Blood transcriptomics predicts progression of pulmonary fibrosis and associated natural killer cells

Yong Huang, Justin M. Oldham, Shwu Fan Ma, Avraham Unterman, Shu Yi Liao, Andrew J. Barros, Catherine A. Bonham, John S. Kim, Rekha Vij, Ayodeji Adegunsoye, Mary E. Strek, Philip L. Molyneaux, Toby M. Maher, Jose D. Herazo-Maya, Naftali Kaminski, Bethany B. Moore, Fernando J. Martinez, Imre Noth

Research output: Contribution to journalArticlepeer-review

2 Scopus citations


compositions from bulk peripheral blood mononuclear RNA-sequencing data that were associated with FVC decline. Measurements and Main Results: The longitudinal model reduced gene-expression variations within stable and progressor groups, resulting in increased statistical power when compared with a cross-sectional model. The FVC predictor for progression anticipated patients with future FVC decline with 78% sensitivity and 86% specificity across independent IPF cohorts. Pattern recognition receptor pathways and mTOR pathways were downregulated and upregulated, respectively. Cellular deconvolution using single-cell RNA-sequencing data identified natural killer cells as significantly correlated with progression. Conclusions: Serial transcriptomic change predicts future FVC decline. An analysis of cell types involved in the progressor signature supports the novel involvement of natural killer cells in IPF progression.

Rationale: Disease activity in idiopathic pulmonary fibrosis (IPF) remains highly variable, poorly understood, and difficult to predict. Objectives: To identify a predictor using short-term longitudinal changes in gene expression that forecasts future FVC decline and to characterize involved pathways and cell types. Methods: Seventy-four patients from COMET (Correlating Outcomes with Biochemical Markers to Estimate Time-Progression in IPF) cohort were dichotomized as progressors (>10% FVC decline) or stable. Blood gene-expression changes within individuals were calculated between baseline and 4 months and regressed with future FVC status, allowing determination of expression variations, sample size, and statistical power. Pathway analyses were conducted to predict downstream effects and identify new targets. An FVC predictor for progression was constructed in COMET and validated using independent cohorts. Peripheral blood mononuclear single-cell RNA-sequencing data from healthy control subjects were used as references to characterize cell type.

Original languageEnglish (US)
Pages (from-to)197-208
Number of pages12
JournalAmerican journal of respiratory and critical care medicine
Issue number2
StatePublished - Jul 15 2021


  • Cell type composition deconvolution
  • Idiopathic pulmonary fibrosis
  • Longitudinal changes of blood gene expression
  • Multigene predictor for progression
  • Relative decline of FVC

ASJC Scopus subject areas

  • Pulmonary and Respiratory Medicine
  • Critical Care and Intensive Care Medicine


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