Downsides of omega-3 supplementation (b/c they make the cell membrane more PUFA => more damaged)

Concern comes from

Also omega-3 doesn’t increase lifespan in ITP.

So many papers extol its positive effects, but I always wonder if there’s a downside… The raw percent of total fat that is omega-3 is usually not high…

In some animal studies, percent of cell that is omega 3 highly predicts lower lifespan

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Although the negative effects of increased unsaturation on longevity in humans is not clear and largely hypothetical at this stage, I think it’s an important factor to consider when determining how much omega-3 to get. Despite the various benefits of omega-3 over the shorter term, ever since I saw the clear inverse relationship between the membrane unsaturation index and life span of different species (including humans) long ago I have been more careful not to overdo my omega-3 intake. It’s also is one of the reasons I aim for a higher EPA/DHA ratio in the fish oil I take.

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Flaxseeds have terrible EPA/DPA ratio, yet Lustgarten just showed that they help for increasing his telomeres [they have other benefits too…]

From the total sum of all other papers I’ve read about flaxseeds, I’ve only seen “good things” not “bad things” (with the obvious caveat that nutrition research on foods that not many people eat is not representative and may not be controlling for confounders)

Flaxseeds are full of lignans and other phytochemicals that may explain their benefits…

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It is an N of 1, considering the fact that people get glucose spikes from different foods, many times the complete opposite foods, it could be the case for blood markers and its relation to food intake. Why is no one copying Lustgarten’s approach publicly here? ISn’t anyone aiming for greatness?

Have you seen his diet? I think very few could or would like to follow it. His age delta is no better than many in this forum have on very less stringent diets. I do admire his ability and willingness to track everything he eats. It is very informative.


I also admire his efforts to use food vs supplements. He has the patience of Job.

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You don’t have to eat his diet, it’s about following the data what makes your biomarkers and other measurements the healthiest. It’s most certainly different.
I might actually eat 400 grams of strawberries a day if I find correlations that they do improve my biomarkers and then when trying so it does. It’s just harder to stick to a diet where there is uncertainty that it works.

Yes, I think it’s the lignans that explain the benefits of flax seeds. They don’t even have fully formed EPA/DHA but merely it’s precursor alpha-linolenic acid.

Personally I wouldn’t do that. I think the biomarkers he measures are for the most part too limited in terms of detecting the desired effects from various foods and interventions. In addition I think the correlations he finds are most often not showing a cause and effect relationship. It’s an exception rather than the rule that the effectiveness of some intervention correlates in a causal manner with some specific blood test. Tracking works best when you know the likely cause and effect pathway and when it’s likely to be significant. An example is tracking changes in LDL cholesterol while taking a statin knowing well that statins act directly to reduce LDL cholesterol. Sure you could find a correlation between statin intake and something completely unrelated to cholesterol, but in such cases the relationship is likely to be caused by unknown confounders and it tells you very little about what’s going on and whether it’s having a beneficial effect or not.


What do you mean with this? Michael aims for the optimal range for ACM association and youthful biomarkers, this has to be worth something.

Regarding causality, that is established when he is testing the correlation by doing the change. Strawberries show a correlation to improved biomarkers, and after testing it it does, it suggest a causal relationship for him. Even if it still not causality, iterated over many foods and over time, if the biomarkers are good that suggest in general the approach is able to find causality since it works.

I mean that for most dietary items or supplements, there is no easily measured biomarker that will tell you whether it is improving or making your health worse. As an example, lets say Lustgarten were to take rapamycin and wanted to track whether it’s improving his health. The main desirable effect of rapamycin is increased autophagy and slowdown of aging. There is no blood test that will tell you whether it’s increasing autophagy or slowing down your aging. Lets take arginine as another example. Some people take the amino acid arginine and one of many reasons to do so is that it is used for synthesis of NO, which in turn is beneficial for the vasculature over the long term (NO production declines with age). There is no blood test that will tell you whether the arginine you ingest is increasing your NO significantly. If it was working it could show as a tiny non-significant reduction in blood pressure or as improved vascular flexibility many years down the line. These effects are not detectable with common blood tests. Truth is most of the blood tests really just give you some clues about the average effect that is occurring from the interventions. They rarely give you enough information to conclude that something is likely working or not working, unless they directly measure the target of the intervention like measuring LDL to determine whether a statin drug is working.

Yes, it is useful to use all-cause mortality data, and I do it too when analyzing my blood tests. However one must be aware of the limitations of this method. In many cases, blood test parameters are associated with mortality because of reverse causality. As an example, having very low muscle mass is associated with mortality, but that’s not necessarily because low muscle mass increases mortality. I think it’s more due to the fact that aging causes sarcopenia so the low muscle mass is more a result of rather than a cause of aging. Therefore, if you increase your muscle mass, you might not be improving or reversing your aging much, you might just as well be hiding the problem. An 80 year old frail man that starts using anabolic steroids to gain some muscle may appear healthier a year later but I would argue he is not healthier at all, except for in the narrow measure of muscle strength. Yet if you were to track his muscle mass and BMI you could wrongly conclude that his increased muscle mass and BMI is a sign that he has lower risk of mortality and has improved his health.

It’s a bit more tricky than that. It’s very hard to be certain of causality in most cases. Even if he were to do several tests with or without some intervention and would see a clear relationship between an intervention and some parameter, that still doesn’t necessarily imply causality. If we take the strawberry intake as an example, if it is correlated with X the strawberry intake might as well be correlated to something else that is correlated to both X and to strawberry intake. Unless you have a reasonable likely biochemical mechanisms by which strawberries could influence X then you don’t have a good basis for thinking the strawberries caused X at least not directly. One example here is that Lustgarten used to find correlation between his beta-carotene intake and his albumin level. His conclusion was that increased consumption of beta-carotene or carrots somehow caused the increase in albumin levels and that this was beneficial because lower albumin is associated with increased mortality. Now if there was a known mechanism by which beta-carotene influences albumin, this might be reasonable. But I have never heard of such a mechanism and Lustgarten didn’t mention any such mechanism either. Therefore it’s a stretch that it’s increasing albumin. There are so many other reasons that might explain this. Hell the beta-carotene, or something in the carrots, might even be interfering with the albumin blood test, giving falsely elevated test results. Another example, imagine someone that uses creatinine to estimate his kidney function. He changes something in his diet and supplement regimen and sees his creatinine drop a bit and thinks that whatever it is he did improved his kidney function. But that is just one of many possibilities. Slight dehydration can elevate creatinine a bit so anything that increases your hydration level at the time of the blood test could reduce your creatinine level giving you the impression that your kidney function has improved, while it didn’t improve at all.

The major problem with all this tracking is not only that the biomarkers don’t usually track the most important parameters, it’s the fact that even in cases where they do, the changes wouldn’t become apparent until after many years. As an example, kidney function declines very gradually with age and usually creatinine levels don’t start to decline much until a threshold is reached and significant decline in function has appeared. This means that your kidney function could go from 90% to 80% gradually without any change in creatinine. Any changes in creatinine that you see in the short term, like within months, are most likely not reflective of any changes in kidney health or function but a reflection of short term regulation. For a lot of important parameters the short term variation and within test variation is far larger than the gradual age-related change seen over several years making most short term fluctuations meaningless.

These are some of the reasons I base my longevity regimen mostly on reading the literature and estimating what is good or not. Blood tests and tracking has a minor role in determining what I do and I mainly interpret blood tests within the context of known biochemical effects of interventions.


I wouldn’t want to bet against striving to having youthful biomarkers or biomarkers in the optimal range for ACM, of course except for the obvious cases of reverse causality like for apoB. The important lesson might be to not overly rely on them for decision making regarding longevity interventions like rapamycin. Of course unless rapamycin for example would make the biomarkers become much worse, reaching some threshold where optimizing biomarkers wins over optimizing based on the scientific literature, and leading to stopping the usage of rapamycin, for example.

I am pretty agnostic about mechanisms, there is a lot of things we don’t know, strawberries might actually respond to a specific person based on their genetic makeup, etc, just like how drugs have different responses, and is distributed over a bell curve or something, the body/microbiome/etc is very complex. If Michael Lustgarten manages to keep optimal biomarkers with his approach, I don’t think it could be because of randomness, that seems unlikely to me. I don’t have particularly high certainty for Michael Lustgarten’s approach, but I still think there’s some value to be had there, it will be most interesting how his biomarkers will change over time.

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I was following you right until the end of your note. Your conclusion about blood tests is reasonable but that merely removes the best chance we had to assess improvement from a base of reasonable or normal health. I suppose we could still watch the blood for bad effects.

We have “how we feel” but that is fraught with self trickery. (Anybody remember the story about the guy in the 1920’s who drank radium water because it made him feel great?).

Relying on “studies” is better than relying on advertisements but no single study is worth much. And there isn’t much data on interactions among many simultaneous chemical interventions. And even the brightest researchers don’t really understand how something like rapamycin works.

How do you avoid a growing accumulation of interventions that have good studies on a standalone basis? Could your blood be fine and you feel good but still be doing yourself harm? This is my worry. I am searching for a program that keeps me away from slipping into unintended aggressiveness.

Thanks for any ideas.


I totally agree with you when you say there is so much we don’t know and strawberries might have an effect on a specific person based on their genes and etc. Blood tests are particularly interesting and valuable to try to determine individual responses. In that respect Lustgartens method is very useful and good.

I agree. One of my main criticism of his approach is that I would argue that we don’t know if he manages to keep optimal biomarkers with his approach. What I mean is that, sure, a lot of the biomarkers he measures appear to be close to optimal, but the biomarkers he’s measuring are very limiting because we’re only scratching the surface when it comes to biomarkers of aging. The biomarkers he measures are more biomarkers of health, not of age-related damage and dysfunction. A true biomarker of the slow process of aging would almost certainly not change from month to month but would take a much longer time to be detected. In most cases the gradual age-related change from one year to the next in a parameter is far smaller than all the other things that fluctuate from one test to the next like the intra individual variation, diurnal variation, and measurement errors.

Then again going mostly by studies instead of blood tests also has it’s downsides. One can certainly argue that even if one does a lot of research and then does what one considers best according to the evidence, one has no way of knowing whether it’s working or not. In the end people have to choose what method they like and are more confident in. If you like taking a lot of blood tests and comparing values to what appears to be optimal ranges and go from there then that can be a good approach for you. Then there is me who has spent tons of time researching aging and trust the conclusions of my research more than I trust the usefulness of the biomarkers that I can measure.


I agree that there hasn’t been enough time to evaluate how Michael’s approach is working for sure.

I don’t think it has to be one or the other, it’s possible to do both. But I totally understand if someone doesn’t see the value in doing all of the tracking, the blood tests, etc and skip that. For me personally I think if I don’t try and have somewhat of a system like Lustgarten, I’m just going to relax and take a PCSK9 inhibitor and some rapa or something and not really take this whole thing serious. Michael has also mentioned he wish he started tracking earlier. I guess it’s because more data make the conclusions better and also in the future allows the use of machine learning algorithms. We will see how Michael’s approach will change over time, I think he is quite dynamic and flexible. I am probably not going to follow this approach for long as it seems difficult, but so far I haven’t minded it too much.

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Doesn’t this have implications beyond omega-3 supplementation? For optimized cell membranes, focus on getting enough saturated fats while not overdoing it on PUFAs? Sort of points in the direction of the superiority of saturated fats in the diet perhaps. I’m not advocating anything, as saturated fats in abundance will increase most folks’ LDC-C, but if every cell in one’s body will have an optimized membrane as a result (which obviously contributes to overall cell health), it does makes one wonder…

There’s a lot to consider when choosing one’s diet and the more we learn the murkier it has become, at least for me.

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Even if you take a cc of fishoil per day, you are barely moving the needle on total PUFA intake, while lowering Triglyceride levels dramatically. Taking more than that makes no sense anyway. If your triglyceride levels are already low, you can consider cutting back on fish oil, but to reduce PUFA intake significantly you will need to focus elsewhere (avoiding cooking oils with PUFAs)

I take 500mg of DHA+EPA daily, and it lowered triglycerides from 330 ( common in diabetics) to under 100.

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That’s true. If one is concerned about the unsaturation index of fatty acids then even moderate doses of omega-3 have an effect. This is probably because omega-3 are more highly unsaturated than omega-6 fatty acids so even though their intake is low relative to the total amount of PUFAs they still have a fairly strong effect on the unsaturation. Here is a study that found that 3 g of EPA with 2 g of DHA increased the unsaturation index of muscle mitochondria in humans. Incorporation of Omega-3 Fatty Acids Into Human Skeletal Muscle Sarcolemmal and Mitochondrial Membranes Following 12 Weeks of Fish Oil Supplementation - PubMed

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on a sidenote, how do you guys who take flaxseed take it without it sticking to your lips/teeth etc.

had to switch to psyllium husk because I was tired of that stuff sticking in my mouth and then coming out on my computer screen when breathed onto it etc.

does it stick in shakes and that seems a bit cumbersome? I tried sucking it with a straw straight into my mouth which didn’t go so well

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That’s true. When relying on studies you have to read a lot of them. I rarely take some supplement that I haven’t spent at least a full work day researching and read dozens of studies on. It’s really time consuming.

That’s a good question. Yes you could absolutely feel fine and your blood tests could look good while some supplement you’re taking is harming you. You need a lot of trust in science and your abilities to analyze it and make good judgement to have confidence in what you’re doing. You also have to be flexible and accept that conditions can change so you need to be ready to change your mind if new research comes along that convinces you to do so. Regardless of the method people use, there is really no easy way to go about this.