Metabolomic profiling to dissect the role of visceral fat in cardiometabolic health

Menni, Cristina; Migaud, Marie E.; Glastonbury, Craig A.; Beaumont, Michelle; Nikolaou, Aikaterini; Small, Kerrin S.; Brosnan, M. Julia; Mohney, Robert P.; Spector, Tim D.; Valdes, Ana M.

doi:10.1002/oby.21488

Cited by 42 publications

(36 citation statements)

References 40 publications

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“…Some of the metabolites we identified as related to weight change have been previously linked to obesity, specifically butyrylcarnitine, which was reported by Moore et al in individuals of both Asian and European descent . We did not find a correlation with BCAAs, which are well‐known markers of visceral fat , obesity in general , and type 2 diabetes . Also, unlike the authors of previous studies , we did not find a strong correlation between weight change and lipids such as LDL or other forms of cholesterol.…”

Section: Discussioncontrasting

confidence: 81%

Metabolomic Profiling of Long‐Term Weight Change: Role of Oxidative Stress and Urate Levels in Weight Gain

Menni

Migaud

Kastenmüller

et al. 2017

Obesity

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ObjectiveTo investigate the association between long‐term weight change and blood metabolites.MethodsChange in BMI over 8.6 ± 3.79 years was assessed in 3,176 females from the TwinsUK cohort (age range: 18.3‐79.6, baseline BMI: 25.11 ± 4.35) measured for 280 metabolites at follow‐up. Statistically significant metabolites (adjusting for covariates) were included in a multivariable least absolute shrinkage and selection operator (LASSO) model. Findings were replicated in the Cooperative Health Research in the Region of Augsburg (KORA) study (n = 1,760; age range: 25‐70, baseline BMI: 27.72 ± 4.53). The study examined whether the metabolites identified could prospectively predict weight change in KORA and in the Prostate, Lung, Colorectal, and Ovarian Cancer (PLCO) study (n = 471; age range: 55‐74, baseline BMI: 27.24 ± 5.37).ResultsThirty metabolites were significantly associated with change in BMI per year in TwinsUK using Bonferroni correction. Four were independently associated with weight change in the multivariable LASSO model and replicated in KORA: namely, urate (meta‐analysis β [95% CI] = 0.05 [0.040 to 0.063]; P = 1.37 × 10−19), gamma‐glutamyl valine (β [95% CI] = 0.06 [0.046 to 0.070]; P = 1.23 × 10−20), butyrylcarnitine (β [95% CI] = 0.04 [0.028 to 0.051]; P = 6.72 × 10−12), and 3‐phenylpropionate (β [95% CI] = −0.03 [−0.041 to −0.019]; P = 9.8 × 10−8), all involved in oxidative stress. Higher levels of urate at baseline were associated with weight gain in KORA and PLCO.ConclusionsMetabolites linked to higher oxidative stress are associated with increased long‐term weight gain.

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Section: Discussioncontrasting

confidence: 81%

Metabolomic Profiling of Long‐Term Weight Change: Role of Oxidative Stress and Urate Levels in Weight Gain

Menni

Migaud

Kastenmüller

et al. 2017

Obesity

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“…A recent metabolic profiling identified significant association between visceral fat lactate levels and markers of type 2 diabetes, and insulin resistance, suggesting a metabolic link between perturbed lactate levels in visceral fat and cardiometabolic diseases. 57 Increased mitochondrial activity and FA oxidation in Fst-Tg mice could reduce glycolysis leading to reduced lactate levels. Our metabolomics data in Epi adipose tissues from Fst-Tg mice demonstrate significant lower lactate levels compared to the WT along with several other carbohydrate metabolites, further suggest that Fst may favorably modulate overall carbohydrate metabolism and provide protection against these diseases.…”

Section: Discussionmentioning

confidence: 99%

Metabolic profiling of follistatin overexpression: a novel therapeutic strategy for metabolic diseases

Singh¹,

Pervin²,

Lee³

et al. 2018

DMSO

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BackgroundFollistatin (Fst) promotes brown adipocyte characteristics in adipose tissues.MethodsAbdominal fat volume (CT scan), glucose clearance (GTT test), and metabolomics analysis (mass spectrometry) of adipose tissues from Fst transgenic (Fst-Tg) and wild type (WT) control mice were analyzed. Oxygen consumption (Seahorse Analyzer) and lipidomics (gas chromatography) was analyzed in 3T3-L1 cells.ResultsFst-Tg mice show significant decrease in abdominal fat content, increased glucose clearance, improved plasma lipid profiles and significant changes in several conventional metabolites compared to the WT mice. Furthermore, overexpression of Fst in 3T3-L1 cells resulted in up regulation of key brown/beige markers and changes in lipidomics profiles.ConclusionFst modulates key factors involved in promoting metabolic syndrome and could be used for therapeutic intervention.

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“…Estimates of visceral fat mass were derived from DXA measurements of whole body composition as previously described. 14 HOMA-IR -Fasting insulin and glucose levels were measured for the twin cohort using the same methods as previously described. 12 The homeostasis model assessment-estimated insulin resistance (HOMA-IR) was calculated multiplying overnight fasting plasma insulin (FPI) by overnight fasting plasma glucose (FPG), then dividing by the constant 22.5, i.e.…”

Section: Methodsmentioning

confidence: 99%

Circulating levels of the anti-oxidant indoleproprionic acid are associated with higher gut microbiome diversity

et al. 2019

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The gut microbiome has recently emerged as an important regulator of insulin resistance and abdominal obesity. The tryptophan metabolite generated by the gut microbiome, indoleproprionic acid (IPA) has been shown to predict the onset of type 2 diabetes. IPA is a metabolite produced by gut microbes from dietary tryptophan that exhibits a high degree of inter-individual variation. The microbiome composition parameters that are associated with circulating levels of this potent anti-oxidant have however not been investigated to date in human populations. In 1018 middle-aged women from the TwinsUK cohort, we assessed the relationship between serum IPA levels and gut microbiome composition targeting the 16S rRNA gene. Microbiome alpha-diversity was positively correlated with serum indoleproprionic acid levels (Shannon Diversity: Beta[95%CI] = 0.19[0.13;0.25], P = 6.41 × 10−10) after adjustment for covariates. Sixteen taxa and 12 operational taxonomic units (OTUs) associated with IPA serum levels. Among these are positive correlations with the butyrate-producing Faecalibacterium prausnitzii, the class Mollicutes and the order RF39 of the Tenericutes, and Coprococcus Negative correlations instead were observed with Eubacterium dolichum previously shown to correlate with visceral fat mass and several genera in the Lachnospiraceae family such as Blautia and Ruminococcus previously shown to correlate with obesity. Microbiome composition parameters explained ~20% of the variation in circulating levels of IPA, whereas nutritional and host genetic parameters explained only ~4%. Our data confirm an association between IPA circulating levels and metabolic syndrome parameters and indicate that gut microbiome composition influences IPA levels.

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Metabolomic profiling to dissect the role of visceral fat in cardiometabolic health

Cited by 42 publications

References 40 publications

Metabolomic Profiling of Long‐Term Weight Change: Role of Oxidative Stress and Urate Levels in Weight Gain

Metabolomic Profiling of Long‐Term Weight Change: Role of Oxidative Stress and Urate Levels in Weight Gain

Metabolic profiling of follistatin overexpression: a novel therapeutic strategy for metabolic diseases

Circulating levels of the anti-oxidant indoleproprionic acid are associated with higher gut microbiome diversity

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