Systematic Bioinformatic Analyses of Nutrigenomic Modifications by Polyphenols Associated with Cardiometabolic Health in Humans—Evidence from Targeted Nutrigenomic Studies Article Swipe
Tatjana Ruskovska
,
Irena Budić-Leto
,
Karla Fabiola Corral‐Jara
,
Vladimir Ajdžanović
,
Anna Arola‐Arnal
,
Francisca Isabel Bravo
,
Georgia-Eirini Deligiannidou
,
Jaroslav Havlík
,
Milkica Janeva
,
Elena Kistanova
,
Christos Kontogiorgis
,
Irèna Krga
,
Marika Massaro
,
Marko Miler
,
Verica Milošević
,
Christine Morand
,
Egeria Scoditti
,
Manuel Suárez
,
David Vauzour
,
Dragan Milenković
·
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.3390/nu13072326
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.3390/nu13072326
Cardiometabolic disorders are among the leading causes of mortality in the human population. Dietary polyphenols exert beneficial effects on cardiometabolic health in humans. Molecular mechanisms, however, are not completely understood. Aiming to conduct in-depth integrative bioinformatic analyses to elucidate molecular mechanisms underlying the protective effects of polyphenols on cardiometabolic health, we first conducted a systematic literature search to identify human intervention studies with polyphenols that demonstrate improvement of cardiometabolic risk factors in parallel with significant nutrigenomic effects. Applying the predefined inclusion criteria, we identified 58 differentially expressed genes at mRNA level and 5 miRNAs, analyzed in peripheral blood cells with RT-PCR methods. Subsequent integrative bioinformatic analyses demonstrated that polyphenols modulate genes that are mainly involved in the processes such as inflammation, lipid metabolism, and endothelial function. We also identified 37 transcription factors that are involved in the regulation of polyphenol modulated genes, including RELA/NFKB1, STAT1, JUN, or SIRT1. Integrative bioinformatic analysis of mRNA and miRNA-target pathways demonstrated several common enriched pathways that include MAPK signaling pathway, TNF signaling pathway, PI3K-Akt signaling pathway, focal adhesion, or PPAR signaling pathway. These bioinformatic analyses represent a valuable source of information for the identification of molecular mechanisms underlying the beneficial health effects of polyphenols and potential target genes for future nutrigenetic studies.
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Metadata
- Type
- review
- Language
- en
- Landing Page
- https://doi.org/10.3390/nu13072326
- https://www.mdpi.com/2072-6643/13/7/2326/pdf?version=1625796278
- OA Status
- gold
- Cited By
- 21
- References
- 97
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W3180672490
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W3180672490Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.3390/nu13072326Digital Object Identifier
- Title
-
Systematic Bioinformatic Analyses of Nutrigenomic Modifications by Polyphenols Associated with Cardiometabolic Health in Humans—Evidence from Targeted Nutrigenomic StudiesWork title
- Type
-
reviewOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2021Year of publication
- Publication date
-
2021-07-06Full publication date if available
- Authors
-
Tatjana Ruskovska, Irena Budić-Leto, Karla Fabiola Corral‐Jara, Vladimir Ajdžanović, Anna Arola‐Arnal, Francisca Isabel Bravo, Georgia-Eirini Deligiannidou, Jaroslav Havlík, Milkica Janeva, Elena Kistanova, Christos Kontogiorgis, Irèna Krga, Marika Massaro, Marko Miler, Verica Milošević, Christine Morand, Egeria Scoditti, Manuel Suárez, David Vauzour, Dragan MilenkovićList of authors in order
- Landing page
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https://doi.org/10.3390/nu13072326Publisher landing page
- PDF URL
-
https://www.mdpi.com/2072-6643/13/7/2326/pdf?version=1625796278Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
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https://www.mdpi.com/2072-6643/13/7/2326/pdf?version=1625796278Direct OA link when available
- Concepts
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Biology, Signal transduction, Nutrigenomics, PI3K/AKT/mTOR pathway, Bioinformatics, Transcriptome, Gene, Computational biology, Genetics, Gene expressionTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
21Total citation count in OpenAlex
- Citations by year (recent)
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2025: 3, 2024: 2, 2023: 6, 2022: 7, 2021: 3Per-year citation counts (last 5 years)
- References (count)
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97Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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