of an IS genome-wide association study and m⁶A-SNP list from the m6AVar database. Next, we performed eQTL and differential expression analysis to support these IS-associated m⁶A-SNPs. Finally, using the identified polymorphisms, a PPI network was constructed using the STRING database, and GO and pathway enrichment analyses were performed using the DAVID online tool. Accordingly, we identified 305 IS-associated SNPs that could affect m⁶A methylation. Next, 158 of these SNPs were determined to have eQTL signals on local genes. We further identified 84 local genes (containing a total of 87 SNPs) that were differentially expressed in IS patients. Finally, we identified several biological processes and pathways related to IS pathogenesis, such as "leukocyte migration" and "focal adhesion." In summary, our study detected dozens of m⁶A-SNPs as critical functional polymorphisms and novel genetic biomarkers for IS susceptibility and provided a new means of elucidating the biological mechanism underlying IS development.

Integrative analysis of genome-wide association studies identifies novel loci associated with neuropsychiatric disorders

Neuropsychiatric disorders, such as autism spectrum disorder (ASD), attention deficit hyperactivity disorder (ADHD), schizophrenia (SCZ), bipolar disorder (BIP), and major depressive disorder (MDD) share common clinical presentations, suggesting etiologic overlap. A substantial proportion of SNP-based heritability for neuropsychiatric disorders is attributable to genetic components, and genome-wide association studies (GWASs) focusing on individual diseases have identified multiple genetic loci shared between these diseases. Here, we aimed at identifying novel genetic loci associated with individual neuropsychiatric diseases and genetic loci shared by neuropsychiatric diseases. We performed multi-trait joint analyses and meta-analysis across five neuropsychiatric disorders based on their summary statistics from the Psychiatric Genomics Consortium (PGC), and further carried out a replication study of ADHD among 2726 cases and 16299 controls in an independent pediatric cohort. In the multi-trait joint analyses, we found five novel genome-wide significant loci for ADHD, one novel locus for BIP, and ten novel loci for MDD. We further achieved modest replication in our independent pediatric dataset. We conducted fine-mapping and functional annotation through an integrative multi-omics approach and identified causal variants and potential target genes at each novel locus. Gene expression profile and gene-set enrichment analysis further suggested early developmental stage expression pattern and postsynaptic membrane compartment enrichment of candidate genes at the genome-wide significant loci of these neuropsychiatric disorders. Therefore, through a multi-omics approach, we identified novel genetic loci associated with the five neuropsychiatric disorders which may help to better understand the underlying molecular mechanism of neuropsychiatric diseases.

Integrative In Silico Analysis of Genome-Wide DNA Methylation Profiles in Schizophrenia

Schizophrenia (SZ) is a complex and severe psychiatric disorder, which has a global lifetime prevalence of 0.4% and a heritability of around 0.81. A number of epigenome-wide association studies (EWAS) have been carried out for SZ, with discordant results. The main aim of this study was to carry out an integrative in silico analysis of available genome-wide DNA methylation profiles in schizophrenia. In this work, an integration of multiple lines of evidence (top candidate genes from several EWAS and genome-wide expression and association data) was carried out, in order to identify top differentially methylated (DM) genes for SZ. In addition, functional enrichment and protein-protein interaction analyses were carried out. Several top differentially methylated genes, such as APC, CACNB2, and PRKN, were found, and an enrichment of binding sites for brain-expressed transcription factors, such as FOXO1, MYB, and ZIC3, was also observed. Moreover, a protein-protein interaction network showed a central role for DISC1 and ZNF688 genes, and experimentally validated targets of MIR-137, such as and KCNB2, NRXN1, and SYN2, were identified among DM genes. This is the first integrative in silico analysis of available genome-wide DNA methylation profiles in schizophrenia. This work identified novel candidate genes and pathways for SZ and provides the basis to explore their role in the pathogenesis of SZ in future studies.