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Updated: May 29, 2026

Imaging Features of Systemic Sclerosis-Associated Interstitial Lung Disease
Published on: June 16, 2020
Local genetic correlations between systemic sclerosis and common cancer types
Karina Patasova1,2,3, Weng Ian Che4, Helga Westerlind5
1Center for Molecular Medicine, Department of Medicine Solna, Karolinska Institutet, Stockholm, Sweden.
Introduction:
The incidence of cancer, encompassing all major types, is significantly higher among patients with systemic sclerosis (SSc) compared to the general population. While previous studies have assessed the global genetic relationships between SSc and various cancers and found no evidence of causality or pleiotropy, these methods average effects across the genome and thus ignore potential opposing directional effects at different loci, thereby missing locus-specific associations. To address this gap, we assessed fine-scaled genetic overlap between SSc and commonly associated cancers, namely breast and lung cancers, as well as hematologic malignancies, by applying local genetic correlation analyses.
Methods:
We assessed the genetic relationship between SSc and cancers that frequently co-occur with SSc: breast cancer and its' four main molecular subtypes: HER2-enriched-like, luminal A and B-like, and triple-negative breast cancers, as well as lung cancer, lymphocytic leukemia, and non-Hodgkin's lymphoma. Published genome-wide association study statistics were obtained from the GWAS catalog and The Breast Cancer Association Consortium, and data were standardized, quality control filtered, and preprocessed. Global and local genetic correlations were evaluated using linkage disequilibrium score regression and Local Analysis of [co]Variant Annotation software. Gene-based cross-trait meta-analysis, colocalization and fine-mapping approaches were used to assess evidence of pleiotropy across regions identified by local genetic correlation analyses. We implemented visualization of the local genetic correlations and functional enrichment analyses of pleiotropic genes from these local correlations.
Results:
We did not detect any significant global genetic correlation between SSc and the analyzed cancer subtypes. However, we identified 23 significant local bivariate correlations; 21 were with different molecular subtypes of breast cancer. However, only the locus shared between SSc and lung cancer showed strong evidence of pleiotropy. Genes within loci shared with lung cancer were involved in cell communication and signaling, extracellular matrix remodelling and skin morphogenesis.
Conclusions:
We report a pleiotropic locus between SSc and lung cancer, illuminating potential pathobiological mechanisms and providing gene candidates for future research.
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