Mapping genomic loci implicates genes and synaptic biology in schizophrenia

Schizophrenia has a heritability of 60-80%1, much of which is attributable to common risk alleles. Here, in a two-stage genome-wide association study of up to 76,755 individuals with schizophrenia and 243,649 control individuals, we report common variant associations at 287 distinct genomic loci. Associations were concentrated in genes that are expressed in excitatory and inhibitory neurons of the central nervous system, but not in other tissues or cell types. Using fine-mapping and functional genomic data, we identify 120 genes (106 protein-coding) that are likely to underpin associations at some of these loci, including 16 genes with credible causal non-synonymous or untranslated region variation. We also implicate fundamental processes related to neuronal function, including synaptic organization, differentiation and transmission. Fine-mapped candidates were enriched for genes associated with rare disruptive coding variants in people with schizophrenia, including the glutamate receptor subunit GRIN2A and transcription factor SP4, and were also enriched for genes implicated by such variants in neurodevelopmental disorders. We identify biological processes relevant to schizophrenia pathophysiology; show convergence of common and rare variant associations in schizophrenia and neurodevelopmental disorders; and provide a resource of prioritized genes and variants to advance mechanistic studies

Mapping genomic loci prioritises genes and implicates synaptic biology in schizophrenia

Schizophrenia has a heritability of 60–80%1, much of which is attributable to common risk alleles. Here, in a two-stage genome-wide association study of up to 76,755 individuals with schizophrenia and 243,649 control individuals, we report common variant associations at 287 distinct genomic loci. Associations were concentrated in genes that are expressed in excitatory and inhibitory neurons of the central nervous system, but not in other tissues or cell types. Using fine-mapping and functional genomic data, we identify 120 genes (106 protein-coding) that are likely to underpin associations at some of these loci, including 16 genes with credible causal non-synonymous or untranslated region variation. We also implicate fundamental processes related to neuronal function, including synaptic organization, differentiation and transmission. Fine-mapped candidates were enriched for genes associated with rare disruptive coding variants in people with schizophrenia, including the glutamate receptor subunit GRIN2A and transcription factor SP4, and were also enriched for genes implicated by such variants in neurodevelopmental disorders. We identify biological processes relevant to schizophrenia pathophysiology; show convergence of common and rare variant associations in schizophrenia and neurodevelopmental disorders; and provide a resource of prioritized genes and variants to advance mechanistic studies

Spatiotemporal Evolution of Functional Structure of Urban Agglomeration in Central Yunnan

This paper selects data related to each representative industry in the Central Yunnan Urban Agglomeration from 2010-2019 as the research sample, and analyzes the functional structure of the Central Yunnan Urban Agglomeration through spatial Gini coefficient, primacy and location quotient. The research results show that: the economic development level of Kunming, a city with high primacy, is insufficient. Moreover, the development differences within the Central Yunnan Urban Agglomeration are large enough and it’s hard to drive economic recovery. The industrial agglomeration of the Central Yunnan Urban Agglomeration is not high. There are fluctuating changes in industries that depend on the natural environment, and the epidemic has a large impact on the pillar industries as well. There are overlapping industrial functions within the Central Yunnan Urban Agglomeration. The complementarity of each function is not high enough, and the degree of regional economic integration is not enough, which is not conducive to economic recovery

Exploring the impact of ambient temperature on respiratory diseases admissions, length of Stay, and hospitalization costs in Lanzhou City, based on distributed lag non-linear model

This study was to explore the relationships between daily mean temperature and hospital admissions, length of stay and hospitalization costs for respiratory diseases, and to estimate the risk effects and burden of disease. A time-series analysis was conducted by distributed lag non-linear model (DLNM) to explore the exposure-lag-response relationships between daily mean temperature and hospital admissions, length of stay, and hospitalization costs for respiratory diseases. The total cumulative exposure between the daily admissions, length of stay and hospitalization costs of respiratory diseases and the daily mean temperature showed significant nonlinear relationships, all with a shape approximately “W”. Extremely low temperature presented the greatest risk to respiratory diseases of admissions, length of stay and hospitalization costs, with the relative risks of 1.66 (95 % CI:1.32–2.09), 1.71 (95 % CI:1.33–2.20), 2.09 (95 % CI:1.53–2.84), respectively. The risks caused by low temperatures have delayed effect, capable of generating higher risks within lag 21 days. In contrast, the effects of high temperatures on the three outcomes only in the short term. The relative risks of exposure to extremely cold weather for elderly patients were the greatest, which were 2.47 (95 % CI:1.89–3.24), 2.11 (95 % CI:1.58–2.81) and 2.59 (95 % CI:1.81–3.70), respectively. In Lanzhou city, both low and high temperatures posed a certain risk to the hospital admissions, length of stay and hospitalization costs of respiratory diseases. Cold temperature exposure is the main risk factor to increase the risks of the three outcomes, and its risks have significant lag effect. Elderly patients are vulnerable to cold temperature exposure

Quantitative Proteomic Analysis of the Metastasis-Inhibitory Mechanism of miR-193a-3p in Non-Small Cell Lung Cancer

Background: microRNAs can repress the expression of target genes by destabilizing their mRNAs or by inhibiting their translation. Our previous findings suggested that miR-193a-3p inhibited the progression of NSCLC both in vitro and in vivo. However, the biological processes and molecular pathways through which this miRNA exerts its positive effects are unknown. Methods: To explore the molecular mechanisms by which miR-193a-3p inhibited NSCLC metastasis, we investigated the changes in the protein profile of SPC-A-1sci (highly metastatic) cells in response to the up-regulation of miR-193a-3p expression using a proteomics approach (iTRAQ combined with NanoLC-MS/MS). Changes in the profiles of the expressed proteins were verified using western blotting and were analyzed using the DAVID and STRING programs. Results: In the two replicated experiments, 4962/4946 proteins were identified, and the levels of expression of 4923/4902 proteins were quantified. In total, 112 of these proteins were differentially expressed. Among them, the up-regulated levels of expression of two of the 62 proteins with up-regulated expression (PPP2R2A and GSN) and the down-regulated levels of expression four of the 50 proteins with down-regulated expression (LMNB2, UHRF1, G3BP1, and HNRNPU) were verified using western blotting. The bioinformatics analysis revealed the interactions and signaling networks of these differentially expressed proteins. Conclusion: miR-193a-3p inhibited the metastasis of lung cancer cells by deregulating the expression of tumor-related proteins. These findings may improve the understanding of the molecular mechanisms underlying the metastatic-inhibitory effect of miR-193a-3p on lung cancer cells

Atractylodin ameliorates bleomycin-induced pulmonary inflammation and fibrosis in mice

Introduction: Idiopathic pulmonary fibrosis (IPF) is a chronic, progressive disease. The commonly used drugs for the treatment of pulmonary fibrosis can only delay the damage of lung function but cannot prolong the life of patients. Atractylodin (ATR), a kind of herbal medicine that has been proven to protect anti-inflammation and attenuate acute lung injury, was investigated to determine whether it could provide a new idea for the treatment of IPF by reducing the inflammatory reaction and collagen formation in the process of pulmonary fibrosis. Methods: In vivo experiments, mice were divided into 6 groups, normal group, model, drug group (10 mg/kg, 30 mg/kg, 90 mg/kg) and positive control group (pirfenidone). Mice were given BLM through trachea, and after 24 h, normal saline, different concentrations of atractylodin and pirfenidone were given respectively. On 7 days, 14 days and 21 days, the weight, lung function, alveolar lavage fluid and lung tissue were tested. In vitro experiments to investigate the effect of atractylodin on fibroses, NIH3T3 cells were induced by TGF-β1 to detect the formation of cellular collagen and the phosphorylation level of Smad2/3 at different time points after their fibrosis. Results: The results showed that atractylodin could alleviate the lung function damage (FVC, FEV100, Tidal volume, tissue elastance) caused by BLM, reduce the inflammatory factors (IL-1β, IL-6, TNF-α), neutrophils and macrophage infiltration in the alveolar lavage fluid, as well as the formation and deposition of collagen (fibronectin, α-SMA, ColA1). In vitro studies have demonstrated that atractylodin can alleviate TGF-β1-induced pulmonary fibrosis by inhibiting the TGF-β1/Smad2/3 pathway. Conclusion: Atractylodin can alleviate the lung function damage and attenuate pulmonary fibrosis induced by BLM through inhibiting the TGF-β1/Smad2/3 pathway. This may provide new ideas for the treatment of IPF

Predicting regulatory variants with composite statistic

Motivation: Prediction and prioritization of human noncoding regulatory variants is critical for understanding the regulatory mechanisms of disease pathogenesis and promoting personalized medicine. Existing tools utilize functional genomics data and evolutionary information to evaluate the pathogenicity or regulatory functions of noncoding variants. However, different algorithms lead to inconsistent and even conflicting predictions. Combining multiple methods may increase accuracy in regulatory variant prediction. Results: Here, we compiled an integrative resource for predictions from eight different tools on functional annotation of noncoding variants. We further developed a composite strategy to integrate multiple predictions and computed the composite likelihood of a given variant being regulatory variant. Benchmarked by multiple independent causal variants datasets, we demonstrated that our composite model significantly improves the prediction performance. Availability: We implemented our model and scoring procedure as a tool, named PRVCS, which is freely available to academic and nonprofit usage at http://jjwanglab.org/PRVCS.Statistic

G Protein-Coupled Receptor 87 (GPR87) Promotes the Growth and Metastasis of CD133⁺ Cancer Stem-Like Cells in Hepatocellular Carcinoma

<div><p>Hepatocellular carcinoma (HCC) is a prevalent disease worldwide, and the majority of HCC-related deaths occur due to local invasion and distant metastasis. Cancer stem cells (CSCs) are a small subpopulation of cancer cells that have been hypothesized to be responsible for metastatic disease. Recently, we and others have identified a CSC population from human HCC cell lines and xenograft tumors characterized by their expression of CD133. However, the precise molecular mechanisms by which CD133⁺ cancer stem-like cells mediate HCC metastasis have not been sufficiently analyzed. Here, we have sorted HCC cells using CD133 as a cancer stem cell (CSC) marker by magnetic-activated cell sorting (MACS) and demonstrated that the CD133⁺ HCC cells not only possess greater migratory and invasive capacity <i>in vitro</i> but are also endowed with enhanced metastatic capacity <i>in vivo</i> and in human HCC specimens when compared to CD133⁻ HCC cells. Gene expression analysis of the CD133⁺ and CD133⁻ cells of the HCC line SMMC-7721 revealed that G protein-coupled receptor 87 (GPR87) is highly expressed in CD133⁺ HCC cells. In this study, we explored the role of GPR87 in the regulation of CD133 expression. We demonstrated that the overexpression of GPR87 up-regulated CD133 expression, promoted CSC-associated migratory and invasive properties <i>in vitro</i>, and increased tumor initiation <i>in vivo</i>. Conversely, silencing of GPR87 expression reduced the levels of CD133 expression. Conclusion: GPR87 promotes the growth and metastasis of CD133⁺ cancer stem-like cells, and our findings may reveal new targets for HCC prevention or therapy.</p> </div

Oxidative stress gene expression, DNA methylation, and gut microbiota interaction trigger Crohn’s disease: a multi-omics Mendelian randomization study

Background Oxidative stress (OS) is a key pathophysiological mechanism in Crohn’s disease (CD). OS-related genes can be affected by environmental factors, intestinal inflammation, gut microbiota, and epigenetic changes. However, the role of OS as a potential CD etiological factor or triggering factor is unknown, as differentially expressed OS genes in CD can be either a cause or a subsequent change of intestinal inflammation. Herein, we used a multi-omics summary data-based Mendelian randomization (SMR) approach to identify putative causal effects and underlying mechanisms of OS genes in CD. Methods OS-related genes were extracted from the GeneCards database. Intestinal transcriptome datasets were collected from the Gene Expression Omnibus (GEO) database and meta-analyzed to identify differentially expressed genes (DEGs) related to OS in CD. Integration analyses of the largest CD genome-wide association study (GWAS) summaries with expression quantitative trait loci (eQTLs) and DNA methylation QTLs (mQTLs) from the blood were performed using SMR methods to prioritize putative blood OS genes and their regulatory elements associated with CD risk. Up-to-date intestinal eQTLs and fecal microbial QTLs (mbQTLs) were integrated to uncover potential interactions between host OS gene expression and gut microbiota through SMR and colocalization analysis. Two additional Mendelian randomization (MR) methods were used as sensitivity analyses. Putative results were validated in an independent multi-omics cohort from the First Affiliated Hospital of Sun Yat-sen University (FAH-SYS). Results A meta-analysis from six datasets identified 438 OS-related DEGs enriched in intestinal enterocytes in CD from 817 OS-related genes. Five genes from blood tissue were prioritized as candidate CD-causal genes using three-step SMR methods: BAD, SHC1, STAT3, MUC1, and GPX3. Furthermore, SMR analysis also identified five putative intestinal genes, three of which were involved in gene–microbiota interactions through colocalization analysis: MUC1, CD40, and PRKAB1. Validation results showed that 88.79% of DEGs were replicated in the FAH-SYS cohort. Associations between pairs of MUC1–Bacillus aciditolerans and PRKAB1–Escherichia coli in the FAH-SYS cohort were consistent with eQTL–mbQTL colocalization. Conclusions This multi-omics integration study highlighted that OS genes causal to CD are regulated by DNA methylation and host-microbiota interactions. This provides evidence for future targeted functional research aimed at developing suitable therapeutic interventions and disease prevention

GPR87 mediates the expression of CD133 in HCC cell lines.

<p>(A) Relative mRNA expression of CD133 in SMMC-7721-lenti-CD133, HCC-LY5-lenti-CD133 and MHCC-97L-lenti-CD133 cells. (B) Relative mRNA expression of GPR87 in SMMC-7721-lenti-CD133, HCC-LY5-lenti-CD133 and MHCC-97L-lenti-CD133 cells. (C) Western blot of GPR87 and CD133 in SMMC-7721-lenti-CD133, HCC-LY5-lenti-CD133 and MHCC-97L-lenti-CD133 cells.</p