Gene Expression Nebulas
A data portal of transcriptomic profiles analyzed by a unified pipeline across multiple species

Gene Expression Nebulas

A data portal of transcriptome profiles across multiple species

PRJNA648957: Multi-omic data integration allows baseline immune signatures to predict hepatitis B vaccine response in a small cohort

Source: NCBI / GSE155198
Submission Date: Jul 27 2020
Release Date:
Update Date: Dec 21 2020

Summary: Vaccination remains one of the most effective means of reducing the burden of infectious diseases globally. Climate change is projected to lead to an increase in the burden of vector- and water-borne, as well as zoonotic infectious diseases including COVID-19. Improving our understanding of the molecular basis for effective vaccine response is of paramount importance if we are to ensure the success of future vaccine development efforts. We applied cutting edge multi-omics approaches to characterize temporal molecular responses following vaccination with hepatitis B virus (HBV) vaccine. Data were integrated across cellular, epigenomic, transcriptomic, proteomic, and fecal microbiome profiles, and correlated to final hepatitis B antibody titres. Using both a molecular-interaction network integration method (NetworkAnalyst) and a data-driven integration approach (DIABLO), we overcame the p>>>n problem and uncovered baseline molecular patterns and pathways associated with more effective vaccine responses to HBV. Correlations were identified with signalling pathways such as JAK-STAT and interleukin signalling, Toll-Like Receptor Cascades, interferon signalling and Th17 cell differentiation. This study provides further evidence that baseline cellular and molecular characteristics of an individual’s immune system influence vaccine responses, and highlights the utility of integrating information across many parallel molecular datasets

Overall Design: A total of 75 samples (15 participants, each sampled at five time points) representing both pre- and post-vaccination blood draws

GEN Datasets:
GEND000409
Strategy:
Species:
Tissue:
Healthy Condition:
Cell Type:
Cell Line:
Development Stage:
Protocol
Growth Protocol: -
Treatment Protocol: -
Extract Protocol: PAXGene RNA purification kit was used on collected whole blood as per manufacturer's instructions
Library Construction Protocol: KAPA stranded RNA-Seq library preparation kit was used as per manufacturer's guidelines
Sequencing
Molecule Type: Poly(A)+ RNA
Library Source:
Library Layout: SINGLE
Library Strand: Forward
Platform: ILLUMINA
Instrument Model: Illumina HiSeq 2500
Strand-Specific: Specific
Samples
Basic Information:
Sample Characteristic:
Biological Condition:
Experimental Variables:
Protocol:
Sequencing:
Assessing Quality:
Analysis:
Data Resource GEN Sample ID GEN Dataset ID Project ID BioProject ID Sample ID Sample Name BioSample ID Sample Accession Experiment Accession Release Date Submission Date Update Date Species Race Ethnicity Age Age Unit Gender Source Name Tissue Cell Type Cell Subtype Cell Line Disease Disease State Development Stage Mutation Phenotype Case Detail Control Detail Growth Protocol Treatment Protocol Extract Protocol Library Construction Protocol Molecule Type Library Layout Strand-Specific Library Strand Spike-In Strategy Platform Instrument Model Cell Number Reads Number Gbases AvgSpotLen1 AvgSpotLen2 Uniq Mapping Rate Multiple Mapping Rate Coverage Rate
Publications
Multi-Omic Data Integration Allows Baseline Immune Signatures to Predict Hepatitis B Vaccine Response in a Small Cohort.
Frontiers in immunology . 2020-11-30 [PMID: 33329547]