Metabolism and Health Impacts of Dietary Sugars

Alam, Yasmine; Kim, Raymond; Jang, Cholsoon

doi:10.12997/jla.2022.11.1.20

Cited by 21 publications

(15 citation statements)

References 93 publications

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“…Purine and pyrimidine metabolism were grouped under nucleotide metabolism. Based on recent findings, we also incorporated 2-hydroxyisobutyrate to histone modifications [ 20 ] indoxyl sulfate [ 21 ] to microbial metabolism and further 2-furoylglycine [ 22 ], 3-methylhistidine [ 23 ], arabinose [ 24 ], sucrose [ 25 ] and xylose [ 24 ] were classified as dietary metabolites. This led to a new classification, with improved chemical taxonomy and physiological characteristics of the urinary metabolites, with nine metabolic classes: (1) amino acids, (2) related to the metabolism of amino acids, (3) carbohydrate metabolism, (4) nucleotide metabolism, (5) nicotinate and nicotinamide metabolism, (6) microbial metabolism, (7) modification of histones, (8) dietary metabolites, and (9) miscellaneous for those metabolites that did not clearly fall into any of the other categories.…”

Section: Methodsmentioning

confidence: 99%

Characteristics of Normalization Methods in Quantitative Urinary Metabolomics—Implications for Epidemiological Applications and Interpretations

Tynkkynen

Ihanus

et al. 2022

Biomolecules

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A systematic comparison is presented for the effects of seven different normalization schemes in quantitative urinary metabolomics. Morning spot urine samples were analyzed with nuclear magnetic resonance (NMR) spectroscopy from a population-based group of 994 individuals. Forty-four metabolites were quantified and the metabolite–metabolite associations and the associations of metabolite concentrations with two representative clinical measures, body mass index and mean arterial pressure, were analyzed. Distinct differences were observed when comparing the effects of normalization for the intra-urine metabolite associations with those for the clinical associations. The metabolite–metabolite associations show quite complex patterns of similarities and dissimilarities between the different normalization methods, while the epidemiological association patterns are consistent, leading to the same overall biological interpretations. The results indicate that, in general, the normalization method appears to have only minor influences on standard epidemiological regression analyses with clinical/physiological measures. Multimetabolite normalization schemes showed consistent results with the customary creatinine reference. Nevertheless, interpretations of intra-urine metabolite associations and nuanced understanding of the epidemiological associations call for comparisons with different normalizations and accounting for the physiology, metabolism and kidney function related to the normalization schemes.

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Section: Methodsmentioning

confidence: 99%

Characteristics of Normalization Methods in Quantitative Urinary Metabolomics—Implications for Epidemiological Applications and Interpretations

Tynkkynen

Ihanus

et al. 2022

Biomolecules

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“…The metabolomics (metabolites), lipidomics (ceramides and sphingolipids), proteomics (protein), epigenomics (such as DNA methylation), glycomics, and GM should be considered to increase the likelihood of establishing accurate diagnosis 45,145 and personalized medicine. 146 In addition to integrating complementary multi-omics data, longitudinal sampling will aid in the identification of functional mechanisms that may serve as therapeutic targets. 147 Specific methylation patterns influencing host-microbiome interaction is a prospective area of study.…”

Section: Systematic Review O Scfas Concentrations In Crc Patients And...mentioning

confidence: 99%

The connection between epigenetics and gut microbiota‐current perspective

Yuan,

Tan,

Bajinka

et al. 2024

Cell Biochemistry & Function

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Both the epigenetic changes and gut microbiota (GM) have attracted a growing interest in establishing effective diagnostics and potential therapeutic strategies for a number of diseases. These disorders include metabolic, central nervous system‐related diseases, autoimmune, and gastrointestinal infections (GI). Despite the number of studies, there is no extensive review that connects the epigenetics modifications and GM as biomarkers that could confer effective diagnostics and confer treatment options. To this end, this review hopes to give detailed information on connecting the modifications in epigenetic and GM. An updated and detailed information on the connection between the epigenetics factors and GM that influence diseases are given. In addition, the review showed some associations between the epigenetics to the maternal GM and offspring health. Finally, the limitations of the concept and prospects into this new emerging discipline were also looked into. Although this review elucidated on the maternal diet and response to offspring health with respect to GM and epigenetic modifications, there still exist various limitations to this newly emerging discipline. In addition to integrating complementary multi‐omics data, longitudinal sampling will aid with the identification of functional mechanisms that may serve as therapeutic targets. To this end, this review gave a detailed perspective into harnessing disease diagnostics, prevention and treatment options through epigenetics and GM.

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“…Regarding the role of sugar on metabolism and dysmetabolism, it is known that the different types of sugars are additive, palatable, and rewarding compounds from food [ 46 ]. Excessive sugar consumption leads to several metabolic disorders, and some related brain pathologies, impairing reward systems which may lead to compulsive eating [ 47 , 48 ].…”

Section: Metabolic Syndrome: Insulin Resistance and Diabetesmentioning

confidence: 99%

Dysmetabolism and Neurodegeneration: Trick or Treat?

et al. 2022

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Accumulating evidence suggests the existence of a strong link between metabolic syndrome and neurodegeneration. Indeed, epidemiologic studies have described solid associations between metabolic syndrome and neurodegeneration, whereas animal models contributed for the clarification of the mechanistic underlying the complex relationships between these conditions, having the development of an insulin resistance state a pivotal role in this relationship. Herein, we review in a concise manner the association between metabolic syndrome and neurodegeneration. We start by providing concepts regarding the role of insulin and insulin signaling pathways as well as the pathophysiological mechanisms that are in the genesis of metabolic diseases. Then, we focus on the role of insulin in the brain, with special attention to its function in the regulation of brain glucose metabolism, feeding, and cognition. Moreover, we extensively report on the association between neurodegeneration and metabolic diseases, with a particular emphasis on the evidence observed in animal models of dysmetabolism induced by hypercaloric diets. We also debate on strategies to prevent and/or delay neurodegeneration through the normalization of whole-body glucose homeostasis, particularly via the modulation of the carotid bodies, organs known to be key in connecting the periphery with the brain.

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Metabolism and Health Impacts of Dietary Sugars

Cited by 21 publications

References 93 publications

Characteristics of Normalization Methods in Quantitative Urinary Metabolomics—Implications for Epidemiological Applications and Interpretations

Characteristics of Normalization Methods in Quantitative Urinary Metabolomics—Implications for Epidemiological Applications and Interpretations

The connection between epigenetics and gut microbiota‐current perspective

Dysmetabolism and Neurodegeneration: Trick or Treat?

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