The University of Southampton
University of Southampton Institutional Repository
Warning ePrints Soton is experiencing an issue with some file downloads not being available. We are working hard to fix this. Please bear with us.

OnPLS-based multi-block data integration: a multivariate approach to interrogating biological interactions in asthma

OnPLS-based multi-block data integration: a multivariate approach to interrogating biological interactions in asthma
OnPLS-based multi-block data integration: a multivariate approach to interrogating biological interactions in asthma
Integration of multi-omics data remains a key challenge in fulfilling the potential of comprehensive systems biology. Multiple-block orthogonal projections to latent structures (OnPLS) is a projection method that simultaneously models multiple data matrices, reducing feature space without relying on a priori biological knowledge. In order to improve the interpretability of OnPLS models, the associated multi-block variable influence on orthogonal projections (MB-VIOP) method is used to identify variables with the highest contribution to the model. This study combined OnPLS and MB-VIOP with interactive visualisation methods to interrogate an exemplar multi-omics study, using a subset of 22 individuals from an asthma cohort. Joint data structure in six data blocks was assessed: transcriptomics; metabolomics; targeted assays for sphingolipids, oxylipins, and fatty acids; and a clinical block including lung function, immune cell differentials, and cytokines. The model identified 7 components, 2 of which had contributions from all blocks (globally joint structure), and 5 that had contributions from 2-5 blocks (locally joint structure). Components 1 and 2 were the most informative, identifying differences between healthy controls and asthmatics, and a disease-sex interaction, respectively. The interactions between features selected by MB-VIOP were visualised using chord plots, yielding putative novel insights into asthma disease pathogenesis, the effects of asthma treatment, and biological roles of uncharacterised genes. For example, the gene ATP6V1G1, which has been implicated in osteoporosis, correlated with metabolites that are dysregulated by inhaled corticoid steroids (ICS), providing insight into the mechanisms underlying bone density loss in asthma patients taking ICS. These results show the potential for OnPLS, combined with MB-VIOP variable selection and interaction visualisation techniques, to generate hypotheses from multi-omics studies and inform biology.
0003-2700
13400-13408
Reinke, Stacey
8ae0da28-99c5-431a-974b-b684cd3c2a3d
Galindo-Prieto, Beatriz
d289454f-6d42-4ea3-9486-7ff07bfed978
Skotare, Tomas
5fdc57d2-5088-47b2-84eb-41ba311cde64
Broadhurst, David Iain
fcfbbcdc-73d1-4c85-a3bc-709d4b521c8f
Singhania, Akul
322f628d-5374-49ec-b7d7-13bb3885d636
Horowitz, Daniel
0a32e660-bac1-4ad1-a2a1-67bc9743ed46
Djukanovic, Ratko
d9a45ee7-6a80-4d84-a0ed-10962660a98d
Hinks, Timothy
97bf168b-fd21-4e42-a4cf-34f85abe9e74
Geladi, Paul
167270d6-dad1-4cf4-b091-4b7e409b63fd
Trygg, Johan
80b576ec-b1db-47dc-bdb7-c6258e423526
Wheelock, Craig E.
a22e130a-c8b7-4fdf-ad52-fc39635063bc
Reinke, Stacey
8ae0da28-99c5-431a-974b-b684cd3c2a3d
Galindo-Prieto, Beatriz
d289454f-6d42-4ea3-9486-7ff07bfed978
Skotare, Tomas
5fdc57d2-5088-47b2-84eb-41ba311cde64
Broadhurst, David Iain
fcfbbcdc-73d1-4c85-a3bc-709d4b521c8f
Singhania, Akul
322f628d-5374-49ec-b7d7-13bb3885d636
Horowitz, Daniel
0a32e660-bac1-4ad1-a2a1-67bc9743ed46
Djukanovic, Ratko
d9a45ee7-6a80-4d84-a0ed-10962660a98d
Hinks, Timothy
97bf168b-fd21-4e42-a4cf-34f85abe9e74
Geladi, Paul
167270d6-dad1-4cf4-b091-4b7e409b63fd
Trygg, Johan
80b576ec-b1db-47dc-bdb7-c6258e423526
Wheelock, Craig E.
a22e130a-c8b7-4fdf-ad52-fc39635063bc

Reinke, Stacey, Galindo-Prieto, Beatriz, Skotare, Tomas, Broadhurst, David Iain, Singhania, Akul, Horowitz, Daniel, Djukanovic, Ratko, Hinks, Timothy, Geladi, Paul, Trygg, Johan and Wheelock, Craig E. (2018) OnPLS-based multi-block data integration: a multivariate approach to interrogating biological interactions in asthma. Analytical Chemistry, 90 (22), 13400-13408. (doi:10.1021/acs.analchem.8b03205).

Record type: Article

Abstract

Integration of multi-omics data remains a key challenge in fulfilling the potential of comprehensive systems biology. Multiple-block orthogonal projections to latent structures (OnPLS) is a projection method that simultaneously models multiple data matrices, reducing feature space without relying on a priori biological knowledge. In order to improve the interpretability of OnPLS models, the associated multi-block variable influence on orthogonal projections (MB-VIOP) method is used to identify variables with the highest contribution to the model. This study combined OnPLS and MB-VIOP with interactive visualisation methods to interrogate an exemplar multi-omics study, using a subset of 22 individuals from an asthma cohort. Joint data structure in six data blocks was assessed: transcriptomics; metabolomics; targeted assays for sphingolipids, oxylipins, and fatty acids; and a clinical block including lung function, immune cell differentials, and cytokines. The model identified 7 components, 2 of which had contributions from all blocks (globally joint structure), and 5 that had contributions from 2-5 blocks (locally joint structure). Components 1 and 2 were the most informative, identifying differences between healthy controls and asthmatics, and a disease-sex interaction, respectively. The interactions between features selected by MB-VIOP were visualised using chord plots, yielding putative novel insights into asthma disease pathogenesis, the effects of asthma treatment, and biological roles of uncharacterised genes. For example, the gene ATP6V1G1, which has been implicated in osteoporosis, correlated with metabolites that are dysregulated by inhaled corticoid steroids (ICS), providing insight into the mechanisms underlying bone density loss in asthma patients taking ICS. These results show the potential for OnPLS, combined with MB-VIOP variable selection and interaction visualisation techniques, to generate hypotheses from multi-omics studies and inform biology.

Text
Reinke et al_OnPLS_manuscript_20180703_Author Accepted (1) - Accepted Manuscript
Download (15MB)

More information

Accepted/In Press date: 18 October 2018
e-pub ahead of print date: 18 October 2018
Published date: 20 November 2018

Identifiers

Local EPrints ID: 425750
URI: http://eprints.soton.ac.uk/id/eprint/425750
ISSN: 0003-2700
PURE UUID: 7c0b4c42-2453-4edd-a9da-ff3333815e9a
ORCID for Ratko Djukanovic: ORCID iD orcid.org/0000-0001-6039-5612

Catalogue record

Date deposited: 02 Nov 2018 17:30
Last modified: 26 Nov 2021 05:12

Export record

Altmetrics

Contributors

Author: Stacey Reinke
Author: Beatriz Galindo-Prieto
Author: Tomas Skotare
Author: David Iain Broadhurst
Author: Akul Singhania
Author: Daniel Horowitz
Author: Timothy Hinks
Author: Paul Geladi
Author: Johan Trygg
Author: Craig E. Wheelock

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×