Genome-wide expression analysis of intra- and extraarticular connective tissue

J Orthop Res. 2009 Apr;27(4):427-34. doi: 10.1002/jor.20774.

Abstract

In comparison to extraarticular ligaments and tendons, the intraarticular ligaments such as the anterior and posterior cruciates exhibit different biochemical, biomechanical, and viscoelastic properties and most importantly, differential abilities to heal after surgical repair. Little is known about the underlying basis for these differences, in large measure due to the paucity of molecular markers distinguishing different classes of tendons and ligaments. To date, there has been no systematic analysis of gene expression differences between different types of connective tissues. We used Affymetrix expression arrays to analyze the differences in gene expression levels between the anterior cruciate, posterior cruciate, and medial collateral ligaments, the patellar and Achilles tendons and the synovium. We have identified five clusters of gene cohorts displaying similar expression patterns. These clusters group into three categories including: (1) genes that are strongly expressed in all connective tissues compared to the synovium control tissue; (2) genes that distinguish intraarticular connective tissues from extraarticular connective tissues; and (3) a group of genes expressed in common by the patellar tendon and the synovium. Our analysis identifies a new marker of tendons and ligaments (fibin2), demonstrates molecular diversity between subtypes of tendons and ligaments, and indicates that the primary molecular subdivision among dense regular connective tissues is intra- versus extraarticular rather than ligament versus tendon.

Publication types

  • Research Support, N.I.H., Extramural

MeSH terms

  • Animals
  • Biomarkers
  • Connective Tissue / metabolism*
  • Embryo, Mammalian / metabolism
  • Gene Expression Profiling*
  • In Situ Hybridization
  • Ligaments / metabolism*
  • Swine
  • Synovial Membrane / metabolism*
  • Tendons / metabolism*

Substances

  • Biomarkers