Metagenomic sequencing of gut microbiota associated with autism spectrum disorders patients
Ontology highlight
ABSTRACT:
ORGANISM(S): feces metagenome
PROVIDER: GSE113540 | GEO | 2020/09/30
REPOSITORIES: GEO
Similar Datasets
Project description:Here we report 16S rRNA data in gut microbiota of autism spectrum disorders compared with healthy volunteers. A total of 1322 operational taxonomic units (OTUs) were identified in the sequence data. The Bacteroidetes and Firmicutes were both dominated phylum in ausitic subjects and healthy controls. Phylum level analysis showed a clear alteration of the bacterial gut community in ASD characterized by a higher Firmicutes (P < 0.05), Proteobacteria (P < 0.001), and Actinobacteria (P < 0.001) than that in healthy controls. However, Bacteroidetes were significantly decreased in ASD patients (P < 0.001).
2020-09-30 | GSE113690 | GEO
Project description:Interventions: Group 1: Surgical patients undergoing surgery for colorectal cancer: immunophenotyping by PBMCs and metagenomic analyses from stool, mucosa, and saliva samples perioperatively and during oncologic follow-up.
Group 2: oncologic patients with chemo- / immune therapy without recent surgery:
Immunophenotyping by PBMCs and metagenomic analyses from stool, mucosa and saliva samples during therapy and oncological follow-up.
Group 3: healthy controls:
Immunophenotyping by PBMCs and metagenomic analyses from stool, mucosa, and saliva samples at the time of screening colonoscopy.
Primary outcome(s): Difference in the differential abundance of the colonic mucosa of patients with CRC vs. healthy controls for evaluation as diagnostic biomarkers based on metagenomic analyzes (microbial pattern)
Study Design: Allocation: ; Masking: ; Control: ; Assignment: ; Study design purpose: diagnostic
| 2439680 | ecrin-mdr-crc
Project description:<b>Background:</b> Autism spectrum disorder (ASD) is defined as a pervasive developmental disorder which is caused by genetic and environmental risk factors. Besides the core behavioral symptoms, accumulated results indicate children with ASD also share some metabolic abnormalities. <b>Objectives:</b> To analyze the comprehensive metabolic profiles in both of the first-morning urine and plasma samples collected from the same cohort of autistic boys. <b>Methods:</b> In this study, 30 autistic boys and 30 tightly matched healthy control (HC) boys (age range: 2.4~6.7 years) were recruited. First-morning urine and plasma samples were collected and the liquid chromatography-mass spectrometry (LC-MS) was applied to obtain the untargeted metabolic profiles. The acquired data were processed by multivariate analysis and the screened metabolites were grouped by metabolic pathway. <b>Results:</b> Different discriminating metabolites were found in plasma and urine samples. Notably, taurine and catechol levels were decreased in urine but increased in plasma in the same cohort of ASD children. Enriched pathway analysis revealed that perturbations in taurine and hypotaurine metabolism, phenylalanine metabolism, and arginine and proline metabolism could be found in both of the plasma and urine samples. <b>Conclusion:</b> These preliminary results suggest that a series of common metabolic perturbations exist in children with ASD, and confirmed the importance to have a comprehensive analysis of the metabolites in different biological samples to reveal the full picture of the complex metabolic patterns associated with ASD. Further targeted analyses are needed to validate these results in a larger cohort.
2022-03-02 | MTBLS2421 | MetaboLights
Project description:Using DNA microarray as a global approach to understanding the molecular basis of autism, we examined gene expression profiling in peripheral blood from 21 young adults with autism spectrum disorder (ASD) and healthy mothers having children with ASD, between whom there was no blood relationship. Several genes which were significantly changed in the ASD group comparing with their age- and gender-matched healthy subjects were mainly involved in cell morphology, cellular assembly and organization, and nerve system development and function. In addition, mothers having children with ASD possessed a unique gene expression signature shown as significant alterations of protein synthesis despite of their nonautistic diagnostic status. Moreover, an ASD-associated gene expression signature was commonly observed in both individuals with ASD and healthy mothers having children with ASD. Total RNA was prepared from venous blood which was taken from each subject. Gene expression profiling of venous blood from subjects with ASD (21), the healthy women who had children with ASD (21) and their age- and gender-matched healthy subjects (42) were obtained using a whole human genome oligonucleotide microarray (Agilent 44K Human whole genome array G4112F, GPL6480) to measure gene expression in these samples according to the manufacture’s protocol. The one GSM sample of microarray analysis was made by individual subject. Differentially expressed genes were determined across all rationed expression values for age- and gender-matched pairs (ASD vs. control, asdMO vs. ctrlMO) using Genespling analysis.
2011-01-13 | E-GEOD-26415 | biostudies-arrayexpress
Project description:Autism spectrum disorders (ASD) are neurodevelopmental disorders characterized by delayed/abnormal language development, deficits in social interaction, repetitive behaviors and restricted interests. The heterogeneity in clinical presentation of ASD, likely due to different etiologies, complicates genetic/biological analyses of these disorders. DNA microarray analyses were conducted on 116 lymphoblastoid cell lines (LCL) from individuals with idiopathic autism who are divided into 3 phenotypic subgroups according to severity scores from the commonly used Autism Diagnostic Interview-Revised questionnaire and age-matched, nonautistic controls. Statistical analyses of gene expression data from control LCL against that of LCL from ASD probands identify genes for which expression levels are either quantitatively or qualitatively associated with phenotypic severity. Comparison of the significant differentially expressed genes from each subgroup relative to the control group reveals differentially expressed genes unique to each subgroup as well as genes in common across subgroups. Among the findings unique to the most severely affected ASD group are genes that regulate circadian rhythm, which has been shown to have multiple effects on neurological as well as metabolic functions commonly dysregulated in autism. Among the genes common to all 3 subgroups of ASD are 5 novel genes which appear to associate with androgen sensitivity, which may underlie the strong 4:1 bias towards affected males. Gene expression profiling of 116 LCL from autistic (87) and nonautistic (29) individuals were obtained using a custom-printed DNA microarray containing 39,936 elements (TIGR 40K Human array, GPL3427) and a reference design in which each sample was compared to the Stratagene Universal Human RNA standard. The 87 autistic samples were divided into phenotypic subgroups (language, mild, savant) on the basis of cluster analyses of scores from an autism diagnostic questionnaire, the Autism Diagnostic Interview-Revised instrument. Differentially expressed genes were determined for all autistic vs. control groups, as well as for each of 3 phenotypic ASD groups and controls.
2010-05-17 | E-GEOD-15402 | biostudies-arrayexpress
Project description:We used SOMAscan to measure >1300 analytes in sera from healthy controls and patients with sJIA, MAS, sJIA-LD and other related diseases.
2022-02-28 | GSE197546 | GEO
Project description:Next-Generation-Sequencing (NGS) technologies have led to important improvement in the detection of new or unrecognized infective agents, related to infectious diseases. In this context, NGS high-throughput technology can be used to achieve a comprehensive and unbiased sequencing of the nucleic acids present in a clinical sample (i.e. tissues). Metagenomic shotgun sequencing has emerged as powerful high-throughput approaches to analyze and survey microbial composition in the field of infectious diseases. By directly sequencing millions of nucleic acid molecules in a sample and matching the sequences to those available in databases, pathogens of an infectious disease can be inferred. Despite the large amount of metagenomic shotgun data produced, there is a lack of a comprehensive and easy-use pipeline for data analysis that avoid annoying and complicated bioinformatics steps. Here we present HOME-BIO, a modular and exhaustive pipeline for analysis of biological entity estimation, specific designed for shotgun sequenced clinical samples. HOME-BIO analysis provides comprehensive taxonomy classification by querying different source database and carry out main steps in metagenomic investigation. HOME-BIO is a powerful tool in the hand of biologist without computational experience, which are focused on metagenomic analysis. Its easy-to-use intrinsic characteristic allows users to simply import raw sequenced reads file and obtain taxonomy profile of their samples.
2021-07-26 | E-MTAB-9189 | biostudies-arrayexpress
Project description:Next-Generation-Sequencing (NGS) technologies have led to important improvement in the detection of new or unrecognized infective agents, related to infectious diseases. In this context, NGS high-throughput technology can be used to achieve a comprehensive and unbiased sequencing of the nucleic acids present in a clinical sample (i.e. tissues). Metagenomic shotgun sequencing has emerged as powerful high-throughput approaches to analyze and survey microbial composition in the field of infectious diseases. By directly sequencing millions of nucleic acid molecules in a sample and matching the sequences to those available in databases, pathogens of an infectious disease can be inferred. Despite the large amount of metagenomic shotgun data produced, there is a lack of a comprehensive and easy-use pipeline for data analysis that avoid annoying and complicated bioinformatics steps. Here we present HOME-BIO, a modular and exhaustive pipeline for analysis of biological entity estimation, specific designed for shotgun sequenced clinical samples. HOME-BIO analysis provides comprehensive taxonomy classification by querying different source database and carry out main steps in metagenomic investigation. HOME-BIO is a powerful tool in the hand of biologist without computational experience, which are focused on metagenomic analysis. Its easy-to-use intrinsic characteristic allows users to simply import raw sequenced reads file and obtain taxonomy profile of their samples.
2021-07-26 | E-MTAB-9191 | biostudies-arrayexpress
Project description:Autism spectrum disorder (ASD) manifests as alterations in complex human behaviors including social communication and stereotypies. In addition to genetic risks, the gut microbiome differs between typically-developing (TD) and ASD individuals, though it remains unclear whether the microbiome contributes to symptoms. We transplanted gut microbiota from human donors with ASD and TD controls into germ-free mice, and reveal that colonization with ASD microbiota was sufficient to induce hallmark autistic behaviors. The brains of mice colonized with ASD microbiota display alternative splicing of ASD-relevant genes. Microbiome and metabolome profiles of mice harboring human microbiota predict that specific bacterial taxa and their metabolites modulate ASD behaviors. Indeed, treatment of an ASD mouse model with candidate microbial metabolites improves behavioral abnormalities and affects neuronal excitability in the brain. We propose that the gut microbiome modulates behaviors in mice via production of neuroactive metabolites, suggesting that gut-brain connections contribute to the pathophysiology of ASD.
2019-07-04 | MTBLS726 | MetaboLights
Project description:Healthy danish metagenomic samples
| PRJEB41786 | ENA