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Longitudinal Blood Transcriptomic Changes Predict Lung Function Decline in patients with Idiopathic Pulmonary Fibrosis

ABSTRACT: Rationale: Molecular markers of disease progression in idiopathic pulmonary fibrosis are needed. Objective: Derive and validate a blood transcriptomic predictor of forced vital capacity (FVC) decline. Methods: A training cohort (n=74) of IPF patients was stratified according to the presence of progressive disease, defined as ≥10% relative decline in FVC over 12 months. Baseline to 4-month within-patient changes in gene expression were correlated with categorical FVC decline. Genes predictive of FVC decline were identified by two-group comparison with false discovery rate <5% followed by logistic LASSO regression and 10-Fold Cross-Validation for gene list prioritization. Independent validation cohorts with differing transcriptome assay platforms and blood transcriptome sampling times from UChicago (n=27), UPMC (n=35), and Imperial (n=24) underwent receiver operating characteristic with area under the curve (AUC) analyses for validation. Results: A longitudinally-derived FVC-gene predictor accurately discriminated most patients with stable and progressive IPF across four independent IPF cohorts with variable transcriptomic assay platforms and sampling times. The FVC-gene predictorand demonstrated sensitivity and specificity of 74.3% and 82.4% in the combined replication cohort. The likelihood ratio, LR+ and LR- were 4.11 and 0.32, respectively. TGF-beta was the highest-ranking canonical pathway by Gene Set Enrichment Analysis. An approach using longitudinal gene expression changes approach dramatically reduced within-group variation compared to cross-sectional expression for improved prediction modeling. Conclusions: This novel FVC-gene predictor developed from short-term longitudinal gene expression changes successfully discriminates most patients with high likelihood of one-year 10% FVC decline. This tool may better reflect disease activity and prove useful for predictive enrichment of clinical trial populations.

ORGANISM(S): Homo sapiens

PROVIDER: GSE133298 | GEO | 2019/09/30

REPOSITORIES: GEO

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Project description:The Rationale: Molecular markers of disease activity that are predictive of forced vital capacity (FVC) progression in idiopathic pulmonary fibrosis are needed. Objectives: Develop a predictor using longitudinal within-patient gene expression differences (ΔGE) in peripheral blood mononuclear cells (PBMC) to predict of FVC progression. Methods: Patients in the training cohort (n=74) experiencing ≥10% relative reduction in FVC% of predicted over 12 months were categorized as progressors in contrast to the remaining stable patients. Baseline to 4-month within-patient ΔGE were correlated with FVC status. FVC-predictor genes were prioritized by two-group comparison with FDR<5%, logistic LASSO regression with p<0.05, and 10-Fold Cross-Validation with ≥50% support. Receiver operating characteristic with area under the curve (AUC) analyses were conducted in training subsets and independent validation cohorts from UChicago (n=27), UPMC (n=35), and Imperial (n=24) where different transcriptome assay platforms and varying transcriptome sampling times were used to derive ΔGE. Results: Intra-subject Compared to cross-sectional analysis of baseline GE, our longitudinal ΔGE variation approach demonstratedlargely reduced within-group sample variation and increased statistic power fin progressor and stable groups for prediction model development. A 25-gene FVC-predictor separated “progressors” from “stable” by Principal Component Analysis in the training and subsets of the training cohort. The resulting FVC-predictor consistently demonstrated high discriminatory performance independent of transcriptome assay platforms and varying sampling times in validation cohorts (AUC= 0.77-0.80). TGF beta was the highest-ranking canonical pathway by Gene Set Enrichment Analysis. Conclusions: Our novel short-term longitudinal within-patient ΔGE approach identified a FVC-predictor which may reflect disease activity and prove to be a reliable biomarker predictive of future FVC decline.