Evidence map›Paper›PMID 30828334›Full record

ArticleFrontiers in immunology2019

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

Marjolein Meijerink, Tim van den Broek, Remon Dulos, Lotte Neergaard Jacobsen, Anne Staudt Kvistgaard, Jossie Garthoff, Léon Knippels, Karen Knipping, Geert Houben, Lars Verschuren and 1 more

Abstract read
In one paragraph

Article in Frontiers in immunology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

  1. Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Marjolein MeijerinkTNO, Zeist, Netherlands.
Tim van den BroekTNO, Zeist, Netherlands.
Remon DulosTNO, Zeist, Netherlands.
Lotte Neergaard JacobsenArla Foods Ingredients, Aarhus, Denmark.
Anne Staudt KvistgaardArla Foods Ingredients, Aarhus, Denmark.
Jossie GarthoffDanone Food Safety Center, Utrecht, Netherlands.
Léon KnippelsDanone Nutricia Research, Utrecht, Netherlands.
Karen KnippingDanone Nutricia Research, Utrecht, Netherlands.
Geert HoubenTNO, Zeist, Netherlands.
Lars VerschurenTNO, Zeist, Netherlands.
Jolanda van BilsenTNO, Zeist, Netherlands.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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

Indexed as

AnimalsBiomarkersDrug-Related Side Effects and Adverse ReactionsHumansImmunotherapyPrognosisSystems BiologyTreatment OutcomeBiomarkersbiomarkersimmune interventionnetwork databasessafety assessmentsystems biology

Identifiers

PMID30828334
PMCPMC6384242

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.