Renal interstitial fibrosis: mechanisms and evaluation

Curr Opin Nephrol Hypertens. 2012 May;21(3):289-300. doi: 10.1097/MNH.0b013e3283521cfa.


Purpose of review: Tubulointerstitial injury in the kidney is complex, involving a number of independent and overlapping cellular and molecular pathways, with renal interstitial fibrosis and tubular atrophy (IFTA) as the final common pathway. Furthermore, there are multiple ways to assess IFTA.

Recent findings: Cells involved include tubular epithelial cells, fibroblasts, fibrocytes, myofibroblasts, monocyte/macrophages, and mast cells with complex and still incompletely characterized cell-molecular interactions. Molecular mediators involved are numerous and involve pathways such as transforming growth factor (TGF)-β, bone morphogenic protein (BMP), platelet-derived growth factor (PDGF), and hepatocyte growth factor (HGF). Recent genomic approaches have shed insight into some of these cellular and molecular pathways. Pathologic evaluation of IFTA is central in assessing the severity of chronic disease; however, there are a variety of methods used to assess IFTA. Most assessment of IFTA relies on pathologist assessment of special stains such as trichrome, Sirius Red, and collagen III immunohistochemistry. Visual pathologist assessment can be prone to intra and interobserver variability, but some methods employ computerized morphometery, without a clear consensus as to the best method.

Summary: IFTA results from on orchestration of cell types and molecular pathways. Opinions vary on the optimal qualitative and quantitative assessment of IFTA.

Publication types

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

MeSH terms

  • Animals
  • Atrophy
  • Biomarkers / metabolism
  • Epithelial-Mesenchymal Transition
  • Fibrosis
  • Genetic Predisposition to Disease
  • Humans
  • Kidney Diseases* / diagnosis
  • Kidney Diseases* / etiology
  • Kidney Diseases* / genetics
  • Kidney Diseases* / metabolism
  • Kidney Tubules* / metabolism
  • Kidney Tubules* / pathology
  • Phenotype
  • Predictive Value of Tests
  • Prognosis
  • Severity of Illness Index
  • Signal Transduction


  • Biomarkers