Cytokine Signatures Differentiate Systemic Sclerosis Patients at High Versus Low Risk for Pulmonary Arterial Hypertension

Kathleen D. Kolstad; Avani Khatri; Michele Donato; Sarah E. Chang; Shufeng Li; Virginia D. Steen; Paul J. Utz; Purvesh Khatri; Lorinda Chung

Disclosures

Arthritis Res Ther. 2022;24(39) 

In This Article

Results

Baseline Characteristics Patient Population

Baseline characteristics of each patient group are described in Table 1. The majority of patients in all groups were women. The majority of patients in the PAH and high-risk PAH groups, but only a third of patients in the low-risk group, were Caucasian. Fifty percent of low-risk SSc group had limited disease and 76% and 71% of high-risk and PAH patients had limited disease, respectively. Anti-centromere (25%) and isolated nucleolar (25%) autoantibody subtypes were most common in the PAH group, while anti-centromere (21%) and Scl-70 (21%) were most common in the high-risk PAH group, and anti-centromere (60%) was most common in the low-risk group. Disease duration was similar among all SSc groups. After 3 years of follow-up, no patient in the low-risk SSc patient group had been diagnosed with PAH. The median and range % predicted FVC, % predicted DLCO, and RVSP values at baseline for the low-risk SSc group were 96 (84–112), 99 (88–124), and 28mmHg (18–35 mmHg), respectively. At follow up the median and range % predicted FVC, % predicted DLCO, and RVSP values were 90 (74–112), 95 (59–116), and 30 mmHg (20–39mmHg), respectively. The patient who developed an RVSP >35 mmHg passed away from metastatic cancer 3 months after an echocardiogram was performed.

Cytokine Array Results

Two cytokines (sVCAM-1 and PDGF-BB) from the 14-plex cytokine array and 22 from the 65-plex cytokine array were removed from further analysis due to low correlation between technical replicates. Principal component analysis (PCA) was used as dimensionality reduction and visualization technique for exploratory analysis of the data. PCA represents an orthogonal transformation of series of potentially coordinated observations into principal components. Typically, the first two to three principal components explain the majority of the variance in data and are used to visualize data in 2- or 3-dimensions. In our analysis, PCA showed unique clustering for each patient group in both arrays. This finding was particularly evident in the 14-plex cytokine array data (Figure 1A and Supplementary Figure 1). Data was analyzed using analysis of variance (ANOVA) and Tukey's honestly significant difference (HSD) test for post hoc comparisons.[8] The heatmaps show the magnitude of the fold changes between conditions and their statistical significance for each comparison. For the 14-plex array data, there was very little difference in cytokine expression comparing high-risk and PAH patient groups; however, these groups had substantially different cytokine profiles compared to low-risk patients and HC patients. In particular, RANTES, IL-12p40, IFN-beta, and IL-1RA were significantly higher in patients with PAH and both high-risk and low-risk patients compared to healthy controls (Figure 2A, B). Importantly, PAI-1, BDNF, sICAM-1, and EGF were significantly higher in the high-risk and PAH groups compared to the low-risk group, were but significantly lower in the low-risk group compared to healthy controls (Figure 2A, B). Leptin and VEGF-D were also significantly higher in the high-risk and PAH groups compared with healthy controls and low-risk patients (Figure 2A, B).

Figure 1.

Principal component analysis plot of 14-plex cytokine array data shows all 182 samples along PC1 and PC2, which represent 43% and 19.4% of the variability, respectively, within the data. PCA plot distinguished different patient groups. Healthy controls and low-risk SSc patients were different from SSc patients with PAH or at high risk of developing PAH. SSc, systemic sclerosis; PAH, pulmonary arterial hypertension

Figure 2.

A Multiple hypotheses corrected p-values for each antigen in every pairwise comparison using Tukey's test. This heatmap shows the magnitude of the fold changes between conditions and their statistical significance for each comparison. The color of each circle represents the fold change between conditions, where red indicates a high fold change, light yellow a low fold change, and blue indicates negative fold change. The size of each circle is proportional to the statistical significance of the difference between conditions, where larger circles represent more significant differences. A white cell represents antigens that were not showing a statistically significant difference between conditions based on the FDR threshold of 5%. B Boxplots of expression of each significant antigen in each of the four groups. Boxes represent inter-quartiles (25% and 75% percentile), and whiskers represent maximum and minimum values. SSc, systemic sclerosis; PAH, pulmonary arterial hypertension

Principal component analysis of the 65-plex array showed the most prominent differences in cytokine profiles when comparing the high-risk and incident PAH patients with HC patients (Supplementary Figure 1). Similar to the 14-plex array results, the PAH and high-risk PAH patient groups had very similar cytokine expression profiles. Each of the 43 cytokines was significantly higher in patients with PAH or high-risk patients compared to HCs, whereas 27 of those were significantly higher in low-risk patients compared to healthy controls (Supplementary Figure 2A-B). Importantly, IL3, MCSF, ENA78, Eotaxin3, and TNFRII were significantly higher in patients with PAH and high-risk patients compared with low-risk patients. However, there were also multiple cytokines that distinguished all SSc groups from HC patients. (Supplementary Figure 2A-B).

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