Plasma metabolomic profiling of dietary patterns associated with glucose metabolism status: The Maastricht Study

Yu, Evan Y.; Ren, Zhewen; Mehrkanoon, Siamak; Stehouwer, Coen D.A.; Greevenbroek, Marleen M.J. van; Eussen, Simone J.P.M.; Wesselius, Anke

doi:10.1186/s12916-022-02653-1

Cited by 6 publications

(4 citation statements)

References 70 publications

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“…They also found that three healthy dietary patterns (Alternative Healthy Eating Index (AHEI), the Dietary Approaches to Stop Hypertension (DASH) diet, and a Mediterranean-style (MDS) diet) shared a common metabolic profile of 24 lipids. Another study found that AHEI was linked to specific fatty acids that lowered the risk of cardiovascular diseases [ 68 ], while MDS and DASH influenced glucose metabolism through circulating metabolites, which suggest prevention strategies for T2DM [ 69 ].…”

Section: Discussionmentioning

confidence: 99%

Associations of Diet with Health Outcomes in the UK Biobank: A Systematic Review

Navratilova,

Lanham-New,

Whetton

et al. 2024

Nutrients

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The UK Biobank is a cohort study that collects data on diet, lifestyle, biomarkers, and health to examine diet–disease associations. Based on the UK Biobank, we reviewed 36 studies on diet and three health conditions: type 2 diabetes (T2DM), cardiovascular disease (CVD), and cancer. Most studies used one-time dietary data instead of repeated 24 h recalls, which may lead to measurement errors and bias in estimating diet–disease associations. We also found that most studies focused on single food groups or macronutrients, while few studies adopted a dietary pattern approach. Several studies consistently showed that eating more red and processed meat led to a higher risk of lung and colorectal cancer. The results suggest that high adherence to “healthy” dietary patterns (consuming various food types, with at least three servings/day of whole grain, fruits, and vegetables, and meat and processed meat less than twice a week) slightly lowers the risk of T2DM, CVD, and colorectal cancer. Future research should use multi-omics data and machine learning models to account for the complexity and interactions of dietary components and their effects on disease risk.

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Section: Discussionmentioning

confidence: 99%

Associations of Diet with Health Outcomes in the UK Biobank: A Systematic Review

Navratilova,

Lanham-New,

Whetton

et al. 2024

Nutrients

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“…Yu et al found that following a healthy dietary pattern such as the Mediterranean diet or the Dietary Approaches to Stop Hypertension diet (DASH) may impact the glucose metabolism through circulating metabolites. This offers a new understanding of how diet influences the glucose metabolism and can help in developing strategies to prevent type 2 diabetes [ 187 ]. Additionally, a pattern characterized by higher levels of very-long-chain saturated fatty acids (VLCSFAs) and lower levels of alpha-linolenic acid (ALA) was linked to a healthier metabolic profile [ 188 ].…”

Section: Role Of Dietary Pattern On Metabolic Healthmentioning

confidence: 99%

Personalizing Nutrition Strategies: Bridging Research and Public Health

Clemente-Suárez,

Peris-Ramos,

Redondo-Flórez

et al. 2024

JPM

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In recent years, although life expectancy has increased significantly, non-communicable diseases (NCDs) continue to pose a significant threat to the health of the global population. Therefore, eating habits have been recognized as key modifiable factors that influence people’s health and well-being. For this reason, it is interesting to study dietary patterns, since the human diet is a complex mixture of macronutrients, micronutrients, and bioactive compounds, and can modulate multiple physiological processes, including immune function, the metabolism, and inflammation. To ensure that the data we acquired were current and relevant, we searched primary and secondary sources, including scientific journals, bibliographic indexes, and databases in the last 15 years with the most relevant articles. After this search, we observed that all the recent research on NCDs suggests that diet is a critical factor in shaping an individual’s health outcomes. Thus, cardiovascular, metabolic, mental, dental, and visual health depends largely on the intake, habits and patterns, and nutritional behaviors. A diet high in processed and refined foods, added sugars, and saturated fats can increase the risk of developing chronic diseases. On the other hand, a diet rich in whole, nutrient-dense foods, such as vegetables, fruits, nuts, legumes, and a high adherence to Mediterranean diet can improve health’s people.

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“…This approach helps identify the molecular mechanisms of complex diseases, as well as for disease monitoring and risk assessment. In the past, targeted and untargeted metabolomics studies have been used to study the metabolome signature of obesity in response to dietary intake [ 20 ], the effects of specific dietary patterns or weight loss [ 21 , 22 ] or gain interventions, and body fat (%) [ 23 ].…”

Section: Introductionmentioning

confidence: 99%

Untargeted Metabolomics and Body Mass in Adolescents: A Cross-Sectional and Longitudinal Analysis

Singh,

Kinnebrew,

Hsu

et al. 2023

Metabolites

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Obesity in children and adolescents has increased globally. Increased body mass index (BMI) during adolescence carries significant long-term adverse health outcomes, including chronic diseases such as cardiovascular disease, stroke, diabetes, and cancer. Little is known about the metabolic consequences of changes in BMI in adolescents outside of typical clinical parameters. Here, we used untargeted metabolomics to assess changing BMI in male adolescents. Untargeted metabolomic profiling was performed on urine samples from 360 adolescents using UPLC–QTOF-MS. The study includes a baseline of 235 subjects in a discovery set and 125 subjects in a validation set. Of them, a follow-up of 81 subjects (1 year later) as a replication set was studied. Linear regression analysis models were used to estimate the associations of metabolic features with BMI z-score in the discovery and validation sets, after adjusting for age, race, and total energy intake (kcal) at false-discovery-rate correction (FDR) ≤ 0.1. We identified 221 and 16 significant metabolic features in the discovery and in the validation set, respectively. The metabolites associated with BMI z-score in validation sets are glycylproline, citrulline, 4-vinylsyringol, 3′-sialyllactose, estrone sulfate, carnosine, formiminoglutamic acid, 4-hydroxyproline, hydroxyprolyl-asparagine, 2-hexenoylcarnitine, L-glutamine, inosine, N-(2-Hydroxyphenyl) acetamide glucuronide, and galactosylhydroxylysine. Of those 16 features, 9 significant metabolic features were associated with a positive change in BMI in the replication set 1 year later. Histidine and arginine metabolism were the most affected metabolic pathways. Our findings suggest that obesity and its metabolic outcomes in the urine metabolome of children are linked to altered amino acids, lipid, and carbohydrate metabolism. These identified metabolites may serve as biomarkers and aid in the investigation of obesity’s underlying pathological mechanisms. Whether these features are associated with the development of obesity, or a consequence of changing BMI, requires further study.

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Plasma metabolomic profiling of dietary patterns associated with glucose metabolism status: The Maastricht Study

Cited by 6 publications

References 70 publications

Associations of Diet with Health Outcomes in the UK Biobank: A Systematic Review

Associations of Diet with Health Outcomes in the UK Biobank: A Systematic Review

Personalizing Nutrition Strategies: Bridging Research and Public Health

Untargeted Metabolomics and Body Mass in Adolescents: A Cross-Sectional and Longitudinal Analysis

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