# GRN and KLRB1 define a shared peripheral-blood transcriptomic signature linking SLE and IPF

## TL;DR

This study identifies GRN and KLRB1 as key genes linking two immune-related diseases, SLE and IPF, using blood transcriptome data and validating findings across multiple patient groups.

## Contribution

The study discovers a shared peripheral-blood transcriptomic signature anchored by GRN and KLRB1, enabling accurate diagnostic models for SLE and IPF with multi-cohort validation.

## Key findings

- GRN and KLRB1 are central to a shared gene signature linking SLE and IPF.
- Diagnostic models using 6 genes for SLE and 4 for IPF achieved high accuracy in discovery and validation cohorts.
- Serum GRN levels were significantly elevated in SLE patients and correlated with disease activity markers.

## Abstract

Systemic lupus erythematosus (SLE) and idiopathic pulmonary fibrosis (IPF) share immune–inflammatory features, yet their convergent peripheral-blood transcriptomic signatures remain incompletely defined. We sought to identify shared blood gene programs linking SLE and IPF, prioritize robust cross-disease markers, and evaluate parsimonious diagnostic models with experimental and external assessments.

Peripheral-blood transcriptomes were analyzed in GEO discovery cohorts (SLE: GSE49454; IPF: GSE33566). Differential expression (limma) and weighted gene co-expression network analysis (WGCNA) were performed separately per disease, and concordant shared signals were integrated to form a shared candidate pool. Consensus feature selection combined LASSO logistic regression, nested cross-validated SVM–RFE, and random forest to derive parsimonious gene panels for SLE and IPF. Logistic-regression models were trained in discovery cohorts and externally validated in independent cohorts (SLE: GSE65391, GSE72509; IPF: baseline samples from longitudinal GSE93606). Experimental validation was conducted in an independent hospital cohort (60 SLE, 30 healthy controls) using PBMC RT–qPCR and serum GRN ELISA, with correlation and covariate-adjusted association analyses. Fixed models were additionally applied without refitting to non-target inflammatory cohorts (RA: GSE93272; ICU sepsis/non-infectious critical illness: GSE134347).

Discovery analyses identified 389 SLE and 248 IPF DEGs and yielded 43 concordantly regulated shared DEGs; WGCNA identified 43 shared module genes, producing a non-redundant shared candidate pool of 78 genes enriched for B-cell and myeloid programs. Consensus selection generated a 6-gene SLE panel (EIF2AK2, GRN, ASGR2, KLRB1, LGALS9, KLF13) and a 4-gene IPF panel (GRN, ARG1, KLRB1, FCMR). The SLE model achieved AUC 0.996 in discovery and validated at AUC 0.888 (GSE65391) and 0.761 (GSE72509); the IPF model achieved AUC 0.906 in discovery and 0.722 in baseline validation. In the hospital cohort, RT–qPCR confirmed dysregulation of the six-gene panel, and serum GRN was markedly elevated in SLE (median [IQR] 43.58 [38.44–54.42] vs. 14.26 [12.79–15.26] ng/mL). Within SLE, serum GRN correlated with SLEDAI and inversely with C3/C4 and WBC; after covariate adjustment, associations with WBC, ESR, C3, and C4 remained significant, whereas associations with hs-CRP and SLEDAI were attenuated. In non-target cohorts, the SLE model showed moderate discrimination for RA (AUC 0.73) but limited discrimination for ICU sepsis (AUC 0.64) and none for non-infectious critical illness (AUC 0.50), while the IPF model showed minimal discrimination for RA (AUC 0.51) but high discrimination for ICU groups (AUC 0.99 and 0.96).

GRN and KLRB1 anchor a shared peripheral-blood transcriptomic signature linking SLE and IPF, enabling parsimonious diagnostic models with multi-cohort validation and clinical experimental support. External in silico applications to other inflammatory contexts indicate context-dependent model behavior, underscoring the importance of cohort-appropriate interpretation and validation.