Since fibrotic disorders are often associated with common syndromes such as chronic inflammation, the goal of our research was to observe foundational gene and network perturbations in multiple types of organ-based fibrosis. The bioinformatic analysis of microarray datasets publicly available for lung, heart, liver and kidney fibrosis has provided an opportunity to investigate the hypothesis that there are foundational molecular mechanisms for all types of organ-based fibrosis. This approach is vital to understanding the core genes involved in fibrosis that mark potential targets for therapy.
The results paint a picture of the development of fibrosis characterized by a core set of genes and molecular pathways. ~17,000 genes were identified as being expressed in at least one dataset with p < 0.05, but only 0.52% of these genes (83 genes up-regulated and 7 genes down-regulated) were significantly differentially expressed across these datasets and were used for further analysis.
Numerous observations indicate that fibrosis, aging and abnormal wound healing may be linked, as both may represent loss of cellular reserve pathways47
. This would explain the abnormal expression of genes implicated in stem cells biology, wound repair and epithelial damage beside the known “myofibroblasts” genes.
To understand the function of these core genes, we used two different programs to analyze the genes and identify their biological and molecular functions. First, IPA software provided the top biological functions and revealed that dermatological diseases as the most disorder that aligned the most significant fit for genes found differentially expressed at p < 10−16. Other relevant functions identified by this approach included inflammatory disease, connective tissue disorders, genetic disorder, and respiratory and cardiac disease, all with p-values < 10−7. IPA then generated networks using the list of genes as “seed” for these networks, with the activity of these networks scored by the mutual information algorithm and confirmed by subjecting each network to a test of significance against a random simulation of mutual information. This aided in identifying which processes were most perturbed by fibrosis. The network deemed the most active in the greatest number of networks (Network 1) and the network most active overall with the highest average mutual information score (Network 2) are involved in critical cellular, immune and matrix functions. The genes and molecules of Network 1 play a key role in connective tissue disorders. Network 2 is important in genetic, skeletal and muscular disorders through several HLA and MHC genes involved in antigen presentation and recognition in immune system response. Secondly, DAVID analysis of the selected genes identified molecular functions of these genes that are in line with the biological functions of their networks and the pathogenesis of fibrosis. Network 1 contained genes important in cell-matrix interactions like integrins are significantly dysregulated per our analysis of the microarray datasets and are potentially play important roles in fibrosis.
In addition, there were many genes with p < 0.05 that were expressed in 5 or more datasets, but had mean fold-changes of smaller magnitude than 1.5 (data not shown). These genes are members of pathways not directly involved in fibrosis, and represent other potential targets. The top biological functions of these networks were involved in hematopoiesis, tissue morphology, cell cycle and death, and may indicate the important influence of stem cells, developmental pathways and repair on organ fibrosis. These functions has p values ranging from 10−5 to 10−2, less significant that the functions of the differentially expressed genes.
Our analysis revealed several genes previously unknown for fibrosis and widely up-regulated in multi-organ fibrosis: WIPF1 (the highest expression, 8 microarrys), ITGBL1 (Integrin, beta-like 1 (with EGF-like repeat domains)
) involved in inflammation49
, EPHA3 (EPH receptor A3
) in mediating developmental processes and homing of hematopoietic cells50
, GRN (Granulin
) in epithelial development, tissue remodeling and wound healing52
. Most of the common down-regulated genes present in our analysis are novel for organ fibrosis: MT1M (Metallothionein 1M
) linked to progressive degeneration of motoneurons in sporadic amyotrophic lateral sclerosis54, FZD5 (Frizzled family receptor 5
) which is part of WNT signaling and ST3GAL6 (ST3 beta-galactoside alpha-2,3-sialyltransferase 6
) important for stem cell development and regeneration55
, SLC1A1 (Solute carrier family 1 (neuronal/epithelial high affinity glutamate transporter, system Xag), member 1
), a major epithelial transporter of glutamate and aspartate57
. Chronic inflammation, extracellular matrix remodeling and epithelial development as part of abnormal wound healing involved in fibrosis are well represented in our analysis by up-regulated genes like LUM (Lumican
, GPNMB (Glycoprotein (transmembrane) nmb59
) or genes downregulated: AQP3 (Aquaporin 3 (Gill blood group)
and IL6R (Interleukin 6 receptor
. It was interesting to see that our analysis has identified a set of well known genes for fibrosis such as chemokine CXCR4 ((C-X-C motif) receptor 4
), SDF1/CXCL12 (Chemokine (C-X-C motif) ligand 12
), metalloproteinases (MMP7, MMP2, at the level of multi-organ fibrosis. In addition, several genes from our analysis have been previously described in gene signatures for organ fibrosis. 14 genes from our list are present in the molecular Banff signature for acute kidney transplant rejection20
. In another fibrosis study, two genes from our list, MMP2 and COL3A1, were found in fibrotic heart, kidney, lung and pancreas tissues, while ADAM28 was found only in lung tissues21
Our analysis indicates that besides regular fibroblasts-myofibroblast genes, there is a common set of genes abnormally expressed, involved in epithelial development, stem cells regeneration and inflammation. We go beyond the approach of single organ fibrosis to address core genes and molecules involved in fibrosis that are present in multiple organs. While these genes may not be the original disease causing genes whose genetic variations leading to the onset or predisposition of these diseases, they reflect a set of potential commonly changed phenotypes at the gene transcription level which can be experimentally tested and as well as targeted in therapy. Nevertheless, our results are only the beginning, as the genes identified give way to experimental research to confirm the role of the identified genes in multi-organ fibrosis, and identify therapeutic targets to slow or even reverse fibrotic activity.