Abstract
Background: Severe asthma is a heterogeneous disease, with a real unmet need in clinical and biological phenotyping. By combining clinical and various omics technologies, a phenotypic handprint of this disease can be produced.
Objective: To integrate blood transcriptomics, serum proteomics and urine lipidomics data from 300 adult U-BIOPRED asthma patients in order to define a blood handprint.
Methods: The omics datasets were fused using the Similarity Network Fusion method (Wang et al, Nature methods, 2014). Stable clusters were defined using spectral clustering and characterised using available clinical data.
Results: Five stable clusters were defined. Cluster 1 (C1) was the most severe with the lowest FEV1% predicted, low FEV1/FVC and the highest proportion of patients on OCS. C2 was the mildest while C3, 4 and 5 had similar clinical characteristics. The clusters seemed mainly differentiated by the white blood cells percentages (WBC).
| Variables/Clusters (N) | C1 (53) | C2 (73) | C3 (55) | C4 (60) | C5 (59) | P-value |
|---|---|---|---|---|---|---|
| FEV1 % predicted | 66 ± 23 | 92 ± 20 | 72 ± 24 | 71 ± 24 | 72 ± 20 | 9.3E-10 |
| FEV1/FVC | 0.63 ± 0.15 | 0.74 ± 0.12 | 0.67 ± 0.13 | 0.62 ± 0.14 | 0.64 ± 0.14 | 2.4E-6 |
| Exacerbations past year, Median (IQR) | 2 (1-4) | 1 (0-2) | 1 (0-3) | 2 (1-3) | 2 (0-3) | 3.9E-2 |
| WBCS x10^3/μl | 9.5 ± 2.4 | 5.9 ± 1.3 | 6.4 ± 1.8 | 8.2 ± 2.5 | 7.7 ± 2.2 | 1.7E-20 |
| Blood neutrophils % | 69 ± 12 | 57 ± 8 | 58 ± 9 | 61 ± 12 | 64 ± 10 | 3.7E-10 |
| OCS (Yes/No/NA) | 30/19/4 | 3/31/33 | 8/38/9 | 18/38/4 | 22/33/4 | 6.6E-5 |
Conclusion: Various omics datasets of blood-related samples were successfully combined, defining five stable clusters of asthma patients mainly differentiated by the percentages of WBC. These results may help refining phenotypes of severe asthma.
IMI grant n°115010 (U-BIOPRED).
- Copyright ©ERS 2015
