{"id":715,"date":"2018-04-17T02:51:12","date_gmt":"2018-04-17T02:51:12","guid":{"rendered":"http:\/\/joshmitteldorf.peachpuff-wolverine-566518.hostingersite.com\/?p=715"},"modified":"2018-05-21T10:54:30","modified_gmt":"2018-05-21T10:54:30","slug":"the-mother-of-all-clinical-trials-part-ii","status":"publish","type":"post","link":"https:\/\/scienceblog.com\/joshmitteldorf\/2018\/04\/17\/the-mother-of-all-clinical-trials-part-ii\/","title":{"rendered":"The Mother of All Clinical Trials, Part II"},"content":{"rendered":"

Part II: Why We Should Trust the Methylation Clocks to Measure Aging<\/span><\/strong><\/p>\n

Last week<\/a>, I proposed that methylation age could be used to measure the benefits of putative anti-aging interventions. \u00a0This procedure has the potential to slash the cost and the duration of testing. The reason is that we don\u2019t have to wait for a <\/span>small percentage<\/b> of experimental subjects to become sick or die. \u00a0The vast majority of subjects in a human anti-aging trial give us no information whatever. \u00a0In contrast, with the aging clock, <\/span>every<\/b> experimental subject is a data point, and the effect on his aging might be measured in a year or two.<\/span><\/em><\/p>\n

The proposal depends critically on the assumption that whatever slows aging will slow the methylation clock, and the converse: whatever slows the methylation clock slows aging. \u00a0Some people will find this hard to believe, because their fundamental conception of aging is an accumulation of damage, so that any association with methylation will be incidental or worse! \u00a0(What if the changes in methylation that accompany aging tell the story of the body\u2019s increasingly powerful efforts to <\/span>repair<\/b> the damage from aging?)<\/span><\/em><\/p>\n

But for those of us who come to the table open to the idea that aging is an epigenetic program, a close (causal) association between methylation and aging seems utterly expected. \u00a0For decades, developmental biologists have assumed that development in childhood is driven by age-dependent gene expression. The only thing that prevents us from seeing that the same is true about aging is a kind of prejudice from evolutionary theory that I have described in <\/span>my book<\/span><\/a> and in <\/span>this blog<\/span><\/a>.<\/span><\/em><\/p>\n

\n

4. Brief History of the Horvath Clock<\/b><\/p>\n

Of many biochemical markers that cells use for epigenetic control, methylation of CpG sites is best studied. \u00a0If you know what that is all the better; if you don\u2019t, all you need to know is methylation is a modification of the DNA by adding a CH3<\/sub> group to Cytosine residues in a promotor region adjacent to a gene. \u00a0Regions with heavy methylation tend to suppress expression of the (usually) adjacent gene. \u00a0Methylation isn\u2019t the only means by which gene expression is controlled \u2014 there are many others. \u00a0\u00a0But it is far the best-studied and, given present technology, it is the only epigenetic marker that can be routinely measured, for a few hundred dollars in a small sample of blood, urine, or nanogram-scale biopsy of other tissue. \u00a0<\/span><\/p>\n

The clock was <\/span>developed by Steve Horvath<\/span><\/a> at UCLA, and first published in 2013, built on an idea of <\/span>Teschendorff<\/span><\/a> from a few years earlier.. \u00a0He identified patient records for methylation measurements of tissue samples from 8,000 individuals, with associated ages. \u00a0Methylation is recorded as a number between 0 and 1 for each Cytosine, indicating the proportion of that site that is methylated. \u00a0He scanned the entire genome for sites that changed most with age, and varied least from one tissue type to another.\u00a0 In this way, he identified 353 sites, and optimized a set of 353 multipliers, such that multiplying levels of methylation at each site by each multiplier and adding the products produced a number that could be mapped onto chronological age.\u00a0\u00a0About 45% of the multipliers are negative (sites losing methylation with age) and 55% positive (gaining methylation). <\/span><\/p>\n

The original Horvath clock correlates 0.95 with chronological age. \u00a0The standard error in predicting any one individual\u2019s age is <\/span>+<\/span><\/span> 4 years. \u00a0<\/span>Averages of N individuals increase the accuracy of the clock by \u221aN<\/i><\/b>, so that the average of 100 individuals is accurate to 0.4 years. \u00a0(This is a general statistical principle that is useful to remember.) \u00a0For our purposes, the relevant question is: measuring the same individual at two different times, how accurate is the difference in Horvath age compared to the elapsed time? \u00a0There is no data on this yet, but we might safely assume that it is well under 4 years, since standard error of 4 years represents mostly individual departures from the average.<\/span><\/p>\n

Five years after Horvath\u2019s original publication, there are several other clocks based on methylation. \u00a0Just this spring, Horvath has developed a new clock, not yet published, which, to my knowledge, is the best standard we have. \u00a0This is the <\/span>Levine\/Horvath clock<\/span><\/a>. \u00a0It is based on 513 methylation sites and it is calibrated not to chronological age, but to a tighter measure of age-based health, derived from blood lipid profies, inflammatory markers, insulin resistance, etc, which Horvath calls \u201cphenotypic age\u201d. \u00a0Consequently, it is less well correlated with chronological age than the original, but it is better able to predict mortality than either the classic Horvath clock or chronological age itself. By this measure, the scatter has been greatly reduced.<\/span><\/p>\n

 <\/p>\n

There is statistical evidence that the Levine clock reliably reports phenotypic age, and there is theoretical reason to believe that what the clock measures is close to the root cause of aging.<\/span><\/p>\n

5. Statistical evidence that the Levine Clock=PhenoAge reliably measures biological age<\/b><\/p>\n

What I find most convincing is the meta-analysis based on historic data. \u00a0Levine and Horvath use old, frozen blood samples to calculate a Horvath and Levine Ages as it was at some past date. \u00a0These are people who have died since the blood was drawn, and Horvath Age accurately \u201cpredicts\u201d the remaining life expectancy of the subjects. \u00a0[<\/span>Chen, Aging 2016<\/span><\/a>]. \u00a0There is less data available for the new Levine clock, but strong indications it performs much better than the Horvath clock for this purpose.<\/span><\/p>\n

In addition, many of the life styles that promote long life have been confirmed to slow the Levine clock, while, conversely, obesity and high blood pressure and insulin resistance have been found to accelerate aging as measured by the Levine clock.<\/span><\/p>\n