In total, 120 patients with AIS and 120 controls with high stroke risk factors were recruited from our hospital between July 2014 and June 2017. For the AIS patients, screening criteria were as follows: (i) primary diagnosis of AIS by clinical presentation, brain non-contrast computed tomography (CT) or diffusion-weighted magnetic resonance imaging, according to the “Guidelines for the Early Management of Patients with Acute Ischemic Stroke: A Guideline for Healthcare Professionals from the American Heart Association/American Stroke Association (AHA/ASA)”; (ii) age more than 18 years; (iii) admitted to our hospital within 24 hours after the symptoms onset; (iv) able to be regularly followed up. Following AIS patients were excluded: (i) had evidence of intracranial hemorrhage; (ii) treated with immunosuppressant within 1 month; (iii) suffered from infection (active or in the preceding 14 days of stroke); (iv) accompanied with hematological malignancies or solid tumors; (v) women who were pregnant or nursing. As for the controls, all of them had no history of stroke or malignancies and were presented with at least three stroke risk factors, such as hypertension, diabetes mellitus, hyperlipidemia, smoke and so on. The Institutional Review Board of our hospital approved the study protocol, and all participants or their guardians provided written informed consents.
Data collection and stroke severity assessment
At entry to the study, the baseline data of AIS patients was obtained through interview and medical records, which included age, gender, body mass index (BMI), smoke, hypertension, diabetes mellitus, hyperlipidemia, hypeluricemia and chronic kidney disease (CKD). Severity of AIS was assessed within the day of admission by use of the National Institutes of Health Stroke Scale (NIHSS) score. The NIHSS score aimed at assessing neurological impairment ranging from 0 to 42, a higher score indicated a more serious nerve damage, and the classification of severity was as follows: 0-1 point, normal or near normal; 2-4 points, mild stroke; 5-15 points, moderate stroke; 16-20 points, moderate-severe stroke; 21-42 points, severe stroke. Besides, controls’ basic characteristics including age, gender, BMI, smoke, hypertension, diabetes mellitus, hyperlipidemia, hypeluricemia and CKD were also documented on the enrollment.
Blood samples collection and determination
Venous blood samples were collected from AIS patients (within 24 hours after symptoms onset) and controls using ethylene diamine tetraacetic acid (EDTA) tubes, and subsequently centrifuged at 1600 g for 10 min (within 30 min) to acquire supernatant, then the supernatant was further centrifuged at 16000g for 10 min to obtain the plasma, which was scored at -80 ℃ for further analysis. Lnc-MALAT1 relative expression in the plasma of AIS patients and controls was determined by real-time quantitative polymerase chain reaction (RT-qPCR). AIS patients’ CRP concentration in plasma was detected using Fully automatic POCT fluorescence immunoassay analyzer (GeteinBiotech, Nanjing, Jiangsu, China), and the plasma levels of inflammatory cytokines including tumor necrosis factor α (TNF-α), interleukin-6 (IL-6), IL-8, IL-10, IL-17 and IL-22 were measured by human enzyme-linked immunosorbent assay (ELISA) kits (Thermo Fisher Scientific, Waltham, Massachusetts, USA) according to the manufacturer’s recommendations.
Using QIAamp RNA Blood Mini Kit (Qiagen, Duesseldorf, Nordrhein-Westfalen, German), total RNA was extracted from plasm samples. Then, reverse transcription to cDNA was performed by PrimeScript™ RT reagent Kit (Perfect Real Time) (Takara, Dalian, Liaoning, China), and qPCR was performed using TB Green™ Fast qPCR Mix (Takara, Dalian, Liaoning, China)). GAPDH was applied as the internal reference. Primers used in the RT-qPCR were as follows: lnc-MALAT1, forward (5'->3'): TCCTAAGGTCAAGAGAAGTGTCAG, reverse (5'->3'): GTGGCGATGTGGCAGAGAA; GAPDH, forward (5'->3'): TGACCACAGTCCATGCCATCAC, reverse (5'->3'): GCCTGCTTCACCACCTTCTTGA.
All AIS patients received appropriate treatments as recommended by 2013 AIS Guidelines (AHA/ASA), and were followed up regularly or as clinically indicated. The last follow-up date was June 30, 2018, and the median follow-up duration was 25.0 months (range: 1.0-42.0 months). RFS was calculated from the date of hospital admission to the date of recurrence or death.
SPSS 24.0 statistical software (SPSS Inc, Chicago, IL, USA) was used for statistical data processing, and the GraphPad Prism 6.01 (GraphPad Software Inc., San Diego, CA, USA) was applied to the graphs plotting. Continuous variables were expressed as mean ± standard deviation (SD) or median and interquartile range (IQR), and the categorical variables were expressed as number (percentage). Differences between groups were determined by Student’s t test, Wilcoxon rank sum test or Chi-square test. Correlations between variables were analyzed by Spearman rank test. Diagnostic value of variable was assessed by receiver operating characteristic (ROC) curve analysis and the derived area under the curve (AUC) as well as 95% confidence interval (CI). RFS profiles were illuminated by plotting the Kaplan-Meier (K-M) curve, and the difference of RFS between groups was determined by the log-rank test. Factors affecting RFS were analyzed by univariate and multivariate Cox's proportional hazards regression models. All tests were 2-sided, and P values <0.05 were considered statistically significant.