A Spreadsheet for Calculating Your Levine Phenotypic Age
An excellent paper by M. E. Levine, et al, entitled "An epigenetic biomarker of aging for lifespan and healthspan" describes a technique for combining nine blood-work values with calendar age to calculate your Mortality Score (probability of death in the next ten years) and your Phenotypic Age, i.e., your apparent biological age as implied by your blood variables. The calculation procedure is rather arcane, involving non-obvious unit conversions, exponentials, and logarithms, so I have produced an Excel spreadsheet (LINK) for performing these calculations.
Levine, et al., also used an elaborate DNA analysis of many blood samples to find what they call the DNAm PhenoAge, a measure of the degree of DNA methylation present, a phenomenon associated with aging. They correlate this measure with the Phenotypic Age, showing that they track very well. My spreadsheet uses a fit to their plots to estimate your DNAm PhenoAge and the modified Mortality Score that it implies.
You may already have blood-work giving the nine blood variables needed to use this spreadsheet, but if not they can be obtained by purchasing the blood-work of LifeExtension's Chemistry Panel & Complete Blood Count (CBC) ($35) and their C-Reactive Protein (CRP), Cardiac ($42). On the spreadsheet at the upper line of blue numbers, you simply enter your values in place of the ones presently there and enter your decimal calendar age in the last column. The calculated results then appear in red on the last line.
It is good to have started a fresh new thread on the Levine's paper and providing your calculator. Thank you again. However, I feel worth also to refer everyone to the thread started by Dan Mc on the same topic/paper where there is an important follow on discussion in particular about integration of several categories of possible biomarkers of aging (e.g. molecular, clinical, anthropometric, machine learning driven, ...), the role of inflammation as characterized by biomarkers as CRP and IL-6 and the intriguing role "geometric" factors as MCV/RDW have.
A nice follow up here could be to gather information on trends along the years rather that only measurement at one point in time as better tacking the interventions we are trying.
I have written to Dr Levine along these line (no reply yet) and wonder if you got a reply on the CRP vs. MCV/RDW role.Reply
Here's an useful small hack - put your numbers in and vary them to see how you can make your bio age go backwards and by what degree. For instance driving your glucose down by 10 points gives you an extra year (at least for my numbers). Higher albumin is better (liver function I believe), as is lower creatinine (indicating healthy kidneys). This can be useful as a tool for what to work on with your blood panel. For example weighing the value of driving glucose down compared to the difficulty (e.g. lifestyle) of doing so.
I think for me the takeaway is the this looks like a good way to estimate the biological age of your blood only. This should be combined with other measures (e.g. reaction time, cardiovascular health, VO2max, etc) to create an overall estimate of your biological age. For weighings, in the absence of better estimates they could all simply be averaged together.
For example, a typical 10 year old has excellent blood work, excellent cardio, balance, reaction time, etc and would come out as being 10 years old. But compare to a poor kid growing up in a nutrition starved environment, presumably that would reflect in their results (slow reaction time, blood work, etc) and they could come out older.Reply
JGC Is the current link to the spreadsheet based directly on the Levine algorithm, or your modified version where you tried to "correct" it to align more closely to the derived methylation profile? As I've posted before, the former is IMO more valuable as it is more directly related to actual health outocmes than the methylation profile; if this is the "modified" version, may I suggest/request that you post both versions and explain the difference?
(Thank you again for doing this at all!).Reply