A pilot study to identify blood-based markers associated with response to treatment with Vedolizumab in patients with Inflammatory Bowel Disease

Abstract

The inflammatory bowel diseases (IBD) known as Crohn's disease (CD) and ulcerative colitis (UC) are chronic inflammatory diseases of the gastrointestinal tract believed to arise because of an imbalance between the epithelial, immune and microbial systems. It has been shown that biological differences (genetic, epigenetic, microbial, environmental, etc.) exist between patients with IBD, with multiple risk factors been associated with disease susceptibility and IBD-related phenotypes (e.g. disease location). It is also known that there is heterogeneity in terms of response to therapy in patients with IBD, including to biological therapies that target very specific biological pathways (e.g. TNF-alpha signaling, IL-23R signaling, immune cell trafficking, etc.). It is hypothesized that the better the match between the biology targeted by these advanced therapies and the predominant disease-associated pathways at play in each patient will favor a beneficial response. The aim of this pilot study was to identify potential biological differences associated with differential treatment response to the anti α4β7 integrin therapy known as Vedolizumab. Our approach was to measure a broad range of analytes in the serum of patients prior to initiation of therapy and at the first clinical assessment visit, to identify potential markers of biological differences between patients at baseline and to see which biomarkers are most affected by treatment in responders. Our focus on early clinical response was to study the most proximal effects of therapy and to minimize confounders such as loss of response that occurs further distal to treatment initiation. Specifically, we performed targeted analyses of >150 proteins and metabolites, and untargeted analyses of >1100 lipid entities, in serum samples from 92 IBD patients (42 CD, 50 UC) immediately prior to initiation of therapy with vedolizumab (baseline samples) and at their first clinical assessment (14-week samples). We found lower levels of SDF-1a, but higher levels of PDGF-ββ, lactate, lysine, phenylalanine, branched chain amino acids, alanine, short/medium chain acylcarnitines, and triglycerides containing myristic acid in baseline serum samples of responders as compared to non-responders. We also observed an increase in serum levels of CXCL9 and citrate, as well as a decrease in IL-10, between baseline and week 14 samples. In addition, we observed that a group of metabolites and protein analytes was strongly associated with both treatment response and BMI status, although BMI status was not associated with treatment response.

Keywords: biomarkers; crohn’s disease; treatment response; ulcerative colitis; vedolizumab.

Figure 1.. Targeted serum protein analyte levels associated with response to Vedolizumab treatment.

Responders to vedolizumab treatment, had higher baseline serum levels of PDGFßß than non-responders (A). In contrast, responders had lower serum levels of SDF-1a at baseline as compared to non-responders (B). In responders, CXCL9/MIG levels increased 61% (FC=1.61) between baseline and week 14, whereas there was a 66% decrease (FC=0.44) in non-responders (C). In contrast, serum levels of IL-10 decreased 15% (FC=0.85) in responders, with a 27% increase (FC=1.27) in non-responders (D). Filled symbols are for individuals where samples were only available at baseline. All plots shown are for “UC”. See also Table S2.

Figure 2.. Targeted serum metabolite levels associated with response to Vedolizumab treatment.

A selected set of analytes that were found to be associated with response at 14 weeks are presented. Elevated baseline levels of the amino acid lysine (A) and the organic acid lactate (B) were associated with response to treatment in patients with UC (P=2.1×10⁻³ and P=1.31×10⁻³, respectively). We also observed that ~2-fold increase in serum levels of the organic acid citrate was associated with response in patients with CD (C). Baseline serum levels of multiple acyl carnitines, including AC 3:0 were also associated (P=2.9×10⁻³) with response (D). Filled symbols are for individuals where samples were only available at baseline. All plots shown are for “UC”, except for citrate (C), where the plot is shown for “CD”. See also Table S3.

Figure 3.. Untargeted serum LC-MS-based lipidomic analyses.

We identified 107 lipid features that were significantly (P<0.05) associated to response (A). Colors in the volcano plot represent the 18 clusters of metabolites identified by WGCNA. The first component (PC1) from the PCA of the 1111 lipid features was significantly associated (P=0.017) with response (B). This PC1 was not only associated with response to therapy but was also associated with BMI (P=5.1×10⁻⁵) (C); dotted lines represent SE of loess fit. Importantly, we did not detect any significant association between BMI and response. The PCA loadings value for each lipid feature was plotted, illustrating that PC1 is primarily driven by the “blue” WGCNA cluster, which is also associated to response (P=5.8×10⁻³) (D). We also found an opposite impact for features from another module (named turquoise), which was not significantly associated to response to therapy (P=0.44). See also Table S4 and S5.