
==== Front
Biomed J
Biomed J
Biomedical Journal
2319-4170
2320-2890
Chang Gung University

S2319-4170(23)00121-X
10.1016/j.bj.2023.100684
100684
Original Article
Symptom-correlated MiRNA signature as a potential biomarker for Kawasaki disease
Chen Chia-Chun ab
Chu Hsueh-Yao a
Chang Ian Yi-Feng ac
Chang Yu-Sun ad
Weng Ken-Pen ef
Chang Ling-Sai gh
Liu Shih-Feng ijk
Kuo Ho-Chang erickuo48@yahoo.com.tw
dr.hckuo@gmail.com
gij∗
a Molecular Medicine Research Center, Chang Gung University, Taoyuan, Taiwan
b Department of Laboratory Medicine, Chang Gung Memorial Hospital at Linkou, Taoyuan, Taiwan
c Department of Neurosurgery, Chang Gung Memorial Hospital at Linkou, Taoyuan, Taiwan
d Graduate Institute of Graduate Institute of Biomedical Science, Chang Gung University, Taoyuan, Taiwan
e Department of Pediatrics, Kaohsiung Veterans General Hospital, Kaohsiung, Taiwan
f School of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan
g Kawasaki Disease Center and Department of Pediatrics, Kaohsiung Chang Gung Memorial Hospital, Kaohsiung, Taiwan
h College of Medicine, Chang Gung University, Kaohsiung, Taiwan
i College of Medicine, Chang Gung University, Taoyuan, Taiwan
j Department of Respiratory Therapy, Kaohsiung Chang Gung Memorial Hospital, Kaohsiung, Taiwan
k Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, Kaohsiung Chang Gung Memorial Hospital, Kaohsiung, Taiwan
∗ Corresponding author. Department of Pediatrics, Kaohsiung Chang Gung Memorial Hospital, No. 123, Dapei Rd., Niaosong Dist., Kaohsiung City 83301, Taiwan. erickuo48@yahoo.com.twdr.hckuo@gmail.com
10 12 2023
10 2024
10 12 2023
47 5 10068428 7 2023
12 11 2023
5 12 2023
© 2023 The Authors
2023
https://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
Graphical abstract

Image 1

Highlights

• The expression levels of ten miRNAs are highly correlated with KD.

• These miRNAs can co-regulate TGF-β signaling involved in KD pathogenesis.

• This symptom-correlated miRNA signature can provide an objective score for KD risk assessment.
==== Body
pmc1 Introduction

Kawasaki disease (KD), also called mucocutaneous lymph node syndrome, is an acute febrile disease of unknown cause that mainly affects children younger than 5 years. The diagnosis of KD typically involves the presence of fever for at least 5 days together with at least 4 of the 5 following clinical symptoms: oral mucosal change, bilateral conjunctivitis, lymphadenopathy, swelling/peeling of extremities, and skin rash [1,2]. Within the first 10 days of fever onset, treatment with high-dose intravenous immunoglobulin (IVIG) can greatly reduce the risk of severe coronary artery lesions (CALs) [3]. If left untreated, up to 25% of KD patients may develop coronary artery aneurysm (CAA), making KD the leading cause of acquired heart disease in young children in developed countries [2,4]. In practice, delayed treatment is due to difficulties in determining these subjective symptoms and differentiating the incomplete KD that does not present with sufficient principal clinical findings [5]. Therefore, it is urgent to develop molecular assays to improve the diagnosis of KD [6].

MicroRNAs (miRNAs) are a group of short noncoding RNA molecules 18–25 nucleotides in length that govern various aspects of cellular functions, immune responses, and pathological abnormalities [7]. In 2013, miRNAs were reported to participate in KD pathogenesis for the first time [8]. With a decade of effort, accumulated studies have demonstrated that aberrant miRNAs play important roles in KD pathophysiology and can be used as potential biomarkers in KD diagnosis and monitoring [9]. However, there is still no consensus on a miRNA-based assay for KD detection in clinical practice. By examining the miRNA profiles of KD patients and fever controls (FC), we discovered in our previous study that the ten most altered miRNAs, miR-183-5p, miR-182-5p, miR-941, miR-148a-3p, miR-223-3p, miR-27a-3p, miR-378a-3p, miR-30e-3p, miR-30c-5p, and miR-140-3p, could be combined as a classification model offering the highest sensitivity of 84.2% and specificity of 92.5% in KD detection in one small cohort of samples [10]. For clinical application, these miRNA biomarkers have to be further validated using a larger cohort of samples to clarify their discriminating powers for incomplete KD and even for non-KD patients with similar symptoms (suspected KD). In addition, the possible biological roles and regulatory mechanisms of these miRNAs in KD pathophysiology have never been comprehensively evaluated and are worthy of further investigation.

In the present study, we retrospectively collected a total of 665 blood samples to evaluate our ten miRNAs as potential KD biomarkers using multiplex RT-qPCR. In addition to validating the discriminating power in complete and incomplete KD, we further demonstrated the specificities in non-KD patients, including nonfever cases and cases of suspected KD, and in KD patients after treatment. We also demonstrated the associations of these miRNAs with KD diagnostic symptoms and proved that the biologically relevant miRNA signature could be used to identify patients who are the most at-risk for KD.

2 Materials and methods

2.1 Study groups

In this retrospective study, 540 gender-matched patients from Kaohsiung Chang Gung Hospital in Taiwan and 665 associated blood samples were included. Of the 540 patients, 40 nonfever patients were recruited as healthy controls (HCs). Two hundred patients who had a fever (FC patients) and 58 suspected KD patients (s-KD) who had similar symptoms but did not fit the diagnostic criteria for KD were also recruited. The above patients were defined as the non-KD control group. As shown in Supplementary Table 1, the patients in the FC and s-KD groups were admitted to the hospital due variously to infected or inflammatory diseases. The KD patients were diagnosed according to criteria of the American Heart Association (AHA), namely, fever that persists for more than 5 days and at least four of the following five clinical criteria: oral mucosal change (such as injected or fissured lips, strawberry tongue), bilateral nonexudative conjunctivitis, cervical lymph node enlargement of over 1.5 cm in diameter, changes in the peripheral extremities (edema and erythema of the hands and feet in acute phase and/or periungual desquamation in subacute phase), and a polymorphous rash [1,2]. The patients with persisting fever for more than 5 days and 2 or 3 compatible clinical criteria were then evaluated with additional laboratory tests related to AHA supplementary criteria. If patients exhibited more than 3 supplemental laboratory criteria (anemia for age, platelet count ≥450,000/mm3 after the seventh day of fever, albumin ≤3.0 g/dL, elevated ALT level, WBC count ≥15,000/mm3, and ≥10 WBC/HPF on urinalysis) or a positive echocardiogram, a diagnosis of incomplete KD was made [1,2]. All recruited KD patients were treated with IVIG (2 g/kg/dose) infused over 12 h, and the numbers of persisting days from fever onset until IVIG treatment were recorded as the fever days. Among 242 KD patients, there were 125 from whom paired blood samples approximately 3 weeks after IVIG treatment (KD-p) were obtained. The clinical characteristics of these patients are summarized in Table 1. This study was approved by Chang Gung Memorial Hospital's Institutional Review Board (IRB number: 202100827A3 and 202000378A3), and written informed consent was obtained from the parents or guardians of all the participants.Table 1 Clinical characteristics of the study patients.

Table 1Variable	Healthy Control	Fever Control	Suspected Kawasaki	Kawasaki Disease	
(HC)	(FC)	Disease (s-KD)	(KD)	
Number of patients	40	200	58	242	
Age, median (IQR), years	1.95 (1.07–2.43)	3.42 (1.75–4.86)	1.63 (0.83–3.40)	1.47 (0.80–2.43)	
Male sex, number (%)	15 (37.5%)	114 (57.3%)	38 (65.5%)	140 (57.9%)	
Laboratory values, medium (IQR)	
 Hemoglobin, g/dL	12.4 (11.9–13.0)	12.1 (11.4–12.8)	11.9 (11.0–12.5)	11.1 (10.5–11.8)	
 C-reactive protein, mg/L	–	15.9 (5.4–50.1)	5.5 (1.4–29.4)	58.7 (25.5–111.6)	
 Platelets count, x103/μl	317.0 (257.8–390.5)	247.0 (189.8–312.8)	339.0 (253.8–427.3)	332.0 (275.5–430.0)	
 White blood cell count, x103/μl	9.0 (7.8–10.1)	7.6 (5.7–10.7)	8.3 (7.2–11.8)	12.5 (10.4–15.7)	
 Segmented neutrophils, %	32.5 (23.7–44.3)	46.0 (31.8–60.6)	44.3 (29.0–52.6)	59.0 (45.0–70.5)	
Coronary artery status, number (%)	
 Normal	–	–	–	172 (71.1%)	
 CAL	–	–	–	70 (28.9%)	
 CAA	–	–	–	16 (6.6%)	
Abbreviations:IQR:interquartile range;CAL:coronary artery lesion;CAA:coronary artery aneurysm.

2.2 Sample collection and miRNA detection

In the present study, we detected these miRNA targets in white blood cells (WBCs) as described previously [10]. In brief, the plasma-removed blood samples were first subjected to red blood cell removal and then to enrich WBC. The WBC collections were further processed with the mirVana miRNA isolation kit (Ambion; Thermo Fisher Scientific, USA) to extract RNAs according to the manufacturer's instructions. The extracted RNAs were stored at −80 °C until use. The RNA concentration was quantified using a Nanodrop 3000 Spectrophotometer (Thermo Fisher Scientific, Waltham, MA, USA). The fixed amounts of purified RNAs were reverse transcribed using a TaqMan miRNA Reverse Transcription Kit (Applied Biosystems, Foster City, CA) with a mixed RT primer, and then each miRNA was detected using the TOOLS miRNA RT‒qPCR primer/probe set (BIOTOOLS, Taipei, Taiwan.) in an ABI 7500 Real-Time PCR System (Applied Biosystems, Foster City, CA) according to the manufacturer's protocol [11]. For adjusting miRNA expression in WBCs, we chose the endogenous small nucleolar RNA, C/D Box 48 (SNORD48) as the normalization control instead of using cell-free miRNAs. The levels of miRNAs were calculated and represented by the ΔCt values.

2.3 Model development and statistical analysis

To optimize the prediction model, we used the LIBSVM method to develop a scoring algorithm based on the expression levels of the ten miRNAs to distinguish KD patients from patients in non-KD controls (including HC, FC, and s-KD) [10]. The automatic script ‘easy.py’ of libsvm-3.24 (https://www.csie.ntu.edu.tw/~cjlin/libsvm/) was used to construct the SVM model with 10-fold cross-validation and default parameters. The discriminating power of the miRNA signature for KD was evaluated by the receiver-operating characteristic (ROC) curve and the area under the ROC curve (AUC). Furthermore, the post-IVIG samples were used as the validation cohort, and the scores of these samples were calculated by the above-described SVM algorithm with the same cutoff value. Descriptive statistics were summarized and presented as the percentage, mean or median, and standard deviation (SD). Intergroup comparisons were conducted using nonparametric statistics, and all statistical analyses were conducted using IBM SPSS Statistics 20 (IBM Corp., Armonk, NY, USA). A p value less than 0.05 (two-tailed) was considered indicative of statistical significance. Plots were graphed using Prism 7 software (GraphPad Software, La Jolla, California, USA).

2.4 Target prediction and pathway analysis

To predict the target genes of the ten miRNAs, ingenuity pathway analysis (IPA, Qiagen) was performed. Among a union of 6118 downstream targets predicted from each miRNA, 46 targets were annotated as KD-associated genes from the IPA database; these genes are summarized in Supplementary Table 5. Furthermore, the expression levels of these predicted genes in WBCs were validated in our previous profiling data using GeneChip Human Transcriptome Array 2.0 (HTA 2.0, Affymetrix, Santa Clara) (GSE109351) [12]. Data on the differentially expressed genes between non-KD samples and KD samples before and after IVIG treatments were implemented in IPA software, and the expression pattern of TGF-β signaling was chosen to be further demonstrated.

3 Results

3.1 Validating the KD discriminating powers of ten potent miRNAs by RT-qPCR

Based on our previous study, the ten miRNAs with the most alterations were identified from small RNA sequencing data and confirmed in a small cohort consisting of FC and KD patients [10]. In the present study, we further clarified the performance of these miRNAs in discriminating KD patients from not only FC but nonfever healthy controls (HC) and s-KD patients, who were symptomatic but not finally diagnosed. As shown in Fig. 1A–J and Supplementary Table 2, all of these miRNAs could be validated and were substantially upregulated in KD patients compared with the FC controls (1.06- to 4.44-fold), although the p value of miR-140-3p was slightly higher than the cutoff value (Fig. 1J and Supplementary Table 2). Noticeably, the expression levels of all miRNAs except miR-30c-5p were slightly elevated in the FC compared to the HC groups (1.05- to 2.35-fold) (Fig. 1A–J and Supplementary Table 2). In the comparison between the s-KD and FC groups, only miR-30c-5p expression was slightly elevated (1.14-fold) (Fig. 1I and Supplementary Table 2). However, as shown in Fig. 1, Table 2, and Supplementary Table 3, the expression levels of these ten miRNAs were the highest and were significantly upregulated in the KD patients relative to patients in all the non-KD controls (1.10- to 4.84-fold, all p < 0.01) (Table 2), especially in the complete KD patients (1.11- to 5.52-fold, all p < 0.01) (Supplementary Table 3). The top nine miRNAs besides miR-140-3p were also significantly upregulated in the incomplete KD (1.17- to 3.09-fold, all p < 0.01) relative to the control groups (Supplementary Table 3). Overall, these miRNAs have great potential for discriminating KD patients from non-KD patients (AUC = 0.575–0.809) (Table 2).Fig. 1 The normalized expression levels of KD-related miRNAs The dot plots show the normalized expression levels of ten miRNAs, including miR-183-5p (A), miR-182-5p (B), miR-941 (C), miR-148a-3p (D), miR-223-3p (E), miR-27a-3p (F), miR-378a-3p (G), miR-30e-3p (H), miR-30c-5p (I), and miR-140-3p (J), detected by RT-qPCR in patient groups. Abbreviations: HC: healthy control; FC: fever control; s-KD: suspected Kawasaki disease; KD: Kawasaki disease; KD-p: Kawasaki disease post-IVIG treatment (∗∗p < 0.01, ∗∗∗p < 0.001 by MWU test).

Fig. 1

Table 2 The normalized expression levels of ten KD-related miRNAs in the control (Ctrl), Kawasaki disease (KD), and post-IVIG (KD-p) groups.

Table 2miRNA	Ctrl (n = 298)	KD (n = 242)	KD-p (n = 125)	KD/Ctrl	KD-p/KD	
mean ± SD	mean ± SD	mean ± SD	Fold	p value	AUC	95% CI	Fold	p value	
miR-183-5p	−11.04 ± 1.84	−8.77 ± 1.87	−12.86 ± 1.42	4.84	4.65E-35	0.809	0.772–0.846	0.06	1.13E-45	
miR-182-5p	−9.87 ± 1.57	−8.06 ± 1.71	−11.33 ± 1.43	3.50	2.84E-30	0.786	0.747–0.825	0.10	1.75E-41	
miR-941	−9.31 ± 1.81	−8.11 ± 1.68	−9.89 ± 1.50	2.31	8.10E-19	0.721	0.678–0.765	0.29	2.26E-24	
miR-148a-3p	−7.35 ± 1.37	−6.72 ± 1.48	−7.99 ± 1.49	1.55	1.07E-11	0.670	0.624–0.716	0.42	1.14E-19	
miR-223-3p	4.11 ± 0.99	4.70 ± 0.97	3.53 ± 1.16	1.51	1.65E-14	0.692	0.647–0.737	0.45	3.60E-22	
miR-27a-3p	−2.49 ± 1.20	−1.95 ± 1.32	−2.64 ± 1.38	1.45	1.95E-10	0.659	0.613–0.706	0.62	9.85E-09	
miR-378a-3p	−4.76 ± 0.68	−4.49 ± 0.70	−4.94 ± 0.74	1.21	9.26E-08	0.634	0.587–0.681	0.73	2.20E-09	
miR-30e-3p	−3.60 ± 0.80	−3.35 ± 0.84	−3.83 ± 0.94	1.19	4.49E-06	0.615	0.567–0.662	0.72	6.61E-10	
miR-30c-5p	−3.32 ± 0.71	−3.08 ± 0.63	−3.35 ± 0.74	1.18	1.10E-05	0.610	0.562–0.657	0.83	5.15E-04	
miR-140-3p	−3.73 ± 0.62	−3.60 ± 0.65	−3.99 ± 0.71	1.10	2.88E-03	0.575	0.526–0.623	0.76	5.26E-09	
∗p values of intergroup comparisons were determined by the MWU test.

3.2 Optimizing the ten-miRNA-based model for KD prediction

To increase the sensitivity for KD detection, the SVM method was used to develop a binary classification model for distinguishing KD patients from non-KD controls. We found that these ten miRNAs could be combined into a miRNA signature with higher discriminating power, and their effects were summarized and expressed as a scoring system for each sample. As shown in Fig. 2A, the risk scores of KD samples (mean = 0.63) were substantially higher than those of control samples (mean = 0.28). The discriminating power of the miRNA signature for KD was improved to 0.882 higher than that of the individual miRNAs (Fig. 2B and Table 2). Impressively, the trend of the scoring distribution of the miRNA signature between these groups was very close to the expression pattern of each miRNA (Fig. 1, Fig. 2). The miRNA signature exhibited good specificity and sensitivity (87.9% and 76.9%, respectively); furthermore, the detection rate was up to 79.7% for complete KD and 67.3% for incomplete KD, just 13.0% and 15.5% for FC and s-KD, respectively, and only 2.5% for HC (Fig. 2D).Fig. 2 Clinical performance of the KD miRNA signature. (A) An SVM model was used to integrate the summed effects of the ten miRNAs into a miRNA signature to distinguish the KD group from the non-KD control group. Scores ranging from 0 to 1 were generated for each sample; the box plot denotes the distribution of scores in the two groups. (B) The discriminating power for KD was evaluated by ROC curve analysis of the scores of the miRNA signature. The optimal cutoff value was calculated from Youden's index on this ROC curve. (C) The dot plot denotes the distribution of scores in the individual group. (D) The samples with scores higher than the cutoff value are marked as positive. The rates of positivity in the individual groups are further represented in a bar chart. (E) Sample scores in the subgroups of KD patients divided by symptom numbers are demonstrated using dot plots. (F) Scores obtained from the same algorithm of the SVM model for 125 post-IVIG samples are calculated. Comparisons of scores of the paired samples from KD patients before and after IVIG treatment are shown. The cutoff value mentioned above is indicated by the dotted line. The red bar shows the mean of the respective groups. Abbreviations: HC: healthy control; FC: fever control; s-KD: suspected Kawasaki disease; KD: Kawasaki disease; KD-p: Kawasaki disease post-IVIG treatment; cKD: complete Kawasaki disease; incKD: incomplete Kawasaki disease (∗p < 0.05, ∗∗∗p < 0.001 by MWU test, Wilcoxon matched-pairs signed rank test, or Kruskal‒Wallis test.)

Fig. 2

3.3 Positive correlation of miRNA expression levels with clinical symptoms of KD

Given the slightly lower sensitivity of this miRNA signature for incomplete KD, we were curious whether the miRNA signature was associated with the major diagnostic symptoms of KD. As shown in Fig. 2E, the miRNA scores in KD patients were substantially elevated along with the symptom numbers (mean = 0.55, 0.63, and 0.69 in KD patients with less than three, four, and five symptoms, respectively) but did not change with the fever days until IVIG treatment (Supplementary Fig. 1). Next, we further demonstrated the association between the expression level of each miRNA and the respective symptom of KD. As summarized in Table 3, each miRNA was positively correlated with at least one symptom of KD in addition to swelling/peeling of hands and feet. We found that the expression levels of six miRNAs were substantially upregulated between KD patients with and without oral mucosal changes. With the same intergroup comparison, there were five, seven, and three substantially upregulated miRNAs for the symptoms of bilateral conjunctivitis, lymphadenopathy, and skin rash, respectively. However, no positive correlation between miRNA expression and any symptom was observed in s-KD patients (Supplementary Table 4). In contrast, only miR-183-5p and miR-182-5p were substantially downregulated in s-KD patients with swelling/peeling of hands and feet compared to those without this symptom. This is the first study to reveal an association between miRNA expression levels and clinical symptoms of KD.Table 3 Correlation of the expression level of each miRNA and the typical symptoms in the KD group.

Table 3miRNA	Oral mucosal change	Bilateral conjunctivitis	Lymphadenopathy	Swelling/peeling of hands and feet	Skin rash	
mean	Fold	p value	mean	Fold	p value	mean	Fold	p value	mean	Fold	p value	mean	Fold	p value	
No (n = 17)	Yes (n = 225)	No (n = 17)	Yes (n = 225)	No (n = 155)	Yes (n = 87)	No (n = 34)	Yes (n = 207)	No (n = 25)	Yes (n = 217)	
miR-183-5p	−10.58	−8.63	3.85	0.001	−10.50	−8.64	3.65	0.000	−8.82	−8.68	1.10	0.630	−9.06	−8.71	1.28	0.287	−9.86	−8.64	2.32	0.011	
miR-182-5p	−9.55	−7.95	3.04	0.001	−9.21	−7.97	2.36	0.007	−8.14	−7.91	1.17	0.406	−8.24	−8.02	1.17	0.478	−8.83	−7.97	1.82	0.016	
miR-941	−9.03	−8.04	1.99	0.015	−9.26	−8.02	2.37	0.003	−8.25	−7.85	1.31	0.064	−8.38	−8.06	1.25	0.174	−9.09	−7.99	2.14	0.013	
miR-148a-3p	−7.39	−6.67	1.65	0.080	−7.59	−6.66	1.91	0.010	−6.85	−6.49	1.28	0.013	−6.68	−6.72	0.97	0.878	−7.13	−6.67	1.38	0.629	
miR-223-3p	3.91	4.76	1.80	0.006	4.27	4.73	1.38	0.076	4.53	4.99	1.37	0.001	4.76	4.69	0.95	0.834	4.48	4.72	1.18	0.308	
miR-27a-3p	−2.38	−1.92	1.37	0.072	−2.56	−1.91	1.58	0.013	−2.09	−1.70	1.31	0.014	−1.79	−1.97	0.88	0.409	−2.20	−1.92	1.21	0.647	
miR-378a-3p	−4.75	−4.47	1.22	0.041	−4.67	−4.47	1.15	0.180	−4.57	−4.34	1.17	0.025	−4.36	−4.50	0.91	0.270	−4.65	−4.47	1.14	0.271	
miR-30e-3p	−3.67	−3.32	1.27	0.109	−3.65	−3.32	1.26	0.071	−3.45	−3.17	1.21	0.010	−3.23	−3.36	0.91	0.424	−3.49	−3.33	1.12	0.936	
miR-30c-5p	−3.38	−3.06	1.25	0.048	−3.23	−3.07	1.12	0.341	−3.16	−2.95	1.16	0.019	−2.96	−3.10	0.91	0.207	−3.15	−3.07	1.06	0.949	
miR-140-3p	−3.75	−3.59	1.12	0.200	−3.71	−3.59	1.09	0.497	−3.70	−3.42	1.21	0.002	−3.58	−3.60	0.98	0.848	−3.79	−3.58	1.16	0.370	
∗p values of intergroup comparisons were determined by the MWU test.

3.4 Downregulation of the miRNA expression levels in post-IVIG samples

To further demonstrate the associations of these miRNAs with KD, we evaluated the miRNA levels in 125 samples from KD patients after IVIG treatment. As shown in Fig. 1 and Table 2, the expression levels of all these miRNAs were substantially downregulated in post-treated samples relative to pretreated samples (from 0.06- to 0.83-fold, all p values < 0.01). Impressively, most of these miRNAs exhibited a return to the normal levels of the healthy controls (Fig. 1 and Supplementary Table 2). Only miR-27a-3p was slightly elevated (1.17-fold), and miR-183-5p and miR-182-5p were still downregulated (0.61- and 0.59-fold, respectively) in post-IVIG samples relative to healthy controls (Supplementary Table 2). Furthermore, we used these post-treated samples to test the prediction model and evaluate the clinical performance of our miRNA signature. As shown in Fig. 2F, the calculated scores of the post-treated samples were dramatically decreased compared to those of the paired samples before treatment (average reduction of 0.47-fold). Based on the same cutoff value, the miRNA signatures of 94.4% of the post-treated samples (n = 118) were predicted as negative results. These data further supported the high correlation of our miRNA signature with KD persistence, and the model could be used to monitor KD after IVIG treatment.

3.5 Identification of the potential signaling pathways regulated by KD-related miRNAs

To further investigate the possible functions of these KD-related miRNAs, we predicted their downstream target genes using QIAGEN's Ingenuity® Pathway Analysis (IPA). There were 6118 predicted genes based on these ten miRNAs. Subsequently, we performed KEGG pathway enrichment, focusing on the most reliable targets, which led to the identification of the top ten associated pathways. Notably, the TGF-β signaling pathway emerged as one of these pathways (Supplementary Fig. 2A). In addition, through the comparison with 125 KD-related genes as annotated by the IPA database, 46 potential target genes of these miRNAs were identified and summarized in Supplementary Fig. 2B and Supplementary Table 5. Among these genes, we noticed the six targets involved in the TGF-β signaling and further validated in our previous HTA 2.0 Transcriptome array data of WBC samples from patients in non-KD control and KD groups [12]. As shown in Supplementary Fig. 3, the expression levels of SMAD3, one of the predicted targets of miR-27-3a, were substantially downregulated in KD patients relative to non-KD controls (0.71-fold) and then returned to the normal levels after IVIG treatment. Furthermore, we demonstrated the overall effects of these KD-related miRNAs in the TGF-β signaling pathway using our transcriptome data. As shown in Fig. 3A, most of the potentially coregulated targets by the KD-related miRNAs in the TGF-β signaling pathway were substantially downregulated in KD patients compared to controls when these miRNAs were upregulated. Subsequently, we analyzed this interaction network in samples after IVIG treatment. Consistent with the downregulation of miRNA expression, the corresponding targets in TGF-β signaling were inversely expressed and substantially upregulated in the post-treated samples compared to the pretreated samples (Fig. 3B). Finally, the most downregulated targets from Fig. 3A, RUNX3, Smad3, and Smad7, could be further validated in our sample cohort. It is noteworthy that the observed trends of these three targets across the five groups exhibited a perfect inverse correlation with the expression patterns of the ten miRNAs (Supplementary Figs. 4,1). As shown in Supplementary Fig. 4, the expression levels of RUNX3, Smad3, and Smad7 were significantly downregulated in KD samples compared to non-KD controls (0.30, 0.36, and 0.44-fold, respectively; p < 0.001), and were notably elevated in post-treated samples compared to the pretreated samples (4.11, 4.12, and 4.89-fold, respectively; p < 0.001). All the results support the conclusion that these miRNAs are heavily involved in TGF-β signaling, which is one of the important pathways in KD pathogenesis.Fig. 3 Schematic overview of KD-related miRNAs in TGF-β signaling pathway. The predicted target genes of the KD-related miRNAs were derived from IPA analyses. Based on our data of HTA 2.0 arrays, the significantly differential expression in comparisons between KD and control groups (A) and pre- and post-IVIG KD groups (B) were highlighted (p < 0.05). Red and green colors were used to indicate upregulated and downregulated genes, respectively, in TGF-β signaling.

Fig. 3

4 Discussion

In recent years, mounting clinical evidence has indicated that miRNAs can serve as potential biomarkers for KD detection with extraordinary specificity and sensitivity [9]. However, there is still no consensus miRNA assay for KD diagnosis to date. In this study, our previously identified ten potential miRNAs [10] were validated in a larger independent cohort of 665 samples, and all these data showed great consistency. The reproducibility supports that the expression patterns of these KD-related miRNAs in WBCs are reliable although some of them with moderated elevation. The detection of miRNAs in WBCs offers distinct advantages, including reduced sample variations and the availability of suitable endogenous controls for normalization, in contrast to the analysis of circulating miRNAs derived from serum or plasma. The correlation analyses clarified that the elevated expression levels of these ten miRNAs in KD patients were not due to the younger age compared with non-KD controls (Supplementary Fig. 5). Integrating the effects of all ten miRNAs can enhance the discriminating ability for KD detection. Furthermore, we explored the associations of the expression levels of these miRNAs with the typical symptoms in KD patients for the first time. The positive correlations with KD symptoms only (Table 3) suggest that these miRNAs have great potential as diagnostic markers due to their capabilities to differentiate KD from other confusing diseases. More impressively, the expression levels of all these miRNAs were substantially downregulated in KD patients after IVIG treatment, becoming close to the normal expression levels observed in nonfever controls (Fig. 1 and Supplementary Table 2). Given these advantages, our KD miRNA signature can efficiently differentiate between patients in KD and non-KD groups and can be used for follow-up after IVIG treatment (Fig. 2).

Many studies have demonstrated the crucial involvement of miRNAs in KD's central pathogenesis, which includes the modulation of immunity, regulation of the inflammatory response, and vascular dysregulation [9]. Notably, miRNAs in WBCs stand out as more biologically relevant biomarkers compared to circulating miRNAs, as they can directly mediate immune responses through the downstream target genes. Through prediction with IPA, our functional analyses based on the downstream target genes of these ten miRNAs suggest the heavy involvement of the TGF-β signaling pathways (Supplementary Figs. 2,3). TGF-β is a multifunctional cytokine that regulates the proliferation, differentiation, apoptosis, and migration of various cell types through SMAD-dependent and SMAD-independent pathways [13,14]. Certainly, TGF-β signaling pathways play important roles in KD pathogenesis [15,16]. The genetic variations of TGFB2, TGFBR2, and SMAD3 in the TGF-β pathways were associated with KD susceptibility, CAL formation, and treatment response [16,17]. By examining the expression levels in coronary artery tissues from KD patients, TGF-β pathways were reported to contribute to aneurysm formation by promoting the generation of myofibroblasts that mediate damage to the arterial wall through the recruitment of CD8+ T cells [18]. Consistent with the decreased levels of TGF-β1 in KD sera during the acute stage [19], we found that many downstream components of the TGF-β pathways in WBCs from KD patients were downregulated by the coordination of these miRNAs at the transcriptional levels for the first time (Fig. 3A). Furthermore, the regulations in TGF-β pathways were reversed after IVIG treatment along with downregulation of these KD-related miRNAs (Fig. 3B).

Among the ten miRNAs, miR-183-5p, miR-182-5p, miR-223-3p, miR-27a-3p, and miR-30c-5p, the upregulation patterns have been reported in KD patients, which aligns with our research findings [[20], [21], [22], [23]]. Conversely, miR-941 expression has been reported to be downregulated in platelets, a distinct sample type from KD patients [21]. Furthermore, several of these miRNAs have been implicated in the mechanistic regulations of KD pathogenesis. The levels of miR-223-3p exhibit an upregulation in acute KD and KD without CAA when compared to cases of KD in the subacute stage and those with CAA, which suggests a potential role in alleviating vascular injury [23,24]. Overexpression of miR-223-3p has demonstrated the capacity to mitigate the development of cardiovascular lesions through the downregulation of interleukin-6 signaling in a KD mouse model [23]. Studies involving KD mice with miR-223 deletion have revealed an exacerbation of cardiovascular lesions and the activation of the NLRP3 inflammasome, further substantiating its protective function [25]. Similarly, in a co-culture setting, platelet-derived miR-223-3p has been observed to promote the differentiation of vascular smooth muscle cells, exerting a protective effect against vascular pathology [24]. According to the higher levels in KD patients with CAL, overexpression of miR-182-5p and miR-183-5p could enhance neutrophil infiltration of the endothelial layer [20]. In addition to TGF-β signaling, miR-27a-3p expression promoted monocyte-mediated TNF-α release within B cells in KD [26].

While the specific roles of the remaining miRNAs in KD pathogenesis have yet to be conclusively established, they exhibit associations with crucial processes such as immune modulation, inflammatory responses, and vascular regulation. Inflammation-related miR-148a-3p was differentially expressed in patients with systemic autoinflammatory disorders [27] and could regulate endothelial cell injury in atherosclerosis [28]. Overexpression of miR-378a-5p not only promoted the proliferation and migration of vascular smooth muscle cells [29] but also regulated cell proliferation and cell cycle through TGF-β2 in liver fibrosis [30]. Myocardial miR-30e-3p could affect cardiac function in myocardial injury and inhibit apoptosis during ischemia/hypoxia via autophagy activation [31,32]. As a potential therapeutic target, upregulating miR-30c-5p and downregulating BCL2L11 could improve myocardial injury in a rat ischemia/reperfusion model [33], and miR-30c-5p targeted Wnt7b/β-catenin to inhibit endothelial cell injury, a feature of atherosclerosis [34]. Finally, miR-140-3p could regulate the proliferation and migration of macrophages by targeting SMAD3 in TGF-β signaling [35]. However, further investigations are essential to elucidate whether these miRNAs play the same roles and regulatory mechanisms in the development and pathogenesis of KD.

5 Conclusions

In summary, the ten miRNAs hold substantial promise as valuable biomarkers for KD and participate in KD pathogenesis, particularly through the TGF-β signaling pathway. The verified miRNA signature exhibits the capability to distinguish complete and incomplete KD cases from suspected patients who manifest similar symptoms or fever, and to further confirm the response of IVIG treatment. Although the miRNA signature needs further validation by independent research centers in prospective studies, it represents a pioneering molecular assay that can provide an objective risk score to facilitate timely KD diagnosis and prevent the occurrence of cardiovascular complications resulting from delayed treatment.

Author contributions

Chia-Chun Chen designed and performed the experiments, analyzed the data, and wrote the manuscript. Hsueh-Yao Chu assisted with data summarization and manuscript writing. Ian Yi-Feng Chang performed bioinformatic analyses. Yu-Sun Chang supported data explanation and manuscript revising. Ken-Pen Weng, Ling-Sai Chang, Shih-Feng Liu, and Ho-Chang Kuo enrolled patients and collected samples. Ho-Chang Kuo further coordinated patient information and provided clinical support.

Grant support

This work was also supported by 10.13039/100012553 Chang Gung Memorial Hospital (CLRPD1J0014, CMRPG8M1421, CMRPG8M1431, CMRPG8L1241-2) and the 10.13039/501100004663 Ministry of Science and Technology of Taiwan (108-2823-8-182-001, NSTC 112-2314-B-182 -032-MY3).

Availability of data

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

Declaration of competing interest

Each author that there is no conflict to disclose. The funding organization(s) played no role in the study design; in the collection, analysis, and interpretation of data; in the writing of the report; or in the decision to submit the report for publication.

Appendix A Supplementary data

The following is the Supplementary data to this article.Multimedia component 1

Multimedia component 1

Acknowledgments

We thank the Molecular Medicine Research Center, Chang Gung University, of the Featured Areas Research Center Program within the framework of the Higher Education Sprout Project by the Ministry of Education (MOE) in Taiwan for technical support. We also thank the Bioinformatics Core Laboratories, Molecular Medicine Research Center, 10.13039/501100002836 Chang Gung University , Taiwan, for analytic support.

Peer review under responsibility of Chang Gung University.

Appendix A Supplementary data to this article can be found online at https://doi.org/10.1016/j.bj.2023.100684.
==== Refs
References

1 McCrindle BW Rowley AH Newburger JW Burns JC Bolger AF Gewitz M Diagnosis, Treatment, and Long-Term Management of Kawasaki Disease: A Scientific Statement for Health Professionals From the American Heart Association Circulation 135 17 2017 e927 99 28356445
2 Newburger JW Takahashi M Gerber MA Gewitz MH Tani LY Burns JC Diagnosis, treatment, and long-term management of Kawasaki disease: a statement for health professionals from the Committee on Rheumatic Fever, Endocarditis and Kawasaki Disease, Council on Cardiovascular Disease in the Young, American Heart Association Circulation 110 17 2004 2747 2771 15505111
3 Newburger JW Takahashi M Burns JC. Kawasaki Disease J Am Coll Cardiol 67 14 2016 1738 1749 27056781
4 Elakabawi K Lin J Jiao F Guo N Yuan Z. Kawasaki Disease: Global Burden and Genetic Background Cardiol Res 11 1 2020 9 14 32095191
5 Wang H Tan X Huang Z Pan B Tian J. Mining incomplete clinical data for the early assessment of Kawasaki disease based on feature clustering and convolutional neural networks Artif Intell Med 105 2020 101859
6 Lee W Cheah CS Suhaini SA Azidin AH Khoo MS Ismail NAS Clinical Manifestations and Laboratory Findings of Kawasaki Disease: Beyond the Classic Diagnostic Features Medicina 58 6 2022 734 35743997
7 Park JH Theodoratou E Calin GA Shin JI. From cell biology to immunology: Controlling metastatic progression of cancer via microRNA regulatory networks OncoImmunology 5 11 2016 e1230579
8 Shimizu C Kim J Stepanowsky P Trinh C Lau HD Akers JC Differential expression of miR-145 in children with Kawasaki disease PLoS One 8 3 2013 e58159
9 Xiong Y Xu J Zhang D Wu S Li Z Zhang J MicroRNAs in Kawasaki disease: An update on diagnosis, therapy and monitoring Front Immunol 13 2022 1016575
10 Kuo HC Hsieh KS Ming-Huey Guo M Weng KP Ger LP Chan WC Next-generation sequencing identifies micro-RNA-based biomarker panel for Kawasaki disease J Allergy Clin Immunol 138 4 2016 1227 1230 27450727
11 Chen CC Chang PY Chang YS You JF Chan EC Chen JS MicroRNA-based signature for diagnosis and prognosis of colorectal cancer using residuum of fecal immunochemical test Biomed J 46 1 2023 144 153 35074584
12 Chang LS Ming-Huey Guo M Lo MH Kuo HC. Identification of increased expression of activating Fc receptors and novel findings regarding distinct IgE and IgM receptors in Kawasaki disease Pediatr Res 89 1 2021 191 197 31816620
13 Tzavlaki K Moustakas A. TGF-β signaling Biomolecules 10 3 2020 487 32210029
14 Vander Ark A Cao J Li X. TGF-β receptors: In and beyond TGF-β signaling Cell Signal 52 2018 112-20
15 Lee AM Shimizu C Oharaseki T Takahashi K Daniels LB Kahn A Role of TGF-β signaling in Remodeling of Noncoronary Artery Aneurysms in Kawasaki disease Pediatr Dev Pathol 18 4 2015 310 317 25856633
16 Shimizu C Jain S Davila S Hibberd ML Lin KO Molkara D Transforming growth factor-beta signaling pathway in patients with Kawasaki disease Circ Cardiovasc Genet 4 1 2011 16 25 21127203
17 Kuo HC Onouchi Y Hsu YW Chen WC Huang JD Huang YH Polymorphisms of transforming growth factor-β signaling pathway and Kawasaki disease in the Taiwanese population J Hum Genet 56 12 2011 840 845 22011813
18 Shimizu C Oharaseki T Takahashi K Kottek A Franco A Burns JC. The role of TGF-β and myofibroblasts in the arteritis of Kawasaki disease Hum Pathol 44 2 2013 189 198 22955109
19 Matsubara T Umezawa Y Tsuru S Motohashi T Yabuta K Furukawa S. Decrease in the concentrations of transforming growth factor-beta 1 in the sera of patients with Kawasaki disease Scand J Rheumatol 26 4 1997 314 317 9310113
20 Li SC Huang LH Chien KJ Pan CY Lin PH Lin Y MiR-182-5p enhances in vitro neutrophil infiltration in Kawasaki disease Mol Genet Genomic Med 7 12 2019 e990
21 Ning Q Chen L Song S Zhang H Xu K Liu J The Platelet microRNA Profile of Kawasaki Disease: identification of Novel Diagnostic Biomarkers BioMed Res Int 2020 2020 9061568
22 Rong X Ge D Shen D Chen X Wang X Zhang L miR-27b Suppresses Endothelial Cell Proliferation and Migration by Targeting Smad7 in Kawasaki Disease Cell Physiol Biochem 48 4 2018 1804 1814 30078021
23 Wang X Ding YY Chen Y Xu QQ Qian GH Qian WG MiR-223-3p Alleviates Vascular Endothelial injury by Targeting IL6ST in Kawasaki Disease Front Pediatr 7 2019 288
24 Zhang Y Wang Y Zhang L Xia L Zheng M Zeng Z Reduced Platelet miR-223 Induction in Kawasaki Disease Leads to Severe Coronary Artery Pathology Through a miR-223/PDGFRβ Vascular Smooth Muscle Cell Axis Circ Res 127 7 2020 855 873 32597702
25 Maruyama D Kocaturk B Lee Y Abe M Lane M Moreira D MicroRNA-223 Regulates the Development of Cardiovascular Lesions in LCWE-Induced Murine Kawasaki Disease Vasculitis by Repressing the NLRP3 Inflammasome Front Pediatr 9 2021 662953
26 Luo Y Yang J Zhang C Jin Y Pan H Liu L Up-regulation of miR-27a promotes monocyte-mediated inflammatory responses in Kawasaki disease by inhibiting function of B10 cells J Leukoc Biol 107 1 2020 133 144 31583766
27 Akbaba TH Akkaya-Ulum YZ Tavukcuoglu Z Bilginer Y Ozen S Balci-Peynircioglu B Inflammation-related differentially expressed common miRNAs in systemic autoinflammatory disorders patients can regulate the clinical course Clin Exp Rheumatol 39 Suppl 132 5 2021 109 117 34251308
28 Wang F Ge J Huang S Zhou C Sun Z Song Y KLF5/LINC00346/miR-148a-3p axis regulates inflammation and endothelial cell injury in atherosclerosis Int J Mol Med 48 2 2021 152 34165154
29 Liu S Yang Y Jiang S Xu H Tang N Lobo A MiR-378a-5p Regulates Proliferation and Migration in Vascular Smooth Muscle Cell by Targeting CDK1 Front Genet 10 2019 22 30838018
30 Yu F Yang J Huang K Pan X Chen B Dong P The Epigenetically-Regulated microRNA-378a Targets TGF-β2 in TGF-β1-Treated Hepatic Stellate Cells Cell Physiol Biochem 40 1–2 2016 183 194 27855367
31 Su B Wang X Sun Y Long M Zheng J Wu W miR-30e-3p Promotes Cardiomyocyte Autophagy and Inhibits Apoptosis via Regulating Egr-1 during Ischemia/Hypoxia BioMed Res Int 2020 2020 7231243
32 Wang XT Wu XD Lu YX Sun YH Zhu HH Liang JB Potential Involvement of MiR-30e-3p in Myocardial Injury Induced by Coronary Microembolization via Autophagy Activation Cell Physiol Biochem 44 5 2017 1995 2004 29237156
33 Meng S Hu Y Zhu J Feng T Quan X. miR-30c-5p acts as a therapeutic target for ameliorating myocardial ischemia-reperfusion injury Am J Transl Res 13 4 2021 2198 2212 34017383
34 Wu H Liu T Hou H Knockdown of LINC00657 inhibits ox-LDL-induced endothelial cell injury by regulating miR-30c-5p/Wnt7b/β-catenin Mol Cell Biochem 472 1–2 2020 145 155 32577947
35 Qiao P Zhu J Lu X Jin Y Wang Y Shan Q miR-140-3p suppresses the proliferation and migration of macrophages Genet Mol Biol 45 2 2022 e20210160
