The Impact of Immune Interventions: A Systems Biology Strategy for Predicting Adverse and Beneficial Immune Effects.


Journal

Frontiers in immunology
ISSN: 1664-3224
Titre abrégé: Front Immunol
Pays: Switzerland
ID NLM: 101560960

Informations de publication

Date de publication:
2019
Historique:
received: 03 12 2018
accepted: 28 01 2019
entrez: 5 3 2019
pubmed: 5 3 2019
medline: 28 10 2020
Statut: epublish

Résumé

Despite scientific advances it remains difficult to predict the risk and benefit balance of immune interventions. Since a few years, network models have been built based on comprehensive datasets at multiple molecular/cellular levels (genes, gene products, metabolic intermediates, macromolecules, cells) to illuminate functional and structural relationships. Here we used a systems biology approach to identify key immune pathways involved in immune health endpoints and rank crucial candidate biomarkers to predict adverse and beneficial effects of nutritional immune interventions. First, a literature search was performed to select the molecular and cellular dynamics involved in hypersensitivity, autoimmunity and resistance to infection and cancer. Thereafter, molecular interaction between molecules and immune health endpoints was defined by connecting their relations by using database information. MeSH terms related to the immune health endpoints were selected resulting in the following selection: hypersensitivity (D006967: 184 genes), autoimmunity (D001327: 564 genes), infection (parasitic, bacterial, fungal and viral: 357 genes), and cancer (D009369: 3173 genes). In addition, a sequence of key processes was determined using Gene Ontology which drives the development of immune health disturbances resulting in the following selection: hypersensitivity (164 processes), autoimmunity (203 processes), infection (187 processes), and cancer (309 processes). Finally, an evaluation of the genes for each of the immune health endpoints was performed, which indicated that many genes played a role in multiple immune health endpoints, but also unique genes were observed for each immune health endpoint. This approach helps to build a screening/prediction tool which indicates the interaction of chemicals or food substances with immune health endpoint-related genes and suggests candidate biomarkers to evaluate risks and benefits. Several anti-cancer drugs and omega 3 fatty acids were evaluated as

Identifiants

pubmed: 30828334
doi: 10.3389/fimmu.2019.00231
pmc: PMC6384242
doi:

Substances chimiques

Biomarkers 0

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

231

Références

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Auteurs

Marjolein Meijerink (M)

TNO, Zeist, Netherlands.

Tim van den Broek (T)

TNO, Zeist, Netherlands.

Remon Dulos (R)

TNO, Zeist, Netherlands.

Lotte Neergaard Jacobsen (L)

Arla Foods Ingredients, Aarhus, Denmark.

Anne Staudt Kvistgaard (A)

Arla Foods Ingredients, Aarhus, Denmark.

Jossie Garthoff (J)

Danone Food Safety Center, Utrecht, Netherlands.

Léon Knippels (L)

Danone Nutricia Research, Utrecht, Netherlands.
Utrecht Institute of Pharmaceutical Sciences, Utrecht University, Utrecht, Netherlands.

Karen Knipping (K)

Danone Nutricia Research, Utrecht, Netherlands.
Utrecht Institute of Pharmaceutical Sciences, Utrecht University, Utrecht, Netherlands.

Geert Houben (G)

TNO, Zeist, Netherlands.

Lars Verschuren (L)

TNO, Zeist, Netherlands.

Jolanda van Bilsen (J)

TNO, Zeist, Netherlands.

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Classifications MeSH