Interferon signature in the blood in inflammatory common variable immune deficiency

Abstract

About half of all subjects with common variable immune deficiency (CVID) are afflicted with inflammatory complications including hematologic autoimmunity, granulomatous infiltrations, interstitial lung disease, lymphoid hyperplasia and/or gastrointestinal inflammatory disease. The pathogenesis of these conditions is poorly understood but singly and in aggregate, these lead to significantly increased (11 fold) morbidity and mortality, not experienced by CVID subjects without these complications. To explore the dysregulated networks in these subjects, we applied whole blood transcriptional profiling to 91 CVID subjects, 47 with inflammatory conditions and 44 without, in comparison to subjects with XLA and healthy controls. As compared to other CVID subjects, males with XLA or healthy controls, the signature of CVID subjects with inflammatory complications was distinguished by a marked up-regulation of IFN responsive genes. Chronic up-regulation of IFN pathways is known to occur in autoimmune disease due to activation of TLRs and other still unclarified cytoplasmic sensors. As subjects with inflammatory complications were also more likely to be lymphopenic, have reduced B cell numbers, and a greater reduction of B, T and plasma cell networks, we suggest that more impaired adaptive immunity in these subjects may lead to chronic activation of innate IFN pathways in response to environmental antigens. The unbiased use of whole blood transcriptome analysis may provides a tool for distinguishing CVID subjects who are at risk for increased morbidity and earlier mortality. As more effective therapeutic options are developed, whole blood transcriptome analyses could also provide an efficient means of monitoring the effects of treatment of the inflammatory phenotype.

Figure 1. Gene expression analysis of CVID blood (training set) compared to healthy controls.

Unsupervised clustering of 9,241 RNA transcripts expressed in whole blood cells selected by Present At least Once (PALO), differentiates CVID patients from healthy controls in the training set.

Figure 2. ANOVA test comparing CVID blood (training set) to healthy controls.

The ANOVA test (FDR 0.05) identifies 2,998 transcripts differentially expressed in whole blood cells of CVID patients with and without inflammatory complications and healthy controls.

Figure 3. Venn diagram representing the number of common and unique transcripts differentially expressed in patients, compared to healthy controls.

Blood from subjects with inflammatory complications contained more upregulated transcripts as compared to those without complications.

Figure 4. Gene expression analysis of CVID blood (test set) compared to healthy controls.

Unsupervised clustering of 11,559 RNA transcripts in whole blood cells, selected by Present At least Once (PALO) differentiates CVID patients from healthy controls in the test set.

Figure 5. ANOVA test (FDR 0.05) comparing CVID blood (test set) healthy controls.

This test identified 1495 transcripts differentially expressed in the blood of CVID patients, identified here with and without inflammatory complications and healthy controls.

Figure 6. Venn diagram representing the number of common and unique transcripts.

Whole blood of subjects with inflammatory complications displayed differentially expressed transcripts as compared to those without such complications or healthy controls.

Figure 7. Modular analysis of differentially expressed transcripts in CVID.

Whole blood modular signatures of CVID subjects in the test set identified significant down regulation of B-cell and T-cell modules and up-regulation of IFN-related modules, preferentially in CVID patients with inflammatory complications. Columns represent the profiles on individual patients and controls, healthy controls and XLA subjects. Spot intensity (red = increased, blue = decreased) indicates transcript abundance within each module as noted.

Figure 8. Statistically significant modules from both training and test sets compared to healthy controls.

Columns are as labeled for subjects with or without complications vs. healthy controls (HC).

Figure 9. IVIg therapy and gene expression analysis.

Eight additional CVID subjects were tested before and 5-7 days after receiving IVIg. Individual transcripts (567) were selected by Welch ANOVA test (MTC: Benjamini and Hochberg, FDR, p-cutoff <0.01) between healthy controls, pre-IVIg and post-IVIg patients.

Figure 10. Production of IFN-γ.

Culture supernatants of PBMCs of CVID subjects with (10) (CVID+) or without inflammatory (10) (CVID-) complications, activated with media alone, added CD3/CD28 beads or PHA, were assessed by ELISA for IFNγ production after 72 hours, and compared to supernatants of similarly treated cells from normal controls.

Figure 11. Production of IFN-α.

For IFN-α production, PBMCs from control subjects (10) and CVID subjects with (+) and without inflammatory (-) complications, were stimulated with increasing amounts of loxoribine. IFN-α in supernatants was assessed by ELISA.