Integration of gene expression data with network-based analysis to identify signaling and metabolic pathways regulated during the development of osteoarthritis

Abstract

Osteoarthritis (OA) is characterized by remodeling and degradation of joint tissues. Microarray studies have led to a better understanding of the molecular changes that occur in tissues affected by conditions such as OA; however, such analyses are limited to the identification of a list of genes with altered transcript expression, usually at a single time point during disease progression. While these lists have identified many novel genes that are altered during the disease process, they are unable to identify perturbed relationships between genes and gene products. In this work, we have integrated a time course gene expression data set with network analysis to gain a better systems level understanding of the early events that occur during the development of OA in a mouse model. The subnetworks that were enriched at one or more of the time points examined (2, 4, 8, and 16 weeks after induction of OA) contained genes from several pathways proposed to be important to the OA process, including the extracellular matrix-receptor interaction and the focal adhesion pathways and the Wnt, Hedgehog and TGF-β signaling pathways. The genes within the subnetworks were most active at the 2 and 4 week time points and included genes not previously studied in the OA process. A unique pathway, riboflavin metabolism, was active at the 4 week time point. These results suggest that the incorporation of network-type analyses along with time series microarray data will lead to advancements in our understanding of complex diseases such as OA at a systems level, and may provide novel insights into the pathways and processes involved in disease pathogenesis.

Wnt5a induces catabolic signaling and matrix metalloproteinase production in human articular chondrocytes

“…We previously found that RNA expression of Wnt5a was increased in the knee joint tissue of DMM mice as OA developed 16 . Similar to our findings, a recent study also reported the presence of Wnt5a protein in articular cartilage of knee OA patients by IHC 13 .…”

“…Moreover, Wnt5a expression was detected at increased levels in osteoarthritic tissues including cartilage, inflamed synovial membrane and acetabular labrum 13–15 . We previously discovered Wnt5a as the most upregulated Wnt family member in a network analysis with time series microarray data from joints of mice with OA induced by destabilization of the medial meniscus (DMM) 16 . However, a role for Wnt5a in human chondrocytes or in cartilage degeneration during development of OA has not been reported.…”

Systems approaches in osteoarthritis: Identifying routes to novel diagnostic and therapeutic strategies

“…Using existing protein‐protein interaction data and an automated sub‐network searching tool (jActiveModules31) Loeser et al, defined a sub‐network associated with genes up‐regulated during the initial 4 weeks after destabilization of the medial meniscus (DMM) in a murine model, including heparin‐binding EGF‐like growth factor (HB‐EGF) 32. Olex et al33 developed this strategy further using time‐course gene expression data from a whole mouse joint model of OA to define perturbed sub‐networks. ECM‐receptor interaction and focal adhesion canonical pathways were enriched across all time‐points.…”

“…A number of contemporary studies have provided useful reference metabolomic and proteomic data from osteophytic cartilage,44 subchondral bone,45 and synovial fluid,46 or considered the role of metabolic pathways derived from transcriptomics data 33, 47. However, our understanding of the homeostatic control of metabolic fluxes in cartilage, bone, and synovial fluid is limited.…”

MOPED 2.5—An Integrated Multi-Omics Resource: Multi-Omics Profiling Expression Database Now Includes Transcriptomics Data

“…Building on the best practices used in different fields, MOPED integrates heterogeneous data into a unified public resource. The integration of multi-omics data can be essential for scientific discovery (Efron and Tibshirani, 2007;Huang, 2014;Huang et al, 2014;Olex et al, 2014), thus by providing a platform for multi-omics data, MOPED can act as a launching point for scientific discoveries.…”