The Prognostic Value of Serum Cytokines in Patients with Acute Ischemic Stroke

Abstract

The inflammatory response is an unavoidable process and contributes to the destruction of cerebral tissue during the acute ischemic stroke (AIS) phase and has not been addressed fully to date. Insightful understanding of correlation of inflammatory mediators and stroke outcome may provide new biomarkers or therapeutic approaches for ischemic stroke. Here, we prospectively recruited 180 first-ever AIS patients within 72 hrs after stroke onset. We used the National Institutes of Health Stroke Scale (NIHSS) to quantify stroke severity and modified Rankin scale (mRS) to assess the 3-month outcome for AIS patients. Initially, we screened 35 cytokines, chemokines, and growth factors in sera from 75 AIS patients and control subjects. Cytokines that were of interest were further investigated in the 180 AIS patients and 14 heathy controls. We found that IL-1RA, IL-1β, IL-4, IL-5, IL-6, IL-7, IL-9, IL-10, IL-13, IL-15, EGF, G-CSF, Flt-3L, GM-CSF and Fractalkine levels were significantly decreased in severe stroke patients. In particular, IL-1β, IL-4, IL-5, IL-7, IL-9, IL-10, IL-15, G-CSF and GM-CSF were significantly reduced in AIS patients with poor outcome, compared to those with good prognosis. IL-6 was notably higher in the poor outcome group. Only IL-9 level decreased in the large infarct volume group. After adjusting for confounders, we found that IL-5 was an independent protective factor for prognosis in AIS patients with an adjusted OR of 0.042 (P = 0.007), whereas IL-6 was an independent risk predictor for AIS patients with an adjusted OR of 1.293 (P = 0.003). Our study suggests the levels of serum cytokines are related to stroke severity, short-term prognosis and cerebral infarct volume in AIS patients.

Full text

http://dx.doi.org/10.14336/AD.2018.0820
*Correspondence should be addressed to: Dr. Kunlin Jin (kunlin.jin@unthsc.edu) and Bei Shao (shaobei56@126.com), Department of
Neurology, The First Affiliated Hospital of Wenzhou Medical University, China. #These authors contributed equally to this study.
Copyright: © 2018 Lin S 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.
ISSN: 2152-5250 1
Original Article
The Prognostic Value of Serum Cytokines in Patients with
Acute Ischemic Stroke
Xianmei Li1,#, Siyang Lin1,#, Xiaoli Chen2, Wensi Huang3, Qian Li4, Hongxia Zhang5, Xudong
Chen1, Shaohua Yang5, Kunlin Jin5, Bei Shao1,*
1Department of Neurology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
2Department of Rehabilitation, Wenzhou People's Hospital, Wenzhou, China
3Department of Neurology, The People's Hospital of Pingyang, Wenzhou, China
4Department of Neurology, Jinhua Municipal Central Hospital, Wenzhou, China
5Department of Pharmacology and Neuroscience, University of North Texas Health Science Center, Fort Worth,
Texas, USA
[Received March 1, 2018; Revised August 18, 2018; Accepted August 20, 2018]
ABSTRACT: The inflammatory response is an unavoidable process and contributes to the destruction of cerebral
tissue during the acute ischemic stroke (AIS) phase and has not been addressed fully to date. Insightful
understanding of correlation of inflammatory mediators and stroke outcome may provide new biomarkers or
therapeutic approaches for ischemic stroke. Here, we prospectively recruited 180 first-ever AIS patients within
72 hrs after stroke onset. We used the National Institutes of Health Stroke Scale (NIHSS) to quantify stroke
severity and modified Rankin scale (mRS) to assess the 3-month outcome for AIS patients. Initially, we screened
35 cytokines, chemokines, and growth factors in sera from 75 AIS patients and control subjects. Cytokines that
were of interest were further investigated in the 180 AIS patients and 14 heathy controls. We found that IL-1RA,
IL-1β, IL-4, IL-5, IL-6, IL-7, IL-9, IL-10, IL-13, IL-15, EGF, G-CSF, Flt-3L, GM-CSF and Fractalkine levels
were significantly decreased in severe stroke patients. In particular, IL-1β, IL-4, IL-5, IL-7, IL-9, IL-10, IL-15,
G-CSF and GM-CSF were significantly reduced in AIS patients with poor outcome, compared to those with good
prognosis. IL-6 was notably higher in the poor outcome group. Only IL-9 level decreased in the large infarct
volume group. After adjusting for confounders, we found that IL-5 was an independent protective factor for
prognosis in AIS patients with an adjusted OR of 0.042 (P = 0.007), whereas IL-6 was an independent risk
predictor for AIS patients with an adjusted OR of 1.293 (P = 0.003). Our study suggests the levels of serum
cytokines are related to stroke severity, short-term prognosis and cerebral infarct volume in AIS patients.
Key words: acute ischemic stroke, cytokines, inflammation, prognosis, stroke severity
Cerebrovascular disease, a global health problem, has
become one of the major cause of adult mortality and
disability worldwide, and ranks second only to ischemic
heart disease [1-3]. Acute ischemic stroke (AIS), caused
by cerebral embolism or arterial thrombosis, accounts for
80-85% of cerebrovascular disease and is the major
subtype of all strokes [4]. Inflammation following AIS is
considered an inevitable pathological process involved in
post-ischemic injury in the brain [5, 6]. After the initial
injury, a series of detrimental secondary events occur and
the blood-brain barrier (BBB) becomes damaged.
Activated peripheral immune cells including neutrophils
and T-cells can then cross the BBB and accumulate at the
site of injury [5]. These cascade reactions would indeed
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Lin S., et al Serum cytokines and ischemic outcome
Aging and Disease • Volume 10, Number 2, April 2019 2
aggravate cerebral infarction, which potentially
contributes to the destruction of cerebral tissue during the
AIS phase [7, 8]. On the other hand, an increasing number
of reports have showed that the inflammatory response
after stroke plays a critical role for functional recovery in
the later stages [9, 10]. A probable reason for this
phenomenon can be attributed to dynamic alterations in
the release of several pro- and anti-inflammatory
cytokines in the brain that could affect the progression of
cerebral infarction [11]. These chemokines are mainly
produced by resident microglial cells and infiltrating
immune cells, which could attract and activate leukocytes
[12, 13]. Some chemokines are even capable of recruiting
nonimmune cells like neural stem cells (NSCs), neural
progenitor cells (NPCs), endothelial cells and bone
marrow stromal cells (BMSCs) to the lesion site which
may exert beneficial impact on protection and recovery
[14]. Th2 type cytokines including interleukin-4 (IL-4)
and interleukin-5 (IL-5) were found to play beneficial
roles in the repair of brain damage, suppress post-stroke
inflammation, and have the capability to induce
neurotrophic factors in astrocytes [15-17]. Interleukin-6
(IL-6), well-known for its pro-inflammatory function also
possess neurotrophic and regenerative capabilities after
cerebral ischemia [18, 19]. Interleukin-7 (IL-7) is a
pleiotropic cytokine with multiple effects. Arya et al.
reported that IL-7 could enhance the expression of
monocyte chemoattractant protein-1 (MCP-1) in patients
with unstable angina, and was associated with
hyperlipidemia and atherosclerosis [20]. Interleukin-9
(IL-9) is a pro-inflammatory cytokine, secreted by Th9
cells. Interleukin-10 (IL-10) is generally viewed as an
anti-inflammatory cytokine that helps to restrain pro-
inflammatory cytokines and depress cytokine receptor
expression and receptor activation [21]. Interleukin-13
(IL-13) is a mediator of allergic inflammation and
different diseases including asthma [22]. Interleukin-15
(IL-15) mainly regulates the activation and proliferation
of T and natural killer (NK) cells. Fractalkine (CX3CL1),
macrophage-derived chemokine (MDC, CCL22) and
macrophage inflammatory protein-1 alpha (MIP-1α,
CCL3) are members of chemokine family, which serve
different functions in inflammation, such as guiding the
migration of immune cells or regulating activation and
maturation of cells. Fms-like tyrosine kinase-3 ligand
(Flt-3L), epidermal growth factor (EGF), granulocyte-
colony stimulating factor (G-CSF), granulocyte-
macrophage colony-stimulating factor (GM-CSF) are
growth factors. Therefore, these inflammatory mediators,
cytokines in particular, have been considered as
biomarkers for stroke pathogenesis and prognosis.
Previous reports characterized an acute immune response
to ischemic stroke by profiling certain cytokines and
chemokines (e.g., IL-1α and β, IL-6, IL-8, IL-9, IL-10, IL-
12, IL-18, TNFα and soluble TNF-receptors p55, p75 and
GRO-α) in the sera or cerebrospinal fluid of stroke
patients [23-25]. However, various known cytokines have
been studied in limited number thereby restricting the
significance of predictive value of these biomarkers in
patient outcome after AIS.
To determine the significance of serum
inflammatory cytokines in patient outcome after acute
ischemic stroke, we simultaneously measured 35
cytokines, chemokines, and growth factors in a single
patient group using a multiplex immunoassay and found
that the levels of inflammatory mediators in the serum can
be used to deduce stroke severity, short-term prognosis
and cerebral infarct volume.
MATERIALS AND METHODS
Study population
One hundred and eighty patients with first-ever AIS were
enrolled at the Department of Neurology, the First
Affiliated Hospital of Wenzhou Medical University, from
April 2014 to September 2016. All AIS patients within 72
hrs after stroke onset were selected based on the criteria
set out by the World Health Organization [26]. Etiology
subtypes of ischemic stroke were classified according to
the criteria of Trial of Org 10172 in Acute Stroke
Treatment (TOAST) [27]. The exclusion criteria for first-
ever AIS patients are: (i) history of any serious central
nervous system disease, such as Parkinson’s disease,
craniocerebral trauma, dementia, hematencephalon,
cerebral infarction or subarachnoid hemorrhage; (ii)
failure of important organs, such as heart failure, severe
liver or renal insufficiency; (iii) autoimmune disease
(AID) or the use of steroids or immunosuppressants; (iv)
a history of cancer; (v) a serious history of infection,
trauma or surgery within 4 weeks prior to onset.
The study followed ethical guidelines and obtained
the approval of the ethics committee at the First Affiliated
Hospital of Wenzhou Medical University. Patient consent
forms were signed by each patient or their relatives before
inclusion.
Data collection
The following basic clinical information of all subjects
during the first 24 hrs after onset of stroke were collected
by well-trained neurologists: gender, age, smoking habit,
alcohol abuse, hypertension, diabetes mellitus (DM),
hyperlipemia, cardiovascular diseases, systolic blood
pressure (SBP) and diastolic blood pressure (DBP) on
admission and biochemical indices. The National
Institutes of Health Stroke Scale (NIHSS) score was used

Lin S., et al Serum cytokines and ischemic outcome
Aging and Disease • Volume 10, Number 2, April 2019 3
to measure the severity of AIS patients by the neurologist
within 24 hrs of admission and discharge [28, 29]. The
minor stroke was defined as NIHSS score < 5 according
to previous studies [30, 31]. The short-term functional
outcome was assessed by telephone interviews or
outpatient service at 3 months after stroke onset using the
modified Rankin scale (mRS, scores range from 0 to 6)
[32]. A poor functional outcome was defined as mRS
score 3-6, while favorable outcome was defined as mRS
score 0-2 [33, 34].
Table 1. Baseline characteristics of AIS patients with favorable or poor outcomes.
Characteristics
Total (N= 167)
Prognosis at 3 months follow-up
P value
Favorable Outcome
(N= 113)
Poor Outcome
(N=54)
Age (years)
63.02 ± 9.84
62.08 ± 10.35
65.00 ± 8.43
0.073
Males (%)
100 (60.0)
73 (64.6)
27 (50.0)
0.073
SBP (mmHg)
162.34 ± 24.41
160.18 ± 22.76
166.87 ± 27.20
0.097
DBP (mmHg)
85.43 ± 13.68
85.48 ± 13.13
85.31 ± 14.90
0.943
Hypertension (%)
141 (84.4)
93 (82.3)
48 (88.9)
0.273
Hyperlipidemia (%)
32 (19.2)
21 (18.6)
11 (20.4)
0.784
Diabetes (%)
55 (32.9)
33 (29.2)
22 (40.7)
0.139
Cardiac disease (%)
19 (11.4)
10 (8.8)
9 (16.7)
0.138
Smoking (%)
57 (34.1)
31 (27.4)
24 (44.4)
0.053
Alcohol drinking (%)
43 (25.7)
33 (29.2)
9 (16.7)
0.064
Stroke etiologic subtypes (%)
0.982
Large-artery atherosclerosis
110 (65.7)
76 (67.3)
34 (62.3)
-
Cardioembolic
13 (7.8)
8 (7.1)
5 (9.3)
-
Small-vessel disease
38 (22.8)
28 (24.8)
10 (18.5)
-
Other or unknown cause
6 (3.6)
2 (1.8)
4 (7.4)
-
BMI (kg/m2)
23.76 ± 3.14
23.72 ± 3.11
23.84 ± 3.23
0.808
Laboratory tests
WBC (109/L)
6.35 (5.57 – 7.79)
6.29 (5.44 – 7.58)
6.51 (5.82 – 8.60)
0.081
Neutrophils (109/L)
3.88 (3.03 – 4.92)
3.70 (2.89 – 4.82)
4.22 (3.38 – 5.74)
0.009
Hs-CRP (mmol/L)
1.86 (0.87 – 3.91)
1.67 (0.60 – 3.30)
2.64 (1.37 – 4.90)
0.027
IL-1RA (pg/mL)
2.21 (0.68 – 8.66)
2.30 (0.97 – 7.710)
1.4 (0.27 – 5.56)
0.165
IL-1α (pg/mL)
2.96 (0.32 – 17.69)
2.96 (0.32 – 17.69)
1.21 (0.08 – 27.21)
0.365
IL-1β (pg/mL)
1.06 (0.73 – 1.60)
1.11 (0.82 – 1.60)
0.87 (0.60 – 1.56)
0.007
IL-4 (pg/mL)
1.82 (0.54 – 6.47)
3.10 (1.13 – 8.15)
0.53 (0.28 – 1.32)
< 0.001
IL-5 (pg/mL)
0.58 (0.35 – 0.82)
0.63 (0.48 – 0.86)
0.32 (0.24 – 0.66)
< 0.001
IL-6 (pg/mL)
1.17 (0.65 – 1.95)
1.17 (0.68 – 1.90)
2.06 (0.49 – 2.13)
0.021
IL-7 (pg/mL)
1.62 (0.86 – 2.5)
1.78 (1.31 – 2.67)
0.77 (0.45 – 1.95)
< 0.001
IL-8 (pg/mL)
4.59 (3.03 – 9.17)
4.59 (3.11 – 7.16)
5.34 (2.86 – 14.43)
0.262
IL-9 (pg/mL)
0.8 (0.36 – 1.15)
0.95 (0.70 – 1.19)
0.31 (0.24 – 0.73)
< 0.001
IL-10 (pg/mL)
0.87 (0.60 – 1.80)
0.96 (0.65 – 2.13)
0.74 (0.49 – 1.22)
0.027
IL-13 (pg/mL)
0.05 (0.02 – 0.17)
0.06 (0.02 – 0.16)
0.03 (0.01 – 0.15)
0.071
IL-15 (pg/mL)
1.3 (0.77 – 1.77)
1.37 (0.94 – 1.98)
0.94 (0.54 – 1.65)
0.002
EGF (pg/mL)
3.92 (0.84 – 20.06)
5.96 (1.04 – 20.59)
1.81 (0.26 – 17.69)
0.084
G-CSF (pg/mL)
8.64 (4.27 – 17.69)
10.77 (5.68 – 16.06)
5.20 (0.20 – 18.61)
0.017
Flt-3 (pg/mL)
0.4 (0.07 – 2.26)
0.47 (0.08 – 2.53)
0.25 (0.03 – 1.60)
0.44
GM-CSF (pg/mL)
4.27 (1.19 – 20.61)
7.71 (2.13 – 26.46)
1.51 (0.83 – 6.47)
< 0.001
Fractalkine (pg/mL)
19.57 (3.62 – 59.16)
17.99 (7.06 – 56.99)
21.75 (0.07 – 60.03)
0.225
IFN-γ (pg/mL)
4.7 (2.06 – 9.17)
4.54 (2.19 – 7.75)
3.76 (1.43 – 13.67)
0.897
MDC (pg/mL)
335.44 (248.06 – 471.03)
337.56 (246.52 – 469.62)
352.74 (251.20 – 540.90)
0.365
MIP-1α (pg/mL)
2.03 (1.43 – 3.8)
2.03 (1.45 – 3.08)
2.39 (1.13 – 7.64)
0.485
Infarct volume (cm3)
1.26 (0.40 – 3.42)
0.86 (0.29 – 2.06)
3.07 (1.02 – 5.93)
< 0.001
NIHSS score on admission,
median (IQR)
3.00 (2.00 – 5.00)
3.00 (1.00 – 4.00)
7.00 (4.00 – 10.00)
< 0.001
NIHSS score on discharge,
median (IQR)
3.00 (1.00 – 5.00)
2.00 (1.00 – 3.00)
6.00 (4.75 – 9.00)
< 0.001
Medication, (%)
Statin
135 (80.8)
99 (87.6)
36 (66.7)
0.002

Lin S., et al Serum cytokines and ischemic outcome
Aging and Disease • Volume 10, Number 2, April 2019 4
All participants were examined using Cranial Magnetic
Resonance Imaging (MRI) scans. The infarction size in
diffusion-weighted imaging (DWI) was measured using
G3PACS software by two neuroradiologists
independently. Firstly, we selected the slice with the
largest lesion by eye and the longest lesion axis (A axis)
on this slice was measured. A second line (B axis) was
drawn perpendicular to the first at the widest dimension.
A third axis, the z (C) axis, was computed by multiplying
the number of slices by slice thickness (7 mm). The
formula was 0.5 x A x B x C [35]. According to a previous
study, a small infarct volume was defined as less than 5
cm³, while a large infarct volume is larger than 5 cm³ [36].
Figure 1. The relationship between various inflammatory cytokines and stroke severity.
The levels of IL-4, IL-5, IL-9, IL-13 and IL-15 were significantly decreased in the severe
stroke group compared with the minor stroke group. Data are presented as mean ± SD, ***P
< 0.001.
Anticoagulation agents
8 (4.8)
6 (5.3)
2 (3.7)
0.448
Antiplatelet agents
132 (79.0)
97 (85.8)
35 (64.8)
0.001
Abbreviations: SBP, systolic blood pressure; DBP, diastolic blood pressure; BMI, body mass index; WBC, leukocyte; Hs-CRP, High-sensitivity C-
reactive protein; IL-1RA, interleukin-1 receptor antagonist; IL-1α, interleukin 1 alpha; IL-1β, interleukin 1 beta; IL-4, interleukin-4; IL-5, interleukin-
5; IL-6, interleukin-6; IL-7, interleukin-7; IL-8, interleukin-8; IL-9, interleukin-9; IL-10, interleukin-10; IL-13, interleukin-13; IL-15, interleukin-15;
Flt-3, Fms-like tyrosine kinase 3; EGF, epidermal growth factor ; G-CSF, granulocyte-colony stimulating factor; GM-CSF, granulocyte-macrophage
colony-stimulating factor; MDC, macrophage-derived chemokine; MIP-1α, macrophage inflammatory protein-1 alpha; IQR, interquartile range;
NIHSS, National Institutes of Health Stroke Scale.

Lin S., et al Serum cytokines and ischemic outcome
Aging and Disease • Volume 10, Number 2, April 2019 5
Table 2. Levels of serum cytokines in different groups of stroke severity.
Median (IQR)
Cytokines
Minor Stroke Group
(N=53)
Severe Stroke Group
(N=94)
P value
Control (N=14)
Hs-CRP (mmol/L)
1.55 (0.59 – 3.50)
2.56 (1.39 – 4.81)
0.019
—
IL-1RA (pg/mL)
2.56 (1.35 – 9.45)
1.94 (0.48 – 8.15)
0.028
0.40(0.07-6.38)
IL-1α (pg/mL)
3.2 (0.35 – 14.43)
1.93 (0.19 – 24.28)
0.234
0.045 (0.02 – 28.49)
IL-1β (pg/mL)
1.11 (0.92 – 1.68)
0.93 (0.61 – 1.51)
< 0.001
0.73 (0.53 – 2.23)
IL-4 (pg/mL)
3.62 (1.48 – 9.31)
0.96 (0.32 – 3.10)
< 0.001
1.03 (0.44 – 5.45)
IL-5 (pg/mL)
0.70 (0.51 – 0.90)
0.40 (0.24 – 0.70)
< 0.001
0.23 (0.18 – 0.42)
IL-6 (pg/mL)
1.34 (0.80 – 2.32)
1.00 (0.49 – 1.76)
< 0.001
0.70 (0.33 – 1.36)
IL-7 (pg/mL)
2.10 (1.45 – 2.84)
1.09 (0.47 – 2.06)
< 0.001
0.82 (0.44 – 2.72)
IL-8 (pg/mL)
4.76 (3.39 – 8.45)
4.09 (2.38 – 11.73)
0.238
21.75 (2.05 – 82.14)
IL-9 (pg/mL)
1.01 (0.77 – 1.29)
0.37 (0.25 – 0.90)
< 0.001
0.33 (0.26 – 0.76)
IL-10 (pg/mL)
1.12 (0.69 – 2.14)
0.70 (0.49 – 1.27)
< 0.001
0.41 (0.23 – 1.16)
IL-13 (pg/mL)
0.075 (0.03 – 0.22)
0.03 (0.01 – 0.11)
< 0.001
0.02 (0.01 – 0.31)
IL-15 (pg/mL)
1.42 (1.07 – 2.13)
0.93 (0.59 – 1.65)
< 0.001
0.83 (0.55 – 1.38)
EGF (pg/mL)
6.69 (1.35 – 22.78)
2.14 (0.36 – 17.05)
0.016
17.83 (1.17 – 53.23)
G-CSF (pg/mL)
12.24 (7.00 – 19.82)
5.73 (0.22 – 14.05)
< 0.001
1.15 (0.27 – 9.91)
Flt-3 (pg/mL)
0.52 (0.10 – 2.83)
0.25 (0.04 – 1.60)
0.007
0.56 (0.10 – 23.93)
GM-CSF (pg/mL)
11.56 (2.42 – 41.66)
1.85 (0.91 – 9.17)
< 0.001
1.17 (0.86 – 5.27)
Fractalkine (pg/mL)
23.93 (7.69 – 73.27)
15.60 (0.20 – 50.88)
< 0.001
6.47 (0.20 – 23.93)
IFN-γ (pg/mL)
5.14 (2.53 – 7.98)
3.58 (1.53 – 11.00)
0.068
2.71 (1.39 – 11.44)
MDC (pg/mL)
333.35 (246.52 – 462.26)
352.74 (249.64 – 540.90)
0.123
731.67 (511.10 – 923.05)
MIP-1α (pg/mL)
2.18 (1.54 – 3.36)
1.75 (1.26 – 4.95)
0.754
5.23 (0.85 – 28.96)
Abbreviations: SBP, systolic blood pressure; DBP, diastolic blood pressure; BMI, body mass index; WBC, leukocyte; Hs-CRP, High-sensitivity C-
reactive protein; IL-1RA, interleukin-1 receptor antagonist; IL-1α, interleukin 1 alpha; IL-1β, interleukin 1 beta; IL-4, interleukin-4; IL-5,
interleukin-5; IL-6, interleukin-6; IL-7, interleukin-7; IL-8, interleukin-8; IL-9, interleukin-9; IL-10, interleukin-10; IL-13, interleukin-13; IL-15,
interleukin-15; Flt-3, Fms-like tyrosine kinase 3; EGF, epidermal growth factor ; G-CSF, granulocyte-colony stimulating factor; GM-CSF,
granulocyte-macrophage colony-stimulating factor; MDC, macrophage-derived chemokine; MIP-1α, macrophage inflammatory protein-1 alpha;
IQR, interquartile range; NIHSS, National Institutes of Health Stroke Scale.
Cytokine measurement
Blood samples of all participants were collected within 24
hrs after admission. The serum levels of cytokines,
chemokines, and growth factors were measured using
human cytokine/chemokine magnetic bead panel kit
(HCYTMAG-60K-PX38, EMD Millipore, Germany). All
procedures were performed according to the
manufacturer's instructions and data were analyzed with
the xPONENT software. Other laboratory parameters
included white blood cell (WBC) count, neutrophil and
high-sensitivity C-reactive protein (Hs-CRP) were tested
in the hospital’s central biochemistry laboratory.
Statistical analysis
All statistical analyses were performed with SPSS version
23.0 (Chicago, IL) and statistical significance was set at P
< 0.05. The Kolmogorov-Smirnov (K-S) test was applied
to assess the normality of continuous variables.
Continuous variables of a normal distribution were
expressed as the mean value ± standard deviation (SD)
and analyzed using the unpaired t-test. Non-normally
distributed variables were expressed as medians with
inter-quartile ranges (IQR) and analyzed using the Mann-
Whitney U test. Meanwhile, the Chi-Squared test was
used to compare frequency and percentage in categorical
variables. Spearman’s rank correlation or Pearson
correlation was performed for bivariate correlation
between NIHSS scores, infarct volume and serum
markers. The relationship between serum markers and 3-
months functional outcome of AIS patients was analyzed
by multivariate logistic regression analysis after adjusting
for confounders. The receiver operating characteristic
(ROC) curve was used to determine the predictive values
of the serum levels of these inflammatory markers to
predict short-term prognosis in AIS patients. In addition,
area under the curve (AUC) was computed as a
measurement of the accuracy of the data.

Lin S., et al Serum cytokines and ischemic outcome
Aging and Disease • Volume 10, Number 2, April 2019 6
Figure 2. The relationship between various inflammatory cytokines and stroke outcomes. The levels of IL-4 and
IL-5 were significantly increased in the favorable outcome group compared with the poor outcome group. However, the
concentration of IL-6 was significantly decreased in the favorable outcome group. Data are presented as mean ± SD, *P
< 0.05, ***P < 0.001.
RESULTS
Baseline patient characteristics
A total of 180 patients that met the inclusion criteria were
recruited and 167 of them completed follow-up (13
patients could not be reached). The average age of AIS
patients was 63.02 ± 9.84 years and 60% of AIS patients
enrolled were male. The median (quartiles) NIHSS score
on admission was 3 (IQR, 2 – 5) and on discharge was 3
(IQR, 1 – 5). Poor outcome at 3 months was found in 54
patients (32.3%) with the average age being 65.00 ± 8.43
years. The characteristics of AIS patients with good or
poor 3-months outcomes are shown in Table 1.
Levels of serum cytokines reveal the severity of stroke
We initially screened 35 inflammatory mediators in 75
patients, and found that IL-4, IL-7, IL-9, GM-CSF and
MIP-1α were significantly decreased in the severe stroke
group, compared with control group (P < 0.05; data not
shown). AIS patients were then divided into two groups
according to the NIHSS score on admission: 53 (31.7%)
patients in the minor stroke group (NIHSS < 5) and 94
(68.3%) patients in the severe stroke group (NIHSS ≥ 5).
The serum levels of IL-1RA, IL-1β, IL-4, IL-5, IL-6, IL-
7, IL-9, IL-10, IL-13, IL-15, EGF, G-CSF, Flt-3L, GM-
CSF, and Fractalkine levels were significantly lower in
the severe versus (vs.) the minor stroke group (Fig. 1).
Circulating levels of IL-1α, MDC, MIP-1α, and IFN-γ not
altered (Table 2). Of note, the level of Hs-CRP was
significantly increased in the severe-stroke group vs. the
minor-stroke group.

Lin S., et al Serum cytokines and ischemic outcome
Aging and Disease • Volume 10, Number 2, April 2019 7
Table 3. Logistic regression model with predictors of poor outcome (N=167).
Characteristics
Unadjusted OR (95% CI)
P value
Adjusted OR (95% CI)
P value
Age (years)
1.032 (0.997 – 1.069)
0.074
—
—
Male (%)
0.548 (0.284 – 1.058)
0.073
—
—
SBP (mmHg)
1.012 (0.998 – 1.026)
0.099
—
—
DBP (mmHg)
0.999 (0.976 – 1.023)
0.942
—
—
Hypertension (%)
1.720 (0.648 – 4.568)
0.276
—
—
Hyperlipidemia (%)
1.121 (0.496 – 2.530)
0.784
—
—
Diabetes (%)
1.667 (0.846 – 3.282)
0.139
—
—
Cardiac disease (%)
2.060 (0.784 – 5.414)
0.143
—
—
Smoking (%)
1.939 (0.990 – 3.800)
0.054
—
—
Alcohol drinking (%)
0.465 (0.204 – 1.056)
0.067
—
—
Stroke etiologic subtypes (%)
1.010 (0.699 – 1.460)
0.958
—
—
Large-artery atherosclerosis
—
—
—
—
Cardioembolic
—
—
—
—
Small-vessel disease
—
—
—
—
Other or unknown cause
—
—
—
—
BMI (kg/m2)
1.013 (0.913 – 1.123)
0.807
—
—
Laboratory tests
WBC (109 /L)
1.192 (0.998 – 1.423)
0.052
—
—
Neutrophils (109 /L)
1.333 (1.075 – 1.654)
0.009
—
—
Hs-CRP (mmol/L)
1.008 (0.985 – 1.033)
0.484
—
—
IL-1RA (pg/ml)
1.004 (0.996 – 1.011)
0.342
—
—
IL-1α (pg/ml)
1.001 (0.998 – 1.004)
0.593
—
—
IL-1β (pg/ml)
0.992 (0.813 – 1.210)
0.937
—
—
IL-4 (pg/ml)
0.869 (0.788 – 0.960)
0.005
—
—
IL-5 (pg/ml)
0.244 (0.087 – 0.682)
0.007
0.039 (0.003 – 0.475)
0.011
IL-6 (pg/ml)
1.051(1.002 – 1.103)
0.041
1.329 (1.095 – 1.612)
0.004
IL-7 (pg/ml)
0.981 (0.909 – 1.059)
0.630
—
—
IL-9 (pg/ml)
0.768 (0.508 – 1.161)
0.211
—
—
IL-10 (pg/ml)
0.962 (0.845 – 1.094)
0.554
—
—
IL-13 (pg/ml)
1.052 (0.853 – 1.299)
0.634
—
—
IL-15 (pg/ml)
0.726 (0.514 – 1.025)
0.069
—
—
EGF (pg/ml)
1.003 (0.996 – 1.009)
0.421
—
—
G-CSF (pg/ml)
1.004 (0.998 – 1.009)
0.165
—
—
GM-CSF (pg/ml)
1.000 (0.994 – 1.007)
0.916
—
—
Flt-3 (pg/ml)
1.015 (0.992 – 1.038)
0.200
—
—
Fractalkine (pg/ml)
1.002 (0.999 – 1.005)
0.244
—
—
IFN-γ (pg/ml)
1.004 (0.996 – 1.013)
0.324
—
—
MDC (pg/ml)
1.001 (1.000 – 1.003)
0.071
—
—
MIP-1α (pg/ml)
1.069 (1.010 – 1.131)
0.021
—
—
Infract volume (cm3)
1.043 (0.997 – 1.090)
0.065
—
—
NIHSS score on admission, median (IQR)
2.148 (1.679 – 2.748)
<0.001
—
—
NIHSS score on discharge, median (IQR)
2.477 (1.855 – 3.307)
<0.001
2.494 (1.364 – 4.562)
0.003
Medications, no. (%)
Statin
0.283 (0.128 – 0.627)
0.002
—
—
Anticoagulation agents
2.135 (0.293 – 5.576)
0.455
—
—
Antiplatelet agents
0.304 (0.141 – 0.656)
0.002
—
—
Abbreviations: SBP, systolic blood pressure; DBP, diastolic blood pressure; BMI, body mass index; WBC, leukocyte; Hs-CRP, High-
sensitivity C-reactive protein; IL-1RA, interleukin-1 receptor antagonist; IL-1α, interleukin 1 alpha; IL-1β, interleukin 1 beta; IL-4,
interleukin-4; IL-5, interleukin-5; IL-6, interleukin-6; IL-7, interleukin-7; IL-8, interleukin-8; IL-9, interleukin-9; IL-10, interleukin-10; IL-
13, interleukin-13; IL-15, interleukin-15; Flt-3, Fms-like tyrosine kinase 3; EGF, epidermal growth factor ; G-CSF, granulocyte-colony
stimulating factor; GM-CSF, granulocyte-macrophage colony-stimulating factor; MDC, macrophage-derived chemokine; MIP-1α,
macrophage inflammatory protein-1 alpha; IQR, interquartile range; NIHSS, National Institutes of Health Stroke Scale.

Lin S., et al Serum cytokines and ischemic outcome
Aging and Disease • Volume 10, Number 2, April 2019 8
Levels of serum cytokines in relation to cerebral
infarction volume
All AIS patients underwent cranial MRI scans and the
median (quartiles) infarct volume was 1.26 (IQR, 0.40 –
3.42). 29 patients belonged to large infarct volume group
(≥ 5cm³; median 3.07; IQR, 1.02 – 5.93) and 138 patients
were in the small infarct volume group (< 5 cm³; median
0.86; IQR, 0.29 – 2.06). Serum Hs-CRP level was
significantly higher in patients with large infarct volumes
(P = 0.014), while IL-9 level increased significantly in the
small infarct volume group (P = 0.034). Interestingly,
serum IL-4 was found to be decreased in the large infarct
volume group although it did not reach significance (P =
0.090) (Table 1).
Figure 3. ROC curve of IL-5 for predicting 3-months
outcome of AIS patients. The optimal cutoff value was 0.385
pg/mL with a sensitivity of 86.6% and a specificity of 37.7%
(AUC: 0.719, 95% CI (0.625 – 0.813; P < 0.001).
Levels of serum cytokines predicts functional outcome
167 patients completed the 3-month follow-up. Poor
prognosis was found in 54 (32.3%) patients with 27 of
them (50.0%) being male and mainly occurred in older
ages and patients with a history of smoking. We found that
serum IL-4 level was significantly lower in AIS patients
with poor outcome compared with those with a good
prognosis 3.10 (IQP 1.13 – 8.15) pg/mL vs. 0.53 (IQR
0.28 – 1.32) pg/mL, P < 0.001), IL-5 level also
significantly decreased in the poor outcome group [0.63
(IQR 0.48 – 0.86) pg/mL vs. 0.32 (IQR, 0.24 – 0.66)
pg/mL, P < 0.001] (Fig. 2). Serum IL-6 was significantly
higher in the poor outcome group (Table 3) while serum
levels of IL-1β, IL-7, IL-9, IL-10, IL-15, G-CSF, GM-
CSF remained relatively constant.
By univariate logistic regression analysis, we found
that the serum concentrations of neutrophils, IL-4, IL-5,
IL-6, and MIP-1α were significantly associated with
functional outcome of AIS patients (Table 3).
Multivariate logistic regression was used to further
analysis these parameters in unadjusted models (including
age, gender, SBP, DM, cardiac disease, smoking, alcohol
drinking, WBCs, neutrophils, serum levels of IL-4, IL-5,
IL-6, MDC and MIP-1α, infract volume, NIHSS scores on
admission and on discharge, the use of antiplatelet agents
and statin). We found that serum concentration of IL-5
functioned as a protective factor and was an independent
predictor for functional outcome of AIS patients with an
adjusted OR of 0.039 (95% CI, 0.003 – 0.475, P = 0.011),
whereas IL-6 was an independent risk factor in functional
outcome with an adjusted OR of 1.329 (95% CI,1.095 –
1.612, P = 0.004). Furthermore, NIHSS score on
discharge has alsobeen used as an indpdendent predictor
of AIS patient outcome. Based on the ROC curve analysis,
the optimal cutoff value of IL-5 for predicting AIS
prognosis was projected to be 0.385 pg/mL (with a
sensitivity of 86.6% and a specificity of 37.7%) and AUC:
0.719, 95% CI (0.625 – 0.813, P < 0.001, Fig. 3).
DISCUSSION
In this study, we found that IL-1RA, IL-1β, IL-4, IL-5, IL-
6, IL-7, IL-9, IL-10, IL-13, IL-15, EGF, G-CSF, Flt-3L,
GM-CSF and Fractalkine levels were significantly
decreased in the severe stroke group. While in AIS
patients with poor outcome, IL-1β, IL-4, IL-5, IL-7, IL-9,
IL-10, IL-15, G-CSF and GM-CSF were significantly
reduced. We also found that IL-5 was an independent
protective factor for prognosis and IL-6 was an
independent risk predictor for AIS patients. Our data
suggest that the levels of serum cytokines were related to
stroke severity, short-term prognosis and cerebral infarct
volume of AIS patients.
A large body of evidence suggests that inflammation
is a major contributor to the pathophysiologic processes
of ischemic stroke. The intimate balance between pro- and
anti-inflammatory cytokines are relevant to the
susceptibility and functional outcome of patients with AIS
[5, 37]. IL-4 is a product of selective immune cells, acting
as a pleiotropic regulator of numerous immune and
inflammatory responses [38, 39]. It has been confirmed
that IL-4 could polarize macrophages from a
proinflammatory M1 phenotype to a “healing” M2
phenotype, which would play an anti-inflammatory role
in tissue repair [40, 41]. Zhao et al. reported that IL-4
secreted by neuronal cells in ischemia acts as a

Lin S., et al Serum cytokines and ischemic outcome
Aging and Disease • Volume 10, Number 2, April 2019 9
neuroprotective mechanism to aid in the regulation of
intracerebral cleanup and repair after stroke [42]. IL-5, a
primary T-cell-derived cytokine, regulates eosinophil
development and is regarded as a significant contributor
to atopic diseases such as asthma [43, 44]. An increasing
number of studies support the idea that IL-5 induces the
production of anti-Ox-LDL antibodies and plays an anti-
atherosclerotic role by enhancing Th2-type immune
responses [45, 46]. Sämpi et al. suggested that IL-5 level
was related to antibodies binding to the Ox-LDL and
inversely connected with carotid intima-media thickness
[47]. Studies have found that the expression levels of IL-
4, IL-5, IL-6, and IL-10 are increased remarkably in the
damaged hemisphere after ischemic stroke. IL-4 is mostly
known as an anti-inflammatory cytokine and IL-5 have
been shown to suppress post-stroke inflammation [16]. In
our study, we found that serum concentrations of IL-4, IL-
5 and IL-9 were significantly elevated in minor stroke
patients and negatively related to the NIHSS score. These
biomarkers were also associated with functional outcome
of AIS patients and markedly decreased in AIS patients
with a poor prognosis. Moreover, we showed that IL-5
possessed a protective role and was an independent factor
that could predict AIS patients’ prognosis. Thus, we
speculate that IL-4, IL-5 and IL-9 could act as protective
factors for AIS. In fact, Xiong et al. demonstrated that IL-
4 was somehow involved in cerebral ischemic outcome as
IL-4 deficiency resulted in a greater degree of ischemic
brain damage [15]. Similarly, Sheikh et al. demonstrated
that pretreatment of HMO6 cells with IL-5 could suppress
the expression of IL-1β and IFNγ-induced mRNA, and
IL-5 had the capability to inhibit focal ischemia-induced
inflammation [17]. Therefore, the regulation of IL-4 or
IL-5 and its associated pathways are potential targets for
the treatment of cerebral ischemia. As a pro-inflammatory
cytokine, IL-9 can promote CCL20 release from
astrocytes and the migration of Th17 cells into the central
nervous system [48]. The mechanisms underlying IL-9
and Th9 cells-mediated ischemic injury are largely
unknown. Like TNF-α and IL-1β, IL-9 may directly
damage brain tissue as they perpetuate pro-inflammatory
actions [49, 50]. Tan et al. demonstrated that the
expression level of IL-9 and percentages of Th9 and Tc9
cells were notably higher in (PBMCs) derived from
ischemic stroke patients. Moreover, an increased level of
IL-9 may compromise the BBB’s integrity through IL-
9R/STAT1,3 pathways [51], but this was negative
correlated with stroke severity.
Notably, there was a controversy regarding the
source of elevated IL-6 levels in the early stroke phase
[52]; IL-6 possessed multipotent functions and was
upregulated during brain injury or the repair process [53].
IL-6 plays a dual role in the inflammatory response
induced by cerebral ischemia. On one hand, IL-6 would
further aggravate the deterioration of brain damage and
counteract neural stem cell proliferation in the acute phase
of cerebral ischemia. On the other hand, IL-6 would
restore and enhance glial cells to prevent collagen
deposition and repair brain damage in the subacute phase
[54]. Previous studies reported that circulating IL-6 was
closely correlated with brain infarct volume or stroke
severity [53, 55], although contradicting results were
reported [25]. Besides, Smith et al. revealed that peak
plasma IL-6 level in stroke patients was correlated with
poor prognosis [55]. A recent report recommended that
IL-6 induced by IL-1 was associated with worse prognosis
in stroke patients, and that clinical outcome would be
improved after the inflammatory factor was reduced by
IL-1 receptor antagonist [56]. Consistently, our study
showed that IL-6 level was significantly elevated in AIS
patients with poor outcome. However, Karen et al.
suggested that IL-6 is beneficial for long-term prognosis
as IL-6 could promote early transcriptional changes in
angiogenesis-related genes after cerebral ischemia, which
afford long-term histological and functional protection
[57]. Therefore, this phenomenon needs to be further
studied. We found that the level of serum IL-7 was
notably reduced in patients with severe stroke and poor
outcome. As a pleiotropic cytokine, IL-7 is capable of
multiple effects [58]. IL-7 could act as a regulator of
growth or anti-apoptosis in pre-B cells, and maintain the
steady state proliferation of mature T cells, which might
effectively reduce neuroinflammatory and some
autoimmune responses through the inhibition of signal
transduction [20, 59]. Cagnin and Damas reported that IL-
7 was upregulated in patients with cardiovascular
atherosclerosis (particularly among patients with acute
myocardial infarction and angina pectoris) compared with
controls [60, 61]. Controversially, other studies showed
that IL-7 level was significantly reduced in stroke patients
compared to controls [62]. Lawson et al. speculated that
IL-7 signaling was a prerequisite for activating optimal
CD4+ T cell and that IL-7R antagonism could be an
effective treatment for CD4+ T cell-mediated
neuroinflammation and several inflammatory
autoimmune diseases [59].
Here, we also found that levels of IL-1β, IL-1RA, IL-
10, IL-13, IL-15, Flt-3L, Fractalkine, EGF, G-CSF and
GM-CSF were lower in the severe stroke group. IL-1β is
an important mediator of the inflammatory response and
involved in a variety of cellular activities, including cell
proliferation, differentiation, and apoptosis. Several
studies found that IL-1β were elevated in the AIS group
[63, 64]. Similarly, IL-1RA levels were found to be
elevated in stroke patients in previous studies [65, 66]. IL-
10 is an anti-inflammatory cytokine produced by T cells
and monocytes, suggesting its participation in vascular
protection, although the exact mechanisms are unclear. In

Lin S., et al Serum cytokines and ischemic outcome
Aging and Disease • Volume 10, Number 2, April 2019 10
an animal model, cerebral infarct volume have been
reduced through intraventricular or systemic
administration of IL-10 [67], and IL-10 has been
suggested to be neuroprotective [67, 68]. IL-13 is
a cytokine mainly secreted by Th2 cells [22]. The
secondary structural features of IL-13 are like IL-4 and
share similar functions with IL-4. IL-13 possess anti-
inflammatory properties and is mainly associated with
diseases involving the airway. However, there are few
reports regarding IL-13’s participation in stroke. IL-15 is
a cytokine with structural similarity to IL-2. Lee et al.
found that IL-15 promote astrocyte survival in response to
OGD, thus can be beneficial to ischemic stroke [69].
However, there is no clinical data showing a link between
IL-15 and stroke. Flt3L is a growth factor, which can
stimulate not only the proliferation and differentiation of
hematopoietic progenitor cells, leading to increased
numbers of pre-B cells, but also the maturation of T, B
and NK cells [70, 71]. Fractalkine was initially discovered
as an adhesion molecule for lymphocytes and monocytes,
natural killer cells, and microglia, indicating its role for
regulating the inflammatory response [72]; Fractalkine
can also decrease microglial activation and release pro-
inflammatory cytokines [73, 74]. EGF, G-CSF and CM-
CSF are trophic factors and capable of neuroprotection.
Administration of EGF and G-CSF in a rat MCAO model
could reduce infarct volume [75, 76]. Navarro et al. found
that the level of GM-CSF was significantly higher in
stroke patients than in healthy controls, and was positively
correlated with NIHSS score [77].
MDC is a member of the CC-chemokine family and
is mainly produced by macrophages and dendritic cells.
There is an increasing number of reports regarding the
involvement of MDC in a variety of diseases, ranging
from allergic reactions to HIV infection and neoplasia
[78]. Kimura et al. suggested that MDC promotes
atherosclerosis by migration or recruitment of monocyte-
derived cells and the stimulation of platelet activity [79].
MIP-1α belong to the CC-chemokine subfamily,
possessing inflammatory and neutrophil chemokinetic
properties [80]. Gourmala et al. revealed an early increase
in macrophage inflammatory protein-1α and macrophage
inflammatory protein-1β messenger RNA levels in a rat
MCAO model [81].
Several limitations in the study should not be
neglected. First, this is a single center study with a small
number of patients. As stroke patients are mostly elderly
persons, it was difficult to find age-matched healthy
subjects. Second, serum cytokine levels were tested only
at admission. Monitoring the dynamic change of serum
biomarker levels will be essential in further studies. Last,
a minor stroke is generally defined as a NIHSS of 5 or
less, which only considers certain deficits but not the fact
that some patients can have a more profound impact on
the quality of life versus others. Therefore, the scale does
not linearly correlate deficit and disability. Recent studies
suggest that score of an NIHSS of 3 or less may be a better
definition of a minor stroke [82, 83].
In conclusion, the present study is the first report to
demonstrate the simultaneous measurement of 35 serum
cytokines, chemokines, and growth factors in patients
with AIS. We found that the serum concentration of these
factors is significantly associated with the outcome for the
AIS patient. Indeed, an increased knowledge of
inflammatory mediators in response to AIS may provide
a basis for the design and development of new
pharmacological approaches to treat stroke.
Acknowledgments
This work is supported by US Public Health Service
Grants NS57186 and AG21980 (to K.J.)
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