Metabolic effects of a 13-weeks lifestyle intervention in older adults: The Growing Old Together Study

Rest, Ondine van de; Schutte, Bianca A.M.; Deelen, Joris; Stassen, Stephanie A.M.; Akker, Erik B. van den; Heemst, Diana van; Dibbets-Schneider, Petra; Veen, Regina. A. van Dipten-van der; Kelderman, Milou; Hankemeier, Thomas; Mooijaart, Simon P.; Grond, Jeroen van der; Houwing-Duistermaat, Jeanine J.; Beekman, Marian; Feskens, Edith J. M.; Slagboom, P. Eline

doi:10.18632/aging.100877

Cited by 23 publications

(27 citation statements)

References 48 publications

(47 reference statements)

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“…The measurements performed for this study were part of the Growing Old Together study11. This article only reports on the baseline measurements.…”

Section: Methodsmentioning

confidence: 99%

“…Blood pressure measurements were calculated as the average of the four measurements and are described in detail by van de Rest et al . 11. Measurement of 1 H-NMR metabolites is described in the article by Soininen et al 12…”

Section: Methodsmentioning

confidence: 99%

“…In the current study only metabolites analyzed by the study of Würtz et al 6. and van de Rest et al 11. were used for the analysis, resulting in 65 metabolites in total.…”

Section: Methodsmentioning

confidence: 99%

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The effect of standardized food intake on the association between BMI and 1H-NMR metabolites

Schutte

Akker

Deelen

et al. 2016

Sci Rep

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Multiple studies have shown that levels of 1H-NMR metabolites are associated with disease and risk factors of disease such as BMI. While most previous investigations have been performed in fasting samples, meta-analysis often includes both cohorts with fasting and non-fasting blood samples. In the present study comprising 153 participants (mean age 63 years; mean BMI 27 kg/m2) we analyzed the effect of a standardized liquid meal (SLM) on metabolite levels and how the SLM influenced the association between metabolites and BMI. We observed that many metabolites, including glycolysis related metabolites, multiple amino acids, LDL diameter, VLDL and HDL lipid concentration changed within 35 minutes after a standardized liquid meal (SLM), similarly for all individuals. Remarkable, however, is that the correlations of metabolite levels with BMI remained highly similar before and after the SLM. Hence, as exemplified with the disease risk factor BMI, our results suggest that the applicability of 1H-NMR metabolites as disease biomarkers depends on the standardization of the fasting status rather than on the fasting status itself. Future studies are required to investigate the dependency of metabolite biomarkers for other disease risk factors on the fasting status.

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“…The measurements performed for this study were part of the Growing Old Together study11. This article only reports on the baseline measurements.…”

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

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The effect of standardized food intake on the association between BMI and 1H-NMR metabolites

Schutte

Akker

Deelen

et al. 2016

Sci Rep

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“…To delay the onset of age-related disease, older people are encouraged changing their lifestyle by adjusting their food and increasing their physical activity (39). To monitor whether the lifestyle intervention is not harmful for the older individual or initiate physiological dysregulation, the new biomarkers for longevity potential or biological age could be developed as a monitoring tool.…”

Section: Discussionmentioning

confidence: 99%

Classification for Longevity Potential: The Use of Novel Biomarkers

Beekman

Heemst

et al. 2016

Front. Public Health

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BackgroundIn older people, chronological age may not be the best predictor of residual lifespan and mortality, because with age the heterogeneity in health is increasing. Biomarkers for biological age and residual lifespan are being developed to predict disease and mortality better at an individual level than chronological age. In the current paper, we aim to classify a group of older people into those with longevity potential or controls.MethodsIn the Leiden Longevity Study participated 1671 offspring of nonagenarian siblings, as the group with longevity potential, and 744 similarly aged controls. Using known risk factors for cardiovascular disease, previously reported markers for human longevity and other physiological measures as predictors, classification models for longevity potential were constructed with multiple logistic regression of the offspring-control status.ResultsThe Framingham Risk Score (FRS) is predictive for longevity potential [area under the receiver operating characteristic curve (AUC) = 64.7]. Physiological parameters involved in immune responses and glucose, lipid and energy metabolism further improve the prediction performance for longevity potential (AUCmale = 71.4, AUCfemale = 68.7).ConclusionUsing the FRS, the classification of older people in groups with longevity potential and controls is moderate, but can be improved to a reasonably good classification in combination with markers of immune response, glucose, lipid, and energy metabolism. We show that individual classification of older people for longevity potential may be feasible using biomarkers from a wide variety of different biological processes.

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“…The method comparison was performed with 40 plasma samples collected from healthy volunteers from the Growing Old Together (GOTO) study [28].…”

Section: Plasma Samplesmentioning

confidence: 99%

Electromembrane Extraction of Highly Polar Compounds: Analysis of Cardiovascular Biomarkers in Plasma

Drouin¹,

Kloots

Schappler³

et al. 2019

Metabolites

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Cardiovascular diseases (CVDs) represent a major concern in today's society, with more than 17.5 million deaths reported annually worldwide. Recently, five metabolites related to the gut metabolism of phospholipids were identified as promising predictive biomarker candidates for CVD. Validation of those biomarker candidates is crucial for applications to the clinic, showing the need for high-throughput analysis of large numbers of samples. These five compounds, trimethylamine N-oxide (TMAO), choline, betaine, l-carnitine, and deoxy-l-carnitine (4-trimethylammoniobutanoic acid), are highly polar compounds and show poor retention on conventional reversed phase chromatography, which can lead to strong matrix effects when using mass spectrometry detection, especially when high-throughput analysis approaches are used with limited separation of analytes from interferences. In order to reduce the potential matrix effects, we propose a novel fast parallel electromembrane extraction (Pa-EME) method for the analysis of these metabolites in plasma samples. The evaluation of Pa-EME parameters was performed using multi segment injection-capillary electrophoresis-mass spectrometry (MSI-CE-MS). Recoveries up to 100% were achieved, with variability as low as 2%. Overall, this study highlights the necessity of protein precipitation prior to EME for the extraction of highly polar compounds. The developed Pa-EME method was evaluated in terms of concentration range and response function, as well as matrix effects using fast-LC-MS/MS. Finally, the developed workflow was compared to conventional sample pre-treatment, i.e., protein precipitation using methanol, and fast-LC-MS/MS. Data show very strong correlations between both workflows, highlighting the great potential of Pa-EME for high-throughput biological applications.

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Metabolic effects of a 13-weeks lifestyle intervention in older adults: The Growing Old Together Study

Cited by 23 publications

References 48 publications

The effect of standardized food intake on the association between BMI and 1H-NMR metabolites

The effect of standardized food intake on the association between BMI and 1H-NMR metabolites

Classification for Longevity Potential: The Use of Novel Biomarkers

Electromembrane Extraction of Highly Polar Compounds: Analysis of Cardiovascular Biomarkers in Plasma

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