Laboratory information of the fatal and control groups^*.

<p>*WBC = white cell count; APTT = activated partial thromboplastin time; PT = prothrombin time; ALT = serum alanine aminotransferase; AST = serum aspartate aminotransferase; n/N = no. of patients/no. of patients with data available.</p>†<p>Data detected from specimen(s) sampled at patient's arrival at the hospital.</p>‡<p>Pre-fatal laboratory data were data detected from the blood specimens of fatal patients sampled within the immediate 48 h before fatality.</p>§<p>Bandemia referred to presence of band cell (immature white blood cell) in peripheral blood.</p>¶<p>Prolongation of PT was defined as a PT>3 seconds than that of control.</p><p>**Prolongation of APTT was defined an APTT>20% than that of control.</p

Demographic and clinical information of the fatal and control groups^*.

<p>*Data are number of patients (%), unless stated otherwise. DSS = Dengue shock syndrome; COPD = chronic obstructive pulmonary disease; GI = gastrointestinal; n/N = no. of patients/no. of patients with data available.</p>†<p>An individual patient might have more than one underlying disease/condition.</p>‡<p>One patient with lung cancer found in the fatal group; 2 patients with breast cancer and 1 with esophagus cancer found in the control group,.</p>§<p>One patient with hypovolemia had a concurrent <i>Enterococcus faecalis</i> bacteremia.</p>¶<p>Blood culture was available in 8 patients; one of them experienced <i>Klebsiella pneumoniae</i> meningitis and the other primary <i>E. faecalis</i> bacteremia, and shock was found in both.</p><p>**The patient had primary <i>Rosemonas</i> bacteremia.</p>††<p>Primary <i>K. pneumoniae</i> bacteremia was found in 1 patient the fatal group, and in 2 patients in the control group.</p>‡‡<p>Three patients concurrently had pulmonary edema.</p>§§<p>One lung cancer patient developed pulmonary edema in day 16 of his hospitalization.</p>¶¶<p>An individual patient might have more than one symptom and/or sign.</p><p>***One originally febrile patient developed hypothermia during hospital stay.</p>†††<p>Three (75%) patients experienced massive GI bleeding.</p

Gene-Gene Associations with the Susceptibility of Kawasaki Disease and Coronary Artery Lesions

<div><p>Kawasaki disease (KD) is a systemic vasculitis primarily affecting children < 5 years old. Genes significantly associated with KD mostly involve cardiovascular, immune, and inflammatory responses. Recent studies have observed stronger associations for KD risk with multiple genes compared to individual genes. Therefore, we investigated whether gene combinations influenced KD susceptibility or coronary artery lesion (CAL) formation. We examined 384 single-nucleotide polymorphisms (SNPs) for 159 immune-related candidate genes in DNA samples from KD patients with CAL (n = 73), KD patients without CAL (n = 153), and cohort controls (n = 575). Individual SNPs were first assessed by univariate analysis (UVA) and multivariate analysis (MVA). We used multifactor dimensionality reduction (MDR) to examine individual SNPs in one-, two-, and three-locus best fit models. UVA identified 53 individual SNPs that were significantly associated with KD risk or CAL formation (<i>p</i> < 0.10), while 35 individual SNPs were significantly associated using MVA (<i>p</i> ≤ 0.05). Significant associations in MDR analysis were only observed for the two-locus models after permutation testing (<i>p</i> ≤ 0.05). In logistic regression, combined possession of <i>PDE2A</i> (rs341058) and <i>CYFIP2</i> (rs767007) significantly increased KD susceptibility (OR = 3.54; <i>p</i> = 4.14 x 10⁻⁷), while combinations of <i>LOC100133214</i> (rs2517892) and <i>IL2RA</i> (rs3118470) significantly increased the risk of CAL in KD patients (OR = 5.35; <i>p</i> = 7.46 x 10⁻⁵). Our results suggest varying gene-gene associations respectively predispose individuals to KD risk or its complications of CAL.</p></div

Recombinant PGE₂ prevention of CD40L expression on CD4+ T cells.

<p>PGE₂ significantly hinders CD40L expression on CD4<b>+</b>T cells in a dose-dependent manner after 24 hours of treatment. *p < 0.05 compared to the average. Data are presented as mean ± standard error. All tests were separately carried out three times each (N = 4).</p

A comparison of plasma PGE₂ levels using ELISA between patients with KD without (n = 100) and with (n = 44) coronary arterial lesions (CAL) prior to receiving IVIG treatment and after IVIG treatment.

<p>*p < 0.05. Data are presented as mean ± standard error.</p

Best fit results using multifactor dimensionality reduction analysis of one-, two-, and three-locus models for CAL formation in KD patients.

<p>^a Average testing balanced accuracy is the accuracy of classifications for cases and controls in the testing dataset (one-twentieth of the data) calculated as (Sensitivity+Specificity)/2.</p><p>^b Average cross validation consistency is the number of times the model was selected as the best model after 20 cross-validation runs.</p><p>^c Significance of accuracy (empirical p-value based on 10,000 permutations).</p><p>** p-value ≤ 0.05</p><p>Best fit results using multifactor dimensionality reduction analysis of one-, two-, and three-locus models for CAL formation in KD patients.</p

A comparison of plasma PGE₂ levels using ELISA between KD patients that responded to IVIG treatment (N = 130) and those that were IVIG resistant (N = 14) prior to receiving IVIG treatment and following IVIG treatment.

<p>*p < 0.05. Data are presented as mean ± standard error.</p

<i>LOC100133214</i> (rs2517892) and <i>IL2RA</i> (rs3118470) gene-gene interaction in a 2-way mode of MDR analysis.

<p>The interaction of <i>LOC100133214</i> and <i>IL2RA</i> was significantly associated with a higher risk of CAL formation using logistic regression of our MDR results from KD patients with CAL (n = 73) and KD patients without CAL (n = 153), with an odds ratio of 5.35 (95% CI: 2.33–12.25) and a <i>p</i>-value of 7.46 x 10⁻⁵. (A) MDR classified the nine interactive items into high- or low-risk CAL groups, which were significantly different in our further analysis using the Chi-square test (<i>p</i> = 3.36 x 10⁻⁶). (B).</p

Multivariate analysis of 345 SNPs associated with KD susceptibility in patients and cohort controls (<i>p</i> ≤ 0.05).

<p>Multivariate analysis of 345 SNPs associated with KD susceptibility in patients and cohort controls (<i>p</i> ≤ 0.05).</p

Comparison cytokines levels between KD patients with high-risk genotypes and low-risk genotypes.

<p>KD patients possessing the high-risk (KD risk: 1) <i>PDE2A</i> (rs341058) and <i>CYFIP2</i> (rs767007) genotypes of KD susceptibility (n = 49) presented with significantly lower plasma levels of TGF-β1 (9489 ± 1605 vs. 16133 ± 3015) compared to KD patients in the low-risk group (KD risk: 0, n = 24), with an odds ratio of 0.59 (<i>p</i> = 0.036). (A) KD patients possessing the high-risk <i>LOC100133214</i> (rs2517892) and <i>IL2RA</i> (rs3118470) genotypes of CAL formation (CAL risk: 1, n = 35) presented with significantly elevated plasma levels of IL-2 (14.1 ± 1.6 vs. 9.6 ± 1.2) compared to KD patients in the low-risk group (CAL risk: 0, n = 38), with an odds ratio of 1.47 (<i>p</i> = 0.028). (B) KD patients possessing the high-risk <i>LOC100133214</i> (rs2517892) and <i>IL2RA</i> (rs3118470) genotypes of CAL formation (CAL risk: 1, n = 35) presented with significantly elevated plasma levels of IL-6 (51.0 ± 14.3 vs. 18.4 ± 3.7) compared to KD patients in the low-risk group (CAL risk: 0, n = 38), with an odds ratio of 2.77 (<i>p</i> = 0.033). (C) KD patients possessing the high-risk <i>LOC100133214</i> (rs2517892) and <i>IL2RA</i> (rs3118470) genotypes of CAL formation (CAL risk: 1, n = 35) presented with significantly elevated plasma levels of IFN-γ (119.2 ± 15.2 vs. 81.8 ± 10.1) compared to KD patients in the low-risk group (CAL risk: 0, n = 38), with an odds ratio of 1.46 (<i>p</i> = 0.041). (D).</p