Treatments for the most prevalent form of arthritis, osteoarthritis (OA), currently are primarily palliative until joints become totally dysfunctional and prosthetic replacement is needed. There are numerous obstacles for developing effective OA therapy. One is the lack of good diagnostic tools for efficiently identifying early stages of the disease and monitoring its progression in small animal models typically used for therapeutic testing. Histopathological evaluation is the traditional assessment for OA, but this requires sacrifice of the animal, uses tedious subjective criteria, may contain sampling error and cannot be used for serial measurements in a single animal. Our overall goal is to establish an innovative method to identify early cartilage damage in OA and to quantitatively assess its progression in vivo. Identification of early OA would permit interventional therapy at the earliest stages of disease when the pathology may be more amenable to intervention. We propose to use monoclonal antibodies (Mab) to native type II collagen (CII) that bind damaged cartilage to identify early subclinical lesions and quantitate disease progression in OA. If successful, this will provide an inexpensive and reproducible method that can be used for diagnosis and to monitor the effects of therapy on OA progression over relatively short to intermediate time periods. We will establish the validity of our approach, using animal models of OA;a well characterized mouse model of surgical transection for destabilization of the medial meniscus (DMM) in mice, and two models of spontaneous osteoarthritis with Dunkin-Hartley guinea pigs and Str/Ort mice that share many features of human OA. We will use and compare two methods of localization of targeted fluorescent probes to damaged cartilage;MabCII labeled with near infrared emitting fluorescent (NIF) dyes and MabCII-targeted nanosomes encapsulating NIF intravenously injected into these animals. The degree of damage will be quantified using IVIS(R) imaging technology and correlated with traditional histopathological indices for the joints identified by fluorescently labeling and in collaborative studies for high resolution MRI. Our hypothesis, supported by preliminary data, is that the fluorescently labeled antibodies (NIF-MabCII) will selectively localize to joints in which the surface of articular cartilage is eroded and CII is exposed. We expect that the technique will be extremely sensitive and identify minimal cartilage damage and that larger and more advanced lesions will bind larger quantities of NIF-MabCII. We will also test the feasibility of modifying this approach for quantitative measurements with MabCII-targeted nanosomes loaded with 99mTc technetium which could be used for evaluation in patients using existing clinical protocols and available equipment.

Public Health Relevance

Osteoarthritis is a degenerative disease of aging cartilage that typically begins as a small lesion that progressively worsens. We will use a selective monoclonal antibody to detect and measure early OA in different animal models and to target small fluorescent liposomes to damaged cartilage.

Agency
National Institute of Health (NIH)
Institute
National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS)
Type
Exploratory/Developmental Grants (R21)
Project #
1R21AR060408-01A1
Application #
8242595
Study Section
Skeletal Biology Structure and Regeneration Study Section (SBSR)
Program Officer
Tyree, Bernadette
Project Start
2012-03-01
Project End
2014-02-28
Budget Start
2012-03-01
Budget End
2013-02-28
Support Year
1
Fiscal Year
2012
Total Cost
$245,237
Indirect Cost
$78,628
Name
University of Tennessee Health Science Center
Department
Orthopedics
Type
Schools of Medicine
DUNS #
941884009
City
Memphis
State
TN
Country
United States
Zip Code
38163
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Cho, Hongsik; Bhatti, Fazal-Ur-Rehman; Yoon, Tae Won et al. (2016) Non-invasive dual fluorescence in vivo imaging for detection of macrophage infiltration and matrix metalloproteinase (MMP) activity in inflammatory arthritic joints. Biomed Opt Express 7:1842-52
Kavanaugh, Taylor E; Werfel, Thomas A; Cho, Hongsik et al. (2016) Particle-based technologies for osteoarthritis detection and therapy. Drug Deliv Transl Res 6:132-47
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