Plasma proteome correlates of lipid and lipoprotein: biomarkers of metabolic diversity and inflammation in children of rural Nepal
2018; Elsevier BV; Volume: 60; Issue: 1 Linguagem: Inglês
10.1194/jlr.p088542
ISSN1539-7262
AutoresSun Eun Lee, Kerry Schulze, Christine P. Stewart, Robert N. Cole, Lee S-F Wu, Abdulkerim Eroglu, James D. Yager, John D. Groopman, Parul Christian, Keith P. West,
Tópico(s)Lipid metabolism and disorders
ResumoProteins involved in lipoprotein metabolism can modulate cardiovascular health. While often measured to assess adult metabolic diseases, little is known about the proteomes of lipoproteins and their relation to metabolic dysregulation and underlying inflammation in undernourished child populations. The objective of this population study was to globally characterize plasma proteins systemically associated with HDL, LDL, and triglycerides in 500 Nepalese children. Abnormal lipid profiles characterized by elevated plasma triglycerides and low HDL-cholesterol (HDL-C) concentrations were common, especially in children with subclinical inflammation. Among 982 proteins analyzed, the relative abundance of 11, 12, and 52 plasma proteins was correlated with LDL-cholesterol (r = −0.43∼0.70), triglycerides (r = −0.39∼0.53), and HDL-C (r = −0.49∼0.79) concentrations, respectively. These proteins included apolipoproteins and numerous unexpected intracellular and extracellular matrix binding proteins, likely originating in hepatic and peripheral tissues. Relative abundance of two-thirds of the HDL proteome varied with inflammation, with acute phase reactants higher by 4∼40#x0025;, and proteins involved in HDL biosynthesis, cholesterol efflux, vitamin transport, angiogenesis, and tissue repair lower by 3∼20#x0025;. Untargeted plasma proteomics detects comprehensive sets of both known and novel lipoprotein-associated proteins likely reflecting systemic regulation of lipoprotein metabolism and vascular homeostasis. Inflammation-altered distributions of the HDL proteome may be predisposing undernourished populations to early chronic disease. Proteins involved in lipoprotein metabolism can modulate cardiovascular health. While often measured to assess adult metabolic diseases, little is known about the proteomes of lipoproteins and their relation to metabolic dysregulation and underlying inflammation in undernourished child populations. The objective of this population study was to globally characterize plasma proteins systemically associated with HDL, LDL, and triglycerides in 500 Nepalese children. Abnormal lipid profiles characterized by elevated plasma triglycerides and low HDL-cholesterol (HDL-C) concentrations were common, especially in children with subclinical inflammation. Among 982 proteins analyzed, the relative abundance of 11, 12, and 52 plasma proteins was correlated with LDL-cholesterol (r = −0.43∼0.70), triglycerides (r = −0.39∼0.53), and HDL-C (r = −0.49∼0.79) concentrations, respectively. These proteins included apolipoproteins and numerous unexpected intracellular and extracellular matrix binding proteins, likely originating in hepatic and peripheral tissues. Relative abundance of two-thirds of the HDL proteome varied with inflammation, with acute phase reactants higher by 4∼40#x0025;, and proteins involved in HDL biosynthesis, cholesterol efflux, vitamin transport, angiogenesis, and tissue repair lower by 3∼20#x0025;. Untargeted plasma proteomics detects comprehensive sets of both known and novel lipoprotein-associated proteins likely reflecting systemic regulation of lipoprotein metabolism and vascular homeostasis. Inflammation-altered distributions of the HDL proteome may be predisposing undernourished populations to early chronic disease. Lipoproteins, circulating complexes of lipid-bound proteins, play central roles in the transport and metabolism of lipids. They support energy metabolism, cholesterol and phospholipids supply to cell membranes, and fat-soluble vitamin transport. Apolipoproteins are integral constituents that determine the physical properties and the metabolic fate of lipoproteins, stabilizing their structure, shuttling cholesterol and triglycerides throughout the body, acting as ligands for cell surface receptors, and regulating enzymatic activities (1Dominiczak M.H. Caslake M.J. Apolipoproteins: metabolic role and clinical biochemistry applications.Ann. Clin. Biochem. 2011; 48: 498-515Crossref PubMed Scopus (128) Google Scholar). For example, apoA-I provides major structural support for HDL, activates LCAT, and acts as a ligand for HDL receptors, facilitating HDL-cholesterol (HDL-C) efflux capacity (2Davidson W.S. Thompson T.B. The structure of apolipoprotein A-I in high density lipoproteins.J. Biol. 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Shigenaga J.K. Moser A.H. Feingold K.R. Grunfeld C. Effects of infection and inflammation on lipid and lipoprotein metabolism: mechanisms and consequences to the host.J. Lipid Res. 2004; 45: 1169-1196Abstract Full Text Full Text PDF PubMed Scopus (1082) Google Scholar). For example, chronic inflammation may induce marked redistribution of HDL protein subpopulations, including enzymes and lipid transfer proteins, compromising HDL functions (23Vaisar T. Tang C. Babenko I. Hutchins P. Wimberger J. Suffredini A.F. Heinecke J.W. Inflammatory remodeling of the HDL proteome impairs cholesterol efflux capacity.J. Lipid Res. 2015; 56: 1519-1530Abstract Full Text Full Text PDF PubMed Scopus (134) Google Scholar). Systemic analysis of inflammation-induced changes in proteins metabolically linked to lipoproteins may offer insights into the mechanisms and causes of dysregulated lipid metabolism and dysfunctional lipoproteins that may compromise vascular health. Compelling epidemiologic and clinical evidence suggests that the metabolic risk factors for cardiovascular disease can be detected and observed to progress throughout childhood (24Newman 3rd, W.P. Freedman D.S. Voors A.W. Gard P.D. Srinivasan S.R. Cresanta J.L. Williamson G.D. Webber L.S. Berenson G.S. Relation of serum lipoprotein levels and systolic blood pressure to early atherosclerosis. The Bogalusa Heart Study.N. Engl. J. Med. 1986; 314: 138-144Crossref PubMed Scopus (877) Google Scholar). However, the family of plasma proteomes of lipoproteins [e.g., direct or indirect correlates of HDL-C and LDL-cholesterol (LDL-C)] in childhood, especially in low-resource societies where subclinical inflammation is common, has rarely been explored. In 2006–2008, we conducted a multipronged health and nutrition assessment of a large population cohort of 6–8-year-old children in the southern rural plains (Terai) of Nepal (25Stewart C.P. Christian P. Schulze K.J. Leclerq S.C. West Jr., K.P. Khatry S.K. Antenatal micronutrient supplementation reduces metabolic syndrome in 6- to 8-year-old children in rural Nepal.J. Nutr. 2009; 139: 1575-1581Crossref PubMed Scopus (95) Google Scholar, 26Christian P. Khatry S.K. Katz J. Pradhan E.K. LeClerq S.C. Shrestha S.R. Adhikari R.K. Sommer A. West Jr., K.P. Effects of alternative maternal micronutrient supplements on low birth weight in rural Nepal: double blind randomised community trial.BMJ. 2003; 326: 571Crossref PubMed Google Scholar). Typical of the region, the studied children were generally undernourished compared with the World Health Organization reference, but nearly 40#x0025; were dyslipidemic, characterized by high triglycerides (≥100 mg/dl) and low HDL-C ( 1.0 g/l and 6#x0025; of children showed CRP >5 mg/l) (31Lee S.E. West Jr., K.P. Cole R.N. Schulze K.J. Christian P. Wu L.S. Yager J.D. Groopman J. Ruczinski I. Plasma proteome biomarkers of inflammation in school aged children in Nepal.PLoS One. 2015; 10: e0144279Crossref PubMed Scopus (21) Google Scholar). AGP was measured using a radial immunodiffusion assay (Kent Laboratories; 0.90 ± 0.1 g/l, CV = 10.0#x0025;). The processes of immune-depletion of high abundant proteins and MS-based proteomics analysis have been previously described (29Cole R.N. Ruczinski I. Schulze K. Christian P. Herbrich S. Wu L. Devine L.R. O'Meally R.N. Shrestha S. Boronina T.N. et al.The plasma proteome identifies expected and novel proteins correlated with micronutrient status in undernourished Nepalese children.J. Nutr. 2013; 143: 1540-1548Crossref PubMed Scopus (40) Google Scholar). Plasma specimens were depleted of six high abundance proteins (albumin, transferrin, immunoglobulin G, immunoglobulin A, anti-trypsin, and haptoglobin) using a Human-6 Multiple Affinity Removal System LC column (Agilent Technologies). Seven depleted samples randomly chosen from the plasma samples of 500 participants and one masterpool sample, which served as an internal standard (32Herbrich S.M. Cole R.N. West Jr., K.P. Schulze K. Yager J.D. Groopman J.D. Christian P. Wu L. O'Meally R.N. May D.H. et al.Statistical inference from multiple iTRAQ experiments without using common reference standards.J. Proteome Res. 2013; 12: 594-604Crossref PubMed Scopus (95) Google Scholar), were digested at 37°C overnight with trypsin using a 1:10 enzyme to protein ratio. Samples were randomly labeled with eight different isobaric tags for relative and absolute quantification (iTRAQ) reagents, which have reporter ions to be detected for relative quantification, and were incubated at room temperature for 2 h. All labeled samples were combined and 90 μl of the combined peptide sample was dissolved in 4 ml of strong cation exchange loading buffer [25#x0025; v/v acetonitrile and 10 mK KH2PO4 (pH 2.8)]. The sample was fractionated into 24 fractions by strong cation exchange chromatography on an Agilent 1200 capillary HPLC system using a PolySulfoethyl A column. Peptides were loaded on to a reverse-phase nanobore column and eluted using a 2–50#x0025; acetonitrile and 0.1#x0025; formic acid gradient for 110 min at 300 nl/min. Eluting peptides were sprayed into an LTQ Orbitrap Velos mass spectrometer (Thermo Scientific) and interfaced with a NanoAcquity ultra-HPLC (Waters). Precursors and the fragment ions were analyzed at resolutions of 30,000 and 15,000, respectively. Spectra from full MS scans and fragmented MS/MS scans were extracted with and without deconvolution using Thermo Scientific Xtract software and searched against the RefSeq 40 protein database. Peptides were identified from Mascot (Matrix Science v2.3) searches through the Proteome Discoverer software (v1.3; Thermo Scientific) with a confidence threshold of 5#x0025; false discovery rate (FDR). A total of 4,705 nonredundant proteins were detected at least one time among 72 iTRAQ experiments conducted to assess plasma samples of the 500 study children (supplemental Table S1). We included 982 proteins quantified in >10#x0025; of all 500 plasma proteins of children (n > 50) in the proteomics analysis. Standard cut-offs for low or high plasma lipid levels for children were derived from the National Cholesterol Education Program Expert Panel on Cholesterol Levels in Children (33Expert Panel on Integrated Guidelines for Cardiovascular Health and Risk Reduction in Children and Adolescents; National Heart, Lung, and Blood Institute Expert panel on integrated guidelines for cardiovascular health and risk reduction in children and adolescents: summary report.Pediatrics. 2011; 128: S213-S256Crossref PubMed Scopus (1806) Google Scholar). Estimation of relative abundance of proteins from reporter ion intensities across all obtained spectra have been previously described (32Herbrich S.M. Cole R.N. West Jr., K.P. Schulze K. Yager J.D. Groopman J.D. Christian P. Wu L. O'Meally R.N. May D.H. et al.Statistical inference from multiple iTRAQ experiments without using common reference standards.J. Proteome Res. 2013; 12: 594-604Crossref PubMed Scopus (95) Google Scholar). Linear mixed effects (LME) models were employed to estimate linear associations between each log2 transformed-lipid or lipoprotein concentration as dependent variables and relative abundance of individual plasma proteins as a fixed effect, and each iTRAQ experiment as a random effect. Lipid values below the lower limit of detection were excluded from these analyses. We also adjusted for fasting status of children in all statistical models, as more than one-third of the children in the study were not fasted at the time of blood draw (25Stewart C.P. Christian P. Schulze K.J. Leclerq S.C. West Jr., K.P. Khatry S.K. Antenatal micronutrient supplementation reduces metabolic syndrome in 6- to 8-year-old children in rural Nepal.J. Nutr. 2009; 139: 1575-1581Crossref PubMed Scopus (95) Google Scholar). We report summary statistics from the LME models, including number of child plasma samples in which a protein was detected, percent change (#x0025;) in lipid or lipoprotein concentration per 2-fold (100#x0025;) increase in relative abundance of a protein, P value calculated by using a two-sided test of a null hypothesis that there is no association between an individual protein and lipid or lipoprotein, q as FDR-adjusted P value to correct multiple comparisons (34Storey J.D. A direct approach to false discovery rates.J. R. Statist. Soc. B. 2002; 64: 479-498Crossref Scopus (3864) Google Scholar), and r as a correlation coefficient between measured plasma lipid or lipoprotein concentration and its respective best linear unbiased prediction from the LME models (35Robinson G.K. That BLUP is a good thing: the estimation of random effects.Stat. Sci. 1991; 6: 15-32Crossref Scopus (1064) Google Scholar). Proteins were considered significantly correlated with an outcome when passing a FDR threshold of 5#x0025; (q < 0.05). Because of their large number, we explored correlations between proteins associated with HDL-C concentration by calculating pairwise protein:protein correlation coefficients for proteins quantified in relative abundance within each iTRAQ experiment and averaged values across iTRAQ experiments. Among proteins correlated with HDL-C, LDL-C, and triglyceride concentrations, we estimated and compare
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