Defining the optimal interferon-stimulated genes panel to reflect serum interferon-α levels in patients with systemic lupus erythematosus.
12 affiliations
- 1Division of Central Laboratory, Hospital Universitario de Canarias, Tenerife, Spain.
- 2Division of Rheumatology, Hospital Doctor Negrín, Las Palmas de Gran Canaria, Spain.
- 3Division of Rheumatology, Hospital Insular, Las Palmas de Gran Canaria, Spain.
- 4Department of Immunology, Hospital Ramón y Cajal, Madrid, Spain.
- 5Department of Immunology, Hospital Universitario Marqués de Valdecilla, IDIVAL, Santander, Spain.
- 6Department of Medical and Surgical Sciences, CIBER Epidemiología y Salud Pública (CIBERESP), University of Cantabria, Santander, Spain.
- 7Division of Rheumatology, IIS-Fundación Jiménez Díaz, Madrid, Spain.
- 8Division of Rheumatology, IIS-Fundación Jiménez Díaz, Madrid, Spain. [email protected].
- 9Department of Medicine and Psychiatry, University of Cantabria, Santander, Spain. [email protected].
- 10Instituto de Investigaciones Sanitarias de Canarias (IISC), Tenerife, Spain. [email protected].
- 11Department of Internal Medicine, University of La Laguna (ULL), Tenerife, Spain. [email protected].
- 12Division of Rheumatology, Hospital Universitario de Canarias, Tenerife, Santander, Tenerife, Spain. [email protected].
Abstract
Background
The type I interferon-alpha (IFN-α) gene expression signature refers to the analysis of specific IFN-stimulated genes (ISG) as a surrogate measure of IFN-α pathway activity. It is widely used to assess IFN-α activity in patients with systemic lupus erythematosus (SLE), as well as to evaluate treatment response or serve as an index of disease activity. ISGs are often aggregated into a composite score that provides a quantitative measure. However, previous literature has employed differing combinations of ISG, and no clear consensus exists regarding which should be preferentially used. Our study aims to identify the combination of IGS that best correlates with serum IFN-α levels in patients with SLE.Methods
A total of 252 patients with SLE were recruited in this cross-sectional study. IFN-α serum levels were measured using Simoa (Single Molecule Array) technique. Based on prior literature, 72 transcripts previously used in other studies in rheumatic musculoskeletal diseases were selected and analyzed by qPCR using Nanostring® technology. Fifty-one distinct IFN scores were computed using previously reported ISG combinations. Besides, LASSO (Least Absolute Shrinkage and Selection Operator) regression analysis was performed to identify the minimal and most parsimonious combination of ISGs associated with serum IFN-α levels.Results
LASSO analysis identified a 13-ISG combination as the most parsimonious predictor of serum IFN-α levels. However, the IFN score constructed using these 13 genes showed lower correlation with serum IFN-α levels than previously reported IFN scores from the literature. This suggests that statistically derived ISG selection is inferior to mechanistically- or pathophysiologically-informed gene combinations. Three literature-derived ISG combinations-IFI44L IFIT1 RSAD2 IFI27 ISG15 SIGLEC1, IFI27 IFI44 IFI44L RSAD2, and IFI44L IFI44 RSAD2 IFI27 IFI6-demonstrated high IFN-α correlations, statistically indistinguishable from each other but significantly superior to the remaining 48 combinations.Conclusions
This study provides evidence-based recommendations for ISG selection in constructing optimal IFN signatures to accurately predict serum IFN-α levels in SLE patients.
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BibTeX
@article{rodriguezgarcia2026defining,
title = {{Defining the optimal interferon-stimulated genes panel to reflect serum interferon-α levels in patients with systemic lupus erythematosus.}},
author = {Marta Rodríguez-García and Fuensanta Gómez-Bernal and Juan Carlos Quevedo-Abeledo and Beatriz Tejera-Segura and Enrique García-Barrera and Luisa María Villar and Javier Gonzalo Ocejo-Vinyals and Nerea Mota-Pérez and Javier Llorca and Raquel Largo and Miguel Ángel González-Gay and Iván Ferraz-Amaro},
journal = {BMC medicine},
year = {2026},
month = jul,
doi = {10.1186/s12916-026-05102-5},
url = {https://europepmc.org/article/MED/42972592},
note = {CC BY-NC-ND},
}
RIS
TY - JOUR
TI - Defining the optimal interferon-stimulated genes panel to reflect serum interferon-α levels in patients with systemic lupus erythematosus.
AU - Marta Rodríguez-García
AU - Fuensanta Gómez-Bernal
AU - Juan Carlos Quevedo-Abeledo
AU - Beatriz Tejera-Segura
AU - Enrique García-Barrera
AU - Luisa María Villar
AU - Javier Gonzalo Ocejo-Vinyals
AU - Nerea Mota-Pérez
AU - Javier Llorca
AU - Raquel Largo
AU - Miguel Ángel González-Gay
AU - Iván Ferraz-Amaro
PY - 2026
DA - 2026/07/31
JO - BMC medicine
DO - 10.1186/s12916-026-05102-5
UR - https://europepmc.org/article/MED/42972592
AB - Background The type I interferon-alpha (IFN-α) gene expression signature refers to the analysis of specific IFN-stimulated genes (ISG) as a surrogate measure of IFN-α pathway activity. It is widely used to assess IFN-α activity in patients with systemic lupus erythematosus (SLE), as well as to evaluate treatment response or serve as an index of disease activity. ISGs are often aggregated into a composite score that provides a quantitative measure. However, previous literature has employed differing combinations of ISG, and no clear consensus exists regarding which should be preferentially used. Our study aims to identify the combination of IGS that best correlates with serum IFN-α levels in patients with SLE.Methods A total of 252 patients with SLE were recruited in this cross-sectional study. IFN-α serum levels were measured using Simoa (Single Molecule Array) technique. Based on prior literature, 72 transcripts previously used in other studies in rheumatic musculoskeletal diseases were selected and analyzed by qPCR using Nanostring® technology. Fifty-one distinct IFN scores were computed using previously reported ISG combinations. Besides, LASSO (Least Absolute Shrinkage and Selection Operator) regression analysis was performed to identify the minimal and most parsimonious combination of ISGs associated with serum IFN-α levels.Results LASSO analysis identified a 13-ISG combination as the most parsimonious predictor of serum IFN-α levels. However, the IFN score constructed using these 13 genes showed lower correlation with serum IFN-α levels than previously reported IFN scores from the literature. This suggests that statistically derived ISG selection is inferior to mechanistically- or pathophysiologically-informed gene combinations. Three literature-derived ISG combinations-IFI44L IFIT1 RSAD2 IFI27 ISG15 SIGLEC1, IFI27 IFI44 IFI44L RSAD2, and IFI44L IFI44 RSAD2 IFI27 IFI6-demonstrated high IFN-α correlations, statistically indistinguishable from each other but significantly superior to the remaining 48 combinations.Conclusions This study provides evidence-based recommendations for ISG selection in constructing optimal IFN signatures to accurately predict serum IFN-α levels in SLE patients.
SN - 1741-7015
ER -