Skeletal muscle transcriptional coactivator PGC-1alpha mediates mitochondrial, but not metabolic, changes during calorie restriction

Calorie restriction (CR) is a dietary intervention that extends lifespan and healthspan in a variety of organisms. CR improves mitochondrial energy production, fuel oxidation, and reactive oxygen species (ROS) scavenging in skeletal muscle and other tissues, and these processes are thought to be critical to the benefits of CR. PGC-1alpha is a transcriptional coactivator that regulates mitochondrial function and is induced by CR. Consequently, many of the mitochondrial and metabolic benefits of CR are attributed to increased PGC-1alpha activity. To test this model, we examined the metabolic and mitochondrial response to CR in mice lacking skeletal muscle PGC-1alpha (MKO). Surprisingly, MKO mice demonstrated a normal improvement in glucose homeostasis in response to CR, indicating that skeletal muscle PGC-1alpha is dispensable for the whole-body benefits of CR. In contrast, gene expression profiling and electron microscopy (EM) demonstrated that PGC-1alpha is required for the full CR-induced increases in mitochondrial gene expression and mitochondrial density in skeletal muscle. These results demonstrate that PGC-1alpha is a major regulator of the mitochondrial response to CR in skeletal muscle, but surprisingly show that neither PGC-1alpha nor mitochondrial biogenesis in skeletal muscle are required for the whole-body metabolic benefits of CR

Metabolites related to purine catabolism and risk of type 2 diabetes incidence; modifying efects of the TCF7L2-rs7903146 polymorphism

Studies examining associations between purine metabolites and type 2 diabetes (T2D) are limited. We prospectively examined associations between plasma levels of purine metabolites with T2D risk and the modifying effects of transcription factor-7-like-2 (TCF7L2) rs7903146 polymorphism on these associations. This is a case-cohort design study within the PREDIMED study, with 251 incident T2D cases and a random sample of 694 participants (641 non-cases and 53 overlapping cases) without T2D at baseline (median follow-up: 3.8 years). Metabolites were semi-quantitatively profiled with LC-MS/MS. Cox regression analysis revealed that high plasma allantoin levels, including allantoin-to-uric acid ratio and high xanthine-to-hypoxanthine ratio were inversely and positively associated with T2D risk, respectively, independently of classical risk factors. Elevated plasma xanthine and inosine levels were associated with a higher T2D risk in homozygous carriers of the TCF7L2-rs7903146 T-allele. The potential mechanisms linking the aforementioned purine metabolites and T2D risk must be also further investigated

Circulating citric acid cycle metabolites and risk of cardiovascular disease in the PREDIMED study

Background and aim Plasma citric acid cycle (CAC) metabolites might be likely related to cardiovascular disease (CVD). However, studies assessing the longitudinal associations between circulating CAC-related metabolites and CVD risk are lacking. The aim of this study was to evaluate the association of baseline and 1-year levels of plasma CAC-related metabolites with CVD incidence (a composite of myocardial infarction, stroke or cardiovascular death), and their interaction with Mediterranean diet interventions. Methods and results Case-cohort study from the PREDIMED trial involving participants aged 55–80 years at high cardiovascular risk, allocated to MedDiets or control diet. A subcohort of 791 participants was selected at baseline, and a total of 231 cases were identified after a median follow-up of 4.8 years. Nine plasma CAC-related metabolites (pyruvate, lactate, citrate, aconitate, isocitrate, 2-hydroxyglutarate, fumarate, malate and succinate) were measured using liquid chromatography-tandem mass spectrometry. Weighted Cox multiple regression was used to calculate hazard ratios (HRs). Baseline fasting plasma levels of 3 metabolites were associated with higher CVD risk, with HRs (for each standard deviation, 1-SD) of 1.46 (95%CI:1.20–1.78) for 2-hydroxyglutarate, 1.33 (95%CI:1.12–1.58) for fumarate and 1.47 (95%CI:1.21–1.78) for malate (p of linear trend <0.001 for all). A higher risk of CVD was also found for a 1-SD increment of a combined score of these 3 metabolites (HR = 1.60; 95%CI: 1.32–1.94, p trend <0.001). This result was replicated using plasma measurements after one-year. No interactions were detected with the nutritional intervention. Conclusion Plasma 2-hydroxyglutarate, fumarate and malate levels were prospectively associated with increased cardiovascular risk

Lysine pathway metabolites and the risk of type 2 diabetes and cardiovascular disease in the PREDIMED study: results from two case-cohort studies

Background: The pandemic of cardiovascular disease (CVD) and type 2 diabetes (T2D) requires the identifcation of new predictor biomarkers. Biomarkers potentially modifable with lifestyle changes deserve a special interest. Our aims were to analyze: (a) The associations of lysine, 2-aminoadipic acid (2-AAA) or pipecolic acid with the risk of T2D or CVD in the PREDIMED trial; (b) the efect of the dietary intervention on 1-year changes in these metabolites, and (c) whether the Mediterranean diet (MedDiet) interventions can modify the efects of these metabolites on CVD or T2D risk. Methods: Two unstratifed case-cohort studies nested within the PREDIMED trial were used. For CVD analyses, we selected 696 non-cases and 221 incident CVD cases; for T2D, we included 610 non-cases and 243 type 2 diabetes incident cases. Metabolites were quantifed using liquid chromatography–tandem mass spectrometry, at baseline and after 1-year of intervention. Results: In weighted Cox regression models, we found that baseline lysine (HR+1 SD increase=1.26; 95% CI 1.06–1.51) and 2-AAA (HR+1 SD increase=1.28; 95% CI 1.05–1.55) were both associated with a higher risk of T2D, but not with CVD. A signifcant interaction (p=0.032) between baseline lysine and T2D on the risk of CVD was observed: subjects with prevalent T2D and high levels of lysine exhibited the highest risk of CVD. The intervention with MedDiet did not have a signifcant efect on 1-year changes of the metabolites. Conclusions: Our results provide an independent prospective replication of the association of 2-AAA with future risk of T2D. We show an association of lysine with subsequent CVD risk, which is apparently diabetes-dependent. No evidence of efects of MedDiet intervention on lysine, 2-AAA or pipecolic acid changes was found

Plasma lipidome and risk of atrial fibrillation: results from the PREDIMED trial

The potential role of the lipidome in atrial fibrillation (AF) development is still widely unknown. We aimed to assess the association between lipidome profiles of the Prevención con Dieta Mediterránea (PREDIMED) trial participants and incidence of AF. We conducted a nested case-control study (512 incident centrally adjudicated AF cases and 735 controls matched by age, sex, and center). Baseline plasma lipids were profiled using a Nexera X2 U-HPLC system coupled to an Exactive Plus orbitrap mass spectrometer. We estimated the association between 216 individual lipids and AF using multivariable conditional logistic regression and adjusted the p values for multiple testing. We also examined the joint association of lipid clusters with AF incidence. Hitherto, we estimated the lipidomics network, used machine learning to select important network-clusters and AF-predictive lipid patterns, and summarized the joint association of these lipid patterns weighted scores. Finally, we addressed the possible interaction by the randomized dietary intervention.Forty-one individual lipids were associated with AF at the nominal level (p < 0.05), but no longer after adjustment for multiple-testing. However, the network-based score identified with a robust data-driven lipid network showed a multivariable-adjusted ORper+1SD of 1.32 (95% confidence interval: 1.16-1.51; p < 0.001). The score included PC plasmalogens and PE plasmalogens, palmitoyl-EA, cholesterol, CE 16:0, PC 36:4;O, and TG 53:3. No interaction with the dietary intervention was found. A multilipid score, primarily made up of plasmalogens, was associated with an increased risk of AF. Future studies are needed to get further insights into the lipidome role on AF.Current Controlled Trials number, ISRCTN35739639

Arginine catabolism metabolites and atrial fibrillation or heart failure risk: 2 case-control studies within the Prevención con Dieta Mediterránea (PREDIMED) trial

Background Arginine-derived metabolites are involved in oxidative and inflammatory processes related to endothelial functions and cardiovascular risks. Objectives We prospectively examined the associations of arginine catabolism metabolites with the risks of atrial fibrillation (AF) or heart failure (HF), and evaluated the potential modifications of these associations through Mediterranean diet (MedDiet) interventions in a large, primary-prevention trial. Methods Two nested, matched, case-control studies were designed within the Prevención con Dieta Mediterránea (PREDIMED) trial. We selected 509 incident cases and 547 matched controls for the AF case-control study and 326 cases and 402 matched controls for the HF case-control study using incidence density sampling. Fasting blood samples were collected at baseline and arginine catabolism metabolites were measured using LC-tandem MS. Multivariable conditional logistic regression models were applied to test the associations between the metabolites and incident AF or HF. Interactions between metabolites and intervention groups (MedDiet groups compared with control group) were analyzed with the likelihood ratio test. Results Inverse association with incident AF was observed for arginine (OR per 1 SD, 0.83; 95% CI: 0.73–0.94), whereas a positive association was found for N1-acetylspermidine (OR for Q4 compared with Q1 1.58; 95% CI: 1.13–2.25). For HF, inverse associations were found for arginine (OR per 1 SD, 0.82; 95% CI: 0.69–0.97) and homoarginine (OR per 1 SD, 0.81; 95% CI: 0.68–0.96), and positive associations were found for the asymmetric dimethylarginine (ADMA) and symmetric dimethlyarginine (SDMA) ratio (OR per 1 SD, 1.19; 95% CI: 1.02–1.41), N1-acetylspermidine (OR per 1 SD, 1.34; 95% CI: 1.12–1.60), and diacetylspermine (OR per 1 SD, 1.20; 95% CI: 1.02–1.41). In the stratified analysis according to the dietary intervention, the lower HF risk associated with arginine was restricted to participants in the MedDiet groups (P-interaction = 0.044). Conclusions Our results suggest that arginine catabolism metabolites could be involved in AF and HF. Interventions with the MedDiet may contribute to strengthen the inverse association between arginine and the risk of HF. This trial was registered at controlled-trials.com as ISRCTN35739639

Plasma Metabolites Associated with Coffee Consumption: A Metabolomic Approach within the PREDIMED Study

Few studies have examined the association of a wide range of metabolites with total and subtypes of coffee consumption. The aim of this study was to investigate associations of plasma metabolites with total, caffeinated, and decaffeinated coffee consumption. We also assessed the ability of metabolites to discriminate between coffee consumption categories. This is a cross-sectional analysis of 1664 participants from the PREDIMED study. Metabolites were semiquantitatively profiled using a multiplatform approach. Consumption of total coffee, caffeinated coffee and decaffeinated coffee was assessed by using a validated food frequency questionnaire. We assessed associations between 387 metabolite levels with total, caffeinated, or decaffeinated coffee consumption (≥50 mL coffee/day) using elastic net regression analysis. Ten-fold cross-validation analyses were used to estimate the discriminative accuracy of metabolites for total and subtypes of coffee. We identified different sets of metabolites associated with total coffee, caffeinated and decaffeinated coffee consumption. These metabolites consisted of lipid species (e.g., sphingomyelin, phosphatidylethanolamine, and phosphatidylcholine) or were derived from glycolysis (alpha-glycerophosphate) and polyphenol metabolism (hippurate). Other metabolites included caffeine, 5-acetylamino-6-amino-3-methyluracil, cotinine, kynurenic acid, glycocholate, lactate, and allantoin. The area under the curve (AUC) was 0.60 (95% CI 0.56–0.64), 0.78 (95% CI 0.75–0.81) and 0.52 (95% CI 0.49–0.55), in the multimetabolite model, for total, caffeinated, and decaffeinated coffee consumption, respectively. Our comprehensive metabolic analysis did not result in a new, reliable potential set of metabolites for coffee consumption

Comparison of Proteomic Assessment Methods in Multiple Cohort Studies

Novel proteomics platforms, such as the aptamer-based SOMAscan platform, can quantify large numbers of proteins efficiently and cost-effectively and are rapidly growing in popularity. However, comparisons to conventional immunoassays remain underexplored, leaving investigators unsure when cross-assay comparisons are appropriate. The correlation of results from immunoassays with relative protein quantification is explored by SOMAscan. For 63 proteins assessed in two chronic obstructive pulmonary disease (COPD) cohorts, subpopulations and intermediate outcome measures in COPD Study (SPIROMICS), and COPDGene, using myriad rules based medicine multiplex immunoassays and SOMAscan, Spearman correlation coefficients range from −0.13 to 0.97, with a median correlation coefficient of ≈0.5 and consistent results across cohorts. A similar range is observed for immunoassays in the population-based Multi-Ethnic Study of Atherosclerosis and for other assays in COPDGene and SPIROMICS. Comparisons of relative quantification from the antibody-based Olink platform and SOMAscan in a small cohort of myocardial infarction patients also show a wide correlation range. Finally, cis pQTL data, mass spectrometry aptamer confirmation, and other publicly available data are integrated to assess relationships with observed correlations. Correlation between proteomics assays shows a wide range and should be carefully considered when comparing and meta-analyzing proteomics data across assays and studies