An Update on DNA Methylation Patterns as a Biomarker of Aging
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The research community is very interested in a reliable method of measuring biological age: not how old you are in years, but how far along you are in the aging process, how much damage has accumulated in cells and macromolecules and how well or poorly your organs and other systems are reacting to that damage. Such a measurement of age is known as a biomarker of aging, and while there are all sorts of measures that correlate fairly well with biological age - good enough for large statistical studies to use in order to mine data for meaning - there is not yet a good, accurate, standardized way to run some numbers and use them as a measure of how aged you are.

Why is this important? Principally because it costs an enormous amount of money to assess the ability of any treatment to slow or reverse aspects of aging and thereby extend healthy life. The only way to know at present is to wait and see, and even in mice that means years and millions of dollars. But what if we could be fairly sure that by taking some measurements after a single treatment, researchers could predict with a high degree of accuracy whether or not aging is reversed or slowed and future life span thus extended? If achieved, that would mean ten times as much work on assessment of possible therapies in mice could take place for a given amount of funding. That's a big deal, even without considering that the only practical way to determine whether a putative life-extending treatment actually works or not in humans is to establish an accurate biomarker of aging based on short term, immediate measures. It simply isn't practical to take the wait and see approach for decades.

Personally I rather hope that the arrival of an accepted biomarker of aging will do much to damp down the level of fraud and misinformation that spills forth from the "anti-aging" marketplace. There's always someone trying to sell a lie to the masses, and it is unfortunate that their voices are so very much louder than those of the scientific community. Given that pretty much nothing sold on the market today will move the needle at all on human life span, and nothing is yet shown to even match the benefits of calorie restriction or exercise, I look forward to a way to demonstrate this unequivocally.

In any case, in recent years the measurement of patterns of DNA methylation has shown promise as a potential biomarker of aging. DNA methylation is a part of the process of epigenetic changes that take place in response to circumstances, altering levels of proteins produced by cells. Our biology is essentially an assembly of fluid machines in which the controlling switches and levers are the levels of various proteins in circulation. Everything reacts to everything else, in a complex never resting dance of overlapping feedback loops at every level. From this, however, patterns emerge. Aging takes a broadly similar path for all of us, and thus there are some broadly similar reactions to its damage in our cells. The trick is having enough computational power and the right tools of biotechnology to be able to pull out those patterns from the thousands of unrelated variations in DNA methylation that exist in all our tissues.

This is a popular science piece, but still has some interesting information on how things are going with the DNA methylation approach to generating a biomarker of aging that might prove useful as a measure of the effectiveness of future treatments for aging:

Biomarkers and ageing: The clock-watcher

Horvath's clock emerges from epigenetics, the study of chemical and structural modifications made to the genome that do not alter the DNA sequence but that are passed along as cells divide and can influence how genes are expressed. As cells age, the pattern of epigenetic alterations shifts, and some of the changes seem to mark time. To determine a person's age, Horvath explores data for hundreds of far-flung positions on DNA from a sample of cells and notes how often those positions are methylated - that is, have a methyl group attached.

He has discovered an algorithm, based on the methylation status of a set of these genomic positions, that provides a remarkably accurate age estimate - not of the cells, but of the person the cells inhabit. White blood cells, for example, which may be just a few days or weeks old, will carry the signature of the 50-year-old donor they came from, plus or minus a few years. The same is true for DNA extracted from a cheek swab, the brain, the colon and numerous other organs. This sets the method apart from tests that rely on biomarkers of age that work in only one or two tissues, including the gold-standard dating procedure, aspartic acid racemization, which analyses proteins that are locked away for a lifetime in tooth or bone.

Others began downloading the epigenetic-clock program from Horvath's website to test it on their own data. Marco Boks at the University Medical Centre Utrecht in the Netherlands applied it to blood samples collected from 96 Dutch veterans of the war in Afghanistan aged between 18 and 53. The correlation between predicted and actual ages was 99.7%, with a median error measured in months. At Zymo Research, a biotechnology company in Irvine, California, Wei Guo and Kevin Bryant wondered whether the program would work on a set of urine samples Zymo had collected from 11 men and women aged between 28 and 72. The correlation was 98%, with a standard error of just 2.7 years.

[Researchers] expect that the most interesting use of the clock will be to detect 'age acceleration': discrepancies between a person's epigenetic and chronological ages, either overall or in one particular part of their body. Horvath says that recent work has found that people with HIV who have detectable viral loads appear older, epigenetically, than healthy people or those with HIV who have suppressed the virus. Another study, not yet published, observes that some tissues show significant age acceleration in morbidly obese people.

Comments

Good short essay. Thanks so much for taking the time to write these and disseminate this information.

Posted by: Jim at April 16, 2014 8:18 PM

My Prof, who is working on the field of biomarkers of aging, told me that such a high correlation is not good for a biomarker of aging. The biomarker would then not predict the biological age, but rather the chronological age.

Posted by: Arthur at April 19, 2014 4:30 AM
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