Transcriptomic Effects of Healthspan-Promoting Dietary Interventions: Current Evidence and Future Directions

Wahl, Devin; LaRocca, Thomas J.

doi:10.3389/fnut.2021.712129

Cited by 8 publications

(3 citation statements)

References 88 publications

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“…In addition, the transcriptome (the sum of the complete set of RNA transcripts produced by the genome) functions as the molecular linkages between genetic/epigenetic information and the proteome, leading to a comprehensive understanding of biological processes and diseases. However, human studies on the role of transcriptome in determining the individual variability of the responses to dietary factors are limited, mainly because of the challenges in assessing the tissue-specific transcriptomic profiles that are more relevant to various conditions affecting different metabolic organs or tissues (96). Various omics mechanisms may affect human health in a concerted manner.…”

Section: Multiomics Algorithm In Nutrition and Precision Healthmentioning

confidence: 99%

Nutrition for precision health: The time is now

2022

Obesity

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Precision nutrition has emerged as a boiling area of nutrition research, with a particular focus on revealing the individual variability in response to diets that is determined mainly by the complex interactions of dietary factors with the multi‐tiered “omics” makeups. Reproducible findings from the observational studies and diet intervention trials have lent preliminary but consistent evidence to support the fundamental role of gene–diet interactions in determining the individual variability in health outcomes including obesity and weight loss. Recent investigations suggest that the abundance and diversity of the gut microbiome may also modify the dietary effects; however, considerable instability in the results from the microbiome research has been noted. In addition, growing studies suggest that a complicated multiomics algorithm would be developed by incorporating the genome, epigenome, metabolome, proteome, and microbiome in predicting the individual variability in response to diets. Moreover, precision nutrition would also scrutinize the role of biological (circadian) rhythm in determining the individual variability of dietary effects. The evidence gathered from precision nutrition research will be the basis for constructing precision health dietary recommendations, which hold great promise to help individuals and their health care providers create precise and effective diet plans for precision health in the future.

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Section: Multiomics Algorithm In Nutrition and Precision Healthmentioning

confidence: 99%

Nutrition for precision health: The time is now

2022

Obesity

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“…To date, several microarray profiling studies have been performed to investigate the Fed-Fast-Refed cycle. However, most transcriptomic studies in the liver have focused on a single aspect of the cycle, such as transition from fed to fasted or from fasted to refed states (Chi et al, 2020;Hwangbo et al, 2020;Wahl and LaRocca, 2021), which might be inadequate. Our study investigated the Fed-Fast-Refed cycle comprehensively and combined RNA-Seq with miRNA-Seq analysis.…”

Section: Introductionmentioning

confidence: 99%

Hepatic gene expression profiles during fed–fasted–refed state in mice

Xiang

Zhou

et al. 2023

Front. Genet.

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Background: Regulation of nutrient status during fasting and refeeding plays an important role in maintaining metabolic homeostasis in the liver. Thus, we investigated the impact of the physiological Fed–Fast–Refed cycle on hepatic gene expression in nutrient-sensitive mice.Methods: We performed transcriptomic analysis of liver samples in fed, fasted and refed groups of mice. Through mRNA-sequencing (RNA-Seq) and miRNA-Seq, we compared fasted and fed states (fasted versus fed cohort) as well as refed and fasted states (refed versus fasted cohort) to detect dynamic alterations of hepatic mRNA–miRNA expression during the fed–fasted–refed cycle.Results: We found dozens of dysregulated mRNAs–miRNAs in the transition from fed to fasted and from fasted to refed states. Gene set enrichment analysis showed that gene expression of the two cohorts shared common pathways of regulation, especially for lipid and protein metabolism. We identified eight significant mRNA and three miRNA clusters that were up–downregulated or down–upregulated during the Fed–Fast–Refed cycle. A protein–protein interaction network of dysregulated mRNAs was constructed and clustered into 22 key modules. The regulation between miRNAs and target mRNAs was presented in a network. Up to 42 miRNA–mRNA-pathway pairs were identified to be involved in metabolism. In lipid metabolism, there were significant correlations between mmu-miR-296-5p and Cyp2u1 and between mmu-miR-novel-chr19_16777 and Acsl3.Conclusion: Collectively, our data provide a valuable resource for the molecular characterization of the physiological Fed–Fast–Refed cycle in the liver.

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“…Like dietary fats and carbohydrates, dietary protein also has a profound impact on aging ( 6 ). Here, Zheng W. et al provide insight into optimal protein consumption in older age by examining the influence of ad-libitum lower protein or higher protein diets on metabolic health in rats, and whether increasing dietary protein intake in older age improves health.…”

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confidence: 99%