ARTICLE pubs.acs.org/jpr
Screening Novel Biomarkers for Metabolic Syndrome by Profiling Human Plasma N-Glycans in Chinese Han and Croatian Populations Jia-Peng Lu,†,‡ Ana Knezevic,§ You-Xin Wang,†,‡ Igor Rudan,||,^ Harry Campbell,^ Zhi-Kang Zou,†,‡ Jie Lan,# Qing-Xuan Lai,# Jing-Jing Wu,†,‡ Yan He,† Man-Shu Song,†,‡ Ling Zhang,*,†,‡ Gordan Lauc,§,z and Wei Wang*,†,#,‡,2 †
School of Public Health and Family Medicine, Capital Medical University, Beijing, 100069, China Genos Ltd, Glycobiology Laboratory, Zagreb, Croatia Croatian Centre for Global Health, University of Split Medical School, Split, and Institute for Clinical Medical Research, University Hospital “Sestre Milosrdnice”, Zagreb, Croatia ^ Public Health Sciences, University of Edinburgh, Edinburgh EH8 9AG, United Kingdom z University of Zagreb, Faculty of Pharmacy and Biochemistry, Zagreb, Croatia # College of Life Science, Graduate University of Chinese Academy of Sciences, Beijing, 100049, China ‡ Municipal Key Laboratory of Clinical Epidemiology, Beijing 100069, China 2 School of Medical Sciences, Edith Cowan Uniersity, Perth 6027, Austalia
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ABSTRACT: N-glycans play an essential role in biological process and are associated with age, gender, and body mass parameters in Caucasian populations, whereas no study has been reported in Chinese populations. To investigate the correlation between N-glycan structures and metabolic syndrome (MetS) components, we conducted a population-based study in 212 Chinese Han individuals. The replication study was performed on 520 unrelated individuals from a Croatian island Korcula. The most prominent observation was the consistent positive correlations between different forms of triantennary glycans and negative correlations between glycans containing core-fucose with MetS components including BMI, SBP, DBP, and fasting plasma glucose (FPG) simultaneously. Significant differences in a number of N-glycan traits were also detected between normal and abnormal groups of BMI, BP, and FPG, respectively. In the multivariate analysis, the level of monosialylated glycans (structure loadings = 0.776) was the most correlated with the MetS related risk factors, especially with SBP (structure loadings = 0.907). Results presented here are showing that variations in the composition of the N-glycome in human plasma could represent the alternations of human metabolism and could be potential biomarkers of MetS. KEYWORDS: N-glycan, Chinese, age, metabolic syndrome (MetS), body mass index (BMI), blood pressure (BP), fasting plasma glucose (FPG)
’ INTRODUCTION N-Glycosylation is the most common complex post-translational modification of proteins.1,2 It is estimated that more than half of all mammalian proteins are N-glycosylated.3 N-Glycans play an essential role as recognition determinants in molecule cell and cell cell interactions.4 6 Because of their complex structures and synthesis, glycans are enriching protein diversity and glycoproteins are considered to be a several orders of magnitude more diverse than proteins alone. Different monosaccharides can be bond to each other in different linkage positions due to existence of large number of specific glycosyltransferases. Additionally, each protein molecule can be glycosylated with different glycans, resulting in different glycoforms of the same protein molecule.7 In a population-based study, a high level of variability of plasma N-glycans was observed.8 Nevertheless, the N-glycan profiles are remarkably stable over a brief r 2011 American Chemical Society
period, for example, within one year in an individual, indicating that alternations of human N-glycan profiles are the consequences of environmental determinants or pathophysiologic situations.9 Therefore, the stable glycan structures could be potential diagnostic biomarkers of diseases. Alternations in levels and compositions of N-glycans have been described in various conditions.10 Glycosylation alternations were proved to be associated with a number of diseases, including rheumatic diseases, inflammatory diseases and cancer.11 13 However, there has been no evidence that chronic disease such as cardiovascular diseases and diabetes mellitus are directly associated with changes in N-glycan profiles. It has been reported that the changes of N-glycan levels could provide a Received: May 5, 2011 Published: September 22, 2011 4959
dx.doi.org/10.1021/pr2004067 | J. Proteome Res. 2011, 10, 4959–4969
Journal of Proteome Research surrogate marker for general health or for age-related disease progression and for monitoring the improvement of health after therapy,14 just as the decreased levels of nongalactosylated glycoforms containing bisecting GlcNAc indicate early features of longevity.15 Furthermore, there is the evidence that body weight affects N-glycosylation16 and body mass is correlated with genetic polymorphisms related to glycosylation.17 Body fat parameters containing body mass index (BMI) and waistto-hip ratio and blood pressure (BP) were found to be significantly associated with human plasma N-glycans in the Croatian population.18 Moreover, statistically significant correlations in the branching, sialylated and core fucosylated glycans are observed for total blood cholesterol, high-density lipoprotein cholesterol, low-density lipoprotein cholesterol and triglycerides.18 Due to the structural diversity of glycans, it is difficult to determine exact glycosylation patterns. Recently, high throughput procedures based on quantitative high performance liquid chromatography (HPLC) make the analysis of the structure and quantification of N-glycans possible in a high-throughput manner.19 To date, there has been no investigation on N-glycan profiles of human plasma with respect to metabolic syndrome (MetS). Our aim is to identify the specific N-glycan structures that are associated with MetS related risk factors in Chinese Han and Croatian populations.
’ MATERIALS AND METHODS Subjects
Between April 2009 and July 2009, we recruited a total of 310 participants of Chinese Han ancestry from individuals that underwent routine health check-ups at Beijing Xuanwu hospital, Capital Medical University. All of the participants had to meet the following inclusion criteria: (1) no history of somatic and psychiatric abnormalities as registered in their medical records and (2) no history of taking any medicine in the past two weeks. Individuals with a diagnosis of specific severe diseases concerning the cardiovascular system, respiratory system, genitourinary system, digestive system and hemeatic system were excluded. Finally, we selected 212 eligible Han individuals, residing in Beijing, China. The mean age of the Chinese subjects was 37.78 ( 17.89 (range: 18 89 years), comprising 99 males (46.7%) and 113 females (53.3%). All of the participants signed the informed consent, and this study was approved by the Ethical Committee of Capital Medical University. Examinees from the Croatian Adriatic Island Korcula were recruited as part of a larger genetic epidemiology program. Participants were identified on the basis of the official voting registers and contacts with the local stakeholders and religious communities on the island. Sampling took place in 2007. All examinees were given detailed study information prior to enrollment, and they had to sign the informed consent to enter the study. The study was approved by the appropriate Ethical Committees in both Croatia and Scotland. A total of 520 unrelated individuals were selected for this study. The mean age of the Croatian subjects was 56.08 ( 13.81 (range: 19 94 years), comprising 188 males (36.2%) and 332 females (63.8%). Phenotype Measurements
After the participants filled in the questionnaire regarding their demographic characteristics, the physical examinations and
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interview were carried out by trained nurses and physicians. Height (in centimeters) and weight (in kilograms) were measured after participants took off their shoes and hats. BMI was calculated as weight in kilograms divided by height in meters squared (kg/m2). BP was measured twice on the right arm by well-trained nurses using a standard mercury sphygmomanometer with the subjects resting at least 5 min in a sitting position. Fasting blood samples were collected in the morning after an overnight fast for at least 12 h by venipuncture for laboratory measurements and glycomic analysis. Fasting plasma glucose (FPG) levels were measured by the glucose oxidase method.20 Criteria of Investigated MetS Related Risk Factors
According to the recommendation by the Working Group on Obesity in China (International Life Science Association, 2001),21 overweight (abnormal group) was defined as 24.0 e BMI < 28.0 and obesity was defined as BMI g 28.0 kg/m2. The Croatian subjects were grouped by BMI in accordance with the National Institutes of Health, U.S.A.;22 overweight individuals were defined with the BMI between 25.0 and 29.9 kg/m2 and obese individuals were defined as BMI g 30 kg/m2. Following the International Diabetes Federation definition (2005),23 abnormal groups were define as follows: (1) raised BP, SBP g 130 mmHg or DBP g 85 mmHg, or treatment of previously diagnosed hypertension and (2) raised FPG, FPG g 100 mg/dL (5.6 mmol/L), or previously diagnosed type 2 diabetes. Sample Collection and N-Glycan Analysis
Venous blood sample (5 mL) was collected from each participant and was taken in vacuum negative pressure tubes containing EDTA and then transported in 4 C immediately. Plasma samples were obtained by centrifugation at 3000 rpm for 10 min and stored at 80 C until analysis. A technique based on a 96-well plate format for analysis of Nglycans released from glycoproteins was confirmed to be a rapid, high sensitivity and high throughput method for N-glycome profiling.19 Briefly, plasma samples (5 μL) were reduced in a polypropylene 96-well flat-bottomed microplate. Then N-glycans were released by adding 50 μL of 0.025 mU/μL peptide Nglycosidase F (PNGaseF, Pozyme, Inc.) and were labeled by adding 5 μL of 2AB labeling solution (LudgerTag 2AB labeling kit, Ludger, Abingdon, U.K.). Sialydase digestion was performed on labeled glycans. Aliquots of the 2AB-labeled glycan samples were dried down in 96-well PCR plates. To these, the following was added: 1 μL of 250 mM sodium phosphate incubation buffer (pH 6.0), 0.5 μL (0.0025 U) of ABS, Arthrobacter ureafaciens sialidase (releases α2 3,6,8 sialic acid, Prozyme, Inc.) and H2O to make up to 5 μL. This was incubated overnight (16 18 h) at 37 C and then passed through AcroPrep 96 Filter Plates, 350 μL well, 10K (Pall Corporation, Port Washington, NY) before applying to the HPLC. Hydrophilic interaction high performance liquid chromatography (HILIC) was performed using a TSK gel Amide-80 5-μm (250 4.6 mm) column for 60-min runs (Tosoh Bioscience, Stuttgart, Germany), at 30 C, with 50 mmol/L formic acid adjusted to pH 4.4 with ammonia solution as solvent A and acetonitrile as solvent B to separate the human glycome into 16 groups (GP1-GP16). After sialidase digestion, the second HILIC procedure divided the N-glycans into 13 groups of desialylated glycans (DG1-DG13). Also, weak anion exchange (WAX) HPLC was performed to separate plasma glycome in four glycan groups according to the number of sialic acids (monosialylated, disialylated, trisialylated and 4960
dx.doi.org/10.1021/pr2004067 |J. Proteome Res. 2011, 10, 4959–4969
Journal of Proteome Research
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Table 1. Demographic and Biochemical Characteristics of All Selected Chinese Individualsa parameters
P value
total
male
female
Number (%)
212 (100)
99 (46.7)
113 (53.3)
Age (years)
37.78 ( 17.89
34.10 ( 14.37
41.01 ( 19.99
0.069
BMI (kg/m2)
23.08 ( 3.78
23.75 ( 3.75
22.49 ( 3.72
0.015b
SBP (mmHg)
118.45 ( 13.89
122.89 ( 12.70
113.86 ( 13.64
