Autoantibody Epitope Spreading in the Pre-Clinical
Phase Predicts Progression to Rheumatoid Arthritis
Jeremy Sokolove1,4*., Reuven Bromberg1,4., Kevin D. Deane5, Lauren J. Lahey1,2, Lezlie A. Derber5,
Piyanka E. Chandra1,2, Jess D. Edison6, William R. Gilliland6, Robert J. Tibshirani2,3, Jill M. Norris7, V.
Michael Holers5, William H. Robinson1,4*
1Division of Rheumatology, Department of Medicine, Stanford University School of Medicine, Stanford, California, United States of America, 2Department of Statistics,
Stanford University School of Medicine, Stanford, California, United States of America, 3Department of Health Research and Policy, Stanford University School of Medicine,
Stanford, California, United States of America, 4VA Palo Alto Health Care System, Palo Alto, California, United States of America, 5Division of Rheumatology, Department
of Medicine, University of Colorado School of Medicine, Anschutz Medical Campus, Aurora, Colorado, United States of America, 6Walter Reed Army Medical Center,
Washington, D.C., United States of America, 7Department of Epidemiology, Colorado School of Public Health, University of Colorado, Aurora, Colorado, United States of
Rheumatoid arthritis (RA) is a prototypical autoimmune arthritis affecting nearly 1% of the world population and is a
significant cause of worldwide disability. Though prior studies have demonstrated the appearance of RA-related
autoantibodies years before the onset of clinical RA, the pattern of immunologic events preceding the development of RA
remains unclear. To characterize the evolution of the autoantibody response in the preclinical phase of RA, we used a novel
multiplex autoantigen array to evaluate development of the anti-citrullinated protein antibodies (ACPA) and to determine if
epitope spread correlates with rise in serum cytokines and imminent onset of clinical RA. To do so, we utilized a cohort of 81
patients with clinical RA for whom stored serum was available from 1–12 years prior to disease onset. We evaluated the
accumulation of ACPA subtypes over time and correlated this accumulation with elevations in serum cytokines. We then
used logistic regression to identify a profile of biomarkers which predicts the imminent onset of clinical RA (defined as
within 2 years of testing). We observed a time-dependent expansion of ACPA specificity with the number of ACPA subtypes.
At the earliest timepoints, we found autoantibodies targeting several innate immune ligands including citrullinated
histones, fibrinogen, and biglycan, thus providing insights into the earliest autoantigen targets and potential mechanisms
underlying the onset and development of autoimmunity in RA. Additionally, expansion of the ACPA response strongly
predicted elevations in many inflammatory cytokines including TNF-a, IL-6, IL-12p70, and IFN-c. Thus, we observe that the
preclinical phase of RA is characterized by an accumulation of multiple autoantibody specificities reflecting the process of
epitope spread. Epitope expansion is closely correlated with the appearance of preclinical inflammation, and we identify a
biomarker profile including autoantibodies and cytokines which predicts the imminent onset of clinical arthritis.
Citation: Sokolove J, Bromberg R, Deane KD, Lahey LJ, Derber LA, et al. (2012) Autoantibody Epitope Spreading in the Pre-Clinical Phase Predicts Progression to
Rheumatoid Arthritis. PLoS ONE 7(5): e35296. doi:10.1371/journal.pone.0035296
Editor: Mehrdad Matloubian, University of California San Francisco, United States of America
Received September 13, 2011; Accepted March 13, 2012; Published May 2 , 2012
This is an open-access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for
any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.
Funding: This study was funded by grants from the United States National Institutes of Health and the American College of Rheumatology. The funders had no
role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing Interests: The authors have declared that no competing interests exist.
* E-mail: email@example.com (JS); firstname.lastname@example.org (WHR)
. These authors contributed equally to this work.
Rheumatoid arthritis (RA) is the most common inflammatory
arthritis worldwide affecting 0.5–1% of the population. Though
RA can present at any age, disease onset typically occurs in the
third to eighth decades of life and can cause significant disability,
often within the first 1–2 years of clinical disease onset . In most
cases, the diagnosis of RA is made clinically and is often delayed
by an initial period of non-specific symptoms. It is now generally
accepted that there is a brief window of opportunity for early
aggressive management of RA and that delay results in increased
joint damage and disability , in most cases, the diagnosis may be
delayed by an initial period of non-specific symptoms. Nearly 70%
of cases of established RA are characterized by the presence of
autoantibodies, either rheumatoid factor (RF) or antibodies
directed against citrullinated proteins (ACPA), of which antibodies
to cyclic citrullinated peptides (anti-CCP) are the most specific
clinical test currently available [3–5]. These antibodies and
inflammatory cytokines [6–8] are present years prior to the onset
of symptoms in RA, suggesting that the autoimmune processes
leading to arthritis are present long before overt disease
Although the presence of RF and anti-CCP antibodies can aid
in making a diagnosis of RA, the sensitivity and specificity of these
tests are limited, especially in the early or preclinical period .
Use of these markers to predict the time of future onset of
clinically-apparent RA is limited by the large time interval during
which anti-CCP antibodies and/or RF may be positive prior to
the development of clinical RA. The ability to define where in the
pre-clinical timecourse an individual patient lies could facilitate
PLoS ONE | www.plosone.org1 May 2012 | Volume 7 | Issue 5 | e35296
not only early identification, but even pre-clinical treatment, in an
effort to prevent RA associated morbidity and/or achieve disease
prevention. Additionally, the ability to identify and observe the
break of immunologic tolerance at the earliest stages of disease
could provide significant insights into the pathogenesis of RA and
could be used to guide initiation of disease modifying or even
tolerizing therapy .
In this study, we utilize preclinical RA serum samples obtained
from a cohort of military patients who ultimately progressed to
clinical RA to characterize autoantibody reactivity and cytokine
levels during the pre-clinical period. We demonstrate epitope
spread of autoantibody responses and a crescendo of cytokine
elevations precede the development of clinical RA. Finally, we
identify a panel of autoantibody and cytokine markers that predict
the imminent development of clinically active RA.
Description of patients and sample characteristics
Baseline demographics are presented in Table 1 and discussed
in the methods. The population studied was representative of the
military population from which it was drawn with a higher
representation of males (60% males) and a slightly younger mean
age of clinical onset (age 39). However, no differences were found
between genders in outcomes in several stratified anlyses (data not
shown). Of 81 subjects included in the analysis, 27 had no
autoantibodies detected in their earliest serum specimen and of
these all demonstrated at least one autoantibody at a future
preclinical RA timepoint. 55 patients were anti-CCP2+ at any
timepoint, of which 26 were anti-CCP2+ at outset and 29
converted from anti-CCP22 to anti-CCP2+ during the period of
Accumulation of autoantibodies precedes that of
cytokines and chemokines
Figure S1 provides a heatmap presenting the overall results of
all markers analyzed, with specimens binned by 2 year intervals
preceding RA diagnosis. Two year intervals were chosen to
provide as many ‘‘windows’’ as possible into the pre-clinical phase
while still allowing a robust number of subjects at each ‘‘bin’’ and
to avoid measuring the same subjects in the same ‘‘bin’’ more than
Though some specimens are highly reactive more than 8 years
prior to the diagnosis of RA, there is a clear accumulation of
autoantibody reactivity over time as individuals approach the
development of clinical RA. A similar trend is noted for
accumulation of cytokines over the pre-clinical period with
temporal lag in the development of cytokine elevations relative
to elevations in autoantibodies.
Anti-CCP2 antibody titer is correlated with increasing
number of ACPAs and followed by a rise in serum
The ACPA immune response targets a broad range of
citrullinated antigens [11,12], however, the exact identity of the
CCP2 peptide epitopes are currently proprietary and thus
unknown. However, the anti-CCP2 test has been demonstrated
to captures several overlapping reactivity of ACPA targets .
We demonstrate a parallel rise in the number of ACPA subtypes
with increasing titer of anti-CCP2 reactivity (Figure 1A and B)
suggesting that the ACPA specificities identified likely represent
the antibodies bound by CCP2, which represents an artificial
mimic of the true citrullinated antigens in RA. Further, our results
suggest that the rise in anti-CCP2 titer at least partially represents
progressive epitope spread of the autoreactive B cell response
targeting citrullinated antigens during the preclinical period.
Notably, the rise in both anti-CCP2 antibody titer and number
of ACPA subtypes is followed by a rise in serum cytokines
(Figure 1C). A very similar rise in hsCRP was noted over the
preclinical period as demonstrated in Figure S4A.
Patterns of autoantibody accumulation
To further evaluate the pattern of autoantibody accumulation
over time, we calculated the proportion of subjects positive for
each biomarker at each timepoint and generated Kaplan Meier
survival curves to compare rates of accumulation (Figure 1E).
Though each to a different extent, we observed a gradual increase
in rates of positivity for each ACPA approaching clinical diagnosis
of RA. Additionally, there were notable differences in the
proportion of subjects targeting each antigen as well as the profile
of antigens targeted by each individual. Citrullinated histone 2B,
citrullinated vimentin, and peptides derived from citrullinated
enolase, and fibrinogen represented the most prominent early
targets in the pre-clinical period of RA with positive titers in over
Table 1. Subject demographics.
Mean Age at diagnosis39.0 39.1
Years prior to diagnosis of first sample, Mean (STD) 6.4 (3.7)6.4 (3.7)
Male49 (60%) 49 (60%)
RaceWhite: 57 (70%) White: 57 (70%)
Black: 20 (25%)Black: 20 (25%)
Other: 4 (5%) Other: 4 (5%)
Samples Per Person, Mean (STD)3.5 (1.2)3.5 (1.2)
Year range (relative to RA diagnosis)
213.6 to 11.7
213.6 to 11.6
Anti-CCP2 Ever Positive (at sample time)55 (68%)0 (0%)
Anti-CCP2 at time of serum sample 130 (46%)0 (0%)
Erosions41 (51%) (7 unknown)
Autoantibody Profiling in Preclinical RA
PLoS ONE | www.plosone.org2May 2012 | Volume 7 | Issue 5 | e35296
25% of subject at 10 year prior to clinical RA onset (Figure 1E).
Similar to the results demonstrated in Figure 1B and C, the rise in
individual antibodies was followed by the appearance of multiple
serum cytokines, again, at a time more proximate to disease onset
ACPA epitope spread is associated with the rise in serum
To assess for associations between the accumulation of
autoantibodies and the presence of inflammatory cytokines, we
evaluated the correlation between the number of ACPA subtypes
with the levels of serum cytokines. Cytokines prominently elevated
in association with increased epitope spread included many of
those classically implicated in RA pathogenesis  including
TNF-a, IL-6, IL-12p70, IFN-c, IL-2, and IL-15 (Figure 1D).
Notably, this pattern extends to only a limited number of cytokines
suggesting specificity of the cytokine rise associated with expansion
of the APCA repertoire. Similar to RA-associated cytokines, level
of hsCRP was found to be associated with increasing number of
ACPA specificities preceding and associated with the
development of anti-CCP2 reactivity
To assess for the development of anti-citrulline reactivity prior
to the onset of anti-CCP2 antibody seroconversion, we performed
paired SAM analysis of samples derived from individuals who
ultimately became anti-CCP2+ but were anti-CCP22 at two
timepoints (at least 9 months apart) prior to anti-CCP2
seroconversion. We found evidence of accumulating autoantibody
specificities targeting citrullinated histones, fibrinogen, biglycan,
and clusterin in subsets of patients preceding the onset of CCP2
reactivity (Figure 2A).
To identify markers associated with the transition from anti-
CCP22 to anti-CCP2+, we performed paired analysis to identify
differences in autoantibody profiles immediately prior to, and the
first timepoint after, anti-CCP2 seroconversion. Our results
demonstrate epitope spread of B cell responses against multiple
citrullinated antigens in a similar time period to that of anti-CCP2
seroconversion (Figure 2B).
Multiplex profiles predict imminent development of RA
The ability to predict when an individual will develop clinical
RA could facilitate early intervention, and perhaps even preven-
tion, of RA. Using our panel of biomarkers, we applied multiple
Figure 1. The number of elevated autoantibodies and cytokines increase as individuals in the preclinical period approach the
clinical diagnosis of RA. A–C, Mean titers of CCP2 (A), mean total number of ACPAs (B), and mean total number of cytokines (C) were evaluated at
each time preclinical timepoint demonstrating a parallel rise in number of ACPA epitopes with rise in anti-CCP2 titer. D, The percent of subjects with
elevated levels of each cytokine was evaluated in relation to number of ACPA subtypes present (representative examples of 48 measured cytokines)
E, The proportion of subjects positive for each ACPA subtype was evaluated over the preclinical period. The X axis represents days relative to the
diagnosis of RA. The Y axis represents the proportion of pre-clinical RA patients with positive value for each marker relative to total number of
specimens available for analysis at that timepoint. A–E, Anti-CCP2 antibody titers were measured by CCP2 ELISA (A), ACPA subtypes were measured
using a custom multiplex autoantigen bead array, serum cytokine concentrations were measured using commercial bead based multiplex cytokine
Autoantibody Profiling in Preclinical RA
PLoS ONE | www.plosone.org 3May 2012 | Volume 7 | Issue 5 | e35296
logistic regression analysis to preclinical-RA patients to determine
when a subject/sample was within two years of clinical RA
(imminent RA) or at a timepoint not yet within two years of
clinical RA. Given the prolonged duration of anti-CCP2 antibody
positivity (approximately 6 years ) in the preclinical phase, this
marker offered minimal predictive utility for imminent onset of
clinical RA. However a panel of autoantibodies and cytokines
derived from our array displayed a moderate sensitivity (58.2%)
and but significant specificity (87%) for identifying patients who
were within 2 years of clinical RA onset (Table 2 and Figure 3A).
This profile includes autoantibodies targeting epitopes derived
from citrullinated fibrinogen (Fibrinogen A 616–635 cit 3 cyc) as
well as citrullinated enolase (Enolase 5–21 cit) and whole
citrullinated vimentin. Cytokines identifies as predictors included
IL-12(p70), IL-1b, IL-5, IL-7, LIF, and TNF-b When each
biomarker was evaluated individually, wide deviation limited
predictive ability (Figure 3B, and figure S2C), however a use of a
multiplex profile of biomarkers predicted imminent onset of RA
(Table 2 and Figure 3A). Notably, several ACPA, become positive
on only 50–70% of cases (for example, enolase 5–21 cit became
positive in approximately 60% of cases) thus identifying one cause
for imperfect sensitivity while at the same time demonstrating the
specificity of the chosen markers.
In this study we use multiplex autoantibody and cytokine
analyses of serum samples to evaluate RA-related autoimmunity
and inflammation in the preclinical period. We identified the
presence of anti-citrulline autoimmunity years before clinical
diagnosis, and demonstrate that preclinical epitope spreading of
ACPA responses is associated with the emergence of subclinical
inflammation and ultimately, the onset of clinical RA. There was a
crescendo in the development of elevated levels of serum
autoantibodies as well as cytokines as individuals approached the
development of clinical RA. These data demonstrate that epitope
spreading of anti-citrulline B cell autoimmunity occurs concur-
rently with increases in anti-CCP2 antibody reactivity, and that
accumulation of anti-citrulline reactivities likely represents the
preponderance of what is measured clinically as the anti-CCP2
antibody response. We found evidence of autoantibody targeting
of several citrullinated proteins including histones, fibrinogen, and
biglycan at the earliest measured timepoints and well prior to
development of anti-CCP2 positivity. Early targeting of these
innate immune ligands provides potential insights into the
mechanisms underlying the initiation of autoimmunity in RA
(discussed below). Additionally, we demonstrate a successive
accumulation of anti-citrulline autoimmunity before, during, and
after the appearance of anti-CCP2 antibody reactivity. Finally, we
identify a profile of ACPA subtypes in combination serum
cytokines which identify pre-disease patients who were within 2
years of clinical RA onset. Though it is not clear that there is a
period when RA is uniquely sensitive to therapy, or that
individuals can be treated in a manner to regain tolerance to
critical self antigens. However, the ability to identify individuals in
the earliest phases of disease would provide a potential window of
opportunity for studies to investigate very early or even preclinical
Similar to work in systemic lupus [15,16], several of the earliest
and most prominent autoantigens identified in our study have
been demonstrated to possess innate immune stimulatory capacity
including fibrinogen , biglycan , and histones . Work
by our group  has demonstrated the ability of citrullinated
fibrinogen-containing immune complexes to co-stimulate macro-
phage cytokine production, and others [19,21,22] have demon-
strated the ability of DNA or RNA-containing immune complexes
to stimulate B-cell proliferation and dendritic cell cytokines
activation via Toll-like receptors. Thus, the presence of citrulli-
nated antigen-immune complex with the potential co-stimulate B
cells and/or macrophage further implies that a break in tolerance
to citrulline modified proteins may function in the initiation,
propagation, and effecter phases of clinical RA development.
Figure 2. Accumulation of ACPA fine specificity before and concurrent with anti-CCP2 antibody seroconversion. A, Paired SAM
analysis was performed on serum specimens from pre-clinical RA patients from whom at least 2 specimens were available prior to anti-CCP2 antibody
seroconversion. B, Paired SAM analysis was performed on serum specimens from pre-clinical RA patients for whom a serum specimen was available
both prior to and after anti-CCP2 antibody seroconversion. The heatmap represents absolute change in Z-score* from the first to the second
timepoint. *Z-score represents the number of standard deviations above or the below the mean level observed in control subjects for each cytokine
or autoantibody thus increase in Z-score represents increased change from normal population.
Autoantibody Profiling in Preclinical RA
PLoS ONE | www.plosone.org4 May 2012 | Volume 7 | Issue 5 | e35296
Several previous studies have examined preclinical autoanti-
bodies including anti-CCP antibodies [3–5], certain anti-citrulli-
nated protein antibodies [23,24], and rheumatoid factor [25–27]
and others have demonstrated a preclinical rise in serum cytokines
or other inflammatory markers [7,8,28]. Similar to our result,
Jorgensen, et al [29,30] observed that the presence of anti-CCP
antibodies and RF preceded the elevation serum cytokines and
Nielen, at al.  found that the appearance of anti-CCP and RF
antibodies shortly preceded a rise in CRP levels. Interestingly, Aho
et al , were unable to show preclinical elevations of CRP, even
in individuals with longstanding elevation of RF, though they did
not measure serum cytokines and it is possible that there is a
narrower window needed to observe a rise in preclinical CRP .
Several groups have determined the sensitivity and specificity of
anti-CCP and RF antibodies in preclinical subjects for the ultimate
diagnosis of RA [3,4]. Here we demonstrate the utility of ACPA
and cytokine profiling to identify individuals at high risk for
imminent progression to RA. Our study demonstrates the use of a
panel of ACPA specific for the citrullinated epitopes present on
our arrays as well as cytokines, in a multiplex fashion, to improve
preclinical diagnostic accuracy and to narrow the temporal period
during which an at-risk individual will develop RA. These profiles
could be applied to identify individuals in populations at high risk
for developing, including first degree relatives [33,34] and those
with early musculoskeletal compaints . The benefit to such
knowledge includes the potential to identify individuals with
imminent or very early RA and thereby provide the opportunity to
intervene at a time either before, or very early in clinical RA
Several groups have attempted to predict which individuals will
progress from early undifferentiated arthritis (UA) to RA [36–38],
and found that the presence of RF and anti-CCP antibodies to be
highly associated with progression to clinical RA. Similarly, van
der Woude and colleagues, using a panel of 5 citrullinated
peptides, observed an increase in the number of epitopes
recognized over the period preceding RA onset as well as in
those progressing from UA to RA . Additionally, a recent
interventional study demonstrated that methotrexate therapy
during the period of UA significantly increased the proportion of
patients entering clinical remission, though this benefit was limited
to patients with anti-CCP antibody reactivity . Thus use of a
more sensitive APCA profile could allow identification of other
who would benefit from such intervention and potentially even
earlier in the pre-RA period. Preclinical autoantibody accumula-
tion has similarly been associated with development of systemic
lupus , multiple sclerosis , and type 1 diabetes. Thus,
multiplex platforms such as ours may be amenable to translation
to other autoimmune conditions and similar techniques to identify
multiplex profiles may be utilized for prediction of disease onset or
outcome in other disease types.
Autoantibody profiling of sera derived from animal models of
RA and multiple sclerosis (MS), in which a single protein is used as
the immunogen, have demonstrated a pattern of intra- and inter-
molecular epitope spreading leading up to and through clinical
disease onset , and autoantibody profiles have been used to
guide tolerizing therapies in the same models [10,43]. Thus
profiling of autoantibody fine specificity has the potential to be
applied to individuals in the earliest phases of clinical arthritis, a
time period during which they would potentially respond to
specific tolerizing therapies.
Our results support a model in which, in the predisposed host
(due to genetics and/or environment), there is an initial break in
tolerance to naturally occurring citrullinated antigen(s) such as
histones  or fibrinogen  which is followed by inter- and
Figure 3. Prediction of imminent RA using multiplex biomarkers. Multiple logistic regression was performed to identify markers from the
reduced set of 21 antibodies and 38 cytokines which could classify pre-clinical RA subjects as being within 2 years of the onset of clinical RA. 5-fold
cross validation was performed and common markers selected for final validation. A, Demonstrated is a receiver operating characteristic (ROC) curve
using the panel of markers listed in table 3. B–C, Mean and standard deviation of values for each individual autoantibody (B) or cytokine (C)
contributing to prediction of imminent onset RA as measured among controls, those RA patients at a timepoint greater than 2 years prior to RA
onset, or those within 2 years of clinical RA onset.
Table 2. Multiplex predictors of imminent RA diagnosis.
Imminent RA Biomarker profile58.2% (32/55)87.0%(92/106)70.0% (32/46)80%(92/115)
Autoantibody Profiling in Preclinical RA
PLoS ONE | www.plosone.org5 May 2012 | Volume 7 | Issue 5 | e35296
intra-molecular epitope spreading. Our finding that autoantibody
targeting of citrullinated histones, fibrinogen, and biglycan, all
molecules that bind innate immune receptors, supports a model in
which citrullination of these antigens could co-ligate receptors on
B cells to trigger an autoantibody response against these molecules.
Given the ability of autoadjuvant-containing immune complexes
to stimulate B cells in systemic lupus , and the ability of
citrullinated fibrinogen immune complexes to co-stimulate mac-
rophage , an analogous mechanism could activate B cells
specific for citrullinated histones or fibrinogen to produce and thus
initiate the process of epitope spreading to a broad range of
citrullinated antigens. We hypothesize that at a threshold in the
number of ACPA and/or development of a critical specificity
profile there is initiation and/or propagation of a subclinical
inflammatory response manifest by a rise in serum cytokines.
Whether this is of articular origin is uncertain, as the relationships
between the likely extra-articular site of initial autoantibody
generation in RA to inflammation in the joint is currently
unknown. In addition, the increase in inflammation may also
reflect alterations in effector functions of ACPA to allow more
effective complement/FcR engagement, or IgE-mediated mast cell
activation. Ultimately, the autoimmune response reaches an
inflammatory threshold characteristic of clinically apparent RA.
Of interest, a nadir was noted in ACPA and cytokines
approximately 4 and 3 years prior to diagnosis, respectively
(Figure 1B,C). It is interesting to hypothesize that this may be
related to a regulatory process which attempts to, and in the case
of those who ultimately develop RA, fails to prevent the
development of clinical autoimmunity. It does not seem related
to processing or storage as samples in this preclinical timeframe as
these samples were collected and processed over a wide time-frame
relative to each other.
Limitations of our study include use of synthetic peptides which
were citrullinated at sites of potential modification, only some of
which have been confirmed in vivo. Similarly, cyclization may
provide not only increased signal to noise but also reactivity to
epitopes not naturally targeted in RA patients. Additionally, it is
possible that, in certain autoantigens, 3-dimensional epitopes are
critical to autoantibody recognition, and thus we may miss
reactivity against antigens that are represented on the array only
by peptides or for which conjugation to beads results in
conformational hindrance. Our arrays include antigens implicated
in the literature and identified through proteomic screens
performed in our laboratory and in the laboratories of our
collaborators , and thus may omit critical autoantigens or
antigenic modifications  not previously described. This is
especially problematic if we seek to extrapolate our results to
seronegative (i.e., true ACPA negative) samples, for which the
target antigens have not been identified. Additionally, the
measurement of only total IgG ACPA and not IgG isotypes, IgA
or IgM may miss signal related to maturation of the adaptive
immune response  or similarly miss a signal from the recently
observed IgE ACPA response . Our study population
represents a relatively younger, healthier, population (reflecting a
typical military population). Thus, our findings may overestimate
specificity for RA in these subjects, especially when compared to
an older and the more heavily female population that would be
encountered when screening a more general population at risk for
RA. We were also limited by the broad variability in the timing of
serum sampling within our cohort. Given the lack of consistent
sampling intervals, in many cases we were unable to define the
exact time of seroconversion for specific epitopes and thus likely
overestimate the proximity to disease onset of their appearance.
We suspect this spread in sampling, in addition to patient
variability, limited our ability to define patterns of autoantibody
fine specificity, especially in the earliest phase of autoimmunity
when the break in immune tolerance first occurs. Similarly, there
is likely wide variety in the timing of presentation with ‘‘clinical
RA’’ both due to to patient delay as well as different thresholds to
assign diagnosis by physicians. It is also notable that time of
diagnosis could be substantially earlier if the new 2010 ACR/
EULAR RA criteria  were utilized rather than 1987 guidelines
. However, it is useful to point out that the median time of
onset of symptoms was ,six months prior to diagnosis, and in no
instance where it could be assessed did symptoms precede the
presence of autoantibodies .
Finally, it is clear that despite attempts to remove redundant
biomarkers, there was still significant overlap in markers used for
our final analysis. Given the high degree of correlation among
ACPA reactivities and between many cytokines, entry of these
markers into our stepwise regression analysis could have poten-
tially yielded other closely-related but valid profiles with similar
predictive ability. Thus it is difficult to definitively establish that
our biomarker panel has unique predictive ability rather than
being representative of a critical accumulation of ACPA and
inflammatory mediators. In conclusion, we demonstrate that
progression from preclinical autoimmunity to clinical RA is
associated with (i) progressive epitope spreading of the ACPA
response, as evidenced by the targeting of additional citrullinated
epitopes (both intramolecular and intermolecular spreading), (ii)
inflammation, as evidenced by increases in blood cytokine levels,
and (iii) that citrullinated protein epitopes derived from fibrinogen,
histones and vimentin are targeted at the earliest observable break
in tolerance to citrullinated antigens in at least a subset of
individuals with preclinical RA. Together, these results further
suggest that the development and epitope spreading of anti-
citrullinated protein autoimmunity plays a central role in the
initiation of RA-associated autoimmunity as well as progression of
individuals from preclinical to clinical RA. Finally, further
development and validation of preclinical ACPA and cytokine
profiling provides the opportunity to identify and potentially
intervene in those individuals at highest risk for imminent
development of clinical RA.
The Department of Defense Serum Repository (DoDSR) was
established in 1989 and has stored serum samples obtained from
the United States Armed Forces personnel on enlistment,
deployment, and, on average, every other year thereafter. Samples
are stored in a central repository at 230 deg C.
For this analysis, the study group included members of the US
Military assigned to the North Atlantic Medical Region who were
seen at the Walter Reed Army Medical Center (WRAMC)
Rheumatology Clinic between 1989–2003 and were diagnosed
with RA. Of 156 new onset cases of RA, 83 were found to have
prediagnosis serum samples available in the DoDSR, with 66
(80%) having two or more prediagnosis serum samples, and 39
(47%) having four prediagnosis samples. Eighty-three control
subjects without RA matched to cases based on age, gender, race,
and region of assignment, and time of serum sampling were
selected from the DoDSR. Of the 83 cases with pre-diagnosis
serum samples, 81 met at least four of seven criteria for RA based
on the 1987 American Rheumatism Association’s revised criteria
and two cases met three of seven criteria and were considered to
have RA by board-certified rheumatologists.
Autoantibody Profiling in Preclinical RA
PLoS ONE | www.plosone.org6May 2012 | Volume 7 | Issue 5 | e35296
Two cases and respective controls were excluded for lack of
available sample within the immediate 10 years preceding clinical
diagnosis. Five samples (3 cases, 2 controls) were excluded due to
fluorescent values of over 800 on reagent blank beads, a control
procedure utilized to identify non-specific elevations in fluores-
cence. Demographic information was obtained by chart review at
the WRAMC (Table 1). The mean age at diagnosis was 39 and
mean time of the earliest serum sample was 6.4 year before
diagnosis, with a mean of 3.5 samples per patient available for
analysis. Reflecting a military population, the cohort was 60%
Investigators at Stanford University were blinded to group
assignments at the time of antibody and cytokine profiling. After
the autoantibody and cytokine testing was completed, the coding
key was provided to link the serum samples to subject data.
The study protocol was approved by the respective Institutional
Review Boards at the Walter Reed Army Medical Center
(WRAMC), the University of Colorado, and Stanford University.
Due to the retrospective nature of this serum repository cohort,
informed consent from subjects was not possible and thus the need
for informed consent for the retrospective serum retrieval protocol
was waived by the ethics committees at WRAMC and University
of Colorado. All investigations conformed to the principles
expressed in the 1975 Declaration of Helsinki .
Clinical autoantibody assays
Anti-CCP2 antibodies assays were performed at the University
of Colorado School of Medicine in the Rheumatology Clinical
Research Laboratory using a CCP2 ELISA kit (Diastat, Axis-
Shield Diagnostics.) as previously described . For anti-CCP2
testing, based on the cut-off level established by the manufacturers,
a level of .5 units was considered positive.
Multiplex cytokine assays
We performed multiplex analysis of 48 cytokines and chemo-
kines (listed in Table S2) using the Bio-PlexTMbead array system
as recommended by the manufacturer. Using manufacturer
provided reagents, we evaluated several commercial reagents to
suppress the effect of heterophilic antibodies and, similar to the
observation of others  and in contrast to our previous
observations with other commercial kits , found that none
consistently suppressed cytokine values in those specimens
containing RF relative to those without RF. Data processing was
performed using Bio-Plex manager software version 4.4.1 and
serum concentrations were interpolated from standard curves for
each respective cytokine. All cytokines were evaluated using Cox
proportional hazards regression and only cytokines with a
significant hazard ratio (P,0.05) between cases and controls were
using in the final analyses (Table S1). This protocol and data
generated were MAIME compliant and were deposited in the
Gene ExpressionOmnibus Repository
Multiplex autoantibody assays
We developed a novel multiplex platform for analysis of 17
autoantibodies targeting putative RA associated autoantigens (and
3 native protein controls; Table S1) using a custom Bio-PlexTM
bead-based autoantibody assays in which antigens are conjugated
to spectrally-distinct beads (described above). Briefly, protein
antigens were coupled to beads using N-hydroxysuccinimide ester
chemistry, and peptide antigens synthesized with C- terminal
biotin (by Fmoc chemistry) and coupled to avidin-coated beads.
Pooled beads were mixed with serum samples and diluents and
incubated at room temperature. After washing, anti-human IgG
antibody conjugated to phycoerythrin (PE) was added to the dyed
beads and incubated at room temperature. After another wash,
the bead mixture was passed through a laser detector (Luminex
200) that identifies beads based on the fluorescence of the dyes.
The amount of antibody bound to each bead was determined by
the fluorescence of PE.
For all analyses, three internal controls consisting of sera pooled
from individuals with low, intermediate, or high autoantibody
reactivity were run in parallel to assure reproducibility. . Each
bead mixture contained serum verification beads and reagent
blank beads (RBB) used to verify the addition of serum and the
absence of significant nonspecific binding, respectively. This assay
yielded highly reproducible results with 7 fold intra-assay
coefficient of variance of 0.9–6.8% and 14 fold inter-assay CV
ranging from 5.9–19.5% (over 90% of beads yielding inter-assay
variances of ,12%; Table S2.) This protocol and data generated
were MAIME compliant and were deposited in the Gene
Expression Omnibus Repository (accession number GSE32021;
For descriptive analyses of the biomarker data as continuous
variables, raw data was normalized by calculating a Z-score using
the formula: ((observed value)-(mean value of control patients))/
(standard deviation). Z-scores were used because of the differing
magnitudes and variances between levels of individual cytokines
and autoantibodies; without standardization the analyses are
dominated by numerical differences rather than comparative
differences in cytokine or autoantibody level. Normalized values
thus represent the number of standard deviation above or the
below the mean level seen in control subjects for each cytokine or
autoantibody. For predictive modeling, data were cube root
transformed and positive markers defined as 3 standard deviations
above the mean levels of that marker in all normal control
In some patients, markers calculated to be positive at an early
timepoint were subsequently calculated to be negative (this was
observed for less than 10% of measurements), however most
ultimately reverted back to positive at a future timepoint. For
descriptive analyses, if a test was positive once, then reverted to
negative without a subsequent positive, the test was counted as
negative. Likewise, if a positive test became negative, but was then
positive on the subsequent measure, then all interval results were
considered positive. For modeling analyses no such correction was
For timepoint comparisons, Z-normalized values were analyzed
by SAM (Significance Analysis of Microarrays Version 3.08) .
Output was sorted based on false discovery rates (FDRs) in order
to identify antigens with the greatest differences in autoantibody
reactivity between RA patients at different time points. We used
hierarchical clustering software ClusterH 3.0 to arrange the SAM
results according to similarities among autoantibody specificities,
and results were displayed using Java TreeviewH (Version 1.1.3).
Predictive modeling of imminent onset RA
To define a profile of markers which is associated with
imminent onset of RA, logistic regression analysis was performed
(JMP, SAS Institute Inc.) between groups defined as (i) imminent
RA (within 2 years of RA diagnosis) or (ii) non-imminent RA.
Modeling was performed on cube root normalized values of
cytokine concentrations or autoantibody florescent intensities
dichotomized as positive or negative (as above). Nested models
Autoantibody Profiling in Preclinical RA
PLoS ONE | www.plosone.org7 May 2012 | Volume 7 | Issue 5 | e35296
were constructed, 20% of samples were held for the test set, and 5
fold internal cross-validation used for marker selection from the
training set. To improve diagnostic homogeneity, our prediction
model was limited to RA subjects whom were ultimately anti-
CCP2+ at time of diagnosis (n=55 subjects, 68%; 438 serum
samples of which 390 were classified as ‘‘non-imminent’’, and 48
were classified as ‘‘imminent’’).
analyzed. Final antigen list was selected as described in the
methods section. Cytokines/chemokines were evaluated using a
commercial 27-plex and 21-plex cytokine/chemokine kit (Bio-Rad
Laboratories). For the all predictive analyses only analytes which
significantly different between RA cases and healthy matched
controls were used for statistical modeling.
List of antigens and cytokines/chemokines
Tab e S2 Representative intra-assay and inter-assay
coefficients of variance (CV) on the BioPlex antigen
array platform. To validate the reliability of the novel bead-
based antigen array 7-fold intra-assay and 14-fold inter-assay CV
during the preclinical period in individuals that devel-
oped RA. Results from preclinical and post-diagnosis serum
specimens were binned by timepoints relative to the time of
diagnosis of clinical RA, and the matched samples from health
controls binned binned in a parallel manner. Results are expressed
as *Z-normalized values for each biomarker, and the scalebar
represents Z-normalized value. *Z-normalized values represent the
number of standard deviations above or the below the mean level
observed in control subjects for each cytokine or autoantibody.
Heatmap of autoantibody and cytokine levels
markers contributing to imminent RA biomarker pro-
file. Scatter plots demonstrate actual values and range of
Alternative demonstration of values of bio-
individual subjects for each biomarker comprising the imminent
RA biomarker profile. Imminent onset RA is defined as onset
within 2 years of serum sampling.
period. The X axis represents days relative to the diagnosis of
RA. The Y axis represents the proportion of pre-clinical RA
patients with positive value for each marker relative to total
number of specimens available for analysis at that timepoint. Note,
cytokines with no observed rise are represented as incomplete lines
to allow visualization of rising curves.
The proportion of subjects positive for each
Mean level of hsCRP evaluated at each preclinical timepoint
demonstrates a rise in concentration during the preclinical period
(as observed for ACPA and cytokine number as well as anti-CCP2
titer demonstrated in Figures 1 A, B, C). B, Percent of subjects
with elevated levels of hsCRP was evaluated in relation to number
of ACPA subtypes present.
Evaluation of preclinical rise in hsCRP. A,
The authors would like to thank Steve Binder and Michelle Delanoy of
Bio-Rad Laboratories (Hercules, CA) for their provision of antigen-coated
beads, technical support, and technical guidance.
Statistical planning and development of methodology was done in
cooperation with RJT but all analyses were performed by JS and RB.
The views expressed herein are those of the authors and do not reflect
the official policy of the Department of the Army, Department of Defense,
or US government.
Conceived and designed the experiments: JS RB KDD LAD JDE WRG
JMN VMH WHR. Performed the experiments: JS RB LJL PEC RJT.
Analyzed the data: JS RB LJL PEC RJT. Contributed reagents/materials/
analysis tools: LAD JDE WRG VMH. Wrote the paper: JS RB KDD JMN
1.Doeglas D, Suurmeijer T, Krol B, Sanderman R, van Leeuwen M, et al. (1995)
Work disability in early rheumatoid arthritis. Ann Rheum Dis 54: 455–460.
O’Dell JR (2002) Treating rheumatoid arthritis early: a window of opportunity?
Arthritis Rheum 46: 283–285.
Nielen MM, van Schaardenburg D, Reesink HW, van de Stadt RJ, van der
Horst-Bruinsma IE, et al. (2004) Specific autoantibodies precede the symptoms
of rheumatoid arthritis: a study of serial measurements in blood donors. Arthritis
Rheum 50: 380–386.
Rantapaa-Dahlqvist S, de Jong BA, Berglin E, Hallmans G, Wadell G, et al.
(2003) Antibodies against cyclic citrullinated peptide and IgA rheumatoid factor
predict the development of rheumatoid arthritis. Arthritis Rheum 48:
Majka DS, Deane KD, Parrish LA, Lazar AA, Baron AE, et al. (2008) Duration
of preclinical rheumatoid arthritis-related autoantibody positivity increases in
subjects with older age at time of disease diagnosis. Ann Rheum Dis 67:
Jagannathan M, Hasturk H, Liang Y, Shin H, Hetzel JT, et al. (2009) TLR
cross-talk specifically regulates cytokine production by B cells from chronic
inflammatory disease patients. J Immunol 183: 7461–7470.
Deane KD, O’Donnell CI, Hueber W, Majka DS, Lazar AA, et al. (2010) The
number of elevated cytokines/chemokines in pre-clinical seropositive rheuma-
toid arthritis predicts time to diagnosis in an age-dependent manner. Arthritis
Kokkonen H, Soderstrom I, Rocklov J, Hallmans G, Lejon K, et al. (2010) Up-
regulation of cytokines and chemokines predates the onset of rheumatoid
arthritis. Arthritis Rheum 62: 383–391.
9. Nishimura K, Sugiyama D, Kogata Y, Tsuji G, Nakazawa T, et al. (2007) Meta-
analysis: diagnostic accuracy of anti-cyclic citrullinated peptide antibody and
rheumatoid factor for rheumatoid arthritis. Ann Intern Med 146: 797–808.
10. Robinson WH, Fontoura P, Lee BJ, de Vegvar HE, Tom J, et al. (2003) Protein
microarrays guide tolerizing DNA vaccine treatment of autoimmune enceph-
alomyelitis. Nat Biotechnol 21: 1033–1039.
11. Snir O, Widhe M, von Spee C, Lindberg J, Padyukov L, et al. (2009) Multiple
antibody reactivities to citrullinated antigens in sera from patients with
rheumatoid arthritis: association with HLA-DRB1 alleles. Ann Rheum Dis 68:
12. Hueber W, Kidd BA, Tomooka BH, Lee BJ, Bruce B, et al. (2005) Antigen
microarray profiling of autoantibodies in rheumatoid arthritis. Arthritis Rheum
13. Ioan-Facsinay A, el-Bannoudi H, Scherer HU, van der Woude D, Menard HA,
et al. (2011) Anti-cyclic citrullinated peptide antibodies are a collection of anti-
citrullinated protein antibodies and contain overlapping and non-overlapping
reactivities. Ann Rheum Dis 70: 188–193.
14. Brennan FM, McInnes IB (2008) Evidence that cytokines play a role in
rheumatoid arthritis. J Clin Invest 118: 3537–3545.
15. Marshak-Rothstein A, Rifkin IR (2007) Immunologically active autoantigens:
the role of toll-like receptors in the development of chronic inflammatory
disease. Annu Rev Immunol 25: 419–441.
16. Arbuckle MR, McClain MT, Rubertone MV, Scofield RH, Dennis GJ, et al.
(2003) Development of autoantibodies before the clinical onset of systemic lupus
erythematosus. N Engl J Med 349: 1526–1533.
17. Sokolove J, Zhao X, Chandra PE, Robinson WH (2011) Immune complexes
containing citrullinated fibrinogen co-stimulate macrophages via toll-like
receptor 4 and Fcgamma receptor. Arthritis Rheum 63: 53–62.
Autoantibody Profiling in Preclinical RA
PLoS ONE | www.plosone.org8May 2012 | Volume 7 | Issue 5 | e35296
18. Schaefer L, Babelova A, Kiss E, Hausser HJ, Baliova M, et al. (2005) The matrix
component biglycan is proinflammatory and signals through Toll-like receptors
4 and 2 in macrophages. J Clin Invest 115: 2223–2233.
19. Leadbetter EA, Rifkin IR, Hohlbaum AM, Beaudette BC, Shlomchik MJ, et al.
(2002) Chromatin-IgG complexes activate B cells by dual engagement of IgM
and Toll-like receptors. Nature 416: 603–607.
20. Sokolove J, Zhao X, Chandra PE, Robinson WH (2010) Immune complexes
containing citrullinated fibrinogen co-stimulate macrophages via toll-like
receptor 4 and Fcgamma receptor. Arthritis Rheum.
21. Boule MW, Broughton C, Mackay F, Akira S, Marshak-Rothstein A, et al.
(2004) Toll-like receptor 9-dependent and -independent dendritic cell activation
by chromatin-immunoglobulin G complexes. J Exp Med 199: 1631–1640.
22. Means TK, Latz E, Hayashi F, Murali MR, Golenbock DT, et al. (2005)
Human lupus autoantibody-DNA complexes activate DCs through cooperation
of CD32 and TLR9. J Clin Invest 115: 407–417.
23. Aho K, von Essen R, Kurki P, Palosuo T, Heliovaara M (1993) Antikeratin
antibody and antiperinuclear factor as markers for subclinical rheumatoid
disease process. J Rheumatol 20: 1278–1281.
24. van de Stadt LA, van der Horst AR, de Koning MH, Bos WH, Wolbink GJ, et
al. (2011) The extent of the anti-citrullinated protein antibody repertoire is
associated with arthritis development in patients with seropositive arthralgia.
Ann Rheum Dis 70: 128–133.
25. Kremer JM, Lee RG, Tolman KG (1989) Liver histology in rheumatoid arthritis
patients receiving long-term methotrexate therapy. A prospective study with
baseline and sequential biopsy samples. Arthritis Rheum 32: 121–127.
26. Faarvang KL, Egsmose C, Kryger P, Podenphant J, Ingeman-Nielsen M, et al.
(1993) Hydroxychloroquine and sulphasalazine alone and in combination in
rheumatoid arthritis: a randomised double blind trial. Ann Rheum Dis 52:
27. Haar D, Solvkjaer M, Unger B, Rasmussen KJ, Christensen L, et al. (1993) A
double-blind comparative study of hydroxychloroquine and dapsone, alone and
in combination, in rheumatoid arthritis. Scand J Rheumatol 22: 113–118.
28. Rantapaa-Dahlqvist S, Boman K, Tarkowski A, Hallmans G (2007) Up
regulation of monocyte chemoattractant protein-1 expression in anti-citrulline
antibody and immunoglobulin M rheumatoid factor positive subjects precedes
onset of inflammatory response and development of overt rheumatoid arthritis.
Ann Rheum Dis 66: 121–123.
29. Jorgensen KT, Wiik A, Pedersen M, Hedegaard CJ, Vestergaard BF, et al.
(2008) Cytokines, autoantibodies and viral antibodies in premorbid and
postdiagnostic sera from patients with rheumatoid arthritis: case-control study
nested in a cohort of Norwegian blood donors. Ann Rheum Dis 67: 860–866.
30. O’Dell JR, Blakely KW, Mallek JA, Eckhoff PJ, Leff RD, et al. (2001) Treatment
of early seropositive rheumatoid arthritis: a two-year, double-blind comparison
of minocycline and hydroxychloroquine. Arthritis Rheum 44: 2235–2241.
31. Nielen MM, van Schaardenburg D, Reesink HW, Twisk JW, van de Stadt RJ, et
al. (2004) Increased levels of C-reactive protein in serum from blood donors
before the onset of rheumatoid arthritis. Arthritis Rheum 50: 2423–2427.
32. Aho K, Palosuo T, Knekt P, Alha P, Aromaa A, et al. (2000) Serum C-reactive
protein does not predict rheumatoid arthritis. J Rheumatol 27: 1136–1138.
33. El-Gabalawy HS, Robinson DB, Hart D, Elias B, Markland J, et al. (2009)
Immunogenetic risks of anti-cyclical citrullinated peptide antibodies in a North
American Native population with rheumatoid arthritis and their first-degree
relatives. J Rheumatol 36: 1130–1135.
34. Kolfenbach JR, Deane KD, Derber LA, O’Donnell CI, Gilliland WR, et al.
(2010) Autoimmunity to peptidyl arginine deiminase type 4 precedes clinical
onset of rheumatoid arthritis. Arthritis Rheum 62: 2633–2639.
35. Firestein GS, Zvaifler NJ (1997) Anticytokine therapy in rheumatoid arthritis.
N Engl J Med 337: 195–197.
36. Quinn MA, Green MJ, Marzo-Ortega H, Proudman S, Karim Z, et al. (2003)
Prognostic factors in a large cohort of patients with early undifferentiated
inflammatory arthritis after application of a structured management protocol.
Arthritis Rheum 48: 3039–3045.
37. van der Helm-van Mil AH, le Cessie S, van Dongen H, Breedveld FC, Toes RE,
et al. (2007) A prediction rule for disease outcome in patients with recent-onset
undifferentiated arthritis: how to guide individual treatment decisions. Arthritis
Rheum 56: 433–440.
38. van Gaalen FA, Linn-Rasker SP, van Venrooij WJ, de Jong BA, Breedveld FC,
et al. (2004) Autoantibodies to cyclic citrullinated peptides predict progression to
rheumatoid arthritis in patients with undifferentiated arthritis: a prospective
cohort study. Arthritis Rheum 50: 709–715.
39. van der Woude D, Rantapaa-Dahlqvist S, Ioan-Facsinay A, Onnekink C,
Schwarte CM, et al. (2010) Epitope spreading of the anti-citrullinated protein
antibody response occurs before disease onset and is associated with the disease
course of early arthritis. Ann Rheum Dis 69: 1554–1561.
40. van Dongen H, van Aken J, Lard LR, Visser K, Ronday HK, et al. (2007)
Efficacy of methotrexate treatment in patients with probable rheumatoid
arthritis: a double-blind, randomized, placebo-controlled trial. Arthritis Rheum
41. Pelayo R, Tintore M, Montalban X, Rovira A, Espejo C, et al. (2007)
Antimyelin antibodies with no progression to multiple sclerosis. N Engl J Med
42. Kidd BA, Ho PP, Sharpe O, Zhao X, Tomooka BH, et al. (2008) Epitope
spreading to citrullinated antigens in mouse models of autoimmune arthritis and
demyelination. Arthritis Res Ther 10: R119.
43. Kuhn KA, Kulik L, Tomooka B, Braschler KJ, Arend WP, et al. (2006)
Antibodies against citrullinated proteins enhance tissue injury in experimental
autoimmune arthritis. J Clin Invest 116: 961–973.
44. Hagiwara T, Nakashima K, Hirano H, Senshu T, Yamada M (2002)
Deimination of arginine residues in nucleophosmin/B23 and histones in HL-
60 granulocytes. Biochem Biophys Res Commun 290: 979–983.
45. Makrygiannakis D, Hermansson M, Ulfgren AK, Nicholas AP, Zendman AJ, et
al. (2008) Smoking increases peptidylarginine deiminase 2 enzyme expression in
human lungs and increases citrullination in BAL cells. Ann Rheum Dis 67:
46. Sokolove J, Zhao X, Chandra PE, Robinson WH (2011) Immune complexes
containing citrullinated fibrinogen costimulate macrophages via Toll-like
receptor 4 and Fcgamma receptor. Arthritis Rheum 63: 53–62.
47. Monach PA, Hueber W, Kessler B, Tomooka BH, BenBarak M, et al. (2009) A
broad screen for targets of immune complexes decorating arthritic joints
highlights deposition of nucleosomes in rheumatoid arthritis. Proc Natl Acad
Sci U S A 106: 15867–15872.
48. Shi J, Knevel R, Suwannalai P, van der Linden MP, Janssen GM, et al. (2011)
Autoantibodies recognizing carbamylated proteins are present in sera of patients
with rheumatoid arthritis and predict joint damage. Proc Natl Acad Sci U S A
49. Schuerwegh AJ, Ioan-Facsinay A, Dorjee AL, Roos J, Bajema IM, et al. (2010)
Evidence for a functional role of IgE anticitrullinated protein antibodies in
rheumatoid arthritis. Proc Natl Acad Sci U S A 107: 2586–2591.
50. Aletaha D, Neogi T, Silman AJ, Funovits J, Felson DT, et al. (2010) 2010
rheumatoid arthritis classification criteria: an American College of Rheumatol-
ogy/European League Against Rheumatism collaborative initiative. Ann
Rheum Dis 69: 1580–1588.
51. Arnett FC, Edworthy SM, Bloch DA, McShane DJ, Fries JF, et al. (1988) The
American Rheumatism Association 1987 revised criteria for the classification of
rheumatoid arthritis. Arthritis Rheum 31: 315–324.
52. (1997) World Medical Association declaration of Helsinki. Recommendations
guiding physicians in biomedical research involving human subjects. JAMA 277:
53. Hueber W, Tomooka BH, Zhao X, Kidd BA, Drijfhout JW, et al. (2007)
Proteomic analysis of secreted proteins in early rheumatoid arthritis: anti-
citrulline autoreactivity is associated with up regulation of proinflammatory
cytokines. Ann Rheum Dis 66: 712–719.
54. Tusher VG, Tibshirani R, Chu G (2001) Significance analysis of microarrays
applied to the ionizing radiation response. Proc Natl Acad Sci U S A 98:
Autoantibody Profiling in Preclinical RA
PLoS ONE | www.plosone.org9May 2012 | Volume 7 | Issue 5 | e35296