Comparative analysis of obesity-related cardiometabolic and renal biomarkers in human plasma and serum.
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ABSTRACT:
SUBMITTER: Rajan MR
PROVIDER: S-EPMC6817872 | biostudies-literature | 2019 Oct
REPOSITORIES: biostudies-literature
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Comparative analysis of obesity-related cardiometabolic and renal biomarkers in human plasma and serum.
Rajan Meenu Rohini MR Sotak Matus M Barrenäs Fredrik F Shen Tong T Borkowski Kamil K Ashton Nicholas J NJ Biörserud Christina C Lindahl Tomas L TL Ramström Sofia S Schöll Michael M Lindahl Per P Fiehn Oliver O Newman John W JW Perkins Rosie R Wallenius Ville V Lange Stephan S Börgeson Emma E
Scientific reports 20191028 1
The search for biomarkers associated with obesity-related diseases is ongoing, but it is not clear whether plasma and serum can be used interchangeably in this process. Here we used high-throughput screening to analyze 358 proteins and 76 lipids, selected because of their relevance to obesity-associated diseases, in plasma and serum from age- and sex-matched lean and obese humans. Most of the proteins/lipids had similar concentrations in plasma and serum, but a subset showed significant differen ...[more]
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Project description:Proteomics have long been applied into characterization of molecular signatures in aging. Due to different methods and instrumentations employed for proteomic analysis, inter-dataset validation needs to be performed to identify potential biomarkers for aging. In this study, we used comparative proteomics analysis to profile age-associated changes in proteome and glutathionylome in mouse kidneys. We identified 108 proteins that were differentially expressed in young and aged mouse kidneys in three different datasets; from these, 27 proteins were identified as potential renal aging biomarkers, including phosphoenolpyruvate carboxykinase (Pck1), CD5 antigen-like protein (Cd5l), aldehyde dehydrogenase 1 (Aldh1a1), and uromodulin. Our results also showed that peroxisomal proteins were significantly downregulated in aged mice, whereas IgGs were upregulated, suggesting that peroxisome deterioration might be a hallmark for renal aging. Glutathionylome analysis demonstrated that downregulation of catalase and glutaredoxin-1 (Glrx1) significantly increased protein glutathionylation in aged mice. In addition, nicotinamide mononucleotide (NMN) administration significantly increased the number of peroxisomes in aged mouse kidneys, indicating that NMN enhanced peroxisome biogenesis, and suggesting that it might be beneficial to reduce kidney injuries. Together, our data identify novel potential biomarkers for renal aging, and provide a valuable resource for understanding the age-associated changes in kidneys.
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Project description:Background Obesity may be associated with a range of cardiometabolic manifestations. We hypothesized that proteomic profiling may provide insights into the biological pathways that contribute to various obesity-associated cardiometabolic traits. We sought to identify proteomic signatures of obesity and examine overlap with related cardiometabolic traits, including abdominal adiposity, insulin resistance, and adipose depots. Methods and Results We measured 71 circulating cardiovascular disease protein biomarkers in 6981 participants (54% women; mean age, 49 years). We examined the associations of obesity, computed tomography measures of adiposity, cardiometabolic traits, and incident metabolic syndrome with biomarkers using multivariable regression models. Of the 71 biomarkers examined, 45 were significantly associated with obesity, of which 32 were positively associated and 13 were negatively associated with obesity (false discovery rate q<0.05 for all). There was significant overlap of biomarker profiles of obesity and cardiometabolic traits, but 23 biomarkers, including melanoma cell adhesion molecule (MCAM), growth differentiation factor-15 (GDF15), and lipoprotein(a) (LPA) were unique to metabolic traits only. Using hierarchical clustering, we found that the protein biomarkers clustered along 3 main trait axes: adipose, metabolic, and lipid traits. In longitudinal analyses, 6 biomarkers were significantly associated with incident metabolic syndrome: apolipoprotein B (apoB), insulin-like growth factor-binding protein 2 (IGFBP2), plasma kallikrein (KLKB1), complement C2 (C2), fibrinogen (FBN), and N-terminal pro-B-type natriuretic peptide (NT-proBNP); false discovery rate q<0.05 for all. Conclusions We found that the proteomic architecture of obesity overlaps considerably with associated cardiometabolic traits, implying shared pathways. Despite overlap, hierarchical clustering of proteomic profiles identified 3 distinct clusters of cardiometabolic traits: adipose, metabolic, and lipid. Further exploration of these novel protein targets and associated pathways may provide insight into the mechanisms responsible for the progression from obesity to cardiometabolic disease.
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Project description:BACKGROUND: Non-human primates (NHP) are now being considered as models for investigating human metabolic diseases including diabetes. Analyses of cholesterol and triglycerides in plasma derived from NHPs can easily be achieved using methods employed in humans. Information pertaining to other lipid species in monkey plasma, however, is lacking and requires comprehensive experimental analysis. METHODOLOGIES/PRINCIPAL FINDINGS: We examined the plasma lipidome from 16 cynomolgus monkey, Macaca fascicularis, using liquid chromatography coupled with mass spectrometry (LC/MS). We established novel analytical approaches, which are based on a simple gradient elution, to quantify polar lipids in plasma including (i) glycerophospholipids (phosphatidylcholine, PC; phosphatidylethanolamine, PE; phosphatidylinositol, PI; phosphatidylglycerol, PG; phosphatidylserine, PS; phosphatidic acid, PA); (ii) sphingolipids (sphingomyelin, SM; ceramide, Cer; Glucocyl-ceramide, GluCer; ganglioside mannoside 3, GM3). Lipidomic analysis had revealed that the plasma of human and cynomolgus monkey were of similar compositions, with PC, SM, PE, LPC and PI constituting the major polar lipid species present. Human plasma contained significantly higher levels of plasmalogen PE species (p<0.005) and plasmalogen PC species (p<0.0005), while cynomolgus monkey had higher levels of polyunsaturated fatty acyls (PUFA) in PC, PE, PS and PI. Notably, cynomolgus monkey had significantly lower levels of glycosphingolipids, including GluCer (p<0.0005) and GM(3) (p<0.0005), but higher level of Cer (p<0.0005) in plasma than human. We next investigated the biochemical alterations in blood lipids of 8 naturally occurring diabetic cynomolgus monkeys when compared with 8 healthy controls. CONCLUSIONS: For the first time, we demonstrated that the plasma of human and cynomolgus monkey were of similar compositions, but contained different mol distribution of individual molecular species. Diabetic monkeys exhibited decreased levels of sphingolipids, which are microdomain-associated lipids and are thought to be associated with insulin sensitivity. Significant increases in PG species, which are precursors for cardiolipin biosynthesis in mitochondria, were found in fasted diabetic monkeys (n?=?8).
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2016-10-01 | GSE85928 | GEO
Project description:Obesity can increase the risk of complex metabolic diseases, including insulin resistance. Moreover, obesity can be caused by environmental and genetic factors. However, the epigenetic mechanisms of obesity are not well defined. Therefore, the identification of novel epigenetic biomarkers of obesity allows for a more complete understanding of the disease and its underlying insulin resistance. The aim of our study was to identify DNA methylation changes in whole-blood that were strongly associated with obesity and insulin resistance. Whole-blood was obtained from lean (n = 10; BMI = 23.6 ± 0.7 kg/m2) and obese (n = 10; BMI = 34.4 ± 1.3 kg/m2) participants in combination with euglycemic hyperinsulinemic clamps to assess insulin sensitivity. We performed reduced representation bisulfite sequencing on genomic DNA isolated from the blood. We identified 49 differentially methylated cytosines (DMCs; q < 0.05) that were altered in obese compared with lean participants. We identified 2 sites (Chr.21:46,957,981 and Chr.21:46,957,915) in the 5' untranslated region of solute carrier family 19 member 1 (SLC19A1) with decreased methylation in obese participants (lean 0.73 ± 0.11 vs. obese 0.09 ± 0.05; lean 0.68 ± 0.10 vs. obese 0.09 ± 0.05, respectively). These 2 DMCs identified by obesity were also significantly predicted by insulin sensitivity (r = 0.68, P = 0.003; r = 0.66; P = 0.004). In addition, we performed a differentially methylated region (DMR) analysis and demonstrated a decrease in methylation of Chr.21:46,957,915-46,958,001 in SLC19A1 of -34.9% (70.4% lean vs. 35.5% obese). The decrease in whole-blood SLC19A1 methylation in our obese participants was similar to the change observed in skeletal muscle (Chr.21:46,957,981, lean 0.70 ± 0.09 vs. obese 0.31 ± 0.11 and Chr.21:46,957,915, lean 0.72 ± 0.11 vs. obese 0.31 ± 0.13). Pyrosequencing analysis further demonstrated a decrease in methylation at Chr.21:46,957,915 in both whole-blood (lean 0.71 ± 0.10 vs. obese 0.18 ± 0.06) and skeletal muscle (lean 0.71 ± 0.10 vs. obese 0.30 ± 0.11). Our findings demonstrate a new potential epigenetic biomarker, SLC19A1, for obesity and its underlying insulin resistance.
| S-EPMC5398771 | biostudies-literature
Project description:BackgroundCholine is an essential nutrient; however, the associations of choline and its related metabolites with cardiometabolic risk remain unclear.ObjectiveWe examined the associations of circulating choline, betaine, carnitine, and dimethylglycine (DMG) with cardiometabolic biomarkers and their potential dietary and nondietary determinants.MethodsThe cross-sectional analyses included 32,853 participants from 17 studies, who were free of cancer, cardiovascular diseases, chronic kidney diseases, and inflammatory bowel disease. In each study, metabolites and biomarkers were log-transformed and standardized by means and SDs, and linear regression coefficients (β) and 95% CIs were estimated with adjustments for potential confounders. Study-specific results were combined by random-effects meta-analyses. A false discovery rate <0.05 was considered significant.ResultsWe observed moderate positive associations of circulating choline, carnitine, and DMG with creatinine [β (95% CI): 0.136 (0.084, 0.188), 0.106 (0.045, 0.168), and 0.128 (0.087, 0.169), respectively, for each SD increase in biomarkers on the log scale], carnitine with triglycerides (β = 0.076; 95% CI: 0.042, 0.109), homocysteine (β = 0.064; 95% CI: 0.033, 0.095), and LDL cholesterol (β = 0.055; 95% CI: 0.013, 0.096), DMG with homocysteine (β = 0.068; 95% CI: 0.023, 0.114), insulin (β = 0.068; 95% CI: 0.043, 0.093), and IL-6 (β = 0.060; 95% CI: 0.027, 0.094), but moderate inverse associations of betaine with triglycerides (β = -0.146; 95% CI: -0.188, -0.104), insulin (β = -0.106; 95% CI: -0.130, -0.082), homocysteine (β = -0.097; 95% CI: -0.149, -0.045), and total cholesterol (β = -0.074; 95% CI: -0.102, -0.047). In the whole pooled population, no dietary factor was associated with circulating choline; red meat intake was associated with circulating carnitine [β = 0.092 (0.042, 0.142) for a 1 serving/d increase], whereas plant protein was associated with circulating betaine [β = 0.249 (0.110, 0.388) for a 5% energy increase]. Demographics, lifestyle, and metabolic disease history showed differential associations with these metabolites.ConclusionsCirculating choline, carnitine, and DMG were associated with unfavorable cardiometabolic risk profiles, whereas circulating betaine was associated with a favorable cardiometabolic risk profile. Future prospective studies are needed to examine the associations of these metabolites with incident cardiovascular events.
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