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Ronald Kohanski of the NIA Discusses Potential Therapies

Ronald Kohanski InterviewRonald Kohanski Interview

It was a pleasure speaking to Dr. Ronald Kohanski at the 2019 Ending Age-Related Diseases conference. Dr. Kohanski joined the field of aging research in 2005 as a Program Officer for the Division of Aging Biology at the National Institute on Aging. He moved on to become its Deputy Director in 2007 and has held the position ever since. Within aging research, he has focused his efforts on the areas of stem cell and cardiovascular biology.

Besides his work at the NIA, Ronald Kohanski is a co-founder and co-leader of the trans-NIH Geroscience Interest Group (GSIG) with which he has organized several summits to discuss and disseminate the group’s focus. The GSIG directs its attention toward aging as the major risk factor for most chronic age-related diseases, and Dr. Kohanski actively encourages researchers to expand studies beyond laboratory animals. He underwrites the importance of addressing the basic biology of aging explicitly in human and non-laboratory animal populations. He believes that age should be considered a fundamental parameter in research that uses animal models of chronic disease.

Dr. Kohanski was trained in the field of biochemistry. He received his PhD from the University of Chicago in 1981, after which he conducted a postdoctoral fellowship with M. Daniel Lane at the Johns Hopkins University School of Medicine. He held a faculty position at the Mount Sinai School of Medicine for 17 years before returning to Johns Hopkins as a faculty member and researcher in the areas of enzymology and developmental biology of the insulin receptor.

Could you describe where the nine hallmarks of aging that are widely accepted by the scientific community of aging researchers intersect with other, for instance environmental, risk factors for morbidity?

I probably can’t give you specific examples at this time, but you could expect a lot of toxins that are present in the environment to impact any of the hallmarks in liver cells because the liver has a function of detoxification. You would also expect immune senescence to be affected negatively by a lot of environmental toxins.

The mechanisms by which those effects would occur – in the case of liver cells – might have to do with their ability to replicate. Steve Artandi has shown that there’s a subset of liver cells that have elevated telomerase activity from birth, and they seem to be the cells that regenerate the liver when there’s been an injury [1]. Toxins in the liver are injurious and they may also interfere with that subset of cells. I don’t know that, but if I were to speculate, which I’m just doing now, I would look in that area.

For immune senescence, environmental impacts will probably be most visible in the thymus, which is already somewhat gone by the time we’re young adults and doesn’t function that well by the time we’re older adults. That might be a case where early life exposures could have long-term effects on immunity: the damage is done before you notice, and then it’s decades before it really hits you. There are almost certainly examples of that.

One of the areas that gets a lot of attention, for environment-biology interactions, would be cancers due to mutagens. Even backing off from cancer, taking the same example, we know that DNA mutations pretty much accumulate somewhat linearly with age. Their relationship with the diseases of aging is nonlinear, but their relationship with the underlying causes is linear.

The non-linearity comes, in part, because the mutations interact. If you have environmental impacts that stress the capacity for DNA repair, then the rate at which mutations accumulate becomes higher. Those include point mutations, and, in replicating cells, possibly some translocations, it may alter retrotransposon activation, things like that. This is all stuff that we heard from André Gudkov at this conference and from Vera Gorbunova as well [2,3]. So you would expect, again speculatively, to be looking in those areas for interactions between the environment and the hallmarks of aging.

I can say that, just this year, we (at the National Institute on Aging) issued a program announcement for people who are interested in studying the impact of extreme weather events on aging. The National Institute of Environmental Health Sciences has a long standing program to look at chronic environmental impacts on aging, independently of the NIA, and I think we also participate in that one. But this is a new program that has to do with extreme weather events specifically, which seem to be occurring in somewhat greater frequency in the than in the past. We have our first set of applications coming in on that, and it will have a three-year direction, so we may be able to better answer your question in a few years.

In a 2016 article that you wrote as a result of a summit co-organized by the National Institute of Health Geroscience Interest Group and the New York Academy of Sciences, you talked about early exposure to disease and its possible influence on the aging process later in life. Could you briefly explain what the most important considerations surrounding that early disease exposure are for aging?

I’ll give a little background and then I hope I can answer your question directly. The first summit (we organized) was just to explain what geroscience was and try to raise people’s interest in it. That was successful. It was about aging as a driver of disease. We actually know that diseases that occur early in life are drivers of aging. That was mentioned in the meeting here as well. The New York Academy of Sciences approached Felipe Sierra, who was the head of the Geroscience Interest Group, and me as his deputy, and asked us if they could run a summit for us. We said, “Sure, if you’re doing all that work, we’ll just provide some ideas, and our main idea is that early diseases are drivers of aging.”

The major impetus (at the second summit) actually was cancer and HIV. Diabetes is a difficult area to encapsulate in aging, because what was adult-onset diabetes is now juvenile-onset diabetes, which is an example of an environmental impact on a specific disease. It has to do with overwhelming the capacity of the system to metabolize glucose, which is diabetes. That’s a hard one.

However, with survivors of childhood cancer, we knew, through work sponsored by the National Cancer Institute and with the recent guidance of its program officer Dr. Paige Green, that there’s a specific interest in the clinical aspects of the long-term effects of childhood cancer treatment. There’s two problems there. One problem is the cancer itself stressing the body. You’d expect chronic stress like that to have an impact on aging. There’s also a range of treatments, some of which are harsher than others. Radiation therapy is pretty harsh. We know that radiation itself will accelerate aging, depending, of course, on your genetic background and other factors. There are some older survivors of the Hiroshima bombing, but most of them died at younger ages, many of them from cancers.

Arti Hurria, unfortunately recently deceased in a car accident, was running the City of Hope’s Center for Cancer and Aging in Duarte, California and was studying all aspects of cancer as an impactor of the human condition. She had psychiatrists, psychologists, social workers, nurses, physicians, basic biologists, aging and cancer researchers: she really covered everything. She built what I hope will go on to be the paradigm for how people working in cancer and people working in aging, and their related fields, will interact with each other. One outcome of the summit was our interaction at the NIA with her on this.

She took the new cancer therapies that came online in 2017 and 2018 and asked “How do these therapies map to the hallmarks of aging?” I had a little bit of an impact on that, because I asked her to do it. We were trying to answer if these therapies impact both cancer and the hallmarks of aging. That might provide some clues as to where the pressure points are with this, but our perspective is still that these hallmarks all interact. There may be one entry point, but it’s a circle. Therefore, you can come out anywhere else on the circle, either tangentially or radially, or whatever it is bouncing around on the inside. These things will, in some way, connect – not all of them, but you can look for the different interactions among them.

The other one (in the second summit) was HIV. Here’s a rare opportunity in a human population suffering from a horrible illness. Through work done by the National Institute on Allergies and Infectious Diseases under Anthony Fauci and researchers in France, they came to a better understanding about what HIV was in the molecular sense, why it behaved the way it did, and some things about those rare escapers, as it were. People that carry the burden of the virus without having so many different manifestations.

The other thing about them is that these people survive, and they show accelerated aging. People who are 50 look like they’re 80. Now it’s obviously better to be alive, but it would be nicer to be alive in better shape. There’s a problem there, like with cancer and aging: how do you separate the disease from the treatment? It turns out that these people have partners, and their partners, in many cases, prophylactically take the drug regimen; so you have the people with the disease on the regimen, and you have age-matched people who are taking the medication but don’t have the burden of disease. Then you have the reference population, which has neither.

There’s a group in the San Francisco area that agreed to be studied. This offers a rare opportunity to be able to look at the hallmarks of aging, and the biology of aging, in a human population without having to create what would be an unethical intervention. You’re not going to give HIV to people. You’re not going to not treat people with HIV, unless they choose that option. It’s also unique, because it’s pretty hard to come up with a reliable model for the disease. SIV is a bit different, so you’re confined to what you can do for people, either in vivo or ex vivo. From structural biology to caregiving, it’s all there. I think the NIH can be quite proud of what they did, and I’m pretty sure we are.

In the same paper, you and your co-authors posed the question whether it would be a good idea to combine future interventions to delay aging with those that fight serious diseases like cancer. Most people would assume that those therapies can only serve to support each other in promoting health. Can you explain why that might not be the case?

I can give you one example, which is probably fairly reasonable. The standard of care before chemotherapy is to eat. If you remember (the movie) The Bucket List, Jack Nicholson just chowed down while Morgan Freeman’s character knew better. Work from Valter Longo at UCSD started out looking at calorie restriction in yeast. He got it to move along through the pipeline, and he developed the idea that maybe the stress response to starvation, or food deprivation, is mounted by normal cells, but not by cancer cells. There’s a way of coupling what we know about the biology of aging and the consequences of chemotherapy. I don’t know quite where that stands at the moment, but it’s an example of how you could use what you understand about aging as an adjunct to diseases.

The etiology of cancer in humans is different from that in many other organisms. The closest one is dogs, and a lot of things have been researched with them, like the Starling cycle of cardiac function, blood transfusions, and even bone marrow replacement. We support a program that looks at aging in pet dogs. Not laboratory dogs, that’s unethical. People will do astonishing things to support the health of their pets and spend vast quantities of money as well, whether they intend to or not. There may be some options (for collaboration) there, because NCI has a large program involving roughly 14 veterinary schools that study cancers in dogs and their treatments. You can ethically and reasonably do a lot of things with a dog: you can restrict the dog from eating, you can give it an alternative diet; they’ll eat whatever you put in front of them.

They’ve actually shown in some small-scale experiments that if you fast before chemotherapy, it becomes more effective. You’re effectively depriving cancer cells of what they need to survive the chemo.

True, but I don’t know if they’ve been able to expand that. One of the things that they’ve tried to do is to provide a specifically formulated diet that would allow people to have some food but still have the same effect. Getting people to not eat for three days, unless you’re some sort of religiously inclined person, that’s not going to happen very often. I myself once fasted for a week. I was about 20 years old and in college, so it wasn’t that big of a deal. You hallucinate a little bit.

Do you do any caloric restriction or intermittent fasting now?

I don’t do anything regularly. People in my office do all sorts of stuff, though. Several of them subscribed to Sinclair’s company to get NR. Not all of them have maintained it, for various reasons, because there are contraindications. Felipe does an 18-hour fast schedule. I do skip breakfast, but if I’m going to give a talk, I’ll eat before. Actually, I get to telework some days, and it’s easier to not eat on those days because the drive to work makes me nauseous, so I have to have something to calm it down. Also, I stopped drinking coffee, because with coffee I’d have to eat.

Laboratory animals in general, and genetically modified mice with accelerated aging phenotypes in particular, have been criticized as having only limited suitability as model organisms in the quest to understand the basic biology of aging. What are your thoughts on the usefulness of these animal models to further our grasp of aging in humans and the efficacy of rejuvenation interventions?

A mixed bag, I would say. If you have access to my talk, the slide after the last one shows the genetically modified laboratory mice that are used in accelerated aging trials, and where they map to the hallmarks of aging. Some of them, of course, map directly to more than one pathway. I’m stuck on nutrient sensing, but that may be out of date now. Regardless, they are useful in many aspects. Senolysis was worked out nicely by Jan van Deursen’s group [4] and also independently by Judy Campisi’s group.

The accelerated aging phenotype has an advantage: they die younger. To what extent it represents an accelerated form of normal aging is going to be very difficult to answer. I think I know how to answer it, because I’m an arrogant scientist. The question is, in the reference strain C57BL/6 unperturbed, what does aging look like in both males and females? What’s the distribution of cell types in tissue? What’s the distribution of cell types in tissue based on RNA-seq profiling at the single-cell level? You can present that N-dimensional data in a tSNE plot and get a lot of information from that about heterogeneity. You can also microscopically visualize what they look like as they age in different tissues.

Of course, you’re not going to do that longitudinally, because you have to take apart the mice. Averages are also not necessarily what you want (to know about), but you will get a distribution of what aging (in this mouse) looks like without a perturbation. You could also ask what aging looks like with a relatively agnostic perturbation, such as feeding at a specific time of day with or without exercise. In that case, you wouldn’t give them rapamycin because that’s not agnostic. You wouldn’t give them any specific drug, but you might just do something that they would otherwise do. You could say: mice with or without a running wheel, which ones will live longer? I don’t know whether that’s been tested, but they’re certainly healthier.

All in all, you can look at what is healthy at different ages and image it: present it in some way that you can look at it and see what changes. That’s what I mean by imaging. Then you get accelerated aging models, and you can ask questions. Do they look like this (baseline) at a certain age, and, if so, in which tissues? Do they have a similar appearance? If the lifespan is normally three years and the accelerated one is only one year, do you see those same changes at a threefold rate in a one-year period? That would answer the question, but it would take about 10 years. In 10 years, things are not going to stand still and wait, but it would be good to know.

Is there a question that no journalist ever asked you that you would like us to ask?

I’ve been asked a bunch of questions about a bunch of things, but nobody asks me about the systems biology of aging. There may be a reason for that, namely that systems biology can be a bit impenetrable. So what’s my definition of systems biology? It’s my definition of aging. I mean, we could sit here all day and philosophize about it.

I think that’s an underappreciated area, but for a range of reasons. Systems biology started out as who can draw the best hairball. What it was asking was “Can you discover the networks that are essential for a living organism?” One of the things that intrigued me about it was the work of Davies. He mapped the first two days of sea urchin development with engineering diagrams, which was essentially a systems biology or systems level understanding of how development took place. I thought that was great because development is under strong selection, and it’s pretty regular. You can always tell what the species (of sea urchin) is without having to sequence the DNA.

It’s the same for humans. If you walk into a room with 100 people, those are 100 (distinctly) different humans. Essentially, what you have is a system that developed under selective pressure, and it has emergent properties. What are emergent properties? Well, robustness is an emergent property. An example of robustness is those 100 people in a room that are 100 distinct Homo sapiens. They don’t look the same, they behave differently, they will have different trajectories (in life), they will have different interests, they will think differently, they will have different abilities to concentrate, etc. Almost everything about them is different, yet they are the same.

Another emergent property of a network is called buffer. For instance, a terrorist network is highly buffered. Parts of it can be removed, and the whole system will function. Buffering contributes to robustness. A lot of success in biology has to do with success in buffering. In a network, to get from one node in a network to another, you can go through multiple paths, and that’s a systems-level buffer. It may be more or less efficient, but it’s there. Another property of a network is noise. Noise is a good example for aging because it functions two ways. Noise is a signal. The periodicity of noise contributes to the signal. It can also contribute to diminishing the robustness of the system, which is how we normally think of noise.

We often think of populations of mice as being genetically identical, but they’re not. When they’re born, they’re different. All the cardiomyocytes of a mouse are not the same; they are not genetically identical. They have the same set of bases, but they’re not always in the same order. There may have been some rerrangements and some mutations. All of this stuff has happened during development, so by the time you get the mouse pup, it’s different from others. That’s not even considering the epigenome, it’s just that some things have happened during development. It turns out that a lot of “bad things” happen during gestation. We tend to think of it as conception, and then there’s birth. However, it’s actually astonishing that it works at all. That’s because the system is robust. It can produce an outcome that represents viable offspring, even in the face of all of these “bad things” that are going on. All in all, I think there’s a case for thinking about these things (model systems) as a whole system, with robustness and all of its emergent properties included.

We (NIA) support a couple of grants on systems biology of aging where we ask what is changing in the system with age. I guess my answer is just that one thing: I’d like to hear more questions about obscure things like systems biology and robustness, stuff like that.

In addition to this interview, Dr. Kohanski also gave a talk entitled Concepts and Perspectives in Geroscience at Ending Age-Related Diseases 2019. He discussed the ways in which aging affects systems and cells, the problems with using lifespan as an endpoint, the concept of resiliency, parabiosis, telomeres, unexpected effects at a distance with regards to interventions, and several in-depth concepts relating to the aging of specific cell types, such as muscle and brain cells.

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[1] Lin, S., Nascimento, E.M., Gajera, C.R., Chen, L., Neuhöfer, P., Garbuzov, A., Wang, S., Artandi, S.E. (2018). Distributed hepatocytes expressing telomerase repopulate the liver in homeostasis and injury. Nature, 556, 244-248.

[2] Simon, M., van Meter, M., Ablaeva, J., Ke, Z., Gonzalez, R.S., Taguchi, T., De Cecco, M., Leonova, K.I., Kogan, V., et al. Inhibition of retrotransposition improves health and extends lifespan of SIRT6 knockout mice. Poster presented at: Cold Spring Harbor meeting; 2018. Doi:

[3] Simon, M., van Meter, M., Ablaeva, J., Ke, Z., Gonzalez, R.S., Taguchi, T., De Cecco, M., Leonova, K.I., Kogan, V., et al. (2019). LINE1 Derepression in Aged Wild-Type and SIRT6-Deficient Mice Drives Inflammation. Cell Metabolism, 29(4), 871-885.

[4] Childs, B.G., Gluscevic, M., Baker, D.J., Laberge, R.M., Marquess, D., Dananberg, J., van Deursen, J.M. (2017). Senescent cells: an emerging target for diseases of ageing. Nature Reviews: Drug Discovery, 16, 718-735.

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