Personalized nutrition using microbial metabolite phenotype to stratify participants and non-invasive host exfoliomics reveal the effects of flaxseed lignan …

DA Mullens, I Ivanov, MAJ Hullar, TW Randolph… - Nutrients, 2022 - mdpi.com
High-fiber plant foods contain lignans that are converted to bioactive enterolignans,
enterolactone (ENL) and enterodiol (END) by gut bacteria. Previously, we conducted an …

Precision nutrition for cardiovascular disease prevention

LC Desjardins, MC Vohl - Lifestyle Genomics, 2023 - karger.com
Abstract Background: Cardiovascular diseases (CVDs) are the leading cause of death
globally, making their prevention a major challenge for modern society. For decades …

Metabotyping for precision nutrition and weight management: hype or hope?

K Pigsborg, F Magkos - Current nutrition reports, 2022 - Springer
Abstract Purpose of Review Precision nutrition requires a solid understanding of the factors
that determine individual responses to dietary treatment. We review the current state of …

Bridging the gap from enterotypes to personalized dietary recommendations: A metabolomics perspective on microbiome research

M Bartsch, A Hahn, S Berkemeyer - Metabolites, 2023 - mdpi.com
Advances in high-throughput DNA sequencing have propelled research into the human
microbiome and its link to metabolic health. We explore microbiome analysis methods …

NAD modulates DNA methylation and cell differentiation

S Ummarino, C Hausman, G Gaggi, L Rinaldi… - Cells, 2021 - mdpi.com
Nutritional intake impacts the human epigenome by directing epigenetic pathways in normal
cell development via as yet unknown molecular mechanisms. Consequently, imbalance in …

GeNuIne (gene–nutrient interactions) Collaboration: Towards implementing multi-ethnic population-based nutrigenetic studies of vitamin B12 and D deficiencies and …

KS Vimaleswaran - Proceedings of the Nutrition Society, 2021 - cambridge.org
Gene–nutrient interactions (GeNuIne) collaboration, a large-scale collaborative project, has
been initiated to investigate the impact of gene–nutrient interactions on cardiometabolic …

Nutritional markers of undiagnosed type 2 diabetes in adults: Findings of a machine learning analysis with external validation and benchmarking

K De Silva, S Lim, A Mousa, H Teede, A Forbes… - PLoS …, 2021 - journals.plos.org
Objectives Using a nationally-representative, cross-sectional cohort, we examined
nutritional markers of undiagnosed type 2 diabetes in adults via machine learning. Methods …

[HTML][HTML] The effect of inflammation and insulin resistance on lipid and lipoprotein responsiveness to dietary intervention

KS Petersen, KJ Bowen, AM Tindall, VK Sullivan… - Current Developments …, 2020 - Elsevier
Lipids and lipoproteins are major targets for cardiovascular disease (CVD) prevention.
Findings from a limited number of clinical trials suggest diet-induced atherogenic lipoprotein …

Multiomic Predictors of Short‐Term Weight Loss and Clinical Outcomes During a Behavioral‐Based Weight Loss Intervention

JC Siebert, MA Stanislawski, A Zaman, DM Ostendorf… - …, 2021 - Wiley Online Library
Objective Identifying predictors of weight loss and clinical outcomes may increase
understanding of individual variability in weight loss response. We hypothesized that …

A multi-omics approach to understand the influence of polyphenols in ovarian cancer for precision nutrition: a mini-review

F Tecchio Borsoi, L Ferreira Alves… - Critical Reviews in …, 2023 - Taylor & Francis
The impact of polyphenols in ovarian cancer is widely studied observing gene expression,
epigenetic alterations, and molecular mechanisms based on new 'omics' technologies …