Hideaki Nagase, Ph.D.
Kennedy Institute of Rheumatology-Centre for Degenerative Diseases, University of Oxford, UK
Osteoarthritis: diagnosis, treatment and challenges
Hideaki Nagase1, Ngee Han Lim1, George Bou-Gharios1, Ernst Meinjohanns2 and Morten Meldal3
- Kennedy Institute of Rheumatology, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, University of Oxford, London, W6 8LH UK
- Carlsberg Laboratory, Copenhagen, Denmark,
- Nano-Science Center, Department of Chemistry, University of Copenhagen, Denmark
Osteoarthritis (OA) is the most prevalent age-related degenerative joint disease. With the expanding ageing population, it imposes a major socio-economic burden on society. A key feature of OA is a gradual loss of articular cartilage and deformation of bone, resulting in the impairment of joint function. Currently, there is no effective disease-modifying treatment except joint replacement surgery. There are many possible causes of cartilage loss (e.g. mechanical load, injury, reactive oxygen species, aging, etc.) and etiological factors (obesity, genetics), but the degradation of cartilage is primarily caused by elevated levels of active metalloproteinases. It is therefore attractive to consider proteinase inhibitors as potential therapeutics. However, there are several hurdles to overcome, namely early diagnosis and continuous monitoring of the efficacy of inhibitor therapeutics. We are therefore aiming at developing non-invasive probes to detect cartilage degrading metalloproteinase activities.
We have designed in vivo imaging probes to detect MMP-13 (collagenase 3) activity that participates in OA by degrade cartilage collagen II and MMP-12 (macrophage elastase) activity involved in inflammatory arthritis. These activity-based probes consist of a peptide that is selectively cleaved by the target proteinase, a near-infrared fluorophore and a quencher. The probe’s signal multiplies upon proteolysis. They were first used to follow the respective enzyme activity in vivo in the mouse model of collagen-induced arthritis and we found MMP-12 activity probe (MMP12AP) activation peaked at 5 days after onset of the disease, whereas MMP13AP activation was observed at 10-15 days. The in vivo activation of these probes was inhibited by specific low molecule inhibitors. We proceeded to test both probes in the mouse model of OA induced by the surgical destabilization of medial meniscus of the knee joints. In this model, degradation of knee cartilage is first detected histologically 6 weeks after surgery with significant erosion detectable at 8 weeks. Little activation of MMP12AP was detected, which was expected, as macrophage migration is not obvious in OA. MMP13AP, on the other hand, was significantly activated in the operated knee at 6 weeks compared with the non-operated contralateral knee, but there were no significant differences between the operated and sham-operated knees. At 8 weeks, however, the signals in the operated knees were significantly higher than both the contralateral and sham-operated controls. Activation of aggrecanases and MMP-13 are observed before structural changes of cartilage. We are therefore currently improving the MMP-13 probe for earlier detection by attaching it to polymers that are retained in cartilage.
Leland H. Hartwell Ph.D.
2001 Nobel Laureate, Physiology & Medicine
Dr. Lee Hartwell received the 2001 Nobel Prize in Physiology / Medicine for his discovery of protein molecules that control the division of cells. He was the President and Director of the Fred Hutchinson Cancer Research Center in Seattle, Washington before moving to Arizona State University’s Center for Sustainable Health.
Dr. Hartwell is also adjunct faculty at Amrita University. He spoke to the delegates at Bioquest from his office in the US, over Amrita’s e-learning platform A-View. Given below are excerpts from his address.
I would like to address the young people in the audience. I know that many of you may have come to this meeting wondering, “How can I become a successful scientist? How can I prepare myself to make a contribution in this world?”
These questions are interesting to me also.
Believe it or not, I am still trying to be a successful scientist. That may surprise you since you probably think that a Nobel laureate must have found the answers. But the problem is that the answers to these questions change with time and the answers are different today than what they were when I began my career fifty years ago. The strategy of the 1960’s doesn’t work so well anymore. What is different now?
First, what we know now is much more. For example, by 1970, no genes from any organisms were sequenced. In 2013, we have the complete sequence of the human genome. Second, not only do we know much more today, accessing that knowledge is easy. Third, obtaining new information is much faster today.
Our rich understanding of science and technology is now needed to solve many serious problems. The human population has reached the size where we are utilizing all available resource of the planet. We are utilizing all of the agricultural land, all of the water, all of the forest and fishing resources. We are also polluting the planet that we live on.
We are polluting the land with fertilizers and pesticides; the oceans with acids and the atmosphere with carbon dioxide. We are using up top soil and ground water, thereby reducing our capacity to feed ourselves. We are using up petroleum, the energy source that our entire economy is dependent on. These are problems we were largely unaware of, fifty years ago. But these are problems that must be solved in your life times.
The big question facing your generation is, how can human beings live sustainably on planet earth. Your two broad goals on sustainability are 1) leave the planet as you first found it for your future generations; don’t use up the resources and don’t pollute the planet 2) everyone deserves to have an equal share of the earth’s resources.
Income strongly determines one’s opportunities in life. Many poor people succumb to chronic diseases and unhealthy environments. This inequality undermines our ability to live sustainably. We can’t ask the poor to leave the planet as they found it if they can’t support their families. Education, healthcare, employment are essential to having a sustainable society.
How can we be a successful scientist in 2013?
1. First choose a problem to solve
2. Ask questions to understand why it is not solved
3. Collaborate with those who can help
4. Develop a solution that works in the real worldChronic diseases are our major burden and this burden will get worse. Heart disease, diabetes, cancer, dementia and other diseases. The good news is that the chronic diseases are largely preventable and more easily curable if detected early. One question that attracts me is how can we detect disease earlier when it can be more easily cured?
Can we use our increasing knowledge in molecular biology to identify biomarkers for early disease detection?
We need to collaborate very closely with clinicians who care for patients to find out exactly where they need help.
I think if we apply our technology to important clinical questions we will actually save medical expenditure and be well on our way to making a great contribution to society.
Rajgopal Srinivasan, Ph.D.
Principal Scientist & Head Bio IT R&D, TCS Innovation Labs, India
Interpretation of Genomic Variation – Identifying Rare Variations Leading to Disease
Genome sequencing technologies are generating an abundance of data on human genetic variations. A big challenge lies in interpreting the functional relevance of such variations, especially in clinical settings. A first step in understanding the clinical relevance of genetic variations is to annotate the variants for region of occurrence, degree of conservation both within and across species, pattern of variation across related individuals, novelty of the variation and know effects of related variations. Several tools already exist for this purpose. However, these tools have their strengths and weaknesses. A second issue is the development of algorithms, which, given a rich annotation of variants are able to prioritize the variants as being relevant to the phenotype under investigation.
In my talk I will detail work that has been done in our labs to address both of the above problems. I will also illustrate the application of these tools that helped identify a rare mutation in the ATM gene leading to a diagnosis of AT in two infants.