Ending Aging-Related Diseases 2019: Lustgarten Presentation

In the first half of this presentation, I talk about my contribution to the gut-muscle axis in older adults, and in the second half, my personalized approach to optimal health!

Also, here’s the article that corresponds to the presentation:
https://www.leafscience.org/the-gut-microbiome-affects-muscle-strength-in-older-adults/

If you’re interested, please have a look at my book!

Michael Lustgarten

Ph.D, Physiology, University of Texas Health Science Center at San Antonio, 2009 B.S., Biochemistry, Queens College, 2003 B.A, English Textual Studies, 1994, Syracuse University

6 thoughts on “Ending Aging-Related Diseases 2019: Lustgarten Presentation

  1. Michael, That was a great presentation. You and I share the same goal and methods.

    I first learned in 2007 about microbial burden from Trevor Marshall and feel there really isn’t anybody out there looking at this as the largest cause of aging.

    You may want to participate in Josh Mittledorf’s clinical trial if you aren’t already.

    1. Hey Lee, that’s good to hear. You were onto microbial burden before me, that idea evolved out of my metabolomic work in aging. I looked for Mittledorf’s clinical trial online-it’s not funded by the NIH-do you have a link?

  2. Great presentation! You list the best predictors of aging by decreasing order of correlation. However, several metrics may be hard or impossible to modify through our personal actions. My question then is: which factors, in your opinion, are the most actionable? Again, by decreasing order of “return on investment”, if you have this information. Thanks!

    1. Thanks psavignac. I find all of the circulating biomarkers to be malleable, even the ones that have been published as being resistant to change. For ex., Lp(a). I couldn’t get it below ~100 for many years, but I wasn’t as serious about my diet or tracking it as I am now. Over the past 6 months, I tested it often, and in conjunction with dietary tracking, have been able to reduce it to a more manageable 70. That’s just 1 example, but with careful enough tracking (and predictive statistical modeling), I believe all of biology can be impacted, with only genetics being the limiting factor. That’s the best that can be done, for now…

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