Lipidomics Reveals Similar Changes in Serum Phospholipid

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Lipidomics reveals similar changes in serum phospholipid signatures of overweight and obese paediatric subjects Sara Anjos, Eva Feiteira, Frederico Cerveira, Tânia Melo, Andrea Reboredo, Simone Colombo, Rosa Dantas, Elisabete Costa, Ana Moreira, Sónia Santos, Ana Campos, Rita Ferreira, Pedro Domingues, and M. Rosario M. Domingues J. Proteome Res., Just Accepted Manuscript • DOI: 10.1021/acs.jproteome.9b00249 • Publication Date (Web): 10 Jul 2019 Downloaded from pubs.acs.org on July 18, 2019

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Journal of Proteome Research

Lipidomics reveals similar changes in serum phospholipid signatures of overweight and obese paediatric subjects Sara Anjos1, Eva Feiteira1, Frederico Cerveira3, Tânia Melo1,2, Andrea Reboredo3, Simone Colombo1 Rosa Dantas4, Elisabete Costa1, Ana Moreira1, Sónia Santos5, Ana Campos1, Rita Ferreira1, Pedro Domingues1, M. Rosário M. Domingues1,2*

1Mass

Spectrometry Centre, Department of Chemistry & QOPNA, University of

Aveiro, Campus Universitário de Santiago, 3810-193 Aveiro, Portugal 2Department

of Chemistry & CESAM&ECOMARE, University of Aveiro, Campus

Universitário de Santiago, 3810-193 Aveiro, Portugal 3Clinical

Pathology, Centro Hospitalar do Baixo Vouga, Aveiro, Portugal

4Endocrinology,

Diabetes and Nutrition, Centro Hospitalar do Baixo Vouga, Aveiro,

Portugal 5Department

of Chemistry & CICECO, University of Aveiro, Campus Universitário de

Santiago, 3810-193 Aveiro, Portugal

Corresponding author: M. Rosário Domingues1

Address reprint requests to: M. Rosário M Domingues, Lipidomic laboratory, Departamento de Química, Universidade de Aveiro, Campus Universitário de Santiago, 3810-193 Aveiro (PORTUGAL) Phone: +351 234 370698 Fax: +351 234 370084 E-mail: [email protected]

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Abstract Obesity is a public health problem and a risk factor for pathologies such type 2 diabetes mellitus, cardiovascular diseases and non-alcoholic fatty liver disease. Given these clinical implications, there is a growing interest to understand the pathophysiological mechanism of obesity. Changes in lipid metabolism have been associated with obesity and obesity-related complications. However, changes in the lipid profile of obese children have been overlooked. In the present work, we analysed the serum phospholipidome of overweight and obese children by HILIC-MS/MS and GC-MS. Using this approach, we have identified 165 lipid species belonging to the classes PC, PE, PS, PG, PI, LPC and SM. The phospholipidome of overweight (OW) and obese (OB) children was significantly different from normal-weight children (control). Main differences were observed in the PI class that was less abundant in OW and OB children and some PS, PE, SM and PC lipid specie are upregulated in obesity and overweight. Although further studies are needed to clarify some association between phospholipid alterations and metabolic changes, our results highlight the alteration that occurs in the serum phospholipid profile in obesity in children.

Keywords: paediatrics, obesity, diagnostic methods, phospholipids, lipid metabolism, lipidomics

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Journal of Proteome Research

Introduction Obesity is increasing globally both in adults as in children and has become a considerable public health problem over the last two decades.1,2 Obesity is a condition characterized by an excessive accumulation of fat in the adipose tissue and is associated with a state of low-grade chronic inflammation, due to the lipotoxicity and an array of deleterious effects triggered by ectopic lipid accumulation in non-adipose tissues.3 Lipotoxicity aggravates the inflammation state and causes cell dysfunction and apoptosis in several organs and tissues, which can lead to insulin resistance, cardiovascular complications and liver disease.3 Consequently, lipotoxicity underlies the onset and the development of several obesity-related metabolic diseases, including type 2 diabetes mellitus (T2DM), dyslipidaemia, cardiovascular diseases (CVD) and non-alcoholic fatty liver disease (NAFLD).4 As obesity has become a worldwide epidemic, there is a strong need to monitor this condition and improve its early diagnosis and prevention of comorbidities. Alterations in plasma lipids, like increased triglycerides (TGs), total cholesterol, low-density lipoprotein (LDL) and oxidized-LDL, along with reduced high-density lipoprotein (HDL) concentrations, have been widely associated with obesity.5 There are evidences that changes in the lipid metabolism, plasma lipids and lipoproteins can underlie the onset of obesity-related complications.6,7 Nowdays lipodmics approaches are being used to study of lipid profile including plasma,.8

and have

at molecular level in biological systems,

recently been used to give new

insights into the

pathogenesis of obesity and related complications.9–11 Published works reported changes in the plasma lipidome of obese subjects when compared with non-obese individuals.5,12,13 Some authors reported a positive association between increased body 3 ACS Paragon Plus Environment

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mass index (BMI) and total plasma levels of TGs, diglycerides (DGs) and free fatty acids (FFAs).14–17 Total levels of sterol lipids, such as cholesterol and cholesteryl esters (CEs), were also found to be increased in obesity, probably associated with an increase of LDL concentrations.14,15 Several molecular species of phosphatidylcholine (PC) bearing polyunsaturated fatty acids, especially PC 38:3, were increased in obesity.15,18 However, Pietiläinen et al.13 reported that docosahexaenoic acid (DHA)-containing PC were decreased in obese subjects, which may be related with the anti-inflammatory effects of this n-3 polyunsaturated fatty acid (PUFA).19 Moreover, many lysophosphatidylcholine (LPC) species, along with the total LPCs levels, were reported to be decreased in obesity.20–22 Whereas saturated LPCs are usually associated with a pro-inflammatory activity, polyunsaturated LPCs may prevent the inflammatory response.23 However Bas et al.22 reported lower concentrations of saturated LPC species in obese subjects, suggesting that LPC metabolism might not be related to proinflammatory signs in obesity. The alterations of ether-linked phospholipids in obesity were also addressed, with some studies reporting an increase,15,24 while others a decrease13,14,25 in the levels of some species of this lipid class. The ether-linked phospholipids were associated with antioxidant properties,26 however, whether this lipid class were elevated as a response to oxidative stress in obesity remains unknown. Lastly, SMs concentrations seem to be increased in obese subjects, in particular, the species SM 32:2 and SM 34:2, which can again reflect an increase in the levels of circulating LDL.18 Studying the alterations of lipids from plasma is crucial for the identification of lipid molecular species that, after accurate validation, may contribute to the diagnosis and monitoring of obesity and associated diseases. However, although the evidence that obesity influences plasma concentrations of several lipid species, most of the data has 4 ACS Paragon Plus Environment

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Journal of Proteome Research

been strictly reported for adult subjects. Unexpectedly, there is much less information available for what concerns lipidomic studies in paediatric subjects. Regarding paediatric obesity and lipidomics, studies were mainly focused on the alteration of the plasma total FA profile and reported an increase of monounsaturated species as FA 16:1 n-7, which can reflect an increase of endogenous lipogenesis, along with a decrease of polyunsaturated species as FA 22:5 n-6, which has been associated with metabolic syndrome.27–29 Only one metabolomic study has focused on the variations in plasma phospholipids in paediatric obesity. This study targeted 163 metabolites, including 107 lipid species of PC, LPC and SM classes, reported decreased levels of alkyl acyl PC (PC-O) and LPC species in the obese subjects.30 However, no studies have so far addressed a comprehensive phospholipidomic profiling in obese or pre-obese (overweight) children. Because lipidomics of childhood obesity has been overlooked and the prevalence of this metabolic disease has been increasing for children,2 in the present study hydrophilic interaction liquid chromatography coupled to mass spectrometry (HILIC-MS/MS) and multivariate statistics was used to analyse the serum phospholipidome of normal-weight (control, CT) overweight (OW) and obese (OB) paediatric subjects. This study aimed to test whether the phospholipid profile showed correlations with pre-obesity and obesity in children. Our study also compared the phospholipid profile of female and male subjects with pre-obesity and obesity. To the best of our knowledge, this is the first lipidomic study that characterizes the serum phospholipid and sphingomyelin profile to classify specific phospholipid signatures in OW and OB children.

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Methods Reagents/Chemicals Phospholipid standards 1,2-dimyristoyl-sn-glycero-3-phosphocholine (dMPC), 1,2-dimyristoyl-sn-glycero-3-phospho-(1’-rac-glycerol) (dMPG), 1,2-dimyristoyl-snglycero-3-phosphoethanolamine phosphocholine

(LPC

(dMPE), 19:0)

1-nonadecanoyl-2-hydroxy-sn-glycero-3and

N-heptadecanoyl-D-erythro-

sphingosylphosphorylcholine (SM (d18:1/17:0)) were purchased from Avanti® Polar Lipids, Inc. (Alabaster, AL), nonadecanoic acid (C19:0) was obtained from SigmaAldrich Chemical Co. (St. Louis, MO, USA). All the standards were used without further purification. Formic acid and ammonium hydroxide were obtained from SigmaAldrich Chemical Co. (St. Louis, MO, USA), perchloric acid was obtained from ChemLab NV (Zedelgem, Germany), and potassium hydroxide was purchased from LABChem (Zelienople, PA, USA) and ammonium molybdate from Panreac (Barcelona, Spain). Ascorbic acid and sodium chloride (NaCl) were purchased from VWR Chemicals (Leuven, Belgium), sodium dihydrogen phosphate dihydrate was obtained from Riedell-de Haën (Seelze, Germany). Chloroform (CHCl3), acetonitrile (ACN), methanol (MeOH) and hexane were purchased by Fisher Scientific (Leicestershire, UK) with a degree of purity suitable for HPLC and were used without further purification. Milli-Q water was used for all experiments, filtered through a 0.22mm filter and obtained using a Milli-Q Millipore system (Synergy®, Millipore Corporation, Billerica, MA, USA).

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Journal of Proteome Research

Study design overview Serum samples were obtained from children between the ages of 8 and 17 years, Centro Hospitalar do Baixo Vouga (Aveiro, Portugal).The samples were fasting samples. The study was approved by the local ethics Committee. The identity of the children was anonymous and informed consent was obtained from parents as appropriate. For each child, the weight and BMI were evaluated, and the children were divided into 3 groups: normal-weight (control, CT), overweight (OW) and obese (OB) children. CT children BMI were between 18.5 and 24.9 kg/m2; OW children presented a BMI between 25 and 29.9 kg/m2; OB children BMI were higher than 30 kg/m2. CT children did not present any hepatic pathology, thyroid changes or T2DM, which could interfere with lipid metabolism. For each child, the serum was collected and analysed by the Clinical Pathology Service of the Centro Hospitalar do Baixo Vouga Levels of glucose, insulin, AST and ALT aminotransferases, haemoglobin A1c, total cholesterol, HDL, LDL, TG and TSH were evaluated for each subject. The baseline characteristics of the study children were presented in Table 1. After collection and analysis, the serum samples of the children were stored at -80 ° C until further study of the lipid profile. Samples were extracted within one week.

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Table 1. Baseline characteristics of the study children.

Normal weight

Overweight

Obese

Gender M/F Age (years)

4/4 13.9 ± 2.5

5/5 14.8 ± 2.1†

BMI (kg/m2) Fasting glucose (mg/dl) Fasting Insulin (mUI/l) HbA1c (%) AST (U/l) ALT (U/l) HDL cholesterol (mg/dl) LDL cholesterol (mg/dl) Total cholesterol (mg/dl) Triglycerides (mg/dl) TSH (mU/l)

21.7 ± 1.2 86.2 ± 8.5 15.0 ± 5.3 4.9 ± 0.4 23.6 ± 7.3 18.1 ± 7.6 53.0 ± 11.4 85.8 ± 19.2 150.9 ± 22.3 85.6 ± 54.5 2.4 ± 1.3

9/5 11.9 ± 2.6 27.2 ± 0.9* 87.1 ± 10.8 15.6 ± 6.5 5.3 ± 0.3* 25.0 ± 6.5 21.4 ± 7.2 49.1 ± 8.2 105.1 ± 24.1 165.6 ± 27.8 73.8 ± 21.3 2.3 ± 0.7

33.5 ± 2.1*† 93.2 ± 7.3 25.7 ± 10.8*† 5.3 ± 0.3 24.9 ± 7.3 24.2 ± 9.3 44.4 ± 7.7 114.5 ± 25.2 173.3 ± 23.6 82.3 ± 22.9 2.4 ± 0.7

The data are expressed as the mean ± standard deviation. BMI are body mass index; HbA1c glycosylated haemoglobin; AST, aspartate aminotransferase; ALT, alanine aminotransferase; HDL, high-density lipoprotein; LDL, low-density lipoprotein; TSH, thyroid-stimulating hormone. *P