Psychiatric disorders are a group of complex psychological syndromes with high prevalence. It has been reported that gut microbiota has a dominant influence on the risks of psychiatric disorders through gut microbiota–brain axis. We extended the classic gene set enrichment analysis (GSEA) approach to detect the association between gut microbiota and complex diseases using published genome-wide association study (GWAS) and GWAS of gut microbiota summary data. We applied our approach to real GWAS data sets of five psychiatric disorders, including attention deficiency/hyperactive disorder (ADHD), autism spectrum disorder (AUT), bipolar disorder (BD), schizophrenia (SCZ) and major depressive disorder (MDD). To evaluate the performance of our approach, we also tested the genetic correlations of obesity and type 2 diabetes with gut microbiota. We identified several significant associations between psychiatric disorders and gut microbiota, such as ADHD and genus Desulfovibrio (P = 0.031), order Clostridiales (P = 0.034). For AUT, association signals were observed for genera Bacteroides (P = 0.012) and Desulfovibrio (P = 0.033). Genus Desulfovibrio (P = 0.005) appeared to be associated with BD. For MDD, association signals were observed for genus Desulfovibrio (P = 0.003), order Clostridiales (P = 0.004), family Lachnospiraceae (P = 0.007) and genus Bacteroides (P = 0.007). Genus Desulfovibrio (P = 0.012) and genus Bacteroides (P = 0.038) appeared to be associated with SCZ. Our study results provide novel clues for revealing the roles of gut microbiota in psychiatric disorders. This study also illustrated the good performance of GSEA approach for exploring the relationships between gut microbiota and complex diseases.

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Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease with strong genetic components. To identity novel risk variants for ALS, utilizing the latest genome-wide association studies (GWAS) and eQTL study data, we conducted a genome-wide expression association analysis by summary data-based Mendelian randomization (SMR) method. Summary data were derived from a large-scale GWAS of ALS, involving 12577 cases and 23475 controls. The eQTL annotation dataset included 923,021 cis-eQTL for 14,329 genes and 4732 trans-eQTL for 2612 genes. Genome-wide single gene expression association analysis was conducted by SMR software. To identify ALS-associated biological pathways, the SMR analysis results were further subjected to gene set enrichment analysis (GSEA). SMR single gene analysis identified one significant and four suggestive genes associated with ALS, including C9ORF72 (P value = 7.08 × 10), NT5C3L (P value = 1.33 × 10), GGNBP2 (P value = 1.81 × 10), ZNHIT3(P value = 2.94 × 10), and KIAA1600(P value = 9.97 × 10). GSEA identified 7 significant biological pathways, such as PEROXISOME (empirical P value = 0.006), GLYCOLYSIS_GLUCONEOGENESIS (empirical P value = 0.043), and ARACHIDONIC_ACID_ METABOLISM (empirical P value = 0.040). Our study provides novel clues for the genetic mechanism studies of ALS.

Inflammatory bowel disease (IBD) is a complex disease, resulting from abnormal immune response to intestinal tract microbiota in genetically susceptible individuals. Crohn's disease and ulcerative colitis (UC) are the two major types of IBD. Transcriptome‐wide association study (TWAS) of IBD was first performed using a large‐scale genome‐wide association study summary data sets of IBD. The FUSION software was applied for TWAS, considering various tissues and cells. The genes identified by TWAS were then validated by the gene expression profiling data sets of IBD. The functional annotation and potential pathways of common differentially expressed genes were further subjected to gene ontology (GO) and pathway enrichment analysis. Integrative analysis of TWAS and messenger RNA (mRNA) expression data detected several tissues related common genes for UC, such as HLA‐DRB1 (PTWAS = 0.024; mRNA expression ratio = 1.700) and TAP2 in colon (P TWAS = 0.047; mRNA expression ratio = 2.170). Further comparing the GO enrichment analysis results of TWAS and mRNA expression data, we identified 11 common GO terms for UC, such as plasma membrane (P value = 5.08 × 10−10) in intestinal tissues and immune response (P = 0.001) in peripheral blood. We also detected several common pathways for UC, including cell adhesion molecules (P = 0.003) in intestinal tissues, IBD (P = 0.049) in whole blood and phagosome (P = 0.0003) in peripheral blood. Our study results provide novel clues for understanding the genetic mechanism of IBD.

Context: Osteoporosis is a metabolic bone disease. The effect of blood metabolites on the development of osteoporosis remains elusive.Objective: To explore the relationship between blood metabolites and osteoporosis.Design and Methods: We used 2286 unrelated white subjects for the discovery samples and 3143 unrelated white subjects from the Framingham Heart Study (FHS) for the replication samples. The bone mineral density (BMD) was measured using dual-energy X-ray absorptiometry. Genome-wide single nucleotide polymorphism (SNP) genotyping was performed using Affymetrix Human SNP Array 6.0 (for discovery samples) and Affymetrix SNP 500K and 50K array (for FHS replication samples). The SNP sets significantly associated with blood metabolites were obtained from a reported whole-genome sequencing study. For each subject, the genetic risk score of the metabolite was calculated from the genotype data of the metabolite-associated SNP sets. Pearson correlation analysis was conducted to evaluate the potential effect of blood metabolites on the variations in bone phenotypes; 10,000 permutations were conducted to calculate the empirical P value and false discovery rate.Results: We analyzed 481 blood metabolites. We identified multiple blood metabolites associated with hip BMD, such as 1,5-anhydroglucitol (P discovery , 0.0001; P replication = 0.0361), inosine (P discovery = 0.0018; P replication = 0.0256), theophylline (P discovery = 0.0048; P replication = 0.0433, gamma-glutamyl methionine (P discovery = 0.0047; P replication = 0.0471), 1-linoleoyl-2-arachidonoyl-GPC (18:2/20:4n6; P discovery = 0.0018; P replication = 0.0390), and X-12127 (P discovery = 0.0002; P replication = 0.0249). Conclusions:Our results suggest a modest effect of blood metabolites on the variations of BMD and identified several candidate blood metabolites for osteoporosis. (J Clin Endocrinol Metab 103: 1850-1855 O steoporosis is a metabolic bone disease, characterized as low bone mass and increased bone fragility. It has been reported that currently .40 million people are at risk of bone fractures, and the incidence of osteoporotic fractures is increasing rapidly in the United States (1). Bone mineral density (BMD) is commonly used to 1850https://academic.oup.com/jcem

Central nervous system involvement is common in HIV infection. We determined the relationship between T-cell subsets and viral load in the cerebrospinal fluid (CSF) of therapy-naive, asymptomatic HIV-infected individuals. A shift from naive to effector-memory CD8 T cells was observed in the CSF of HIV-infected individuals compared with controls. The HIV load strongly correlated with CD8 T cells in CSF. Effector-memory CD8 T cells were positively and effector CD8 T cells were negatively associated with viral replication in CSF.

AimOsteoarthritis (OA) is caused by complex interactions between genetic and environmental factors. Epigenetic mechanisms control the expression of genes and are likely to regulate the OA transcriptome. We performed integrative genomic analyses to define methylation-gene expression relationships in osteoarthritic cartilage.Patients and MethodsGenome-wide DNA methylation profiling of articular cartilage from five patients with OA of the knee and five healthy controls was conducted using the Illumina Infinium HumanMethylation450 BeadChip (Illumina, San Diego, California). Other independent genome-wide mRNA expression profiles of articular cartilage from three patients with OA and three healthy controls were obtained from the Gene Expression Omnibus (GEO) database. Integrative pathway enrichment analysis of DNA methylation and mRNA expression profiles was performed using integrated analysis of cross-platform microarray and pathway software. Gene ontology (GO) analysis was conducted using the Database for Annotation, Visualization and Integrated Discovery (DAVID).ResultsWe identified 1265 differentially methylated genes, of which 145 are associated with significant changes in gene expression, such as DLX5, NCOR2 and AXIN2 (all p-values of both DNA methylation and mRNA expression < 0.05). Pathway enrichment analysis identified 26 OA-associated pathways, such as mitogen-activated protein kinase (MAPK) signalling pathway (p = 6.25 × 10-4), phosphatidylinositol (PI) signalling system (p = 4.38 × 10-3), hypoxia-inducible factor 1 (HIF-1) signalling pathway (p = 8.63 × 10-3 pantothenate and coenzyme A (CoA) biosynthesis (p = 0.017), ErbB signalling pathway (p = 0.024), inositol phosphate (IP) metabolism (p = 0.025), and calcium signalling pathway (p = 0.032).ConclusionWe identified a group of genes and biological pathwayswhich were significantly different in both DNA methylation and mRNA expression profiles between patients with OA and controls. These results may provide new clues for clarifying the mechanisms involved in the development of OA.Cite this article: A. He, Y. Ning, Y. Wen, Y. Cai, K. Xu, Y. Cai, J. Han, L. Liu, Y. Du, X. Liang, P. Li, Q. Fan, J. Hao, X. Wang, X. Guo, T. Ma, F. Zhang. Use of integrative epigenetic and mRNA expression analyses to identify significantly changed genes and functional pathways in osteoarthritic cartilage. Bone Joint Res 2018;7:343–350. DOI: 10.1302/2046-3758.75.BJR-2017-0284.R1.

A novel double-stranded RNA (dsRNA) mycovirus, designated Magnaporthe oryzae partitivirus 1 (MoPV1), was isolated from a strain of the plant pathogenic fungus Magnaporthe oryzae. The MoPV1 genome has two dsRNA genome segments. The larger segment (1763 bp) has a single open reading frame (ORF) with a conserved RNA-dependent RNA polymerase (RdRp) domain. The smaller segment (1491 bp) contains a single ORF encoding a putative coat protein (CP). Homology searches and phylogenetic analysis indicated that MoPV1 is a new member of the genus Gammapartitivirus. This is the first report of a mycovirus of the family Partitiviridae identified in Magnaporthe oryzae.