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There is a great discrepancy between the age results of all these biological clocks that I don’t fully understand except to say they are based on different data sets and small samples. I’ve used x 2 and x 1, but they seem to be using older Horvath clocks. Epigenetic clocks don’t say why there is an age discrepancy because deep learning doesn’t explain itself. GrimAge seems the best biological clock (per “DNAm GrimAge stands out among existing epigenetic clocks in terms of its predictive ability for time-to-death (Cox regression P=2.0E-75), time-to-coronary heart disease (Cox P=6.2E-24), time-to-cancer (P= 1.3E-12” – ) and I don’t think there is yet a commercial version of it. I am using another company to test my epigenome, for $99 so this will be the 3rd test and is fairly inexpensive. “…centenarians are younger (8.6 years) than expected based on their chronological age.” Īlso Michael said that the Levine clock was cheaper to do. It is likely that this could be ameliorated with additional loci and/or further refined modeling of the currently used set.”
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This is at least partly due to saturation, i.e., DNA methylation proportion at some loci approaching 0 or 1, and confounding with the effects of other age-related processes will also play a role. DNA methylation clock models begin to degrade as subjects enter old age. “The age prediction properties of both Horvath and Hannum et al. There were not enough older people in the previous samples, so cpg saturation makes clocks errors greater in those cohorts. Indeed all these biological clocks seem lightly correlated. If you’re interested, please have a look at my book! To quantify your biological age using Levine’s Phenotypic Age calculator, here’s the Excel link! DNAmPhenoAge_gen (1) Going forward, I expect my creatinine and WBCs to come down to their average values, which would result in a biological age that is closer to 30y on my next blood test. Once it passes, I expect it to return to close to my average WBC value, ~4.5. This increase is more than likely a result of the flu/infection that I’m battling. For the next blood test, I’ll reduce, but not eliminate my intake of meat, eggs, and cheese, and I expect that my creatinine levels will decrease back towards my average 2015-2019 value of 0.94 mg/dL.Īlso note my WBCs-although they’re not higher than the 3.5-6 optimal range (see ), they’re increased when compared with my average 2015-2019 value of 4.5. Note that creatinine levels increase with age (see ), so if I can avoid that by altering my diet, I will. For me, eating more animal protein and less total fiber may not be optimal, as my creatinine levels also rose in 2019 when I performed a similar dietary experiment. Conversely, I increased my intake of meat, eggs, and cheese intake during that period, to see if eating less fiber and more animal products would negatively impact my blood test results. My average daily fiber intake has been ~100g/day for a few years, and over the past 3 months, I purposefully reduced that to ~70g/day. My biological age was 32.75y, which is less than my 2019 average value, and better than I expected considering the factors mentioned above! Note that there is room for improvement, including my creatinine and WBC levels, which both increased when compared with my average 2015-2019 values (which included 23 blood tests). So how did these variables affect my biologic age? Let’s have a look at the data! Since my last blood test 3+ months ago, my average calorie intake was 2553, which is 5-10% less than my maintenance intake, 2700-2800 calories/day. In contrast, I’ve been purposefully in a mild caloric restriction in an attempt to reduce my body fat from a relatively lean 10-12% to lower values. I expected to see a worse biological age, as over the past week, I’d been hit with the flu, and since my last measurement in 2019, I made a few changes to my diet that I didn’t expect to favorably affect it. On Feb 12, I had my first blood test measurement of 2020. That’s 12 years younger than my chronological age in 2019, 46y! In 2019, I measured all 9 of its analytes 3 times, with biological age readings of 35.39y, 35.58y, and 31.3y, for an average 2019 biological age of 34.09y (see ). Measurement of biological age with Levine’s Phenotypic Age calculator is strongly correlated with chronological age ( r=0.94 see ).
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