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Longitudinal Biomarker Optimization: A Road To Maximize Health And Longevity?

blood testing

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#1 Michael Lustgarten

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Posted 13 November 2022 - 12:19 PM


https://www.youtube....h?v=eR-0HunPH4E

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#2 albedo

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Posted 13 November 2022 - 01:43 PM

Great, Michael, as usual!

I surely have missed the point but aren't all the studies you compare your longitudinal values with cross-sectional? You make the point I think for RDW but isn't the same from glucose and albumin too?

Beside that (surely my misunderstanding) good point as usual on reference of the lab (here Quest) vs what you always bring in rightly in comparing with ACM data.



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#3 Michael Lustgarten

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Posted 14 November 2022 - 12:51 PM

Great, Michael, as usual!

I surely have missed the point but aren't all the studies you compare your longitudinal values with cross-sectional? You make the point I think for RDW but isn't the same from glucose and albumin too?

Beside that (surely my misunderstanding) good point as usual on reference of the lab (here Quest) vs what you always bring in rightly in comparing with ACM data.

 

Thanks albedo. Yes, I've compared my data against cross sectional data in all of the videos in the past, with a few exceptions (WBCs from the BLSA study, for ex., which is a longitudinal study). In theory, the proper comparison is my longitudinal data against other longitudinal studies, but as I mentioned in the video, the published cross-sectional data largely is the same as longitudinal with the difference being very large sample sizes in the cross-sectional data.


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#4 albedo

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Posted 14 November 2022 - 03:54 PM

Thank you. I am pretty sure you know the concept of "ageotype" from Snyder. He interestingly has a paper where he uses, as both of us, Levine's Phenotypic Age longitudinally from his cohort (see Fig 3-e attached)

 

Ahadi S, Zhou W, Schüssler-Fiorenza Rose SM, Sailani MR, Contrepois K, Avina M, Ashland M, Brunet A, Snyder M. Personal aging markers and ageotypes revealed by deep longitudinal profiling. Nat Med. 2020 Jan;26(1):83-90. doi: 10.1038/s41591-019-0719-5. Epub 2020 Jan 13. PMID: 31932806; PMCID: PMC7301912.

https://pubmed.ncbi....h.gov/31932806/

 

 

Attached File  Screenshot 2022-11-14 164903.jpg   41.54KB   0 downloads

"Phenotypic age regression on the chronological age of individuals (n = 43). The gray trend line is the overall regression line
for the cohort. The colored lines are the fitted regression lines for each individual."



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#5 Michael Lustgarten

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Posted 14 November 2022 - 06:06 PM

Yep, I'm familiar, thanks albedo. I'm grateful that people like Snyder exist, as there are few who track so many metrics!


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