Profiling Plasma Peptides for the Identification of
Potential Ageing Biomarkers in Chinese Han Adults
Jiapeng Lu1,8., Yuqing Huang2., Youxin Wang1,8, Yan Li6, Yujun Zhang6, Jingjing Wu1,8, Feifei Zhao1,8,
Shijiao Meng1,8, Xinwei Yu1,8, Qingwei Ma6, Manshu Song1,8*, Naibai Chang7*, Alan H. Bittles4,5,
1School of Public Health and Family Medicine, Capital Medical University, Beijing, People’s Republic of China, 2Department of Chest Surgery, Beijing Haidian Hospital,
Beijing, People’s Republic of China, 3College of Life Sciences, Graduate University of Chinese Academy of Sciences, Beijing, People’s Republic of China, 4School of
Medical Sciences, Edith Cowan University, Perth, Australia, 5Centre for Comparative Genomics, Murdoch University, Perth, Australia, 6Bioyong Technologies Inc, Beijing,
People’s Republic of China, 7Department of Hematology, Beijing Hospital, Beijing, People’s Republic of China, 8Municipal Key Laboratory of Clinical Epidemiology,
Beijing, People’s Republic of China
Advancing age is associated with cardiovascular disease, diabetes mellitus and cancer, and shows significant inter-individual
variability. To identify ageing-related biomarkers we performed a proteomic analysis on 1890 Chinese Han individuals, 1136
males and 754 females, aged 18 to 82 years, using weak cation exchange magnetic bead based MALDI-TOF-MS analysis. The
study identified 44 peptides which varied in concentration in different age groups. In particular, apolipoprotein A-I (ApoA1)
concentration gradually increased between 18 to 50 years of age, the levels of fibrinogen alpha (FGA) decreased over the
same age span, while albumin (ALB) was significantly degraded in middle-aged individuals. In addition, the plasma peptide
profiles of FGA and four other unidentified proteins were found to be gender-dependent. Plasma proteins such as FGA, ALB
and ApoA1 are significantly correlated with age in the Chinese Han population and could be employed as indicative ageing-
Citation: Lu J, Huang Y, Wang Y, Li Y, Zhang Y, et al. (2012) Profiling Plasma Peptides for the Identification of Potential Ageing Biomarkers in Chinese Han
Adults. PLoS ONE 7(7): e39726. doi:10.1371/journal.pone.0039726
Editor: Angelo Scuteri, INRCA, Italy
Received March 14, 2012; Accepted May 25, 2012; Published July 3, 2012
Copyright: ? 2012 Lu et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted
use, distribution, and reproduction in any medium, provided the original author and source are credited.
Funding: The study was financially supported by National Science Technology Major Special Project on Major New Drug Innovation (2010ZX09401) http://www.
nmp.gov.cn/, National ‘‘Twelfth Five-Year’’ Plan for Science and Technology Support (2012BAI37B03) http://kjzc.jhgl.org/, Major State Basic Research Program-973
of China (No. 2011CB503806) http://program.most.gov.cn/, National Natural Science Foundation of China (30901238, 31070727 and 81001281) http://www.nsfc.
gov.cn/Portal0/default152.htm. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing Interests: YL, YZ and QM are employees of Bioyong Technologies Inc. There are no patents, products in development or marketed products to
declare. This does not alter the authors‘ adherence to all the PLoS ONE policies on sharing data and materials, as detailed online in the guide for authors.
* E-mail: email@example.com (MS); firstname.lastname@example.org (NC); email@example.com (WW)
. These authors contributed equally to this work.
Ageing is a multidimensional process, usually with gradual
onset, which results from the effects of genetic and environ-
mental interactions , and a basic understanding of ageing is
crucial for unraveling the mechanisms of longevity and ageing-
related diseases [2,3]. There also is an urgent need for readily
accessible and reproducible biological markers of ageing . In
genetic association studies, gene variants including ACE ,
APOE , FOXO1A and 3A  have been shown to be
associated withageing and
populations, via the regulation of biological pathways such as
insulin signaling, inflammation and caloric restriction .
Recent research has indicated that variation in RNA-editing
genes is associated with longevity , while mitochondrial DNA
(mtDNA) mutations, telomeric length and telomerase activity
also are believed to contribute to ageing  and age-related
Genetic variants in DNA sequences may result in several
different types of changes in the translation of RNA and/or the
expression of proteins. With physiological cellular processes, e.g.
immune surveillance of tumors , metastasis, oncogenic
longevity indifferent ethnic
transformation , and pathological conditions, several proteins
show alternations in their levels or patterns of expression in the
human circulatory system. It has been reported that telomeric
length and telomerase activity vary significantly with ageing in the
peripheral blood cells of humans . Furthermore, our recent
study found that the N-Glycan profile of human plasma is
significantly age-dependent in both Chinese and Croatian
populations . Proteomics provides a powerful tool for the
study of protein expression variability between individuals and in
different disease states. A fractionation method, which selectively
separates peptides on the chromatographic surfaces of magnetic
beads according to chemical differences, has been developed for
direct use with matrix-assisted laser desorption/ionization time-of-
flight mass spectrometry (MALDI-TOF-MS) analysis. The method
can be applied to human body fluids, such as blood, saliva and
urine which offer the advantages of minimal invasiveness, low cost,
and ready acquisition and processing . Blood in particular is
an accessible source of molecular biomarkers with biological
information on many physiological and pathological processes
. Human plasma proteins play an important role in different
biological processes, including the mediation and modulation of
PLoS ONE | www.plosone.org1July 2012 | Volume 7 | Issue 7 | e39726
cell adhesion and signaling transactions in signal pathways. In
recent years, proteomic studies of plasma proteins have increas-
ingly focused on human ageing and longevity [17,18,19].
However, because of small sample sizes and a lack of sub-
structured age groups it has been difficult to reproducibly profile
plasma protein changes with ageing.
We have performed a detailed proteomic analysis to investigate
ageing-related proteins in a large sample of Chinese Han adults
using weak cation exchange magnetic bead-based MALDI-TOF-
MS analysis. The study is the first investigation of qualitative and
quantitative changes in human plasma proteins that occur with
ageing in this major human population.
Materials and Methods
We recruited a total of 1927 participants of Chinese Han
ancestry from individuals undergoing routine health check-ups at
Beijing Xuanwu Hospital, Capital Medical University. All
participants had to meet the following inclusion criteria: (1) no
history of somatic or psychiatric abnormalities registered in their
medical records; and (2) no history of medication during the
preceding two weeks. Individuals with a diagnosis of specific severe
diseases of the cardiovascular, respiratory, genitourinary, digestive
and haematopoetic systems were routinely excluded. Based on the
exclusion criteria, a total of 1890 eligible Han individuals resident
in Beijing, China, were selected. Prior to recruitment all
participants provided signed informed consent, and the study
was approved by the Ethical Committee of Capital Medical
University, Beijing, China.
The subjects were separated into five age groups, i.e., 18–29,
30–39, 40–49, 50–59 and $60 years old, with 713 (37.7%), 464
(24.6%), 382 (20.2%), 211 (11.2%) and 120 (6.3%) subjects in each
of these groups, respectively. The physical examinations 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. Body mass index
(BMI) was calculated as weight in kilograms divided by height in
meters squared (kg/m2). Blood pressure (BP) was measured twice
on the right arm by well trained nurses using a standard mercury
sphygmomanometer with the subjects pre-resting for at least 5 min
in a sitting position.
2. Proteomic Analysis
2.1 Plasma samples.
obtained according to a standard protocol. Fasting blood samples
were collected from the subjects in the morning by venipuncture
and allowed to clot at 37uC for 0.5 h. Plasma was separated by
centrifugation at 3000 rpm for 15 min and then stored at 280uC
until proteomic analysis.
2.2 Plasma pretreatment with magnetic beads.
plasma samples were fractionated using weak cation exchange
magnetic beads (MB-WCX), according to the instructions
provided by the supplier (ClinProtTM, Bruker Daltonics, Billerica,
USA). The samples were purified and isolated in three steps:
binding, washing, and elution. Firstly, 10 ml beads, 10 ml MB-
WCX binding solution (BS) and 5 ml plasma samples were added
in a tube, mixed carefully and incubated for 5 min. Secondly, the
tube was placed on the magnetic bead separation device (Bruker
Daltonics, Billerica, USA) and the beads were collected at the tube
wall for 1 min. The supernatant was then removed and 100 ml
magnetic bead washing solution (WS) were added, and mixed
thoroughly. After washing three times and removing the super-
natant, another 5 ml magnetic bead eluting solution (ES) were
The plasma samples for analysis were
added and the beads collected at the tube wall in the separation
device for 2 min. After transferring the clear supernatant into a
fresh tube, 5 ml of magnetic bead stabilizing solution (SS) were
added and the tubes mixed thoroughly. The resultant eluates were
then stored at –20uC.
2.3 Anchor chip spotting and protein profiling.
eluted samples were diluted 1:10 in a matrix solution of 0.3 g/l a-
cyano-4-hydroxycinnamic acid in ethanol and acetone (2:1) which
was prepared daily. For example, 1 ml of eluate was added to 10 ml
of matrix solution, and then 1 ml of the mixture was spotted onto a
MALDI-TOF-MS target (AnchorChipTM, Bruker Daltonics, Bill-
erica, USA) and dried at room temperature before analysis.
MALDI-TOF-MS measurements were performed using an
Autoflex TOF instrument (Bruker Daltonics, Billerica, USA). For
quality control purposes, 11 peptides were used as an external
standard preparation with an average molecular weight deviation
of no more than 100 mg/g. The standard preparation was
recalibrated before data acquisition on every eighth sample. In
additional, 13 samples of reference sera were run as external
standards with a coefficient of variability of less than 30%
indicative of acceptable system performance. Profile spectra were
acquired from an average of 400 laser shots per sample. This
determined the peak m/z values or intensities in the mass range of
600–10 000 Da.
2.4 Peptide sequences.
MS/MS experiments for peptide
identification were performed using a nano-liquid chromatogra-
phy–electrospray ionization–tandem mass spectrometry (nano-
LC/ESI–MS/MS) system consisting of an Aquity UPLC system
(Waters, Milford, MA, USA) and a LTQ Obitrap XL mass
equipped with a nano-ESI source. The peptide solutions were
loaded toaC18 trap
(180 mm620 mm65 mm (symmetry)) with a flow rate of 15 ml/
min. The desalted peptides were then analyzed by C18 analytical
(75 mm6150 mm63.5 mm (symmetry)) at a flow rate of 400 nl/
min. Mobile phases A (5% acetonitrile, 0.1% formic acid) and B
(95% acetonitrile, 0.1% formic acid) were used for the analytical
columns. The gradient elution profile was as follows: 5%B–50%B–
80%B–80%B–5%B–5%B in 100 min. The MS instrument was
operated in a data-dependent model, with a full scan range of
400–2000 m/z and a mass resolution of 100 000 (m/z 400). The
eight most intense monoisotopic ions were the precursors for
collision-induced dissociation, and the MS/MS spectra were
limited to two consecutive scans per precursor ion followed by 60 s
of dynamic exclusion.
The resultant chromatograms were analyzed with
BioworksBrowser 3.3.1 SP1 software (Thermo FisherScientific,
Bremen, Germany) and the resulting mass lists were used for
database search with SequestTM(IPI Human (3.45)) software
(Thermo Scientific, Waltham, MA, USA). Parameters for gener-
ating the peak list comprised a parent ion and fragment mass
relative accuracy set at 50 mg/g and 1 Da, respectively.
3 Statistical Analysis
ClinProTools (ClinProt software version 2.0, Bruker Daltonics,
Billerica, USA) was used to subtract the baseline, normalize the
spectra (using total ion current) and determine the peak m/z
values and intensities in the mass range of 600 to 10 000 Da. The
signal-to-noise (S/N) ratio was set higher than 5, and to align the
spectra a mass shift of no more than 0.1% was determined. The
peak area was used for quantitative standardization and a
comparison of relative peak intensity levels between classes was
Proteomic Analysis in Plasma Protein
PLoS ONE | www.plosone.org2July 2012 | Volume 7 | Issue 7 | e39726
also calculated within the software suite. Statistical analyses were
performed by SPSS 13.0 software (IBM Corporation, New York,
USA). Independent-sample t tests were used for the analysis of
normally distributed continuous data, and Mann-Whitney tests for
non-normally distributed continuous data. Chi-square tests were
used for categorical data analysis. In all cases P,0.05 was
accepted as statistically significant.
1. Characteristics of the Subjects
The demographic characteristics of the involved subjects are
summarized in Table 1. A total of 1890 individuals were recruited
into the study, composed of 1136 males (60.1%) and 754 females
(39.9%). The overall median age was 34.00 (95% CI 27.00–45.25)
years, with an age range of 18–82 years. There was no significant
difference in the male and female age ranges. The heights,
weights, SBP and DBP of males were significantly higher
(P,0.001), but the male’s BMI was significantly lower than that
of females (P=0.001).
2. Plasma Peptide Profiles of the Sample
In the plasma peptide profiles of the 1890 Chinese Han
individuals, 84 peptides were detected with masses in the range
0.6–10.0 kDa (Figure 1). There were 65 high frequency peptides
that were detected in more than 20% subjects and six with
frequencies of more than 90% (m/z 877.93, 861.95, 1061.9,
1083.63, 2023.95 and 2368.42).
3. Age- and Gender-associations with Plasma Peptide
To further explore whether plasma peptide profiles are affected
by age, we quantitatively compared the 84 peptide profiles across
the five age groups, with 44 peptides showing significant
differences (P,0.05) between the five age groups (Table S1). Of
these 44 peptides, 27 profiles differed significantly (P,0.05)
between age groups 18–29 and 40–49 years old. Six of the
peptide profiles (m/z 2487.01, 2883.99, 3027.57, 3041.41,
3428.10 and 6981.30) were highly elevated in the 40–49 year
age group (P,0.001) and four of them (m/z 1076.14, 2012.31,
2044.75 and 2065.31) were highly degraded in persons aged 40–
49 years (P,0.001). Only a single peptide was differentially
detected between 30–39 years and $60 years (m/z 1300.91).
We observed that three peptides (m/z 2487.01, 2883.99,
3428.10) gradually increased in concentration in subjects from
18–49 years of age (Figure 2A), while a peptide with m/z 1076.14
showed the reverse trend (Figure 2B). Another four peptides (m/z
2012.31, 2035.22, 2044.75 and 2065.31) were significantly lower
(P,0.05) in the 40–49 year old group when compared to 18–29
year old individuals, but the levels of these peptides rose in the age
group$60 years (Figure 3).
To determine whether the plasma peptide profiles were gender-
dependent, we then analyzed the variability of the peptide profiles
between males and females within each age group. Several
significant differences between the peptide profiles of males and
females were observed (Table S2). Prior to 50 years of age, the
peptide with a mass of 1076.14 was the only significant profile
difference among the three age groups 18–29, 30–39, 40–49 years,
being present at a lower concentration in males than females.
Dividing the study population by gender, we still found that the
peptide with m/z 1076.14 increased significantly (P,0.05) from
18 to 49 years in both males and females (Figure 4). We obtained
more consistently significant changes peptides in the 50–59 and
$60 age groups (m/z 4441.05, 4464.47, 4527.74, 4575.12). All of
the peptides exhibiting a significant change with ageing had
approximately a 1.5 times higher concentration in females than
males, indicating that these particular peptide profiles were
4. Identification of Significant Peptides
Several peaks were identified using the nano-LC/ESI–MS/
MS (Table 2). These proteins were derived from peptide
fragments of the hyperpolarization-activated cyclic nucleotide-
gated potassium channel 1 (HCN1). According to the results
mentioned above, apolipoprotein A-I (ApoA1) and keratin 18
(KRT18) increased with age, while the level of fibrinogen alpha
chain (FGA) decreased with age. In addition, uncharacterized
protein Albumin (ALB) and Pro-Platelet basic protein (PPBP)
were degraded in the group of middle-aged individuals (aged
Table 1. Demographic data of the study subjects.
TotalMale FemaleP value
No. 1890 1136 (60.1%) 754 (39.9%)
Median age (year)34.00 (27.00–45.25)34.00 (27.00–45.00)36.00 (26.00–46.00) 0.512
18–29713 (37.7%)420 (37.0%)293 (38.9%)
30–39464 (24.6%)301 (26.5%)163 (21.6%)
40–49382 (20.2%) 212 (18.7%)170 (22.5%)
50–59211 (11.2%) 111 (9.8%)100 (13.3%)
$60 120 (6.3%)92 (8.1%) 28 (3.7%)
Median height (cm) 169.00 (163.00–173.00)172.00 (169.00–176.00) 162.00 (158.00–166.00)
Median weight (Kg) 67.00 (58.00–76.00) 73.00 (66.00–81.00)57.00 (52.00–63.00)
Median BMI (Kg/m2) 23.67 (21.18–25.91)23.32 (21.05–25.61) 24.08 (21.45–26.34)0.001*
Median SBP (mmHg) 120.00 (110.00–130.00)120.00 (112.00–130.00) 114.00 (104.00–124.00)
Median DBP (mmHg)78.00 (70.00–82.00) 80.00 (70.00–86.00) 72.00 (66.00–80.00)
*P,0.05 was accepted as statistically significant. Data are shown in median and interquartile ranges. BMI: Body Mass Index; SBP: Systolic blood pressure; DBP: Diastolic
Proteomic Analysis in Plasma Protein
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Ageing is a complex and gradual process involving both
physiological and pathological changes in humans. Most previous
investigations have focused on ageing-related biological mecha-
nisms, such as caloric restriction and oxidative stress, genetic
mechanisms of ageing and signal pathways [20,21]. The recent
discovery of ageing-related biomarkers which was enabled by the
development of advanced proteomics technology , means that
biomarker studies are becoming a key feature of ageing research
and as a result potential biomarkers involved in the ageing process
have been reported in different populations [17,18,19].
Proteomic analysis permits investigation of the qualitative,
quantitative, and functional characteristics of protein profiles, and
MALDI-TOF-MS is one of the effective and sensitive approaches
for the identification of potential biomarkers of health and disease
[23,24]. The bead-based fractionation method, which selectively
separates certain peptides according to different chemical chro-
matographic surfaces on the outer layer of magnetic beads, has
been developed for direct use in MALDI-TOF-MS analysis
[25,26]. In combination with bioinformatics software (ClinProt
software version 2.0, Bruker Daltonics, Billerica, USA), weak
cation exchange magnetic beads (WCX-MB) pretreatment and
MALDI-TOF-MS analysis provides a powerful tool for analyzing
and identifying novel biologically informative molecules and has
been successfully applied to biomarker research in cancer [27,28].
Changes in the circulating concentrations of human proteins
can serve as predictive measures of health and disease, e.g. a
decrease in the plasma level of ALB was a predictor of mortality
and correlated with age and health status [29,30], and plasma
fibrinogen (FGA) was found to be an independent risk factor
associated with increased cardiovascular morbidity and mortality
[31,32]. Human ageing is associated with a generalized decline in
the synthesis rates of muscle proteins , but little information is
available on the effect of ageing on liver proteins despite the fact
that almost all human plasma proteins are synthesized and
secreted by the liver.
In this study, we analyzed the plasma protein profiles of study
subjects by performing MALDI–TOF MS combined with WCX-
MB pretreatment to investigate the effect of ageing on plasma
peptide levels. The subjects’ plasma samples were divided into five
age groups to compare the concentrations and profiles of their
plasma peptides. The results showed that 44 peptide peaks differed
significantly between the five age groups in the Chinese Han
population. The relative concentrations of 27 peptide peaks were
significantly different between the 18–29 and 40–49 year age
groups, apparently reflecting the differing physiological status of
Of the proteins examined, the levels of FGA and ALB were
highly degraded in the 40–49 years old group. In addition, the
level of FGA decreased with age between 18 and 50 years of age. It
was reported that serum albumin levels decreased with increasing
age in both men and women in Americans . The association of
albumin concentration with decreased physical function may be
explained by two biological mechanisms. On one hand, albumin is
a negative acute phase protein which decreases with chronic
inflammation. Pro-inflammatory cytokines causing muscle atrophy
have been shown to be associated with physical disability  or
function decline . Therefore to some degree the association
between albumin and physical function could be explained by
chronic inflammation. In addition or alternatively, the albumin
concentration has been correlated with age-associated skeletal
muscle loss in elderly people . Increased muscular atrophy
gradually results in a reduction of muscle strength, which could
mediate the associations between albumin and physical function.
The decreased concentrations of FGA and ALB also might be
caused by a reduction in liver synthetic capacity. An in vivo study
reported a decline in liver weight and generalized liver atrophy
Figure 1. Proteome profiling of a representative healthy individual.
Proteomic Analysis in Plasma Protein
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with ageing, suggesting degraded hepatic capacity for protein
synthesis . However, contrary results were reported in several
epidemiological studies with age-related FGA increases in different
populations [38,39], and there also has been a failure to confirm
an age-related change in the synthesis rate and concentration of
Figure 2. Changes in the expression of peptide profiles with age. (A) Increases in the levels of peptide fragments m/z 2487.01, 2883.99 and
3428.10 with age. (B) Decrease in the level of peptide fragment m/z 1076.14 with age, *P,0.05.
Figure 3. Age-related alteration of the expression of four peptide fragments. The levels of peptide fragments m/z 2012.31, 2035.22,
2044.75 and 2065.31 are significantly lower in the age group 40–49 years. *P,0.05.
Proteomic Analysis in Plasma Protein
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Plasma ApoA1 protein has been reported to significantly
increase with age . As a major protein component of high
density lipoprotein (HDL) in plasma, the level of ApoA1 is
positively associated with HDL cholesterol (HDL-C) levels and it is
one of the indicators of cardiovascular risk. The concentrations of
ApoA1 increased gradually from 18 to 50 years of age in our
study. Another study in Chinese population also identified that
serum apoA1 enhanced greatly with aging, while it decreased
gently after 70 years old , and. in an in vivo study, the
expression of ApoA1 gene influenced by age was reported .
However, transcriptional rate of the ApoAl gene and synthesis of
hepatic ApoA l protein were decreased with age. This positive
relationship of plasma ApoA1 concentration with age was
attributed to decreased turnover rate of plasma proteins, which
is a common feature of aging. Furthermore, we also found that
other proteins, e.g. HCN1, KRT18 and PPBP, were significantly
correlated with age, which is the first such report, although as yet
the specific mechanism remains to be elucidated.
The ageing process and longevity show gender differences. By
comparing the peptide profiles of males and females within each
age group we found that the peptide with mass of 1076.14 (FGA)
was significantly higher in females than males among the persons
younger than 50 years, indicating that FGA was gender-
dependent, but this difference disappeared in persons over 50
years of age. A consistently higher level of fibrinogen in females
than males was reported in a British study on children .
However, no differences were observed between men and women
of various ages in a Japanese cohort study .
In gender terms, we observed that the levels of four unidentified
peptides (m/z 4441.05, 4464.47, 4527.74, 4575.12) were 1.5 times
higher in females than males in the 50–59 and $60 year age
groups. It seems probable that the different hormone levels and
regulation pathway between males and females, especially the
substantial estrogen change in females during the perimenopausal
period, contribute to these differences in the plasma peptide
In conclusion, we applied proteomic tools to analyze the plasma
profiles of 1890 Chinese Han individuals. The results demonstrat-
ed that plasma peptides including FGA, ALB and ApoA1 are
significantly correlated with age and could serve as convenient
biomarkers for ageing-related changes. In addition, our study
suggested that certain plasma peptide profiles are gender-
among the different age groups.
Comparisons of protein expression profiles
profiles between male and female in different age
Significant differences of protein expression
Figure 4. The expression of peptide m/z 1076.14 in males and females. The level of peptide fragment m/z 1076.14 decreases with age in
both males and females. * P,0.05.
Table 2. Proteins identification from the significant peptide
Mass: m/z value, N/A: not available, FGA: fibrinogen alpha chain, ALB: Albumin,
PPBP: Pro-Platelet basic protein, HCN1: hyperpolarization-activated cyclic
nucleotide-gated potassium channel 1, ApoA1: apolipoprotein A-I, KRT18:
Proteomic Analysis in Plasma Protein
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Acknowledgments Download full-text
We acknowledge and thank all participants for their cooperation and
Conceived and designed the experiments: NC MS WW. Performed the
experiments: QM YZ YL. Analyzed the data: JL YW YH. Wrote the
paper: JL WW AHB. Data collection and entry: JW FZ SM XY.
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Proteomic Analysis in Plasma Protein
PLoS ONE | www.plosone.org7July 2012 | Volume 7 | Issue 7 | e39726