Host and Environmental Factors Influencing Individual Human Cytokine Responses

Horst, Rob ter; Jaeger, Martin; Smeekens, Sanne P.; Oosting, Marije; Swertz, Morris A.; Li, Yang; Kumar, Vinod; Diavatopoulos, Dimitri A.; Jansen, Annemarie; Lemmers, Heidi; Toenhake-Dijkstra, Helga; Herwaarden, Antonius E. van; Janssen, Matthijs; Molen, Renate G. van der; Joosten, Irma; Sweep, Fred C.G.J.; Smit, Johannes W. A.; Netea‐Maier, Romana T.; Koenders, Mieke M J F; Xavier, Ramnik J.; Meer, J.W.M. van der; Dinarello, Charles A.; Pavelka, Norman; Wijmenga, Cisca; Notebaart, Richard A.; Netea, Mihai G.

doi:10.1016/j.cell.2016.10.018

Cited by 367 publications

(404 citation statements)

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“…In three complementary studies, we report the environmental, genetic, and microbiome factors associated with cytokine production induced by different microbial stimulations in a cohort of 500 healthy volunteers. While accompanying studies demonstrate the impact of environmental and host factors (genetic and non-genetic) for the modulation of cytokine production ter Horst et al, 2016), in this study we provide evidence that the gut microbiome also has biologically relevant effects.…”

Section: Discussionmentioning

confidence: 59%

“…An earlier study showed that host genetic variants modulate pathogen sensing in dendritic cells stimulated with microbial ligands , and we now present a much broader assessment of the genetic and environmental factors (ter Horst et al, 2016) that modulate cytokine production. Nongenetic factors such as age, gender, and season have a strong influence on cytokine production capacity, and genome-wide analyses have identified 17 independent loci that influence cytokine production at a genome-wide level.…”

Section: Discussionmentioning

confidence: 90%

“…First, general characteristics of the host such as age and gender have an important impact on inflammation. Men display a higher production of monocyte-derived proinflammatory cytokines, whereas women have a greater Th17 response (ter Horst et al, 2016). These differences may provide a partial explanation for differences in pathologies between men and women: men are more susceptible to metabolic and cardiovascular diseases, whereas women more often have autoimmune diseases (Regitz-Zagrosek, 2006;Regitz-Zagrosek et al, 2006).…”

Section: Discussionmentioning

confidence: 99%

“…Both cytokines were positively correlated with C. comes, suggesting immunostimulatory properties of this microorganism on the acute phase pathway. In an accompanying manuscript examining host factors that influence cytokine response, ter Horst et al found correlations between IL-1β and the acute phase protein AAT (alpha-1-antitrypsin) (ter Horst et al, 2016). We therefore assessed the impact of C. comes on the circulating concentrations of AAT and found a positive correlation (r = 0.08, p = 0.08) ( Figure S3) providing further evidence for the connection between C. comes and acute phase responses.…”

Section: Taxonomic Associations With Fungal-induced Cytokine Responsesmentioning

confidence: 99%

“…We identified specific bacterial species and genera that are predicted to influence cytokine production capacity, and found putative interactions between microbial metabolism and tumor necrosis factor alpha (TNFα) and interferon gamma (IFNγ), a subset of which we experimentally validated. This work is complemented by two accompanying studies linking cytokine responses to host genetics and to host and environmental factors independent of the microbiome (ter Horst et al, 2016) yielding a comprehensive picture of the factors influencing human cytokine responses and host defense.…”

Section: Introductionmentioning

confidence: 99%

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Linking the Human Gut Microbiome to Inflammatory Cytokine Production Capacity

Schirmer¹,

Smeekens²,

Vlamakis³

et al. 2016

Cell

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SummaryGut microbial dysbioses are linked to aberrant immune responses, which are often accompanied by abnormal production of inflammatory cytokines. As part of the Human Functional Genomics * Correspondence: xavier@molbio.mgh.harvard.edu (R.J.X.), mihai.netea@radboudumc.nl (M.G.N.). Lead ContactPublisher's Disclaimer: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. Author ContributionsMS performed the metagenomics data analyses and correlation analyses. SPS, MJ, MO, AK, and MJB performed the immunological assays and processed and analyzed the data. MS, HV, EAF, CH, MGN, and RJX interpreted the results. MS, EAF, and CH led the computational methods and research development. SPS, MJ, and MO collected clinical samples. SPS, TJ, and LJ performed functional validation experiments. MS, SPS, HV, CH, MGN, and RJX assembled and wrote the paper. MS, HV, MGN, and RJX served as project leaders. JF, AZ, LABJ, CW, MGN, and RJX designed the cohort study. CH, CW, MGN, and RJX served as principal investigators. Table S1. Related to Figure 3. Correlation coefficients for all significant species associations Table S2. Related to Figure 3. FDR values for all significant species associations Table S3. Related to Figure 3. Correlation coefficients for all significant genus associations Table S4. Related to Figure 3. FDR values for all significant genus associations Table S5. Related to Figure 4. Correlation coefficients for all significant pathway associations Table S6. Related to Figure 4. FDR values for all significant pathway associations Table S7. Related to Figure 4. Correlation coefficients for all significant GO category associations Table S8. Related to Figure 4. FDR values for all significant GO category associations HHS Public Access Author Manuscript Author ManuscriptAuthor Manuscript Author ManuscriptProject (HFGP), we investigate how differences in composition and function of gut microbial communities may contribute to inter-individual variation in cytokine responses to microbial stimulations in healthy humans. We observe microbiome-cytokine interaction patterns that are stimulus-specific, cytokine-specific, and cytokine-and stimulus-specific. Validation of two predicted host-microbial interactions reveal that TNFα and IFNγ production are associated with specific microbial metabolic pathways: palmitoleic acid metabolism and tryptophan degradation to tryptophol. Besides providing a resource of predicted microbially-derived mediators that influence immune phenotypes in response to common microorganisms, these data can help to define principles for understanding disease susceptibility. The three HFGP stud...

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Section: Discussionmentioning

confidence: 59%

Section: Discussionmentioning

confidence: 90%

Section: Discussionmentioning

confidence: 99%

Section: Taxonomic Associations With Fungal-induced Cytokine Responsesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Linking the Human Gut Microbiome to Inflammatory Cytokine Production Capacity

Schirmer¹,

Smeekens²,

Vlamakis³

et al. 2016

Cell

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214

185

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Gut microbiota alterations and health status in aging adults: From correlation to causation

Rong

et al. 2021

Aging Medicine

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Aging is a major concern in modern society. An aging population places a larger burden on socio-economic and healthcare systems.Aging people may develop various age-related chronic diseases, with inter-individual differences mainly due to lifestyle and living environment, genetic background, and accidents. Elderly people with poor health status have a poorer quality of life than healthy individuals. However, the major factors that determine the differences in the health status of the elderly remain unknown. Furthermore, whether these differences can be evaluated, or even modulated, via convenient and effective approaches is unclear.

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Epigenetic and Transcriptional Variability Shape Phenotypic Plasticity

et al. 2017

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Epigenetic and transcriptional variability contribute to the vast diversity of cellular and organismal phenotypes and are key in human health and disease. In this review, we describe different types, sources, and determinants of epigenetic and transcriptional variability, enabling cells and organisms to adapt and evolve to a changing environment. We highlight the latest research and hypotheses on how chromatin structure and the epigenome influence gene expression variability. Further, we provide an overview of challenges in the analysis of biological variability. An improved understanding of the molecular mechanisms underlying epigenetic and transcriptional variability, at both the intra- and inter-individual level, provides great opportunity for disease prevention, better therapeutic approaches, and personalized medicine.

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Host and Environmental Factors Influencing Individual Human Cytokine Responses

Cited by 367 publications

References 93 publications

Linking the Human Gut Microbiome to Inflammatory Cytokine Production Capacity

Linking the Human Gut Microbiome to Inflammatory Cytokine Production Capacity

Gut microbiota alterations and health status in aging adults: From correlation to causation

Epigenetic and Transcriptional Variability Shape Phenotypic Plasticity

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