Let's assume that's true-which data in the video do you disagree with, that low total TGs may be optimal for reducing CHD mortality risk, or that specific TGs are associated with an increased odds of living past 85y?
Excellent video. So many markers to track, though. Mike, in addition to the 25-30 or so blood markets you always present in your summary tables, and in addition to RHR, AHR, HRV, Vo2max, and strength, what would be your recommended top 3-5 or so biomarkers to track? I appreciate your points of view. I don't yet track NAD, telomeres, etc., but it is hard to know how to prioritize.
Thanks David. An argument can be made for RDW, as it's a major contributor to PhenoAge, but also glucose, hsCRP, albumin, and RBCs. That excludes kidney and liver function markers, and immune cells, though, which are also important.
@@conqueragingordietrying123 I put this in a comment below: Summing the species more or less is just applying the the statement "while triacylglycerols with >56 carbon or >3 double bonds were associated with lower all-cause mortality" from the Wang paper. That's OK for an average person in the cohort, but if your a long way from the average, it could break down. An example above is test 3, TAG16:0_40:8 which contributes to most of the highest sum, whereas TAG16:0_16:0_16:0 would not be within >56 carbon or >3 double bonds. Resolving all this would require looking at total TAGs or % TAGs, individual fatty acids, and probably other metabolites with one or two resolved fatty acids, plus doing some combinatorics on the TAGs. Maybe some interventional style fatty acid experiments. Doable with effort, correlations are likely to be messy for a while.
@@conqueragingordietrying123@ conqueragingordietrying1797 You'd have to admit, it's getting complicated and harder for anyone not turning their body into a longevity lab to expect the results you get.
@@conqueragingordietrying123 I'm in the camp that its the specific fatty acids of the TAGs, rather than the TAG itself, with the major reasoning being the robust evidence everywhere I've seen for lower total TGs being better for mortality. My take is TGs should be as low as possible, but of what there is, we maximise the percentage with the favourable fatty acids, and minimise the unfavourable ones.
I noticed that creatine is also identified in the upper left quadrant. Does this mean supplementing with creatine will increase the odds of living to 85?
It's an association (not causation), but based on that data, having relatively high circulating levels of creatine could be good for increasing the odds of living to > 85y. It may be a marker of muscle mass...
Thx prof.Lustgarten for this another great analysis. In terms of mortality، very probably the health benefit of maintaining glycerides levels under 40-50 mg/dL more than compensate for the risk of having those longevity promoting triglycérides , whose lab assessment is maybe costly and not available in certain countries, at a high level ?
Hi Abdelilah, definitely on keeping total TGs relatively low. For those who want more specificity, it's good to know that a subset of TGs may be important for health (or a marker of good health), which is a reason for making the video...
@@conqueragingordietrying123 The plot seems slightly skewed to the right, implying that the average trygliceride is more likely to cause harm than good. The question than becomes, if one has high good tryglicerides and low bad tryglicerides, should one still maintain total TGs low or one can go higher and that overall would lead to a lower mortality risk than just low total TG? Can this be verified by looking at other biomarkers? (If one has high good tryglicerides maybe there are positive correlations with other biomarkers?) And then you realize this is only a tiny tiny fraction of the possible things to optimize LOL. At least you are entertained for the next >70 years 😂
I really don't get it. Firs, what is the meaning of plotting longevity against all cause mortality, as one can be expressed by the other? If doing that at all, the deviance from the regression line is telling something for this plot. otherwise longevity or ACM alone is completely sufficient. I also do not understand the IOLLO way of counting to 3 . They indicate Tri-AcylGlycerides as 56:6, for instance, but then they list only 2 fatty acids, which yield the some of the respective species. Can you please help me out here? Finally, given what we know - and not know - about fatty acids metabolism, I think summing up across the "species" is not correct. I suggest to analyze each subtype for its own. Would you agree?
On a standard ACM plot, there's no indication of age at death. By plotting longevity vs ACM, it accounts for age at death There are eight 56:6 TG species in iollo's kit, not 2... I think they should be summed, as metabolomics can't generally differentiate between individual fatty acids found in TGs, but recognizes them as a singular species (i.e. 56:6, with less specificity in terms of which 3 FAs are included, as in the paper) iollo's kit can identify at least one of the FAs in the TGs, which is good news, relative to only identifying it as 56:6.
The longevity vs ACM plot is just a way of testing whether specific metabolites are related to one and not the other. As you can see they lie along a straight line through zero which indicates that "statistically" metabolites that favour ACM also favour longevity. Iollo can only resolve one of the 3 fatty acids, then the other two get summed together. This creates a combinatorial problem that Mike resolves by listing all combinations of 1 fatty acid + 2 iollo combined fatty acids as the sum of 3 fatty acids to interface with the paper which only reported the sum of the 3 fatty acids.
@@conqueragingordietrying123 On monnoo's last point: Summing the species more or less is just applying the the statement "while triacylglycerols with >56 carbon or >3 double bonds were associated with lower all-cause mortality" from the Wang paper. That's OK for an average person in the cohort, but if your a long way from the average, it could break down. An example above is test 3, TAG16:0_40:8 which contributes to most of the highest sum, whereas TAG16:0_16:0_16:0 would not be within >56 carbon or >3 double bonds. Resolving all this would require looking at total TAGs or % TAGs, individual fatty acids, and probably other metabolites with one or two resolved fatty acids, plus doing some combinatorics on the TAGs. Maybe some interventional style fatty acid experiments. Doable with effort, correlations are likely to be messy for a while
@@jamesgilmore8192 Hmm, isolating (and correlating) FAs that contribute most to each specific longevity-associated TG may throw away important data. On the other hand, summing them assumes that they're all important contributors, even if only a couple drive the signal. There isn't a perfect approach, and whatever error that is inherent is carried forward for every test...
@@jamesgilmore8192 thank you both fo the explanation. So, the IOLLO piece I understood, is a technical constraint, anyway amazing that they can do it. I got puzzled cuz i took the example given by Michael too literal. Anyway, if you think about the difference between O3, O6 and O7 vs saturated FA, or CLA, not even talking about the super-long FA. it appears to me that *just* summing them up is not a proper approach to deal with that technical gap. For the longevity against ACM, of course I understand that there is a statistical relation. If the risk for dying is reduced, longevity is increased, and if one lives longer, that person obviously did not die. It appears as if the authors do not trust those quantifications and seek for a confirmation. Of course, the Acm does not tell the odds of reaching 85 y, but thats not really the intention of that correlation. As mentioned, I think the residuals are much more interesting. There is also the question whether from such a chart positive and negative associations should be followed. For serine a mechanistic point can be made, for creatine certainly not (bad kidneys or high muscle mass?). Thus, there might be a survivor bias lurking. So, the question is, how much can we trust that plot? How could it be resolved that with the same odds for reaching 85y, the HR for ACM is drastically different, and vice versa....
@@conqueragingordietrying123 I hope they will add it, it seems promising although most of the data comes from researchers that are also selling it as a supplement and the most compelling of it is in cell culture instead of human RCTs so I am somehwat suspicious. I guess that if it is as good as they claim and the story of it being the most relevant aging marker for dolphins holds for humans, it would show quite clearly.
Hi Michael, I was curious to know what's your take on IF. Prof Fontana seems to stress that has to be done carefully as recent association stusies seems to caution on a generalised one size fit all IF. Meanwhile Prof Longo recently maintained that 12hrs IF routine is safe. Obviously these views are not mutually exclusive but I was wondering what's your take on this issue? thanks a lot
Hi @carlov5740, rather than general recommendations for IF, a major focus of the channel is tracking objective biomarkers to see if a given intervention is detrimental, neutral, or positive for health With that in mind, there's no pattern in my data for a daily fast (up to 18h on some days) being bad for health-related biomarkers. It also helps me in terms of sticking to daily calorie goals, which may be the biggest factor underlying it all...
Just eat like some clever russian siberians eat: 1. Milk porige with broken whole oatmel or wheat grain for breakfast at 7-8 in morning. GHI butter for garnish. 2, Some any dish with a meat and any garnish you want for dinner at 12-13 in middday. 3. All by one the onion, potato, carrot, beat and some cabbage chopped and boiled 30 minutes in some water and some wegetable oil added for supper at 17-18 in evening. And nothing else till next morning. All food must be not processed. Try it for nice health and no doctor to call.
Excellent segment
Thanks @KTPurdy!
Thanks!
It’s estimated that upwards of 80% of American adults are metabolically unhealthy so using them as a basis for comparison makes no sense.
Let's assume that's true-which data in the video do you disagree with, that low total TGs may be optimal for reducing CHD mortality risk, or that specific TGs are associated with an increased odds of living past 85y?
Thanks for this.
Excellent video. So many markers to track, though. Mike, in addition to the 25-30 or so blood markets you always present in your summary tables, and in addition to RHR, AHR, HRV, Vo2max, and strength, what would be your recommended top 3-5 or so biomarkers to track? I appreciate your points of view. I don't yet track NAD, telomeres, etc., but it is hard to know how to prioritize.
Thanks David. An argument can be made for RDW, as it's a major contributor to PhenoAge, but also glucose, hsCRP, albumin, and RBCs. That excludes kidney and liver function markers, and immune cells, though, which are also important.
Interesting and complex. The analysis is very tricky.
Why is it tricky, James?
@@conqueragingordietrying123 I put this in a comment below:
Summing the species more or less is just applying the the statement "while triacylglycerols with >56 carbon or >3 double bonds were associated with lower all-cause mortality" from the Wang paper. That's OK for an average person in the cohort, but if your a long way from the average, it could break down. An example above is test 3, TAG16:0_40:8 which contributes to most of the highest sum, whereas TAG16:0_16:0_16:0 would not be within >56 carbon or >3 double bonds. Resolving all this would require looking at total TAGs or % TAGs, individual fatty acids, and probably other metabolites with one or two resolved fatty acids, plus doing some combinatorics on the TAGs. Maybe some interventional style fatty acid experiments. Doable with effort, correlations are likely to be messy for a while.
@@jamesgilmore8192 Ah, which is which I've focused on specific TGs that add up to those indicated on the Odds of Reaching 85y Table...
@@conqueragingordietrying123@ conqueragingordietrying1797 You'd have to admit, it's getting complicated and harder for anyone not turning their body into a longevity lab to expect the results you get.
@@conqueragingordietrying123 I'm in the camp that its the specific fatty acids of the TAGs, rather than the TAG itself, with the major reasoning being the robust evidence everywhere I've seen for lower total TGs being better for mortality. My take is TGs should be as low as possible, but of what there is, we maximise the percentage with the favourable fatty acids, and minimise the unfavourable ones.
I noticed that creatine is also identified in the upper left quadrant. Does this mean supplementing with creatine will increase the odds of living to 85?
It's an association (not causation), but based on that data, having relatively high circulating levels of creatine could be good for increasing the odds of living to > 85y. It may be a marker of muscle mass...
From which paper is the first graphic of this video? The Nguyen et al paper you have linked doesn't contain it.
It's in the supplementary data...
At 1:20 in the video, the graph shows three labeled triglycerides(C56:8, C58:11, C58:7) that were not part of your tracking later. Why was that?
Hi @doughughes257, 56:8 is included on my tracking list, but not the others because (unfortunately) they're not included on iollo's list
Thx prof.Lustgarten for this another great analysis.
In terms of mortality، very probably the health benefit of maintaining glycerides levels under 40-50 mg/dL more than compensate for the risk of having those longevity promoting triglycérides , whose lab assessment is maybe costly and not available in certain countries, at a high level ?
Hi Abdelilah, definitely on keeping total TGs relatively low. For those who want more specificity, it's good to know that a subset of TGs may be important for health (or a marker of good health), which is a reason for making the video...
@@conqueragingordietrying123 The plot seems slightly skewed to the right, implying that the average trygliceride is more likely to cause harm than good. The question than becomes, if one has high good tryglicerides and low bad tryglicerides, should one still maintain total TGs low or one can go higher and that overall would lead to a lower mortality risk than just low total TG?
Can this be verified by looking at other biomarkers? (If one has high good tryglicerides maybe there are positive correlations with other biomarkers?)
And then you realize this is only a tiny tiny fraction of the possible things to optimize LOL. At least you are entertained for the next >70 years 😂
Is there a test that I can get from my doctor?
Afaik, it's only available through companies that offer metabolomic analysis. That link is in the video's description
triglycerides are synthsized from carbohydrates (diet)? High intake of starchy foods.
Triglycerides = glycerol bound to 3 fatty acids
Is it a marker of excessive carb or fat intake?
Overconsumption of calories is more likely
@@conqueragingordietrying123But very often low carbers have high cholesterol but normal triglycerides. Which is something they like to emphasize
Another excellent one! Ill reach out to set up a podcast with you soon!
I really don't get it. Firs, what is the meaning of plotting longevity against all cause mortality, as one can be expressed by the other? If doing that at all, the deviance from the regression line is telling something for this plot. otherwise longevity or ACM alone is completely sufficient.
I also do not understand the IOLLO way of counting to 3 . They indicate Tri-AcylGlycerides as 56:6, for instance, but then they list only 2 fatty acids, which yield the some of the respective species. Can you please help me out here?
Finally, given what we know - and not know - about fatty acids metabolism, I think summing up across the "species" is not correct. I suggest to analyze each subtype for its own. Would you agree?
On a standard ACM plot, there's no indication of age at death. By plotting longevity vs ACM, it accounts for age at death
There are eight 56:6 TG species in iollo's kit, not 2...
I think they should be summed, as metabolomics can't generally differentiate between individual fatty acids found in TGs, but recognizes them as a singular species (i.e. 56:6, with less specificity in terms of which 3 FAs are included, as in the paper)
iollo's kit can identify at least one of the FAs in the TGs, which is good news, relative to only identifying it as 56:6.
The longevity vs ACM plot is just a way of testing whether specific metabolites are related to one and not the other. As you can see they lie along a straight line through zero which indicates that "statistically" metabolites that favour ACM also favour longevity.
Iollo can only resolve one of the 3 fatty acids, then the other two get summed together. This creates a combinatorial problem that Mike resolves by listing all combinations of 1 fatty acid + 2 iollo combined fatty acids as the sum of 3 fatty acids to interface with the paper which only reported the sum of the 3 fatty acids.
@@conqueragingordietrying123 On monnoo's last point:
Summing the species more or less is just applying the the statement "while triacylglycerols with >56 carbon or >3 double bonds were associated with lower all-cause mortality" from the Wang paper. That's OK for an average person in the cohort, but if your a long way from the average, it could break down. An example above is test 3, TAG16:0_40:8 which contributes to most of the highest sum, whereas TAG16:0_16:0_16:0 would not be within >56 carbon or >3 double bonds. Resolving all this would require looking at total TAGs or % TAGs, individual fatty acids, and probably other metabolites with one or two resolved fatty acids, plus doing some combinatorics on the TAGs. Maybe some interventional style fatty acid experiments. Doable with effort, correlations are likely to be messy for a while
@@jamesgilmore8192 Hmm, isolating (and correlating) FAs that contribute most to each specific longevity-associated TG may throw away important data. On the other hand, summing them assumes that they're all important contributors, even if only a couple drive the signal. There isn't a perfect approach, and whatever error that is inherent is carried forward for every test...
@@jamesgilmore8192 thank you both fo the explanation. So, the IOLLO piece I understood, is a technical constraint, anyway amazing that they can do it. I got puzzled cuz i took the example given by Michael too literal. Anyway, if you think about the difference between O3, O6 and O7 vs saturated FA, or CLA, not even talking about the super-long FA. it appears to me that *just* summing them up is not a proper approach to deal with that technical gap.
For the longevity against ACM, of course I understand that there is a statistical relation. If the risk for dying is reduced, longevity is increased, and if one lives longer, that person obviously did not die. It appears as if the authors do not trust those quantifications and seek for a confirmation. Of course, the Acm does not tell the odds of reaching 85 y, but thats not really the intention of that correlation. As mentioned, I think the residuals are much more interesting. There is also the question whether from such a chart positive and negative associations should be followed. For serine a mechanistic point can be made, for creatine certainly not (bad kidneys or high muscle mass?). Thus, there might be a survivor bias lurking. So, the question is, how much can we trust that plot? How could it be resolved that with the same odds for reaching 85y, the HR for ACM is drastically different, and vice versa....
At 6:21 the video skips forward and there’s missing content ???
Hi @tylermcgonigal6031, just a minor YT glitch, no missing content...
Does anyone know if any specific saturated fatty acid has been associated with lower all cause mortality?
Yep, very long chain FAs:
www.ncbi.nlm.nih.gov/pmc/articles/PMC10795918/
@@conqueragingordietrying123 That paper might be suggesting peanuts, rosemary, cloves, macadamias, and maybe portobello mushrooms.
Do you have any data on the fatty acid c15:0?
Unfortunately, iollo's kit doesn't currently include it
@@conqueragingordietrying123 I hope they will add it, it seems promising although most of the data comes from researchers that are also selling it as a supplement and the most compelling of it is in cell culture instead of human RCTs so I am somehwat suspicious. I guess that if it is as good as they claim and the story of it being the most relevant aging marker for dolphins holds for humans, it would show quite clearly.
Hi Michael, I was curious to know what's your take on IF. Prof Fontana seems to stress that has to be done carefully as recent association stusies seems to caution on a generalised one size fit all IF. Meanwhile Prof Longo recently maintained that 12hrs IF routine is safe. Obviously these views are not mutually exclusive but I was wondering what's your take on this issue? thanks a lot
Hi @carlov5740, rather than general recommendations for IF, a major focus of the channel is tracking objective biomarkers to see if a given intervention is detrimental, neutral, or positive for health
With that in mind, there's no pattern in my data for a daily fast (up to 18h on some days) being bad for health-related biomarkers. It also helps me in terms of sticking to daily calorie goals, which may be the biggest factor underlying it all...
@@conqueragingordietrying123 thanks Michael
Just eat like some clever russian siberians eat:
1. Milk porige with broken whole oatmel or wheat grain for breakfast at 7-8 in morning. GHI butter for garnish.
2, Some any dish with a meat and any garnish you want for dinner at 12-13 in middday.
3. All by one the onion, potato, carrot, beat and some cabbage chopped
and boiled 30 minutes in some water and some wegetable oil added for supper at 17-18 in evening.
And nothing else till next morning. All food must be not processed.
Try it for nice health and no doctor to call.
Hi @AndroidSon, I prefer greater specificity, with an objective, data-driven approach to diet
And where can I find those clever Russian Siberians on the Rejuvenation Olympics leader board?
@@HvdHaghen
On the planet Earth somewhere at!