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Metabolomics of the interaction between PPAR-alpha and age in the PPAR-alpha- mouse.

Atherton HJ, Gulston MK, Bailey NJ, Cheng KK, Zhang W, Clarke K, Griffin JL - Mol. Syst. Biol. (2009)

Bottom Line: Expression of the receptor is high in the liver, heart and skeletal muscle, but decreases with age.Hepatic glycogen and glucose also decreased with age for both genotypes.Furthermore, the combined metabolomic and multivariate statistics approach provides a robust method for examining the interaction between age and genotype.

View Article: PubMed Central - PubMed

Affiliation: Department of Biochemistry & Cambridge Systems Biology Centre, University of Cambridge, Cambridge, UK.

ABSTRACT
Regulation between the fed and fasted states in mammals is partially controlled by peroxisome proliferator-activated receptor-alpha (PPAR-alpha). Expression of the receptor is high in the liver, heart and skeletal muscle, but decreases with age. A combined (1)H nuclear magnetic resonance (NMR) spectroscopy and gas chromatography-mass spectrometry metabolomic approach has been used to examine metabolism in the liver, heart, skeletal muscle and adipose tissue in PPAR-alpha- mice and wild-type controls during ageing between 3 and 13 months. For the PPAR-alpha- mouse, multivariate statistics highlighted hepatic steatosis, reductions in the concentrations of glucose and glycogen in both the liver and muscle tissue, and profound changes in lipid metabolism in each tissue, reflecting known expression targets of the PPAR-alpha receptor. Hepatic glycogen and glucose also decreased with age for both genotypes. These findings indicate the development of age-related hepatic steatosis in the PPAR-alpha- mouse, with the normal metabolic changes associated with ageing exacerbating changes associated with genotype. Furthermore, the combined metabolomic and multivariate statistics approach provides a robust method for examining the interaction between age and genotype.

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(A) 1H-NMR spectra showing the difference in glucose and glycogen concentration between PPAR-α- liver tissue samples (black) and controls (blue) at 3 and 13 months. (B) PCA plot showing the clusterings of 3m (open circles), 5m (open diamonds), 7m (stars), 9m (open triangles), 11m (black squares) and 13m (crosses) liver tissue across principal component 1. Note the x-axis is the order of samples in terms of age and does not represent a principal component. (C) 1H-NMR spectra showing the difference in glucose and glycogen concentration between 3 and 13 months for liver tissue extracts from PPAR-α- mice. Each spectrum is the average of the five spectra obtained from all animals at that age. Key: red, 3 months; blue, 5 months; black, 11 months; green, 13 months. (D) peak area of the anomeric 1H α-glucose (δ 5.24) and glycogen (δ 5.40) for spectra from the extracts of liver tissue from PPAR-α- mice (▪) and control mice (◊) (E) PLS plot regressing age of animal (y-axis) against the metabolic profile of the liver tissue (x-axis) in control mice as measured by 1H-NMR spectroscopy. PPAR-α- mice were then mapped on to the same model. (F) Validation plot of PLS model in (E). Triangles predict the R2 score and filled squares are Q2 scores. Values to the right were the actual values for the PLS model, whereas those on the left were formed by random permutation of the Y variable. (G) Predicted age compared with actual age for a PLS plot regressing age of the animal against the metabolic profile of the liver tissue in control mice as measured by 1H-NMR spectroscopy. PPAR-α- mice were then mapped on to the same model. Each point represents the mean±standard deviation. (H) PLS plot showing the age-related perturbations in aqueous soluble metabolites occurring in the PPAR-α- liver (3–13 months) measured by GC-MS with corresponding significant metabolic changes annotated. (I) Percentage glucose in selected PPAR-α- tissues relative to age-matched control tissues (error bars represent standard error) *P<0.05; **P<0.01; ***P<0.001. (J) PLS plot showing the age-related perturbations in aqueous soluble metabolites occurring in diaphragm tissue from PPAR-α- and control mice (3–13 months) measured by NMR spectroscopy. (K) PLS plot showing the age-related perturbations in aqueous soluble metabolites occurring in soleus tissue from PPAR-α- and control mice (3–13 months) measured by NMR spectroscopy. Key for all panels: ◊ control mice; ▪ PPAR-α- mice.
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f1: (A) 1H-NMR spectra showing the difference in glucose and glycogen concentration between PPAR-α- liver tissue samples (black) and controls (blue) at 3 and 13 months. (B) PCA plot showing the clusterings of 3m (open circles), 5m (open diamonds), 7m (stars), 9m (open triangles), 11m (black squares) and 13m (crosses) liver tissue across principal component 1. Note the x-axis is the order of samples in terms of age and does not represent a principal component. (C) 1H-NMR spectra showing the difference in glucose and glycogen concentration between 3 and 13 months for liver tissue extracts from PPAR-α- mice. Each spectrum is the average of the five spectra obtained from all animals at that age. Key: red, 3 months; blue, 5 months; black, 11 months; green, 13 months. (D) peak area of the anomeric 1H α-glucose (δ 5.24) and glycogen (δ 5.40) for spectra from the extracts of liver tissue from PPAR-α- mice (▪) and control mice (◊) (E) PLS plot regressing age of animal (y-axis) against the metabolic profile of the liver tissue (x-axis) in control mice as measured by 1H-NMR spectroscopy. PPAR-α- mice were then mapped on to the same model. (F) Validation plot of PLS model in (E). Triangles predict the R2 score and filled squares are Q2 scores. Values to the right were the actual values for the PLS model, whereas those on the left were formed by random permutation of the Y variable. (G) Predicted age compared with actual age for a PLS plot regressing age of the animal against the metabolic profile of the liver tissue in control mice as measured by 1H-NMR spectroscopy. PPAR-α- mice were then mapped on to the same model. Each point represents the mean±standard deviation. (H) PLS plot showing the age-related perturbations in aqueous soluble metabolites occurring in the PPAR-α- liver (3–13 months) measured by GC-MS with corresponding significant metabolic changes annotated. (I) Percentage glucose in selected PPAR-α- tissues relative to age-matched control tissues (error bars represent standard error) *P<0.05; **P<0.01; ***P<0.001. (J) PLS plot showing the age-related perturbations in aqueous soluble metabolites occurring in diaphragm tissue from PPAR-α- and control mice (3–13 months) measured by NMR spectroscopy. (K) PLS plot showing the age-related perturbations in aqueous soluble metabolites occurring in soleus tissue from PPAR-α- and control mice (3–13 months) measured by NMR spectroscopy. Key for all panels: ◊ control mice; ▪ PPAR-α- mice.

Mentions: The metabolic deficits of the PPAR-α- mouse were most evident in the liver where PPAR-α expression is highest in the mouse. Using 1H-NMR spectroscopy, tissue had a decreased glucose concentration relative to age-matched controls at all time points (Figure 1A). By 13 months, the glucose concentration in the PPAR-α- mice was 12.0±2.0% of that of the 3 month PPAR-α- mice, and 15.2±1.4% of that in age-matched controls. Subsequent application of PCA to all PPAR-α- data (3–13 months) demonstrated that this effect, associated with ageing, was the dominant trend in the overall data set (Figure 1B) and the reduction in glucose becomes more pronounced with age (Figure 1C and D). This reduction in glucose is also accompanied by a significant decrease in glycogen concentration (Figure 1D). Using partial least squares (PLS) to model the metabolic changes associated with ageing in the NMR spectroscopy data set of aqueous extracts from the liver tissue, a robust predictive model was produced for the control group (R2(X)=0.22; R2(Y)=0.72; Q2=0.70 for the first component; Figure 1E). This model passed cross-validation according to random permutation of the Y variable (age) (Figure 1F). The correlation between these metabolic changes and age were robust enough to allow the prediction of the age of individual animals according to their liver tissue metabolic fingerprints (Figure 1G). However, using the same model to predict the age of the PPAR-α- mice from their liver tissue profiles as measured by NMR spectroscopy of the aqueous extracts demonstrated that the 13-month-old animals were predicted to be significantly older (P<0.001; Student's t-test between predicted age of wild-type and mutant mice) and in general PPAR-α- mice were fitted to be above the line of the control mouse data. Reversing this analysis, control animals were predicted to be younger than their actual age according to a PLS model based on the metabolic changes detected in the liver tissue of PPAR-α- mice (data not shown). The ageing trends for both mouse genotypes were associated with decreases in glucose (δ 3.46–3.90), leucine and isoleucine (δ 0.94–1.02) and increases in fatty acids (δ 1.26–1.30); lactate (δ 1.30–1.34); choline/phosphocholine (δ 3.20) and taurine (δ 3.24).


Metabolomics of the interaction between PPAR-alpha and age in the PPAR-alpha- mouse.

Atherton HJ, Gulston MK, Bailey NJ, Cheng KK, Zhang W, Clarke K, Griffin JL - Mol. Syst. Biol. (2009)

(A) 1H-NMR spectra showing the difference in glucose and glycogen concentration between PPAR-α- liver tissue samples (black) and controls (blue) at 3 and 13 months. (B) PCA plot showing the clusterings of 3m (open circles), 5m (open diamonds), 7m (stars), 9m (open triangles), 11m (black squares) and 13m (crosses) liver tissue across principal component 1. Note the x-axis is the order of samples in terms of age and does not represent a principal component. (C) 1H-NMR spectra showing the difference in glucose and glycogen concentration between 3 and 13 months for liver tissue extracts from PPAR-α- mice. Each spectrum is the average of the five spectra obtained from all animals at that age. Key: red, 3 months; blue, 5 months; black, 11 months; green, 13 months. (D) peak area of the anomeric 1H α-glucose (δ 5.24) and glycogen (δ 5.40) for spectra from the extracts of liver tissue from PPAR-α- mice (▪) and control mice (◊) (E) PLS plot regressing age of animal (y-axis) against the metabolic profile of the liver tissue (x-axis) in control mice as measured by 1H-NMR spectroscopy. PPAR-α- mice were then mapped on to the same model. (F) Validation plot of PLS model in (E). Triangles predict the R2 score and filled squares are Q2 scores. Values to the right were the actual values for the PLS model, whereas those on the left were formed by random permutation of the Y variable. (G) Predicted age compared with actual age for a PLS plot regressing age of the animal against the metabolic profile of the liver tissue in control mice as measured by 1H-NMR spectroscopy. PPAR-α- mice were then mapped on to the same model. Each point represents the mean±standard deviation. (H) PLS plot showing the age-related perturbations in aqueous soluble metabolites occurring in the PPAR-α- liver (3–13 months) measured by GC-MS with corresponding significant metabolic changes annotated. (I) Percentage glucose in selected PPAR-α- tissues relative to age-matched control tissues (error bars represent standard error) *P<0.05; **P<0.01; ***P<0.001. (J) PLS plot showing the age-related perturbations in aqueous soluble metabolites occurring in diaphragm tissue from PPAR-α- and control mice (3–13 months) measured by NMR spectroscopy. (K) PLS plot showing the age-related perturbations in aqueous soluble metabolites occurring in soleus tissue from PPAR-α- and control mice (3–13 months) measured by NMR spectroscopy. Key for all panels: ◊ control mice; ▪ PPAR-α- mice.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
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f1: (A) 1H-NMR spectra showing the difference in glucose and glycogen concentration between PPAR-α- liver tissue samples (black) and controls (blue) at 3 and 13 months. (B) PCA plot showing the clusterings of 3m (open circles), 5m (open diamonds), 7m (stars), 9m (open triangles), 11m (black squares) and 13m (crosses) liver tissue across principal component 1. Note the x-axis is the order of samples in terms of age and does not represent a principal component. (C) 1H-NMR spectra showing the difference in glucose and glycogen concentration between 3 and 13 months for liver tissue extracts from PPAR-α- mice. Each spectrum is the average of the five spectra obtained from all animals at that age. Key: red, 3 months; blue, 5 months; black, 11 months; green, 13 months. (D) peak area of the anomeric 1H α-glucose (δ 5.24) and glycogen (δ 5.40) for spectra from the extracts of liver tissue from PPAR-α- mice (▪) and control mice (◊) (E) PLS plot regressing age of animal (y-axis) against the metabolic profile of the liver tissue (x-axis) in control mice as measured by 1H-NMR spectroscopy. PPAR-α- mice were then mapped on to the same model. (F) Validation plot of PLS model in (E). Triangles predict the R2 score and filled squares are Q2 scores. Values to the right were the actual values for the PLS model, whereas those on the left were formed by random permutation of the Y variable. (G) Predicted age compared with actual age for a PLS plot regressing age of the animal against the metabolic profile of the liver tissue in control mice as measured by 1H-NMR spectroscopy. PPAR-α- mice were then mapped on to the same model. Each point represents the mean±standard deviation. (H) PLS plot showing the age-related perturbations in aqueous soluble metabolites occurring in the PPAR-α- liver (3–13 months) measured by GC-MS with corresponding significant metabolic changes annotated. (I) Percentage glucose in selected PPAR-α- tissues relative to age-matched control tissues (error bars represent standard error) *P<0.05; **P<0.01; ***P<0.001. (J) PLS plot showing the age-related perturbations in aqueous soluble metabolites occurring in diaphragm tissue from PPAR-α- and control mice (3–13 months) measured by NMR spectroscopy. (K) PLS plot showing the age-related perturbations in aqueous soluble metabolites occurring in soleus tissue from PPAR-α- and control mice (3–13 months) measured by NMR spectroscopy. Key for all panels: ◊ control mice; ▪ PPAR-α- mice.
Mentions: The metabolic deficits of the PPAR-α- mouse were most evident in the liver where PPAR-α expression is highest in the mouse. Using 1H-NMR spectroscopy, tissue had a decreased glucose concentration relative to age-matched controls at all time points (Figure 1A). By 13 months, the glucose concentration in the PPAR-α- mice was 12.0±2.0% of that of the 3 month PPAR-α- mice, and 15.2±1.4% of that in age-matched controls. Subsequent application of PCA to all PPAR-α- data (3–13 months) demonstrated that this effect, associated with ageing, was the dominant trend in the overall data set (Figure 1B) and the reduction in glucose becomes more pronounced with age (Figure 1C and D). This reduction in glucose is also accompanied by a significant decrease in glycogen concentration (Figure 1D). Using partial least squares (PLS) to model the metabolic changes associated with ageing in the NMR spectroscopy data set of aqueous extracts from the liver tissue, a robust predictive model was produced for the control group (R2(X)=0.22; R2(Y)=0.72; Q2=0.70 for the first component; Figure 1E). This model passed cross-validation according to random permutation of the Y variable (age) (Figure 1F). The correlation between these metabolic changes and age were robust enough to allow the prediction of the age of individual animals according to their liver tissue metabolic fingerprints (Figure 1G). However, using the same model to predict the age of the PPAR-α- mice from their liver tissue profiles as measured by NMR spectroscopy of the aqueous extracts demonstrated that the 13-month-old animals were predicted to be significantly older (P<0.001; Student's t-test between predicted age of wild-type and mutant mice) and in general PPAR-α- mice were fitted to be above the line of the control mouse data. Reversing this analysis, control animals were predicted to be younger than their actual age according to a PLS model based on the metabolic changes detected in the liver tissue of PPAR-α- mice (data not shown). The ageing trends for both mouse genotypes were associated with decreases in glucose (δ 3.46–3.90), leucine and isoleucine (δ 0.94–1.02) and increases in fatty acids (δ 1.26–1.30); lactate (δ 1.30–1.34); choline/phosphocholine (δ 3.20) and taurine (δ 3.24).

Bottom Line: Expression of the receptor is high in the liver, heart and skeletal muscle, but decreases with age.Hepatic glycogen and glucose also decreased with age for both genotypes.Furthermore, the combined metabolomic and multivariate statistics approach provides a robust method for examining the interaction between age and genotype.

View Article: PubMed Central - PubMed

Affiliation: Department of Biochemistry & Cambridge Systems Biology Centre, University of Cambridge, Cambridge, UK.

ABSTRACT
Regulation between the fed and fasted states in mammals is partially controlled by peroxisome proliferator-activated receptor-alpha (PPAR-alpha). Expression of the receptor is high in the liver, heart and skeletal muscle, but decreases with age. A combined (1)H nuclear magnetic resonance (NMR) spectroscopy and gas chromatography-mass spectrometry metabolomic approach has been used to examine metabolism in the liver, heart, skeletal muscle and adipose tissue in PPAR-alpha- mice and wild-type controls during ageing between 3 and 13 months. For the PPAR-alpha- mouse, multivariate statistics highlighted hepatic steatosis, reductions in the concentrations of glucose and glycogen in both the liver and muscle tissue, and profound changes in lipid metabolism in each tissue, reflecting known expression targets of the PPAR-alpha receptor. Hepatic glycogen and glucose also decreased with age for both genotypes. These findings indicate the development of age-related hepatic steatosis in the PPAR-alpha- mouse, with the normal metabolic changes associated with ageing exacerbating changes associated with genotype. Furthermore, the combined metabolomic and multivariate statistics approach provides a robust method for examining the interaction between age and genotype.

Show MeSH
Related in: MedlinePlus