TACKLING ARTHRITIS USING A BIOMECHANICAL AND SYSTEMS BIOLOGY APPROACH

Abstract: 

Arthritis is the leading cause of disability in the developed world affecting one of every six people and results in a economic burden that corresponds to ~2.5% of the GDP. The most common type of arthritis is osteoarthritis (OA), a painful disease characterized by cartilage degeneration. An imbalance of regulatory proteins governs cartilage degeneration and the progression of OA.

In this proposal we build a multidisciplinary team comprised of orthopaedic surgeons, biologists and engineers in order to understand the cellular mechanisms that lead to osteoarthritis and suggest novel therapeutic interventions.

Two different approaches will be combined to correlate signaling networks of chondrocytes with cartilage degeneration: Systems Biology and Biomechanics. The systems biology approach is based on high throughput proteomic and genomic measurements coupled with computational algorithms. Chondrocytes will be studied under 100+ stimuli using gene expression and novel proteomic assays.

The datasets will be analyzed using statistical, machine learning, and optimization algorithms in order to

  • identify novel catabolic players,
  • construct signaling pathways of normal and OA chondrocytes, and
  • identify novel therapeutic interventions.

On the biomechanics front, biphasic computational models and indentation tests will be employed to monitor cartilage degeneration in-vitro and real-time by measuring the Young modulus and permeability of the tissue. This approach will be used to evaluate the in-vitro efficacy of inhibitors to block cartilage deterioration.

Our goal is three fold:

  1. identify novel players of cartilage degeneration,
  2. deliver detailed signaling maps of chondrocytes, and
  3. find inhibitors with proven in-vitro efficacy.

The results will shed a light into possible treatments of osteoarthritis and suggest novel therapeutic interventions.

Project info

Acronym:
TABS
Scientific Coordinator:
Alexopoulos Leonidas
Research Team 2 Leader:
Kollia Panagoula
Research Team 3 Leader:
Dailiana Zoi

Stats

I.D.:
3
Mis:
380168
Duration (months):
45
Budget:
600 000.00
Diavgeia:
ΑΔΑ: Β4139-Ο7Θ

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