Association of serum macrophage migration inhibitory factor with large hemisphere infarction and malignant cerebral edema after acute ischemic stroke

doi:10.21203/rs.3.rs-2377088/v1

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Association of serum macrophage migration inhibitory factor with large hemisphere infarction and malignant cerebral edema after acute ischemic stroke

https://doi.org/10.21203/rs.3.rs-2377088/v1

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Background：Macrophage migration inhibitory factor (MIF) is a crucial cytokine involved in inflammation after ischemic stroke, but little is known about its role in large hemisphere infarction (LHI) and malignant cerebral edema (MCE). We aimed to explore whether MIF and its related biomarkers (toll-like receptors [TLRs] and matrix metalloproteinase-9 [MMP-9]) were associated with LHI and MCE in patients with acute ischemic stroke (AIS).

Methods: We prospectively enrolled patients with AIS within 24 h from symptom onset. LHI was defined as cerebral infarction involving more than 1/3 of middle cerebral artery territory within 6 hours from onset or over 1/2 within 48 hours from onset. MCE was defined as a decreased level of consciousness, anisocoria and (or) midline shift over 5mm, basal cistern effacement, or an indication for decompressive craniectomy during hospitalization. Follow-up CTs within 7 days were needed for screening the presence of MCE. Logistic regression was performed to analyze the association of the above inflammatory biomarkers with LHI and MCE.

Results: Our present study included 263 patients (median age: 72 years; male: 50.6%), and 49.4% (130/263) developed LHI (median time from onset to LHI: 3h). Compared with patients without LHI, patients with LHI had a higher median serum level of MIF (median time from onset to blood collection: 3h; 9.51 vs. 7.26 ng/ml, p=0.036) and MMP-9 (36.77 vs. 29.88 ng/ml, p<0.001). MIF over 7.94 ng/ml (adjusted odds ratio [adOR] 1.836, 95% CI 0.988-3.415, p=0.055) and MMP-9 over 34.91ng/ml (adOR 3.283, 95% CI 1.722-6.258, p<0.001) were associated with an increased risk of LHI, separately. Fifty-five patients developed MCE, and the median time from onset to MCE was 32.06 h. Compared with patients without MCE, patients with MCE had a higher level of MIF (9.41 vs. 8.30 ng/ml, p=0.516) and MMP-9 (36.18 vs. 32.35 ng/ml, p=0.006), although the difference was not statistically significant for the former. After adjusted for confounders, neither MIF nor MMP-9 level was significantly associated with the risk of MCE. We did not find any independent association of TLR2/4 with either LHI or MCE.

Conclusions: This study indicated that higher levels of MIF and MMP-9 were related to LHI. There were trends of association between a higher level of serum MIF/MMP-9 and an increased risk of MCE after AIS, which was warranted further validation in future larger studies.

large hemispheric infarction

malignant cerebral edema

macrophage migration inhibitory factor

toll-like receptor

matrix metalloproteinase-9

Large hemisphere infarction (LHI) is a serious subtype of acute ischemic stroke (AIS), and is associated with high mortality[1–3]. The poor prognosis of LHI is mainly due to malignant cerebral edema (MCE)[4]. MCE reaches its peak several days after the onset of AIS, and is characterized by midline shift on imaging and brain herniation[5, 6]. The fatality rate of MCE can be up to 80% under conservative treatment. However, only around 10% of patients with MCE undergo decompressive hemicraniectomy[7–9]. Therefore, early identification of AIS patients with high risk of MCE can help with screening, monitoring and early intervention to improve outcomes.

Certain blood inflammatory biomarkers might help elucidate etiological or mechanism factors, therapeutic targets, and refining prognostication in LHI and MCE[10]. Macrophage migration inhibitory factor (MIF) is expressed in neuron and endothelial cells, and increases with immune response, hypoxia adaption and inflammation[11]. Previous study showed that the elevated MIF levels might predict mortality in critically ill patients[12]. In addition, in an animal model of cerebral ischemia, MIF knockout mice were found to have a smaller infarct size and better functional outcome than wild-type mice[13] ^[. And animal studies suggested that MIF has deleterious effects on the brain after diffuse axonal injury by upregulating toll-like receptor (TLR) 2 and TLR4, which have prognostic roles in ischemic deficits and cerebral edema[14–16]. Moreover, TLR2 and TLR4 may activate mitogen-activated protein kinase and the IΚB kinase pathway to upregulate the matrix metalloproteinase-9 (MMP-9), which is recognized as a key biomarker for disruption of blood brain barrier[15–17]. Based on these promising results from animal studies, the role of MIF and its related biomarker MMP-9, TLR2, and TLR4 in LHI and MCE in AIS patients needed to be investigated.

Study design

We prospectively screened patients admitted to Department of Neurology in West China Hospital within 24 hours of symptom onset between 1 January 2019 and 30 June 2021. The eligible criteria were as follows: (1) age ≥ 18 years, (2) with a diagnosis of AIS, (3) within 24 hours of symptom onset, (4) anterior circulation infarction confirmed by brain CT/MRI. Patients were excluded if they (1) did not have brain CT within 24 h after stroke onset, (2) did not repeat brain CT/MRI within 7 days after stroke onset, (3) had cerebral trauma, tumor, inflammation, infection or metabolic disorder, (4) had hemolytic blood samples or inadequate blood samples collected for analysis. The study was approved by the Scientific Research Department of West China Hospital (Ethics No. 2017[130] and No. 2020[174]) and conformed to the Declaration of Helsinki. Written informed consent were obtained from all subjects.

Data Collection

Baseline characteristics were collected on admission, which included demographic characteristics (age and sex), clinical variables (systolic and diastolic blood pressure, severity of neurological impairment assessed by the National Institutes of Health stroke scale score [NIHSS]), and vascular risk factors (hypertension, diabetes mellitus, hyperlipidemia, atrial fibrillation, valvular heart disease, coronary artery disease, transient ischemic attack, previous ischemic or hemorrhagic stroke, smoking status, and alcohol consumption). The NIHSS score was evaluated by trained neurologists on admission. The etiology of the AIS was assessed for each participant according to the Trial of ORG 10172 in Acute stroke treatment classification. Treatment during hospitalization (e.g endovascular therapy, intravenous thrombolysis, anticoagulant therapy) was recorded.

Biomarker Measurement

Blood samples were collected within 24 hours on admission. Blood samples at 24, 48, 72 hours, and 7 days from onset of symptom were collected when available in patients with LHI. Blood samples were stored overnight at 4℃, and then centrifuged at 1000 g for 20 minutes (Thermo Fisher Scientific, Massachusetts, USA). The supernatant (serum) was transferred to an Eppendorf Tube and stored at -80℃ before batch testing. Serum MIF (E-EL-H1530c, Elabscience Biotechnology Co., Wuhan, China), TLR2(E-EL-H0951c, Elabscience), TLR4 (E-EL-H5820c, Elabscience) and MMP-9 (E-EL-H6075, Elabscience) levels were tested with enzyme-linked immunosorbent assay kits according to the manufacturer’s protocol (https://www.elabscience.cn/). Optical density was measured by Microplate System (Bio-rad Laboratories, Inc, California, USA). Laboratory technicians who measured these 4 biomarkers were blinded to the clinical outcomes of patients.

Definition Of Outcomes

LHI was defined as cerebral infarction involving more than 1/3 of middle cerebral artery territory within 6 hours from onset or over 1/2 within 48 hours from onset on brain CT/MRI[18]. MCE was defined as a decreased level of consciousness, anisocoria and (or) midline shift over 5mm, basal cistern effacement, and indications for decompressive craniectomy during hospitalization[19]. Follow-up CTs within 7 days were needed for screening the presence of MCE.

Statistical analysis

For continuous variables with a normal distribution, means and standard deviations (SD) were used. For skewed data, medians (interquartile range [IQR]) were used. Categorical data were reported as frequencies and percentages. Differences between categorical variables were compared by chi-squared or Fisher’s exact test, and differences from continuous variables were analyzed by the Mann-Whitney U test or Student’s t test, as appropriate.

Receiver operating characteristics (ROC) curves were configured to establish cutoff points of serum MIF, TLR2/4 and MMP-9 levels that dichotomized each biomarker. The effect of each elevated biomarker on study outcomes was adjusted for age and NIHSS score which were two important clinical factors associated with LHI and MCE in model 1, and were additionally adjusted for variables that had a p value of < 0.05 in univariate analysis in model 2[18]. In addition, participants were categorized according to the number of evaluated biomarkers (> cutoff point). Spearman’s coefficients were calculated for the correlation between biomarkers.

All analyzes were performed using SPSS 25.0 (IBM, Chicago, IL, USA), except for the analyses of temporal changes of MIF, TLR2, TLR4 and MMP-9 levels which were performed using GraphPad Prism 9.0.0 (GraphPad Software, San Diego, CA, USA). All p values were 2 tailed, and a significance level of 0.05 was used.

Baseline characteristics

Among 599 consecutive AIS patients enrolled (Fig. 1), 336 patients were excluded due to lack of brain CT within 24 h or repeated CT/MRI images (n = 48), a history of brain trauma, tumor, inflammation, infection or metabolic disorder (n = 62), hemolytic blood samples or no blood sample (n = 226). Finally, 263 patients (median age 72.0 years, 52.5% male) with a median NIHSS score of 13 (IQR 5–18) were included in our present study. The demographic and clinical characteristics, and biomarkers were shown in Table 1. The median time from stroke onset to LHI development and the occurrence of MCE on CT

Table 1

The baseline of all patients (N = 263)
Variable	Total patients	LHI	Non-LHI	P-value	MCE	Non-MCE	P-value
	263	130(49.4%)	133(50.6%)		55(20.9)	208(79.1)
Demographics
Age, y	72 (61.0–80.0)	74 (66.8–81.3)	70 (58.5–79)	0.020	74 (68–81)	71 (59–80)	0.066
Male, n (%)	133(50.6)	59 (47.92)	79 (55.15)	0.023	25 (45.5)	113 (54.3)	0.241
Condition on admission
SBP, mmHg	145.00(128.00-161.00)	149.00(127.75–163.00)	141.00(128.00-157.50)	0.290	149.00(127.75–163.00)	141.00(128.00-157.50)	0.429
DBP, mmHg	80.00(71.00–89.00)	79.00(71.75–94.25)	80.00(70.00–88.00)	0.565	79.00 (71.75–94.25)	80.00(70.00–88.00)	0.560
NIHSS score	13(5–18)	15 (13–19)	5 (2–13)	< 0.001	15 (12–21)	10 (4–17)	< 0.001
Vascular risk factors
Hypertension, n (%)	146(55.5)	74 (56.9)	70 (53.9)	0.484	34 (61.8)	110 (52.9)	0.237
Diabetes, n (%)	51(19.4)	28 (21.5)	23 (17.3)	0.384	16 (29.1)	35 (16.8)	0.041
Hyperlipidemia, n (%)	7(2.7)	5 (3.9)	2 (1.5)	0.238	2 (3.6)	5 (2.4)	0.973
Atrial fibrillation, n (%)	86(30.07)	58 (44.6)	27 (20.3)	< 0.001	25 (45.5)	60 (28.8)	0.019
Valve heart disease, n (%)	31(11.8)	17 (13.1)	13 (9.8)	0.401	8 (14.5)	22 (10.6)	0.410
CAD history, n (%)	33(12.5)	12 (9.2)	23 (17.3)	0.299	7 (12.7)	25 (12.0)	0.896
Transient ischemic attacks, n (%)	1(0.4)	1 (0.8)	0 (0.00)	0.312	0 (0.0)	1 (0.5)	0.606
Previous stroke history	43(16.3)	14 (10.8)	29 (21.8)	0.017	7 (12.7)	36 (17.3)	0.401
Previous ischemic stroke, n (%)	35(13.3)	12 (9.2)	23 (17.3)	0.054	6 (10.9)	29 (13.9)	0.556
Previous hemorrhagic stroke, n (%)	8(3.0)	2 (1.5)	6 (4.5)	0.160	1 (1.8)	7 (3.37)	0.879
Smoking history, n (%)	68(25.9)	33 (25.4)	34 (25.6)	0.973	12 (21.8)	55 (26.4)	0.484
Drinking history, n (%)	51(19.4)	30 (23.1)	20 (15.0)	0.097	10 (18.2)	40 (19.2)	0.860
TOAST classification				0.001			0.024
Large-artery atherosclerosis, n (%)	79(28.9)	49 (37.7)	27 (20.3)		24 (43.6)	53 (25.5)
Small-artery occlusion, n (%)	35(13.3)	12 (9.2)	23 (17.3)		3 (5.5)	31 (14.9)
Cardio-embolism, n (%)	105(39.9)	57 (43.9)	48 (36.1)		23 (41.8)	82 (39.4)
Other etiology, n (%)	8(3.0)	4 (3.1)	4 (3.0)		1 (1.8)	7 (3.4)
Undetermined etiology, n (%)	36(14.8)	8 (6.2)	31 (23.3)		4 (7.3)	35 (16.8)
Novel biomarkers
MIF, ng/ml	8.54(5.34–13.83)	9.51 (5.77–15.23)	7.26 (5.06–12.61)	0.043	9.41 (5.43–16.66)	8.30 (5.33–13.25)	0.516
MMP-9, ng/ml	32.86(24.90-47.69)	36.77 (29.32–94.68)	29.88 (20.86–35.50)	< 0.001	36.18(28.15–104.70)	32.35 (23.69–39.91)	0.006
TLR2, ng/ml	10.97(4.31–27.82)	12.46 (3.33–30.09)	9.65 (4.46–23.50)	0.505	10.77(2.29–32.87)	11.79(4.48–27.70)	0.792
TLR4, pg/ml	589.15(279.58-1291.01)	611.56 (325.68-1244.39)	502.72 (235.44-1245.55)	0.503	599.79(265.14-1333.41)	533.07(280.01-1208.46)	0.795
In-hospital treatment
Endovascular therapy, n (%)	71(27.0)	37 (28.5)	34 (25.6)	0.597	15 (27.3)	56 (26.9)	0.959
Intravenous thrombolysis, n (%)	43(16.3)	15 (11.5)	30 (22.6)	0.018	8 (14.5)	37 (17.8)	0.570
Anticoagulant therapy n (%)	54(20.5)	24 (18.5)	29 (21.8)	0.499	7 (12.7)	46 (22.1)	0.123
Antiplatelet therapy n (%)	214(81.4)	95 (73.1)	120 (90.2)	< 0.001	38 (69.1)	177 (85.1)	0.006

Table 2

Adjusted odd ratios (ORs) for the subcategorized groups of LHI and MCE according to the model^a
Independent variables	LHI			MCE
	Univariate analysis	Model 1	Model 2	Univariate analysis	Model 1	Model 2
	Odds ratio(95%CI)			Odds ratio(95%CI)
MIF (ng/ml)
< 7.94(reference)	1.00	1.00	1.00
≥ 7.94	1.881(1.153–3.071) 0.011	1.865(1.071–3.245) 0.028	1.829(1.035–3.232) 0.038
MMP-9(ng/ml)
< 34.91(reference)	1.00	1.00	1.00
≥ 34.91	3.892(2.321–6.525) < 0.001	3.390(1.906–6.029) < 0.001	3.482(1.910–6.345) < 0.001
< 34.76(reference)				1.00	1.00	1.00
≥ 34.76				2.013 (1.102–3.679) 0.023	1.728 (0.915–3.265) 0.092	1.765(0.919–3.387) 0.088
Abbreviations: LHI, large hemisphere infarction, MCE, malignant cerebral edema, MIF, Macrophage migration inhibitory factor, MMP-9, matrix metalloproteinase-9
a. Model 1 was adjusted for age and NIHSS, Model 2 of LHI was adjusted for age, gender, NIHSS score, history of stroke and atrial fibrillation; Model 2 of MCE was adjusted for age, gender, NIHSS score, history of diabetes and atrial fibrillation

higher median MIF (9.41 [ 5.43–16.66] vs. 8.30 [5.33–13.25], p = 0.516) and higher MMP-9 (36.18 [28.15–104.70] vs. 32.35 [23.69–39.91], p = 0.006) level. After adjusted for confounding factors, MMP-9 level were not independently associated with the presence of MCE. No difference was found in TLR2/4 concentration between patients in MCE group and non-MCE group (Table 1).

Association between multiple biomarkers and LHI/MCE

The association between the number of elevated biomarkers and LHI / MCE were shown in Table 3. Overall, the incidence of LHI increased with the rise in the number of elevated biomarkers. After adjustment for age and gender, patients with 4 elevated biomarkers had 9-fold higher LHI risk (OR 9.051, 95% CI 2.538–35.572, p = 0.001) compared with the participants without elevation of any biomarkers. For the outcome of MCE, there was not any significant difference between the incidence of MCE and number of elevated biomarkers.

Table 3 Multivariable-adjusted ORs (95% Cis) of LHI/MCE according to the number of elevated biomarkers among AIS patients

No. of biomarkers	Events, n (%)	OR (95% CI)	p Trend
LHI
0 (n=31)	6 (19.35)	reference
1 (n=71)	25 (35.21)	2.152 (0.768-6.033)	0.145
2 (n=81)	49 (60.49)	6.186 (2.248-17.023)	<0.001
3 (n=59)	35 (59.32)	6.349 (2.221-18.155)	0.001
4 (n=21)	15 (71.43)	9.501 (2.538-35.572)	0.001
MCE
0 (n=25)	2 (8.00)	reference
1 (n=75)	17 (22.67)	3.030 (0.640-14.251)	0.162
2 (n=75)	13 (17.33)	2.135 (0.441-10.333)	0.346
3 (n=61)	15 (24.59)	3.625 (0.753-17.455)	0.108
4 (n=27)	8 (29.63)	4.024 (0.747-21.664)	0.105

Abbreviations: OR = odds ratio; CI = confidence interval; LHI = large hemisphere infraction; MCE = malignant cerebral edema. Multivariable model included age, sex.

Dynamic change of biomarkers in LHI group

For a subgroup of 20 patients with LHI, we did the dynamic analysis of these 4 biomarkers. The serum level of MIF was decreased from 24h, and reached the lowest level at 7d in these four time points (Fig 3a). The level of MMP-9 reached to the peak at 48h, decreased at 72h, and increased at 7d (Fig 3b). TLR2 and TLR4 reached its nadir at 72 hours (Fig 3c-d). The median levels of MIF at 24h, 48h, 72h, and 7d were 14.08, 13.55, 12.22 and 11.27 ng/ml respectively, the median levels of MMP-9 were 235.0, 308.7, 234.4 and 264.6ng/ml respectively, the median levels of TLR2 were 15.54, 9.88, 4.05, 6.83ng/ml, and the median levels of TLR4 were 532.3, 385.3, 258.7, 301.9 pg/ml.

With an aim to explore the associated biomarkers of LHI and MCE, we enrolled patients admitted within 24 h after the onset of AIS, and collected their blood samples on admission. We found that a higher level of serum concentration of MIF at baseline was significantly associated with LHI, and had possible association with a higher risk of MCE. We also found that a higher level of serum concentration of MMP-9 at baseline was associated with both LHI and MCE. However, we didn’t find any association between TLR2/4 and LHI or MCE.

Macrophage migration inhibitory factor (MIF) is involved in various physiological processes such as immune response, hypoxia adaptation, and inflammation. Previous clinical and experimental studies of ischemic stroke have found that the expression of MIF is significantly increased after cerebral infarction[13, 20, 21]. LHI is the type of cerebral infarction with the worst prognosis due to its dangerous condition and many complications[22]. At present, the diagnosis of LHI mainly relies on CT or MRI. However, in the early stage of AIS, CT is not sensitive for infarct lesions[23]. To compensate for the defect of CT in early stage of stroke, DWI (diffusion-weighted imaging) is required for early detection of LHI. For some remote areas, DWI could not be performed, so biomarkers related to LHI, such as MIF and MMP-9, could help to identify the occurrence of LHI. Li’s study showed that serum MIF levels at admission were positively correlated with infract volume in patients with AIS[24]. This conclusion supported our study’s result, and we found the direct correlation between MIF and LHI, which extended Li’s study. The potential mechanism could be that increased MIF levels promote monocyte and neutrophil recruitment and infiltration in brain lesions following stroke[24]^]. Therefore, other inflammatory biomarkers related to MIF might also have the association with LHI.

Thus, we also found a positive linear correlation between MIF and MMP-9. Wang's study found that in oral squamous cell carcinoma, MIF could affect its progression and metastasis by regulating MMP-2/9 upstream[25]. In addition, both the findings in murine macrophages and osteoblasts suggested that MIF can lead to upregulation of MMP-9 expression by activating inflammatory pathways. After AIS, MIF promotes blood-brain barrier disruption and expands infarct area by downregulating tight junction associated proteins[26, 27]. Therefore, we reasoned that MIF could affect the occurrence of complications such as MCE through the regulation of MMP-9 in patients with LHI.

There was no clinical study that demonstrated an association between Toll-like receptors and LHI or M CE. Our study found that TLR2/4 was lower in patients with LHI. In vivo knockdown of the TLR2 gene in mice reduced inflammatory cell infiltration and neuronal apoptotic damage after brain infarction, and knockdown of theTLR4 gene reduced infarct area[15, 17]. This result was opposite to our findings, and the reasons were as following. Firstly, this study was study in animal model, but we studied TLRs level in patients’ serum. Animal experiments might behave differently from humans. Secondly, TLRs were associated with inflammatory responses to subacute stress[15, 28]. The median time of our blood sample was 3 hours, so the time was the early stage of stroke. According to the temporal analysis of our study, levels of TLRs might not change at 3 hours. Thirdly, the sample size was not large enough to draw the conclusion.

All these four biomarkers can be easily measured and had available assays, and it is useful to create a panel included these 4 biomarkers and use it as a routine blood test in patients with AIS to find the patients who had ability to develop LHI or MCE early. Our findings suggested detecting the multiple biomarkers at baseline was a good way to identify high-risk patients with LHI or MCE. patients who had several elevated biomarkers, needed to choose the suitable therapeutic interventions and reduce the occurrence of complication[29].

The limitations of our study were as following: firstly, we enrolled 263 AIS patients into analysis, and the proportion of patients with LHI was higher than 15.65-20% in patients as pervious reported. The reason is that some of the AIS patients without LHI were unwilling to provide blood sample. Secondly, up to now, evidence is lacking to prove the combined impact of MIF, TLR2/4 and MMP-9. Therefore, some of our hypotheses need animal experiments to verify the mechanism. Thirdly, it is worth discussing whether the level of biochemical markers in serum could reflect the level of markers in brain. Although our conclusion was significant in plasma, whether the same change in the brain barrier needs more direct detection methods, such as the detection of biochemical markers in cerebrospinal fluid. Nevertheless, considering the clinical implementation and patient acceptance, it was easier to predict the malignant outcome through the detection of serum biomarkers. Because the number of patients at different time points was not large enough to perform the analysis, the study on the dynamic changes of the four biomarkers only described the median level of the biomarkers at different time points.

This study indicated that higher levels of MIF and MMP-9 were related to LHI. There were trends of association between a higher level of serum MIF/MMP-9 and an increased risk of MCE after AIS, which was warranted further validation in large cohort studies.

LHI: Large hemisphere infarction; AIS: Acute ischemic stroke; MCE: Malignant cerebral edema; ICU：Intensive care unit; MIF: Macrophage migration inhibitory factor; MMP: Matrix metalloproteinase; NICU: Neuro-intensive care unit; CT: Computed tomography; MRI: Magnetic resonance imaging; NIHSS: National Institutes of Health stroke scale score; SD: Standard deviation; IQR: Interquartile range; ROC: Receiver operating characteristics; ESM: Electronic supplemental material

Ethics approval and consent to participate

The study was approved by the Scientific Research Department of West China Hospital (Ethics No. 174. 2020) and conformed to the Declaration of Helsinki.

Consent for publication

Not applicable

Availability of data and materials

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

Competing interests

The authors declare that they have no competing interests.

Funding

This research was supported by the National Natural Science Foundation of China (grant numbers 81974181)

Authors’ Contributions

Ming Liu was responsible for the design and quality control of this article. Wen Guo, Mangmang Xu, Xindi Song, Yajun Cheng and Yilun Deng were responsible for the inclusion of patients. Wen Guo, Mangmang Xu, Xindi Song were responsible for the evaluation of patients' imaging results, while Guo Wen were responsible for the collection and detection of blood samples. Wen Guo wrote the draft of this manuscript.

Acknowledgements

The authors would like to thank Yanan Wang gave suggestion to this study.

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Association of serum macrophage migration inhibitory factor with large hemisphere infarction and malignant cerebral edema after acute ischemic stroke

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