Associations between host gene expression, the mucosal microbiome, and clinical outcome in the pelvic pouch of patients with inflammatory bowel disease.

Dataset overview

Participants 205

Samples 255

Reuse readiness 8.9/10 evidence-backed score

Associations between host gene expression, the mucosal microbiome, and clinical outcome in the pelvic pouch of patients with inflammatory bowel disease.

Morgan XC, Kabakchiev B, Waldron L, Tyler AD, Tickle TL, Milgrom R, Stempak JM, Gevers D, et al. · Genome biology · 2015

Abstract

<h4>Background</h4>Pouchitis is common after ileal pouch-anal anastomosis (IPAA) surgery for ulcerative colitis (UC). Similar to inflammatory bowel disease (IBD), both host genetics and the microbiota are implicated in its pathogenesis. We use the IPAA model of IBD to associate mucosal host gene expression with mucosal microbiomes and clinical outcomes. We analyze host transcriptomic data and 16S rRNA gene sequencing data from paired biopsies from IPAA patients with UC and familial adenomatous polyposis. To achieve power for a genome-wide microbiome-transcriptome association study, we use principal component analysis for transcript and clade reduction, and identify significant co-variation between clades and transcripts.<h4>Results</h4>Host transcripts co-vary primarily with biopsy location and inflammation, while microbes co-vary primarily with antibiotic use. Transcript-microbe associations are surprisingly modest, but the most strongly microbially-associated host transcript pattern is enriched for complement cascade genes and for the interleukin-12 pathway. Activation of these host processes is inversely correlated with Sutterella, Akkermansia, Bifidobacteria, and Roseburia abundance, and positively correlated with Escherichia abundance.<h4>Conclusions</h4>This study quantifies the effects of inflammation, antibiotic use, and biopsy location upon the microbiome and host transcriptome during pouchitis. Understanding these effects is essential for basic biological insights as well as for well-designed and adequately-powered studies. Additionally, our study provides a method for profiling host-microbe interactions with appropriate statistical power using high-throughput sequencing, and suggests that cross-sectional changes in gut epithelial transcription are not a major component of the host-microbiome regulatory interface during pouchitis.

doi:10.1186/s13059-015-0637-x ↗ PMID 25887922 ↗ PMC4414286 ↗

Study facts

Organism: Homo sapiens
Platform: Illumina MiSeq v2
Age group: adult
Disease groups: —
Anatomical sites: —

Data availability

Analysis code

Strengths & limitations for reuse

Strengths

Raw reads are advertised
Feature/OTU tables are advertised
Taxonomic tables are advertised
Analysis code is available
Participant-to-sample mapping is available
Participant counts are documented
Sample counts are documented

Extraction evidence & provenance

Each extracted field is shown with the source excerpt and location used to resolve it.

Assay

Field	Value	Evidence
`assay.paired_end`	True	generating paired-end reads of 175 bp in each direction. Section `Methods—16S profiling and sequencing`, offset 75200
`assay.platform`	Illumina MiSeq v2	Sequencing was performed on the Illumina MiSeq v2 platform Section `Methods—16S profiling and sequencing`, offset 75000
`assay.primers_reported`	True	Primers: 515 F [GTGCCAGCMGCCGCGGTAA] and 806R [GGACTACHVGGGTWTCTAAT]. Section `Methods—16S profiling and sequencing`, offset 74200
`assay.read_depth_reported`	29914	A mean sequence depth of 29,914 sequences/sample was obtained Section `Methods—Bioinformatic processing of sequences`, offset 77300
`assay.read_length`	175	generating paired-end reads of 175 bp in each direction. Section `Methods—16S profiling and sequencing`, offset 75200
`assay.sequencing_type`	amplicon_16s	The 16S gene dataset consists of Illumina MiSeq sequences targeting the V4 variable region. Section `Methods—16S profiling and sequencing`, offset 69000
`assay.target_region`	V4	Illumina MiSeq sequences targeting the V4 variable region. Section `Methods—16S profiling and sequencing`, offset 73500

Cohort

Field	Value	Evidence
`cohort.age_group`	adult	The cohort consisted of 265 patients (51% women) aged between 18 and 78 years Section `Results`, offset 6200
`cohort.disease_activity_metadata_available`	True	to numerically score inflammation, the severity of objective traits was graded Section `Methods—Patient cohort`, offset 58000
`cohort.study_design`	cross_sectional	a large, metadata-rich, cross-sectional cohort Section `Results`, offset 4800
`cohort.total_participants`	205	we analyzed 205 IPAA patients with biopsies collected from the pouch and afferent limb Section `study.description`, offset —
`cohort.treatment_exposure_documented`	True	For this cohort, antibiotic use was reported as ‘true’ if patients had taken antibiotics in the 30 days prior to biopsy collections. Section `Methods—Patient cohort`, offset 62000
`cohort.treatment_response_metadata_available`	True	Acute Pouchitis (AP) based on historical or current documentation of inflammation of the pouch resolving after a single course of antibiotics Section `Methods—Patient cohort`, offset 34300

Data_Assets

Field	Value	Evidence
`data_assets.analysis_code`	True	Input files used for MaAsLin are available from [72]. Section `Using multivariate analysis with linear modeling to model host/microbe metadata associations`, offset 89000
`data_assets.feature_or_otu_table`	True	this pipeline picks OTUs using a reference-based method and constructs an OTU table Section `Methods—Bioinformatic processing of sequences`, offset 63400
`data_assets.open_access`	True	"isOpenAccess": "Y" Section `Publication metadata`, offset —
`data_assets.pipeline_or_tool_versions`	True	a data curation pipeline implemented in QIIME 1.5.0 as pick_reference_otus.py Section `Methods—Bioinformatic processing of sequences`, offset 72400
`data_assets.qc_or_negative_controls_reported`	True	The resulting OTU tables are checked for mislabeling and contamination Section `Methods—Bioinformatic processing of sequences`, offset 63500
`data_assets.raw_reads`	True	16S sequence data for this project have been filtered to remove human sequences and are publicly available Section `Data availability`, offset 73000
`data_assets.sample_metadata`	True	Metadata are available at [ 74 ]. Section `Data availability`, offset 81400
`data_assets.taxonomic_table`	True	Taxonomy is assigned using the Greengenes predefined taxonomy map Section `Methods—Bioinformatic processing of sequences`, offset 72700

Specimens

Field	Value	Evidence
`specimens.body_site`	pouch and afferent limb	with biopsies collected from the pouch and afferent limb Section `study.description`, offset —
`specimens.inflamed_status_available`	True	the inflammation score was defined as the sum of these traits Section `Methods—Patient cohort`, offset 58000
`specimens.longitudinal_sampling`	False	a large, metadata-rich, cross-sectional cohort Section `Results`, offset 4800
`specimens.number_of_samples`	255	from a total of 255 samples representing 204 individuals Section `Results`, offset 6500
`specimens.participant_to_sample_mapping_available`	True	255 samples representing 204 individuals; these comprised 196 PPI samples and 59 pouch samples. Section `Results`, offset 6500
`specimens.sample_type`	mucosal_biopsy	Tissue biopsies were obtained from the mid-portion of the pouch and the PPI during pouchoscopy. Section `Methods—Sample collection`, offset 64000