Quantitative proteomic analysis of plasma after remote ischemic conditioning in acute ischemic stroke

Abstract

Remote ischemic conditioning (RIC) has been demonstrated to be effective in acute ischemic stroke, and numerous biomarkers have been investigated; however, few studies have simultaneously detected several biomarkers and observed their dynamic changes. We aimed to identify serum biomarkers whose changes are associated with RIC following stroke. This was an exploratory analysis of the RICAMIS trial, in which patients with serum samples collected were enrolled and divided into treatment groups. Serum samples were collected at admission, 3 days after randomization, and at discharge. Serum biomarkers with significantly different changes between groups were identified. Of the 25 enrolled patients, 9 patients were assigned to the RIC group, while 16 patients were assigned to the Control group. Compared with Control group, 9 serum biomarkers were found to significantlychange at admission versus 3 days after randomization, as well as at admission versus discharge in the RIC group. These included neurological biomarkers (V-type proton ATPase subunit G3 and secretogranin-3), vascular-related biomarkers (angiopoietin-related protein 6, Histone-lysine N-methyltransferase 2D, keratin type I cytoskeletal 18, and mitogen-activated protein kinase 3), inflammatory biomarkers (macrophage receptor and Nonspecific cytotoxic cell receptor protein-1), and trypsin-1. This is the first study to identify changes in serum biomarkers after RIC treatment in patients with acute ischemic stroke by quantitative proteomic analysis, which will provide the guidance for selecting target population in future clinical trials. The relationship of identified biomarkers with RIC efficacy warrants further investigation.

Introduction

Reperfusion therapies, including intravenous thrombolysis and endovascular therapy, are standard strategies for acute ischemic stroke;^1,2 however, these strategies are limited by strict eligibility criteria and imperfect treatment efficacy^3,4. In recent years, exploring cerebral protection as an adjunct therapy to improve prognosis following stroke has been a hot topic⁵. To date, few cerebral protective strategies have been translated from preclinical or clinical trials in clinical practice⁶.

Remote ischemic conditioning (RIC), which involves intermittently blocking the blood flow of limbs and producing transient ischemia with the intention of protecting the brain, has been demonstrated to have the potential benefits for stroke in both animal models and clinical trials^7,8. The Remote Ischemic Conditioning for Acute Moderate Ischemic Stroke (RICAMIS) trial demonstrated that RIC treatment initiated within 48 h of stroke onset safely and significantly improved excellent functional outcomes at 90 days among patients with acute moderate ischemic stroke who did not receive any reperfusion therapy⁹. However, in the Remote Ischemic Conditioning in Patients With Acute Stroke Trial (RESIST), RIC initiated in the prehospital setting and continued in the hospital did not significantly improve functional outcomes at 90 days¹⁰. The efficacy and mechanism of RIC are worth further exploration.

In previous animal and clinical studies, RIC following ischemic stroke has been found to be associated with changes in several serum biomarkers^11,12. Moreover, proteomic analysis identified plasma correlates of RIC in the context of experimental traumatic brain injury and ischemic stroke^13,14. Previous proteomic study mainly focused on blood samples from experimental animals¹⁴ and data from human biomarkers were limited to a small number of prespecified biomarkers¹². Up to date, no study has comprehensively investigated the changes in serum biomarkers after receiving RIC treatment in patients with acute ischemic stroke through proteomic analysis. This may help to understand the potential mechanism of RIC in clinical practice and select target population benefited from RIC. Based on the RICAMIS trial, we designed an exploratory analysis to investigate the changes in serum biomarkers following RIC.

Results

As shown in Figs. 1 and 51 patients with acute moderate ischemic stroke were consecutively screened in the current study, and 26 patients were excluded for various reasons: 9 patients did not have any blood sample collected, and 17 patients had incomplete blood sample collections. Finally, 25 patients were recruited into the study, including 9 patients in the RIC group and 16 patients in the control group. Baseline characteristics and outcomes of included patients were balanced between treatment groups (Table 1).

Fig. 1.

Flow Diagram. RIC, remote ischemic conditioning; Control, usual care alone without RIC treatment; RICAMIS, Remote Ischemic Conditioning for Acute Moderate Ischemic Stroke.

Table 1.

Baseline characteristics and Outcomes.

	RIC (N = 9)	Control (N = 16)	P Value
Baseline Characteristics
Age, median (IQR), y	70 (58–79)	64 (56–71)	0.69
Sex (F), No. (%)	3 (33.3)	6 (37.5)	0.84
Current smoker, No. (%)	2 (22.2)	3 (18.8)	0.75
Current drinker, No. (%) a	1 (11.1)	2 (12.5)	0.71
Comorbidities, No. (%) b
Hypertension	5 (44.4)	8 (50.0)	0.79
Diabetes	1 (11.1)	3 (18.8)	0.62
Previous ischemic stroke c	1 (11.1)	2 (12.5)	0.92
Previous transient ischemic attack	1 (11.1)	2 (12.5)	0.92
Blood pressure at randomization, median (IQR), mmHg
Systolic	151 (135–157)	152 (140–161)	0.85
Diastolic	90 (84–94)	85 (80–94)	0.72
Blood glucose, median (IQR), mmol/L	6.29 (5.96–7.95)	7.62 (6.67–9.63)	0.28
Baseline NIHSS score, median (IQR) d	6 (6–10)	7 (6–8)	0.56
Estimated premorbid function (mRS), No. (%) e
No symptoms (score, 0)	9 (100.0)	14 (87.5)	0.27
Symptoms without any disability (score, 1)	0 (0.0)	2 (12.5)
OTT, median (IQR), h	25.0 (14.6–29.6)	27.5 (18.3–43.2)	0.41
Duration of hospitalization, median (IQR), d	11 (8–13)	11 (10–14)	0.99
Presumed stroke cause, No. (%) f
Large artery atherosclerosis	3 (33.3)	5 (31.3)	0.17
Small artery occlusion	3 (33.3)	5 (31.3)
Cardioembolic	2 (22.2)	0 (0.0)
Undetermined cause	1 (11.1)	6 (37.5)
Outcomes
NIHSS score at discharge, median (IQR)	6 (2–7)	6 (3–7)	0.98
mRS score at 90 days, median (IQR)	2 (1–3)	2 (1–4)	0.89
Mortality at 90 days, No. (%)	0 (0.0)	0 (0.0)	0.99

IQR indicates interquartile range; mRS, modified Rankin Scale; NIHSS, National Institute of Health Stroke Scale; OTT, time from onset of symptom to treatment; RIC, remote ischemic conditioning. ^a Current drinker means consuming alcohol at least once a week within 1 year before onset of the disease and consuming alcohol continuously for more than 1 year. ^b The comorbidities were based on the patient or family report. ^c Previous ischemic stroke referred only to the patients with pre-stroke mRS ≤ 1. ^d Patients with NIHSS scores of 6 to 16 were eligible for this study; NIHSS scores range from 0 to 42, with higher scores indicating more severe neurological deficit. ^e Patients with mRS scores of 0 to 1 were eligible for this study; Scores on the mRS of functional disability range from 0 (no symptoms) to 6 (death). ^f The presumed stroke cause was classified according to the Trial of Org 10,172 in Acute Stroke Treatment (TOAST) classification system using clinical findings, brain imaging, and laboratory tests. Other determined causes included pulmonary embolism, peripheral vessel incident, and cardiovascular incident.

Different serum biomarkers changed at 3-Day versus admission

Compared with the control group, 60 serum biomarkers with significant changes between admission and 3 days after randomization were observed in the RIC group (P < 0.05). Scatter and volcano plots showed all measured serum biomarkers (Fig. 2A and B), while a heatmap displayed different serum biomarkers (Fig. 2C).

Fig. 2.

Different Serum Biomarkers With Significant Change at Admission and 3-Day Between Groups. (A) Volcano plot for detected serum biomarkers. X-axis represents the average of change in serum levels between two groups while Y-axis represents the –log₁₀ P value; cyan point represents the biomarkers with a significant difference, while red point represents the serum biomarkers without significant difference. (B) Scatter plot for detected serum biomarkers. X-axis represents the average of change in serum levels in the RIC group, while Y-axis represents the average of change in serum levels in the control group. Compared with the control group, blue point represents decreased serum biomarkers, while red point represents increased serum biomarkers. (C) Heatmap for identified serum biomarkers. Red color represents increased serum biomarkers, while blue color represents decreased serum biomarkers; the darker the color, the more significant the difference of serum biomarkers. RIC, remote ischemic conditioning; Control, usual care alone without RIC treatment; D1, the day at admission (before randomization); D2, the day at 3 days after randomization.

Different serum biomarkers changed at discharge versus admission

Compared with the control group, 92 serum biomarkers with significant changes between admission and discharge were observed in the RIC group (P < 0.05). Scatter and volcano plots showed all measured serum biomarkers (Fig. 3A and B), while a heatmap displayed different serum biomarkers (Fig. 3C).

Fig. 3.

Different Biomarkers With Significant Change at Admission and Discharge Between Groups. (A) Volcano plot for detected serum biomarkers. X-axis represents the average of change in serum levels between two groups while Y-axis represents the –log₁₀ P value; cyan point represents the serum biomarkers with a significant difference, while red point represents the serum biomarkers without significant difference. (B) Scatter plot for detected serum biomarkers. X-axis represents the average of change in serum levels in the RIC group, while Y-axis represents the average of change in serum levels in the control group. Compared with control group, blue point represents decreased serum biomarkers, while red point represents increased serum biomarkers. (C) Heatmap for identified serum biomarkers. Red color represents increased serum biomarkers, while blue color represents decreased serum biomarkers; the darker the color, the more significant the difference of serum biomarkers. RIC, remote ischemic conditioning; Control, usual care alone without RIC treatment; D1, the day at admission (before randomization); D3, the day at discharge.

Identified serum biomarkers and function enrichment

After screening, nine serum biomarkers with significantly different changes between treatment groups across three time points were identified. These included increased angiopoietin-related protein 6 (ANGPTL-6), macrophage receptor (MARCO), and nonspecific cytotoxic cell receptor protein-1 (NCCRP-1), as well as decreased levels of V-type proton ATPase subunit G3 (ATP6V1G3), histone-lysine N-methyltransferase 2D (KMT2D), keratin type I cytoskeletal 18 (KRT-18), mitogen-activated protein kinase 3 (MAPK-3), trypsin-1 (PRSS-1), and secretogranin-3 (SCG-3).

A comprehensive gene ontology (GO) enrichment analysis was conducted to gain deeper insight into the main functions of the identified serum biomarkers. The GO analysis consisted of biological processes and molecular functions. The biological process analysis showed that KMT2D and MAPK-3 were involved in the regulation of histone modification and positive regulation of chromatin organization (Fig. 4A). The molecular function analysis indicated that KRT-18 and MAPK-3 were associated with scaffold protein binding (Fig. 4B). The Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis revealed that ATP6V1G3 and MAPK-3 were part of the mTOR signaling pathway (Fig. 4C).

Fig. 4.

Protein Function Analysis of Identified Serum Biomarkers. (A) Enriched biological processes of identified serum biomarkers. (B) Enriched molecular function of identified serum biomarkers. (C) Enriched pathway enriched by identified serum biomarkers. X-axis represents the enrichment, while Y-axis represents the biological process, the molecular function, and the pathway. The deeper the color, the larger the P value.

Discussion

To the best of our knowledge, this is the first report to identify significant changes in nine serum biomarkers between the RIC and control groups, including increased serum biomarkers such as ANGPTL-6, MARCO, and NCCRP-1, as well as decreased biomarkers, such as ATP6V1G3, KMT2D, KRT-18, MAPK-3, PRSS-1, and SCG-3.

In the previous study, the ATP6V1G3 was reported to be associated with mitochondrial energy metabolism in the post-stroke neurovascular system, possibly contributing to the neuroprotection after a stroke¹⁶. However, this was the first time that the other eight biomarkers were identified in the field of ischemic stroke. Among these biomarkers, similar to ATP6V1G3, the KMT2D, KRT-18, ANGPTL-6, and SCG-3 were involved in the regulation of mitochondrial function and angiogenesis in cardioprotection. On one hand, in terms of regulating mitochondrial function, KMT2D was important for the regulation of mitochondrial respiration,¹⁷ and KRT-18 conferred cardioprotection by maintaining mitochondrial integrity and function¹⁸. On the other hand, in terms of promoting angiogenesis, ANGPTL-6 was previously reported to contribute to endothelial repair through MAPK pathway and mediate angiogenesis,^19,20 while SCG-3 was associated with neovascularization and angiogenesis^21,22. Nevertheless, given the opposite changes in ANGPTL-6 and SCG-3 following RIC treatment, specific mechanisms involving these two serum biomarkers warrant further investigation. Based on the functional enrichment analysis, regulation of histone modification and the mTOR signaling pathway were significantly enriched items. KMT2D is a histone methyltransferase that has been previously reported to contribute to angiogenesis in the ischemic heart by regulating the transcriptional activation of VEGF²³. The MAPK/mTOR signaling pathway is involved in hypoxia-inducible factors induced angiogenesis,²⁴ which is also mediated by RIC treatment²⁵. Collectively, we inferred that some of the identified serum biomarkers in this study may contribute to the regulation of mitochondrial function and angiogenesis following RIC treatment. This hypothesis should be verified through animal experiments based on cerebral ischemia/reperfusion injury.

Interestingly, we found three serum biomarkers that were not associated with the above biological processes and lacked internal connections. For example, NCCRP-1 is required for a competent acute stress response and may play a role in the activation of non-specific cytotoxic cells²⁶. Given the significant increase in NCCRP-1 in the RIC group compared with the control group, more increased NCCRP-1 in the RIC group may be attributed to the acute stress responses elicited by RIC treatment. Additionally, macrophages was previously reported to decrease after receiving RIC treatment in a myocardial infarction model,²⁷ making it difficult to explain the increased serum levels of MARCO in the current study. The function of PRSS-1 is not clear and warrants further investigation in the future. Furthermore, fluctuations in major neuronal injury biomarkers, including UCH-L1, NSE, GFAP, hypoxia-inducible factors-1alpha, and S100beta, were not observed in the current study. This effect is likely due to the mechanism of RIC, which appears to promote recovery—such as by facilitating angioneurogenesis and neuroplasticity in the peri-infarction area—rather than exerting simple neuroprotection⁹.

There were several limitations in the current study. The main one was small sample size with imbalance between two groups, which limited the generalizability and statistical robustness. For example, the difference in blood glucose levels and proportion of patients with diabetes history between this study and RICAMIS trial could affect the representativeness of our results and complicate the elucidation of RIC mechanisms. This exploratory analysis had the consequential inability to control for confounding factors such as age and stroke severity, rendering our study underpowered and introducing selection bias. Furthermore, the smaller sample size in the RIC group limited our ability to explore the association between significantly different serum biomarkers and functional outcomes after RIC treatment, such as changes in NIHSS or mRS scores. Whether the involvement of the identified serum biomarkers in the neuroprotection of RIC treatment and the underlying mechanisms, if they are involved in this protection, are worth further exploration by in vitro or in vivo experiments. Additionally, the serum levels of the identified biomarkers need to be further confirmed by other examinations, such as ELISA tests, in a larger cohort. Although biomarkers identified with dynamic changes during different time points may be associated with RIC effect, those with transient changes in the early stage should not be ignored which may also produce biological effect. Finally, as the neutral results of the RESIST trial,¹⁰ the generalizability of the results needs to be validated in other cohort, especially non-Chinese populations.

In conclusion, for the first time, the present study prospectively investigated the changes in serum biomarkers in patients with acute moderate ischemic stroke receiving RIC treatment who were not eligible for reperfusion treatments. The study found that three increased and six decreased serum biomarkers involved in the regulation of mitochondrial energy metabolism and angiogenesis in the RIC group compared with the control group. The role of these serum biomarkers warrants further investigation. The identified biomarkers might contribute to select target patients, however the relationship should be analyzed between outcomes and dynamic change in a cohort with large sample size and different populations.

Methods

Study population and procedure

The current study was an exploratory subgroup analysis of the RICAMIS trial,⁹ which was a multicenter, randomized clinical trial designed to assess the efficacy of RIC in acute ischemic stroke. Inclusion criteria were age ≥ 18 years, functioning independently before stroke (modified Rankin Scale [mRS] scoring 0 or 1), and diagnosis of acute moderate ischemic stroke (NIHSS score of 6 to 16 at admission) within 48 h. Exclusion criteria were receipt of intravenous thrombolysis or endovascular therapy, contraindications to RIC treatment, or diagnosis of cardiogenic embolism. The study was registered with ClinicalTrials.gov (NCT03740971), approved by the Ethics Committee of General Hospital of Northern Theater Command (No. k [2018] 43), and conducted in accordance with the Declaration of Helsinki. Written informed consent was obtained from patients or their legally authorized representatives.

In the RICAMIS trial, patients from two prespecified participating centers were enrolled in the current study, and those lacking any serum sample at admission (before randomization), or 3 days after randomization, or at discharge were excluded. According to whether patients received RIC treatment as an adjunct to usual care based on current guidelines, the enrolled patients were divided into two treatment groups: the RIC group and the control group. RIC treatment was performed using 5 cycles of cuff inflation (200 mm Hg for 5 min) and deflation (for 5 min), for a total procedure time of 50 min, twice daily for 10–14 days. Further details of RIC treatment have been described in a previous report⁹. The baseline characteristics of patients were obtained from the electronic database (http://ricamis.medsci.cn; Shanghai Meisi Medical Technology Co., Ltd.), which included age, sex, current smoking status, alcohol consumption, medical history, blood pressure at randomization, blood glucose levels, NIHSS score at randomization, mRS score before stroke, symptom onset-to-treatment time, hospitalization duration, and presumed stroke cause.

Laboratory determinations

About 4 ml of peripheral venous blood were collected from each patient at admission, 3 days after randomization, and discharge. The samples were then centrifuged at 1,000 × g for 10 min at 4℃, transferred into a 1.8-milliliter cryotubes, and stored at − 80℃ until detection. According to the manufacturer’s instructions, quantitative proteomic analysis (Jingjie PTM Biolabs Co.Ltd., Hangzhou, China) was used to simultaneously detect and quantify the biomarkers in the collected serum samples. Functional enrichment analyses were performed to explore possible interactions among identified serum biomarkers, using biological processes, molecular functions, and KEGG pathway analyses¹⁵. Identified serum biomarkers were defined as those with significantly different changes at 3 days after randomization and at discharge compared with at admission between the two treatment groups (e.g., [change between 3 days and admission in the RIC group] versus [change between 3 days and admission in the control group]; [change between discharge and admission in the RIC group] versus [change between discharge and admission in the control group]).

Statistical analysis

Descriptive statistics were performed to compare baseline characteristics between treatment groups. Continuous variables with abnormal distributions were described as medians and interquartile ranges. The Mann-Whitney U test was used to analyze continuous variables. Categorical variables were described as numbers and proportions. The Pearson χ² test was used to analyze categorical variables.

The empirical Bayes-based linear model method was used to analyze the differential expression of serum biomarkers between different time points with the R package limma. Differential expression was evaluated by adjusting the P value (Benjamini-Hochberg method) based on moderated t statistics. In all analyses, differences were considered statistically significant with P < 0.05. The free statistical software R (version 4.1.3) was used for the outcomes and graphs in quantitative proteomic analysis.

Author contributions

HSC contributed to conception and design of the study; YC contributed to analysis of data and drafted the original manuscript; FL and JRC contributed to the acquisition of data and figure preparation.

Funding

This study was supported by grants from the Science and Technology Project Plan of Liaoning Province (2023-MSLH-348, 2022JH2/101500020). The funders of the study had no role in the study design, data collection, data analysis, data interpretation or writing of the report.

Data availability

The data that support findings of study are available from the corresponding author on reasonable request.

Declarations

Competing interests

The authors declare no competing interests.