Reducing Myc gene activity extends healthy lifespan in mice

No bones about it Young mice have good bone density whether they have two copies (top row; +/+) or one copy (bottom row; +/-) of the Myc gene. As they age, researchers found, mice with just one copy maintain better bone density and stay healthy longer. Sedivy lab/Brown University

Mice with one rather than the normal two copies of the gene Myc (also found in humans) lived 15 percent longer and had considerably healthier lives than normal mice, according to a new Brown University-led study in Cell.

PROVIDENCE, R.I. [Brown University] — A team of scientists based at Brown University has found that reducing expression of a fundamentally important gene called Myc significantly increased the healthy lifespan of laboratory mice, the first such finding regarding this gene in a mammalian species.

Myc is found in the genomes of all animals, ranging from ancestral single-celled organisms to humans. It is a major topic of biomedical research and has been shown to be a central regulator of cell proliferation, growth, and death. It is of such widespread and fundamental importance that animals cannot live without it. But in humans and mice, too much expression of the protein that Myc encodes has been closely linked to cancer, making it a well-known but elusive target of drug developers.

In a new study in the journal Cell, the scientists report that when they bred laboratory mice to have only one copy of the gene, instead of the normal two, thus reducing the expression of the encoded protein, those mice lived 15 percent longer on average — 20 percent longer for females and 10 percent longer among males — than normal mice. Moreover, the experimental mice showed many signs of better health into old age.

The experimental — “heterozygous” — mice grew to be about 15 percent smaller than the normal mice (a probable disadvantage in the wild) but that was the only discernable downside found to date for lacking a second copy of the gene, said senior author John Sedivy, the Hermon C. Bumpus Professor of Biology and professor of medical science at Brown.

“The animals are definitely aging slower,” he said. “They are maintaining the function of their organs and tissues for longer periods of time.”

Physiological differences

That assessment is based on detailed studies of the physiology — down to the molecular level — of the heterozygous and normal mice. The researchers conducted these experiments to try to understand the longevity difference between the two groups.

John Sedivy “The animals are definitely aging slower [and[ they are maintaining the function of their organs and tissues for longer periods of time.”

Co-lead author Jeffrey Hoffman, a medical and doctoral student, led the studies of the health of the mice, including various bodily systems. In many cases they were just like their normal counterparts. They reproduced just as well, for example.

“These mice are incredibly normal, yet they are really long-lived,” Sedivy said. “The reason why we were struck by that is because in many other longevity models like caloric restriction or treatment with rapamycin, the animals live longer but they also have some health issues.”

Instead the Myc heterozygous mice simply experienced fewer problems of aging. They did not develop osteoporosis, they maintained a healthier balance of immune system T cells, had less cardiac fibrosis, were more active, experienced less age-related slowing of their metabolic rate, produced less cholesterol, and exhibited better coordination.

Graduate student and co-lead author Xiaoai Zhao, meanwhile, led the molecular analysis of several pathways known to be involved in regulating longevity to find out how they might be different. Sure enough, heterozygous mice exhibited changes in IGF-1 signaling and nutrient and energy-sensing pathways, but how Myc engages those mechanisms is still not clear. Of particular interest, heterozygous mice showed less protein synthesis in several tissues. Regulation of this process is known to be under direct Myc control, and its reduction by a variety of means is known to extend lifespan in diverse species from yeast to mammals.

Genome-wide patterns of gene expression showed that Myc heterozygotes had significant differences in pathways related to metabolism and the immune system. Those patterns, however, only overlapped somewhat with patterns seen in other lifespan extending interventions.

Zhao and Hoffman’s studies also argue against a role for Myc in an oft-cited paradigm of greater longevity: upregulation of a variety of stress defense mechanisms. Their experimental mice seemed to suffer from as much stress and consequences of stress as normal mice.

The different benefits of Myc reduction compared to other laboratory longevity extenders shows that just as there are many ways the body can break down with aging, Sedivy said, there may be many ways to forestall that.

“There is more than one way to become long-lived,” Sedivy said.

Help for humans?

In the long term, Sedivy said he is optimistic that the findings about Myc could prove to matter to human health.

Finding the right target for a drug in one of Myc’s key metabolic or immune system pathways may or may not extend human lifespan, he said, but it might help people stay healthier as they age — for example, if it can reduce osteoporosis in people the way it does in mice. In particular, Sedivy said, it emphasizes the importance of the process of protein synthesis as a target of interventions that are likely to have widespread benefits on many organ systems.

And the study also offers encouragement to companies seeking to develop cancer drugs that block Myc overexpression. As important as normal Myc expression is to physiology, it appears that at least in mice there were many substantial benefits in reducing it by, say, half. Thus, Sedivy said, any drug that can target Myc directly is likely to find many applications beyond cancer.

In addition to Sedivy, Hoffman, and Zhao, the paper’s other authors are Marco De Cecco, Abigail Peterson, Luca Paglilaroli, Jayameenakshi Manivannan Bin Feng, Thomas Serre, Kevin Bath, Haiyan Xu, and Nicola Neretti of Brown; Gene Hubbard, Wenbo Qi, and Holly Van Remmen of the University of Texas; Yongqing Zhang and Rafael de Cabo of the National Institute on Aging; and Richard Miller of the University of Michigan.

The National Institutes of Health (grants R37AG016694, F30AG035592), the Ellison Medical Foundation, and the Glenn Award for Research on the Biological Mechanism of Aging supported the research. Some experiments were conducted in the Brown University molecular pathology and genomics cores.

Not just a longer life, but a healthier, stronger body “Do you think she might be a Myc hypomorph?” Drawing: Emma Sedivy

Source: Brown University

New technology may identify tiny strains in body tissues before injuries occur

The top image shows how the new algorithm is able to identify an area (in red) where stress has created a weak spot in a small piece of plastic wrap. The older method (shown in the bottom half of the picture) is unable to pinpoint the place where the plastic wrap is weakening.
Credit: John Boyle, © The Royal Society (used with permission)

Researchers at Washington University in St. Louis have developed algorithms to identify weak spots in tendons, muscles and bones prone to tearing or breaking. The technology, which needs to be refined before it is used in patients, one day may help pinpoint minor strains and tiny injuries in the body's tissues long before bigger problems occur.

The research is available online Aug. 27 in the Journal of the Royal Society Interface, which publishes research at the nexus of the physical and life sciences.

"Tendons are constantly stretching as muscles pull on them, and bones also bend or compress as we carry out everyday activities," said senior investigator Stavros Thomopoulos, PhD, professor of orthopaedic surgery. "Small cracks or tears can result from these loads and lead to major injuries. Understanding how these tears and cracks develop over time therefore is important for diagnosing and tracking injuries."

To that end, Thomopoulos and his colleagues developed a way to visualize and even predict spots where tissues are weakened. To accomplish this, they stretched tissues and tracked what happened as their shapes changed or became distorted.

The paper's first author, John J. Boyle, a graduate student in biomedical engineering, combined mechanical engineering fundamentals with image-analysis techniques to create the algorithms, which were tested in different materials and in animal models.

"If you imagine stretching Silly Putty or a swimming cap with a picture on it, as you pull, the picture becomes distorted," Boyle said. "This allows us to track how the material responds to an external force."

In one of the experiments described in the paper, Boyle sprayed a pattern of dots on plastic wrap, stretched it and tracked the dots.

"As you pull and stretch the plastic wrap, eventually tears begin to emerge," he explained. 

"The new algorithm allowed us to find the places where the tears were beginning to form and to track them as they extended. Older algorithms are not as good at finding and tracking localized strains as the material stretches."

In fact, one of the two new algorithms is 1,000 times more accurate than older methods at quantifying very large stretches near tiny cracks and tears, the research showed. And a second algorithm has the ability to predict where cracks and failures are likely to form.

"This extra accuracy is critical for quantifying large strains," said Guy Genin, PhD, professor of mechanical engineering and co-senior investigator on the study. "Commercial algorithms that estimate strain often are much less sensitive, and they are prone to detecting noise that can arise from the algorithm itself rather than from the material being examined. The new algorithms can distinguish the noise from true regions of large strains."

Thomopoulos, who also is a professor of biomedical engineering and of mechanical engineering, works with Genin to study the shoulder's rotator cuff, a group of tendons and muscles that connect the upper arm to the shoulder blade. They want to learn why some surgeries to repair rotator cuff injuries ultimately fail. Their goal is to increase the odds that the tissue in the shoulder will heal following surgery, and they believe the new algorithms could help them get closer to that goal.

How soon the new algorithms could be used in patients depends on getting better images of the body's tissues. Current imaging techniques, such as MRI and ultrasound, lack the required clarity and resolution.

Genin also explained that although the goal of the current study is to better understand how forces at work on human tissue cause injury and stress, the algorithms also could help engineers identify vulnerable parts of buildings and other structures. Our muscles and bones, he said, are influenced by the same strains that affect those structures.

"Whether it's a bridge or a tendon, it's vital to understand the ways that physical forces cause structures and tissues to deform so that we can identify the onset of failures and eventually predict them," he said.

In the long run, they want to use the algorithms to prevent additional injuries following surgery to repair knees, shoulders and other tissues. They also said it may be possible some day to predict problems before they occur.

The group, which applied for a provisional patent earlier this year, hopes the algorithms will be useful to researchers in the medical and engineering fields.

As a piece of plastic wrap is stretched, the new algorithms identify the location (in red) where it is weakening, which is where the material eventually breaks.

Source: Washington University in St. Louis

Software to automatically outline bones in x-rays

An image from the Bone Finder software. Credit: Image courtesy of Manchester University

Research into disorders such as arthritis is to be helped by new software developed at the University of Manchester which automatically outlines bones -- saving thousands of hours of manual work.

Amidst a national shortage of radiographers in the UK and an increasing requirement for researchers to work with large databases of radiograph images, the software which is being funded by the Engineering and Physical Sciences Research Council, is being designed to automatically pick out the shapes of bones in the images, rather than relying on individual researchers.

The system can already identify hips, but the researchers from the University's Institute of Population Health will now adapt it to map out knees and hands and to be able to learn to identify other bones and structures within the body.

The funding will allow further development to ensure the system is accurate enough that it can be used in hospitals to help provide faster diagnosis of problems in patients.

Professor of Computer Vision, Tim Cootes said: "Mapping the outlines of bones from radiographs is hard work that takes time and skill. When researchers into conditions like arthritis are working with hundreds of images, it's a very inefficient way of obtaining data.

"The idea of this software is to take the routine tasks out of human hands, so scientists can 

focus on drawing conclusions and developing treatments."

The funding of £300,000 lasts for three years and builds on earlier work which developed software, called Bonefinder, to identify problems and find the outlines of hips. This free software has been adopted by a number of research groups, including some based in Oxford and California.

Professor Cootes added: "We have a growing problem with arthritis which affects more than 30% of over 65s and costs around £30 billion to the UK economy year.

"Ultimately we want to get this technology into hospitals where it can save time and resources for the benefit of patients."

Source: Manchester University