The artificial sweetener erythritol and cardiovascular event risk

Witkowski, Marco; Nemet, Ina; Alamri, Hassan S.; Wilcox, Jennifer; Gupta, Nilaksh; Nimer, Nisreen; Haghikia, Arash; Li, Xinmin S.; Wu, Yuping; Saha, Prasenjit Prasad; Demuth, Ilja; König, Maximilian; Steinhagen‐Thiessen, Elisabeth; Čajka, Tomáš; Fiehn, Oliver; Landmesser, Ulf; Tang, W.H. Wilson; Hazen, Stanley L.

doi:10.1038/s41591-023-02223-9

Cited by 84 publications

(108 citation statements)

References 53 publications

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“…Erythritol is a naturally derived sugar alcohol commonly used in processed foods, the consumption of which may increase platelet reactivity and thrombosis formation. In a discovery cohort of over 1000 patients, greater blood levels of erythritol were associated with increased three-year risk of major cardiovascular outcomes 3. While further studies are needed to establish risks, patients should be aware of consumption of this additive in commonly consumed foods.…”

Section: Family Medicine — Adult General Internal Medicinementioning

confidence: 99%

UpToDate®

2023

The Nurse Practitioner

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Section: Family Medicine — Adult General Internal Medicinementioning

confidence: 99%

UpToDate®

2023

The Nurse Practitioner

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“…In this Viewpoint, we focus on the documented influences of NNSs on glycemic responses in exemplifying some of the key considerations and open questions challenging the exploration of the NNS effects on metabolic health, while suggesting approaches that may meet these challenges. Other suggested associations between NNS usage and nonmetabolic human disease, such as recently reported effects on acute cardiovascular events ( 2 ), merit similar considerations but are beyond the scope of this Viewpoint.…”

mentioning

confidence: 92%

Nonnutritive sweeteners and glucose intolerance: Where do we go from here?

Nobs¹,

Elinav²

2023

Journal of Clinical Investigation

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“…Therefore, an automated process to create the chemical to publication linking can be used to identify the prior publication that can support the mechanistic interpretation obtained from the pathway and network analysis 23 . Finally, it is important to validate the mechanistic interpretation using independent datasets or follow up experiments 7 to provide further support for the underlying biological mechanisms.…”

Section: Introductionmentioning

confidence: 99%

“…Analysis of these metabolic genes, their products, and endogenous metabolites using omics approaches, including genomics, transcriptomics, proteomics, and metabolomics, can identify metabolic processes that are important during different life stages in normal and adverse health conditions 3 . These molecular omics approaches are discovering new insights into how metabolic processes are altered by diseases, toxic exposures and baseline genetic variations, enabling new prevention and therapeutic strategies for human diseases [4][5][6][7] .…”

Section: Introductionmentioning

confidence: 99%

IDSL.GOA: Gene Ontology Analysis for Interpreting Metabolomic datasets

Mahajan

Fiehn

Barupal

2023

Preprint

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Biological interpretation of metabolomics datasets often ends at a pathway analysis step to find the over-represented metabolic pathways in the list of statistically significant metabolites. However, the map definitions and the metabolite coverage vary among different curated databases, leading to inaccurate and contradicting interpretations. For the lists of gene, transcripts and proteins, Gene Ontology (GO) terms over-presentation analysis has become a standardized approach for the biological interpretation. GO terms are not limited to predefined pathways but can also include relevant metabolic processes that are not included in pathway databases. Despite the several advantages of GO terms over traditional pathway maps, GO analysis has not been achieved for metabolomics datasets. To overcome this, we present a new knowledgebase and the online tool, Gene Ontology Analysis by the Integrated Data Science Laboratory for Metabolomics and Exposomics (IDSL.GOA) to conduct GO over-representation analysis for a metabolite list. The IDSL.GOA knowledgebase covers 2,324 metabolic GO terms and associated 2,818 genes, 22,264 transcripts, 20,158 proteins, 1,482 EC annotations, 2,430 reactions and 2,212 metabolites. IDSL.GOA analysis of a case study of older vs young female brain cortex metabolome highlighted over 250 GO terms being significantly overrepresented (FDR <0.05). The analysis suggested that in the older female brain cortex region, nucleotide salvage processes are severely affected. On contrast, for the same metabolite list, MetaboAnalyst and Reactome Pathway Analysis suggested less than 5 pathways at FDR <0.05, and none of them were related to nucleotide salvage pathways. We showed how IDSL.GOA identified key and relevant GO metabolic processes that were not mentioned by a commonly used pathway analysis approach. Overall, we suggest that metabolomics researchers should not limit the interpretation of metabolite lists to only pathway maps and can also leverage GO terms as well. IDSL.GOA provides a powerful tool for this purpose, allowing for a more comprehensive and accurate analysis of metabolite pathway data. IDSL.GOA tool can be accessed at https://goa.idsl.me/

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The artificial sweetener erythritol and cardiovascular event risk

Cited by 84 publications

References 53 publications

UpToDate®

UpToDate®

Nonnutritive sweeteners and glucose intolerance: Where do we go from here?

IDSL.GOA: Gene Ontology Analysis for Interpreting Metabolomic datasets

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