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  1. Today
  2. Very interesting: Though I practice some “convenience CE” I more formally maintain low dietary BCAA and (M+C). So this new publication piqued my interest. It is testimony to the mounting documented crosstalk between CE and geroprotective nutrient sensing metabolic pathways. https://www.nature.com/articles/s41586-019-1503-x
  3. Yesterday
  4. https://www.ahajournals.org/doi/10.1161/JAHA.119.012865 just published and me thinks a good study because they controlled for so many confounders that are often associated with plant based eaters. IAC, the association was as you might expect the more whole plant foods that are eaten the lower the cardiovascular mortality as well as overall mortality
  5. Front Endocrinol (Lausanne). 2019; 10: 27. Published online 2019 Feb 1. doi: 10.3389/fendo.2019.00027 PMCID: PMC6367275 PMID: 30774624 ROLE of IGF-1 System in the Modulation of Longevity: Controversies and New Insights From a Centenarians' Perspective Giovanni Vitale,1,2,* Giuseppe Pellegrino,3 Maria Vollery,4 and Leo J. Hofland5 Author information Article notes Copyright and License information Disclaimer Go to: Abstract Human aging is currently defined as a physiological decline of biological functions in the body with a continual adaptation to internal and external damaging. The endocrine system plays a major role in orchestrating cellular interactions, metabolism, growth, and aging. Several in vivo studies from worms to mice showed that downregulated activity of the GH/IGF-1/insulin pathway could be beneficial for the extension of human life span, whereas results are contradictory in humans. In the present review, we discuss the potential role of the IGF-1 system in modulation of longevity, hypothesizing that the endocrine and metabolic adaptation observed in centenarians and in mammals during caloric restriction may be a physiological strategy for extending lifespan through a slower cell growing/metabolism, a better physiologic reserve capacity, a shift of cellular metabolism from cell proliferation to repair activities and a decrease in accumulation of senescent cells. Therefore, understanding of the link between IGF-1/insulin system and longevity may have future clinical applications in promoting healthy aging and in Rehabilitation Medicine.
  6. Ron, I could not read the full article by Burgers et al. since presently sci-hub is not reachable from here. Judging by the plots only, even at 150 ng/ml the hazard ratio is pretty high for cancer, whereas it's zero for CVD. I must confess the scale on the Y axis makes me wonder, it reads log hazard ratio but there is a zero and negative numbers which clashes with the definition of logarithms. So I dont't know the exact parameter and if there is some tricky scale effects which amplifies the vertical scale. Higher IGF-1 is ostensibly beneficial to the nervous system and skeletal muscle-system, but I know no literature about that. Very regular exercise according to Longo may substitute higher IGF-1 to boost muscle protein synthesis and avoid sarcopenia. In such a way it would be possible not to increase protein when over 65. In theory, at least. Obviously, familiarity with cancer or previous cancers would suggest strongly to try and do whatever is possible to keep IGF-1 at the optimum range of 100-120 mg/ml, if it is possible at all to manage IGF-1 in such an accurate fashion (probably not). Also, if familiarity or previous cancers are present, it makes sense to adopt a more accurate risk level analyzing IGFBP and free IGF-1, if we have data, benchmarks, optimum ranges about them to guide us in a preventional scheme. Further confounding factors may be IGF-1 receptor sensitivity and activation of the post-receptor pathway. An optimum plasma IGF-1 may turn out to result in high IGF-1 signaling effects (for example in the mTOR pathway) in the presence of high receptor sensitivity and the other way around Maybe I'll have to listen again to the Peter Attia podcast with Barzilai, where they discuss IGF-1 and longevity. I remember Barzilai said that the lower IGF-1 in some more longeve people may be reverse causation (they are not more longeve because of the low IGF-1 but they are approaching death and the drop in IGF-1 is a consequence of that)
  7. Ron Put

    Jeanne Calment was a fraud?!!

    Tom, your skepticism seems to me a bit too much like a "god is in the gaps" argument. There is enough data at this point to establish some basic probabilities. "Probably" is a key word in life, as well as genetics, period. To give another analogy, If you wear a seat belt and have airbags in your car, your chances of surviving a crash generally increase compared to someone who does not. But there are specific instances where these safety measures may not work, and even be detrimental. For instance, under very specific circumstances, people of slight stature, may even receive more damage by such safety devices than from a particular crash. If I understand your absolutist argument, you should be waiting until we have "smart" materials and safety devices which adapt to an individual's physical characteristics AND the conditions. AND have absolutely no error rate.... And yet, you appear to throw your skepticism out of the window the moment you are presented with a PR blurb touting an "app that makes it easy for everyone to understand the right foods for their unique metabolism in order to improve long-term health and manage weight more easily." Or, the moment you see a BBC headline proclaiming that a quarter of a million CENTENARIANS have gone missing in Japan.... 😄
  8. Hi Matt! That's definitely true for me. I began CR in April, 1996. -- Saul
  9. TomBAvoider

    Jeanne Calment was a fraud?!!

    replacing vegetables with bacon and drinking a bottle of wine a day is probably not a wise decision for anyone That "probably" does a lot of work there, Ron. If you wanted something more definite - and about equally useful as your observation - you could have said "replacing vegetables with arsenic and a gunshot to the head is probably not a wise decision for anyone". But if instead we move to a real-life scenario, it may in fact be that someone will do much better by replacing those F&V with fat in a more high fat and very low carb diet. Those are the kind of diets that are studied, and we know that for some that is more effective - again, no one size fits all, even with F&V. Dean, I agree with Pollan's maxim, but I think my point rather is that compared to, say, ten years ago, I am far less excited by nutritional studies - at this point I just think that those results are not terribly relevant to me as an individual, as I figure it's purely a matter of chance whether they apply to me or not. In other words, my general level of doubt has escalated the older I get - it doesn't mean that I therefore jump to some kind of opposite conclusion, rather, that I hold my opinions much more tentatively and with much less conviction compared to a decade or two ago. And a corollary to that - I am equally doubtful of the certitude of others in these matters, which might result in arguments on these boards :)
  10. Dean Pomerleau

    Jeanne Calment was a fraud?!!

    That seems like a very sensible approach to determining what to eat. It is pretty similar to my own dietary practices and I suspect most other people around here. As far as I can tell about the only significant thing about the "common wisdom" that has changed in the nearly 20 years we've been chatting about diet and CR is the switch to a much reduced amount of protein - from the early days when it thought that the macronutrient ratio of the Zone Diet (with 30% of calories from protein protein) was the right way to eat for CR folks trying to maximize health and longevity. I think a pithy summary is Michael Pollan's maxim - Eat whole foods, mostly plants and not too much. --Dean
  11. Ron Put

    Jeanne Calment was a fraud?!!

    Looking at the Promethease description for rs4977574, it states: "Some studies - but not others - report a slightly increased risk for myocardial infarction." While this points to an interesting aberration, replacing vegetables with bacon and drinking a bottle of wine a day is probably not a wise decision for anyone, based on preponderance of all available evidence. Humans are made up of more than rs4977574 and my guess is that other factors may be at play as well. Here is something else to ponder: "RESULTS: There were 925 cases with CAD and 634 without CAD enrolled in the present study. The G allele conferred a significant increase in risk of CAD (odds ratio = 1.47, P = 0.003 in the dominant model; odds ratio = 1.36, P = 0.018 in the recessive model). During a median of 11 years (inter-quartile range between 5.2 and 12.5 years) of follow-up, neither the total nor the cardiovascular mortality was different among CAD subjects with different genotypes. Using Cox regression analysis, genotypes of rs4977574 still failed to predict cardiovascular mortality (hazard ratio = 1.25, P = 0.138 in the dominant model; hazard ratio = 1.05, P = 0.729 in the recessive model). CONCLUSIONS: The rs4977574 at chromosome 9p21 is associated with presence of CAD in Han Chinese. However, rs4977574 could not predict cardiovascular mortality in these CAD subjects during the eleven-year period of the study." https://www.ncbi.nlm.nih.gov/pubmed/24804228?dopt=Abstract
  12. TomBAvoider

    Jeanne Calment was a fraud?!!

    Dean, thank you for your very reasonable response. I agree that obviously we operate in a world of imperfect information and imperfect tools. How do we formulate a strategy in such an environment? My approach is really a very traditional one, the same as utilized in most longevity studies in humans: biomarkers. I have regular blood tests (quarterly in the last 18 months, although that will be tapering off to once yearly) and I use a glucometer daily. I have attempted to modify my diet and see what impact they may have on biomarkers. Of course, this is extremely hazy as there are so many moving parts that it's extremely difficult to pin down any particular variable as responsible - f.ex. I lowered my protein intake in an effort to lower BUN, and that worked, but I have no idea if that wasn't confounded by a thousand other things that were going on at the same time, like exercise changes etc. I did that in response to my taking a statin as it can be hard on the kidneys and liver so I thought I'd do all I can to get good liver and kidney numbers through diet and exercise. Given how crude those tools are and how many variables there are, it's really groping in the dark. But it's the best I have. In this context, I pay much less attention to nutritional studies, but rather follow a few very simple principles. My thinking is based on this: https://jamanetwork.com/journals/jama/fullarticle/2673150 The study put people on different macronutrient diets, but took pains to use only the highest quality ingredients (to avoid quality of food disputes) and the conclusion was that in aggregate it's impossible to point to any one as superior - however the flip side of it is that some people did very well on one and very poorly on another, and there was no way to predict who would do what. There was no one "best" diet. Consequently, the lead researcher reached the conclusion that rather than attempt to follow any particular diet, it's better to follow a very few crude principles, as he outlines in this 4-minute video: Although there is no "best diet" - ultimately, he boils down the principles to just three: cut out added sugar, refined grains and take in tons of F&V. This emphasis of the third principle on F&V is of course highly ironic given the previous study we just discussed, where evidence shows that people respond differently even to F&V. Which only says, we may know even less than the 3 principles Gardner outlines. Still, I take that as a good baseline for a generalized approach, always keeping in mind that it may prove wrong at some point - hence, I use my glucometer, and if I find a given food is suboptimal, I cut if off, no matter its reputation (in my case bananas - supposedly a good fruit!).
  13. Good points and data, mccoy. I am still unsure I grasp the data, or at least am not entirely comfortable with what I am grasping from the data. Part of it may be my confusion of what constitutes "high" levels in a lot of the studies (apart from the Longo studies). From what I read, it would appear that higher IGF-1 levels are beneficial, up to close to 200 ng/ml, as long as one does not have cancer. If cancer is present, then IGF-1 is detrimental. Yet other studies find no relation between IGF-1 and longevity, unless too low or too high. Even looking at the levels in Fig. 2 above, the A/A homozygous subjects show about 200 ng/ml on average at the age of 75-85, which is actually rather high for that age (kind of like Okinawans having higher levels of testosterone than the general population). Again, this is likely my own confirmation bias talking, but the questions it rises are still valid, I think.
  14. Low 24-hour core body temperature as a thrifty metabolic trait driving catch-up fat during weight regain after caloric restriction. Calonne J, Arsenijevic D, Scerri I, Miles-Chan JL, Montani JP, Dulloo AG. Am J Physiol Endocrinol Metab. 2019 Aug 20. doi: 10.1152/ajpendo.00092.2019. [Epub ahead of print] PMID: 31430205 Abstract The recovery of body weight after substantial weight loss or growth retardation is often characterized by a disproportionately higher rate of fat mass vs lean mass recovery, with this phenomenon of 'preferential catch-up fat' being contributed by energy conservation (thrifty) metabolism. To test the hypothesis that a low core body temperature (Tc) constitutes a thrifty metabolic trait underlying the high metabolic efficiency driving catch-up fat, the Anipill® system - with the telemetry capsules implanted in the peritoneal cavity - was used for continuous monitoring of Tc for several weeks in a validated rat model of semistarvation-refeeding in which catch-up fat is driven solely by suppressed thermogenesis. In animals housed at 22°C, 24h Tc was reduced in response to semistarvation (-0.77°C, p<0.001), and remained significantly lower than in controls during the catch-up fat phase of refeeding (-0.27°C on average, p<0.001); the lower Tc during refeeding being more pronounced during the light phase than during the dark phase of the 24h cycle (-0.30°C vs -0.23°C, p<0.01), and with no between-group differences in locomotor activity. A lower 24h Tc in animal showing catch-up fat was also observed when the housing temperature was raised to 29°C (i.e. at thermoneutrality). The reduced energy cost of homeothermy in response to caloric restriction persists during weight recovery, and constitutes a thrifty metabolic trait that contributes to the high metabolic efficiency that underlies the rapid restoration of the body's fat stores during weight regain, with implications for obesity relapse after therapeutic slimming and the pathophysiology of catch-up growth. KEYWORDS: Thermogenesis; Thrifty phenotype; caloric restriction; catch-up growth; obesity Longitudinal analysis of the impact of loneliness on cognitive function over a 20-year follow-up. Wang H, Lee C, Hunter S, Fleming J, Brayne C; CC75C Study Collaboration. Aging Ment Health. 2019 Aug 20:1-7. doi: 10.1080/13607863.2019.1655704. [Epub ahead of print] PMID: 31429312 Abstract Background: Loneliness and cognitive impairment are both commonly experienced by older old people, but evidence for the association between these has been inconsistent. Moreover, most evidence has been cross-sectional in nature and largely based on studies with relatively young later life age groups rather than 'the oldest old'. We aimed to test the potential impact of loneliness amongst older old people on their cognitive function over a 20-year period. Method: Data were drawn from wave 3 to wave 10 of the Cambridge City over-75s Cohort (CC75C) study. The impact of loneliness on transition between normal and impaired cognitive states was examined by multi-state modelling. The associations between loneliness changes and cognitive function decline were tested by using generalized estimating equation (GEE) with an independent working correlation structure. Missing data were imputed by using multiple imputation chained equations. Results: At wave 3, 713 participants were interviewed, of whom 657 (92%) had Mini-Mental State Examination (MMSE) assessments. Of individuals who had an MMSE score, approximately one quarter reported feeling lonely, and another 16% felt slightly lonely. The prevalence of feeling lonely or slightly lonely varied between waves. Results from multi-state modelling indicated that loneliness was not related to cognitive function transitions, and results from the GEE model showed that loneliness was not significantly associated with cognitive function decline after adjusting for cohort effects, follow-up time, sex, education, and interaction terms for sex, education and time. Conclusions: Loneliness did not exert long-term harmful effects on cognitive function in the oldest old. KEYWORDS: Loneliness; cognition; longitudinal analysis; older people The Effect of Pharmaceutical Innovation on Longevity: Patient Level Evidence from the 1996-2002 Medical Expenditure Panel Survey and Linked Mortality Public-use Files. Lichtenberg FR. Forum Health Econ Policy. 2013 Jan 1;16(1):1-33. doi: 10.1515/fhep-2012-0032. PMID: 31419866 Abstract This study uses patient-level data to analyze the effect of technological change embodied in pharmaceuticals on the longevity of elderly Americans. Previous patient-level studies could not control for important patient attributes such as education, income, and race; they did not provide estimates of the effect of using newer drugs on life expectancy, or of the overall cost-effectiveness of new drugs relative to old drugs; and they were not based on nationally representative samples of individuals. Our data, primarily derived from the Medical Expenditure Panel Survey and the Linked Mortality Public-use Files, enable us to overcome those limitations. We investigate the effect of the vintage (year of U.S. Food and Drug Administration approval) of the prescription drugs used by an individual on his or her survival and medical expenditure, controlling for a number of demographic characteristics and indicators and determinants of health status. When we control only for age, sex, and interview year, we estimate that a 1-year increase in drug vintage increases life expectancy by 0.52%. Controlling for a much more extensive set of other attributes (the mean year the person started taking his or her medications, and dummy variables for activity limitations, race, education, family income as a percent of the poverty line, insurance coverage, Census region, body mass index, smoking, and more than 100 medical conditions) has virtually no effect on the estimate of the effect of drug vintage on life expectancy. Between 1996 and 2003, the mean vintage of prescription drugs increased by 6.6 years. This is estimated to have increased the life expectancy of elderly Americans by 0.41-0.47 years. This suggests that not less than two-thirds of the 0.6-year increase in the life expectancy of elderly Americans during 1996-2003 was due to the increase in drug vintage. The 1996-2003 increase in drug vintage is also estimated to have increased annual drug expenditure per elderly American by $207, and annual total medical expenditure per elderly American by $218. This implies that the incremental cost-effectiveness ratio (cost per life-year gained) of pharmaceutical innovation was about $12,900. This estimate of the cost per life-year gained from the use of newer drugs is a small fraction of leading economists' estimates of the value of (willingness to pay for) an additional year of life. It is also consistent with estimates from clinical trials. KEYWORDS: innovation; longevity; mortality; pharmaceuticals; prescription drugs Platelet Indices and Risk of Death and Cardiovascular Events: Results from a Large Population-Based Cohort Study. Patti G, Di Martino G, Ricci F, Renda G, Gallina S, Hamrefors V, Melander O, Sutton R, Engström G, De Caterina R, Fedorowski A. Thromb Haemost. 2019 Aug 20. doi: 10.1055/s-0039-1694969. [Epub ahead of print] PMID: 31430798 Abstract Studies evaluating the relationship between platelet indices and cardiovascular (CV) outcomes yielded conflicting results. We assessed the incidence of adverse events according to baseline quintiles of platelet indices in the prospective cohort of the Malmö Diet and Cancer Study. A total of 30,314 individuals (age 57 ± 8 years) were followed for a median of 16 years (468,490 person-years). Outcome measures included all-cause death, CV death, myocardial infarction (MI), and ischemic stroke. The fifth quintile of platelet count (> 274.6 × 109/L) was associated with higher incidence of all-cause death (hazard ratio {HR} 1.20, 95% confidence interval [CI] 1.09-1.32, p < 0.001), CV death (HR 1.19, 95% CI 1.00-1.42; p = 0.044), MI (HR 1.32, 95% CI 1.12-1.54; p = 0.001), and ischemic stroke (HR 1.27, 95% CI 1.08-1.50, p = 0.004) compared with the first quintile (≤ 185 × 109/L), and also associated with a lower survival, regardless of previous history of MI (p for interaction = 0.58) or stroke (p for interaction = 0.42). In the highest quintile, history of stroke had a higher risk of CV death (HR 3.18, 95% CI 1.54-6.54) compared with no previous stroke (HR 1.12, 95% CI 0.96-1.31). The risk of MI and stroke was greatest in the fifth quintile, regardless of previous MI or previous stroke, respectively. The risk of all adverse events was similar across different quintiles of mean platelet volume. In conclusion, elevated platelet count is associated with higher mortality and risk of CV events, regardless of previous MI and stroke. Platelet count may thus be a useful marker for further stratification of CV risk, and especially of death. Protective Effects of Dietary MUFAs Mediating Metabolites against Hypertension Risk in the Korean Genome and Epidemiology Study. Lee H, Jang HB, Yoo MG, Chung KS, Lee HJ. Nutrients. 2019 Aug 16;11(8). pii: E1928. doi: 10.3390/nu11081928. PMID: 31426326 [pdf availed from PMID site.] Abstract BACKGROUND AND AIMS: Metabolites related to dietary factors can be used to identify biological markers to prevent metabolic disease. However, most studies have been conducted in the United States and Europe, and those in the Asian region are limited. We investigated the effects of dietary monounsaturated fatty acids (MUFAs) and metabolites on new-onset hypertension in the Korean Genome and Epidemiology Study. METHOD AND RESULTS: A total of 1529 subjects without hypertension were divided into tertiles of dietary MUFAs intake. After a 4-year follow-up, 135 serum metabolites were measured using the AbsoluteIDQ p180 kit. During the 4-year follow-up period, 193 new-onset hypertension incidences were observed. The highest MUFAs intake group was inversely associated with the risk of hypertension compared with the lowest MUFAs intake group (odds ratio (OR) = 0.49, (95% confidence interval (CI) = 0.29-0.82)). Of the 135 metabolites, eight were significantly associated with MUFAs intake. Phosphatidylcholine-diacyl (PC aa) C 38:1 and hydroxysphingomyelin (SM OH) C 16:1 were associated with a decrease in hypertension risk (PC aa C 38:1, OR = 0.60 (95% CI = 0.37-0.96); SM OH C 16:1, OR = 0.42 (95% CI = 0.20-0.90)). The highest MUFAs intake group had a significantly decreased risk of hypertension, even considering PC aa C 38:1 and SM (OH) C 16:1 as a mediator. CONCLUSION: We confirmed that dietary MUFAs intake, and PC aa C 38:1 and SM (OH) C 16:1 had protective effects against hypertension. Furthermore, high MUFAs intake combined with PC aa C 38:1 and SM (OH) C 16:1 has the most significant effect on reducing the risk hypertension. KEYWORDS: hypertension; metabolites; monounsaturated fatty acid /MUFAs
  15. Hi All, I found this to be an incredibly enjoyable Q & A from Dr. Greger. His energy is infectious!
  16. Dean Pomerleau

    Jeanne Calment was a fraud?!!

    Nice find Tom. I'd completely forgotten about that one. That is the kind of evidence (and astute analysis 🙂) I was looking for from you. First, it should be noted that the study [1] that I analyzed in that thread didn't find vegetables to be bad health-wise for anyone - simply that they didn't appear beneficial for people who carry a particular allele the way they were for others without the allele with respect to one particular health outcome (cardiovascular disease). But that still leaves the strong (even likely) possibility that the people with the allele who benefit little from veggies would fair even worse when it comes to CVD if they substituted veggies for other foods that nutrition science has found to be unhealthy (e.g. processed meats, refined carbs). Not to mention the fact that they would very like fair worse when it comes to other health outcomes like cancer or diabetes if they eliminated veggies in favor of those other, generally recognized as unhealthy foods. Yes, exactly. Or maybe some other genetic or environmental factor makes the results of [1] irrelevant for you or me specifically. I agree that "N of 1" medicine would likely be very helpful. If I were a woman I'd like to know if I had the BRCA gene which dramatically elevates risk of breast and ovarian cancer so I could consider taking proactive measures or at least monitor for cancer very carefully. Epistemic humility is a good thing, and certainly warranted in the case of nutrition, particularly when it comes to interpreting and applying studies done in animals, or people very different along various axes from ourselves. But until we each have medical nanobots swimming through our bloodstreams assessing the impact of every specific food and environmental factor on our personal risk of CVD, cancer, dementia, eczema, fatty liver, etc, it seems like controlled studies of the correlations between foods and health outcomes is all we've got. We've got to eat something, and unless you're advocating that we abandon the scientific method entirely, we have to base our food choices on the data we've got. Saying there just isn't enough evidence from nutrition science to believe that eating vegetables will be better for you personally than eating say hot dogs (obviously an extreme example), seems like a degree of skepticism that won't serve anyone very well. I see Ron's analogy as an apt one here. There are some people with genes that make them much more resistant to cancer than others, allowing them to smoke with abandon and still live to 100 (e.g. George Burns). We know this to be the case, but we don't yet have the knowledge or the tools to tell if a particular person is so lucky. In light of this uncertainty, would you suggest we should take all the studies showing that smoking causes cancer in the general population "with a metric ton of salt" and light up a cigar, gambling you might be one of the lucky ones? Or would you instead use some sort of baysian reasoning to predict your likelihood of cancer will go up if you smoke, or if you eat hot dogs instead of vegetables? I personal would (and do) opt for the latter, baysian approach, knowing full well I might be an outlier, or the study may have had fatal flaws that I'm not aware of, or that I might get hit by a bus tomorrow, meaning all my efforts to maximize my probability of a long and healthy life based on the available science will be for nothing. Personalized medicine sounds terrific, but in the meantime we've got to make choices based on the available data. I suspect your feel (and behave) in the same way, and that we aren't as different as it might seems. But I'm curious about how you see things. --Dean ------------ [1] BMC Med Genet. 2014 Dec 31;15(1):1220. [Epub ahead of print] The chromosome 9p21 variant interacts with vegetable and wine intake to influence the risk of cardiovascular disease: a population based cohort study. Hindy G, Ericson U, Hamrefors V, Drake I, Wirfält E, Melander O, Orho-Melander M. Full Text: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4331503/pdf/12881_2014_Article_138.pdf Abstract BackgroundChromosome 9p21 variants are associated with cardiovascular disease (CVD) but not with any of its known risk markers. However, recent studies have suggested that the risk associated with 9p21 variation is modified by a prudent dietary pattern and smoking. We tested if the increased risk of CVD by the 9p21 single nucleotide polymorphism rs4977574 is modified by intakes of vegetables, fruits, alcohol, or wine, and if rs4977574 interacts with environmental factors on known CVD risk markers.MethodsMultivariable Cox regression analyses were performed in 23,949 individuals from the population-based prospective Malmö Diet and Cancer Study (MDCS), of whom 3,164 developed CVD during 15 years of follow-up. The rs4977574 variant (major allele: A; minor allele: G) was genotyped using TaqMan® Assay Design probes. Dietary data were collected at baseline using a modified diet history method. Cross-sectional analyses were performed in 4,828 MDCS participants with fasting blood levels of circulating risk factors measured at baseline.ResultsEach rs4977574 G allele was associated with a 16% increased incidence of CVD (95% confidence interval (CI), 1.10¿1.22). Higher vegetable intake (hazard ratio (HR), 0.95 [CI: 0.91¿0.996]), wine intake (HR, 0.91 [CI: 0.86¿0.96]), and total alcohol consumption (HR, 0.92 [CI: 0.86¿0.98]) were associated with lower CVD incidence. The increased CVD incidence by the G allele was restricted to individuals with medium or high vegetable intake (Pinteraction¿=¿0.043), and to non- and low consumers of wine (Pinteraction¿=¿0.029). Although rs4977574 did not associate with any known risk markers, stratification by vegetable intake and smoking suggested an interaction with rs4977574 on glycated hemoglobin and high-density lipoprotein cholesterol (Pinteraction¿=¿0.015 and 0.049, respectively).ConclusionsOur results indicate that rs4977574 interacts with vegetable and wine intake to affect the incidence of CVD, and suggest that an interaction may exist between environmental risk factors and rs4977574 on known risk markers of CVD. PMID: 25551366
  17. TomBAvoider

    Jeanne Calment was a fraud?!!

    AHA! I found the thread I spoke of, Dean! Very interesting: Absolutely stunning. Here we have in BLACK AND WHITE a scenario where the vaunted F&V don't do jack sh|t. You wrote: "In summary, this study suggests that if you have one or (especially) two G alleles for rs4977574, you are at higher risk for cardiovascular disease, and that consuming wine, but not vegetables, can help lower your risk." Take that WFPB! Again, and again, it's all about the individual. I might benefit not at all from F&V - despite all of Ron's probabilities. I was supremely correct to be deeply sceptical about the applicability of any population based study for any individual application. Now, to throw another wrench into this, upping the complexity even more - who is to say that if I combine F&V with a very particular health regimen and some intervention or another, those F&V might not be beneficial to me after all! See, as I said, I'm sceptical a priori of all such studies, including this one. My point is - until we have much better tools, we should take all such studies, including WFPB and this genetic F&V and wine one with a metric ton of salt. Personalized medicine for the win. I rest my case.
  18. Last week
  19. TomBAvoider

    Jeanne Calment was a fraud?!!

    Small steps - we're barely beginning, a long way to go. But at least it's small progress in the right direction, a gathering of tools: https://www.cell.com/cell/pdfExtended/S0092-8674(16)30849-2 https://phys.org/news/2016-07-quantitating-human-proteome.html
  20. TomBAvoider

    Jeanne Calment was a fraud?!!

    Dean, where have I attacked you or anyone else? I rather resent your stating "You can attack Ron (or me) all you want." - I have done no such thing, other than respond to Ron's attacks which were based on attempting to smear sources and not focus on the merits of arguments - in fact the opposite, I urged Ron to please stick to arguments and not range wildly questioning my credulity/scepticism, comparing to Russian misinformation, medieval times, antivaxxers etc. Please desist from making such inaccurate accusations. Thank you. In any case, Dean, certainly genetic differences aren't the only factor. In fact, we know that, because if indeed identical twins can have drastically different physiological reactions to food, that's kind of the point. And while I've cited the gut biome as one variable among many, it is hardly the only one. The point rather is that an individual constitutes a totality of influences that are both internal and external. In other words, there are literally millions of variables, and hence why it is impossible to get exactly the same effects on two different individuals. Even the argument about gut biome is not entirely correct - it is NOT true that as long as you consume an identical given diet to someone else, your gut biome will become substantially the same - that is clearly untrue because diet is not the only factor impacting your gut biome, it is your physiology as in your immune system, your anatomy (example, when I had my colonoscopy, the doctor who perfomed it told me I had an unusually long gut, which has all sorts of discreet health impacts, susceptability to diverticulosis etc. - all nothing to do with diet, or rather the same diet will have a different impact on someone with a different gut anatomy), your lifestyle choices, medications, supplements, exercise etc. - on and on and on. In fact, not too long ago, we had a study showing the dramatic impact of whole body vibration on the gut biome and drastic physiological impact to the point of powerfully influencing diabetes and blood sugar. And WBV has nothing to do with diet - so that's an example of how a completely non-dietary factor impacts the gut biome. Who would've thought that vibration would have such an impact? Again, that points to the fact that we are dynamic systems with millions of variables in extremely complex interactions. We can therefore never simply assume that "whelp, change your diet to vegetarian/vegan and your gut biome will be just like the other guy" - nope, it won't be just the same, because there are tons of non-dietary factors that impact that. Furthermore, while we talk about genetics and gut biome and blood surgar, these are just a few factors. Who has the odd idea that somehow those of us who recognize the importance of personalized medicine limit ourselves to just those factors? Just blood sugar, or just gut biome? Not in the least! As I said, there are tons and tons of variables. We know that even the exact same genetic profile will have a different health outcome based on slight external enviromental differences, which is why the whole giant field of epigenetics exists. Every individual is... an individual. As to plant based diets or any other kinds of diets - yes, there will be genetic differences. In fact, I remember a few years ago, we were exploring SNPs that impacted health and diet and Dean you were participating in it - wherein I discovered that I was one of those individuals (according to 23 and me data), for whom F&V did nothing, and in fact with more consumption tended to slightly negative outcomes. If you remember, you can probably dig up that thread. Yes, there are drastic differences between individuals - and I'll come back to the idea that just because WFPB diets may be better as a class for large numbers of people, it means a hill of beans wrt. an particular individual, as in you. Ron, you make very puzzling remarks, indicating to me that you did not understand my points at all: This actually seems to support the notion that there are some general guidelines which apply to human populations regardless of specific genetic attributes. Come again? Where did I say that genetic differences are the only factors that affect health outcomes, period, never mind gut biome? I cited that study to make the opposite claim - that even if, the genetic profiles were identical (as in identical twins), you would still have different gut biomes (similarity is greater only by 2% from 35% to 37%) and different reactions to food, and different health outcomes. In other words, I'm making the opposite point - even if you normalize genes and diet (as in identical diet down to the molecule), you would still have differential outcomes, and furthermore you could go down a long list of other factors you can normalize (exercise, medications, supplements etc., etc., etc.) and still come up with different health outcomes. Because we are unique individuals, there are widespread differences with all those factors in turn - which is why we all react differently to exercise, to how we gain/lose weight, how we react to medication and supplements and so on. Not merely do these factors work differently for different people, but their interactions in turn explode the complexity of dynamic systems for differential health outcomes. And so, one diet does not fit all. Now, can one make crude observations which would hold true for health outcomes for large groups of people, or indeed everyone? Sure. For example, eating lobster and then undergoing cephalectomy (i.e. beheading) will have a negative health impact on all individuals. But what is the value of such crude observations? My argument in a nutshell: all such nutritional studies are to be treated extremely sceptically and are of limited value for any individual application, because the recommendations are far too crude/blunt as an instrument. In the same spirit I have a salad recommendation - please avoid adding hemlock to your dressing if you care about health outcomes; thanks, I guess. Let me try one more time - even though I've already made this point which you somehow are not absorbing. I have not claimed (in effect) that smoking tobacco "does not signifacantly increase[blah, blah]" - I have not claimed that studies showing WFPB diets don't show large numbers of people benefitting healthwise vs another diet. Here, I'll cite it for you again, since you somehow missed it - see my post you are responding to: Meanwhile, I never claimed that certain diets/behaviors compared to other distinct behaviors don't lead to better health for great numbers (NOT ALL!) of people. I guess I'll just have to repeat what I said, because the answer to your point has already been made: "You need to tailor the dietary advice to the individual even if they do better on a given diet (say, whole food) that's true for the majority, or percentage X of the population. If everyone followed exactly the same whole foods, plant based or whatever the best diet study says, and even if everyone was an identical [genetic] copy of everyone else, you would still have different outcomes for any given individual compared to another - this clearly follows from the study showing that even identical twins react differently to the identical food." Let us not forget (Dean and Ron) where all this started from. It started with my claim that vast numbers of nutrition studies have limited value for any given individual to the point where they may in fact be irrelevant - because if we all have our unique responses to any given diet, then knowing that "oh, a large number of people react X" is of little value to you (other than perhaps probabilistic). Perhaps an analogy would help. Every one of us has a unique set of fingerprints. I think we would want for any crime investigation to focus on us as unique individuals with our unique fingerprints and not be told, well, "we performed a survey study in our prisons, and the largest group of criminals has an X pattern of fingerprints, and since your fingerprints fall into this broad group too, we've decided you belong in prison" (fingerprints fall into different group patterns). It does me no good to know that X diet is good for large (or small) numbers of people according to this or that study. I am a unique individual with a unique health signature, and I'd like to tailor my health interventions and diet to myself, not some statistical group identified somewhere in some study. As to ZOE and attacks on the credibility of the sources - what I really care is about the strength of the arguments and casting aspersions on the author of those arguments is not useful in my opinion - we should be a priori sceptical of all. Because I can do exactly the same for any number of those studies you cite - in fact, we know nutritional studies and medical studies in general are notoriously unreliable and fail replication. Just because you don't know about the various conflicts of interest and machinations behind the scenes for academic credit, publish or perish pressures, bias and so on for a particular study, doesn't mean you should relax about it. Tons of scientists have had commercial ventures - including the favorite around these boards, David Sinclair. Guarante has Elixir, Longo has Prolon, Barzilai has his, and on and on it goes. I am equally sceptical of ALL of them. In fact I've said so repeatedly, including in a previous post: "In any case, they are trying to develop a system whereby you send in a sample of your gut microbiome, which they test and then attempt to tell you what an optimal diet would be for you. At this point, I'm sure it's super crude if it works at all, but this is the general direction I think future dietary recommendation must go of necessity - precisely because each of us is unique, therefore each of us will have a unique diet that is optimal just for us." [emph. mine] I don't get hung up on ZOE or any other commercial ventures - I suspect they may not even work at all! That is not the point. The point is that the direction is correct - toward personalized medicine, personalized recommendation, personalized practices, even if these early commercial applications are not worth much or anything at all. Sibirak: If, however, this precise individual diet calibration you propose can't be done in a reliable, systematic, scientifically-proven way at this point in time, what are the implications of that fact? The implications are that something is true or not, even if we don't have the tools at present to affect outcomes. We need personalized medicine, even if at present we are barely starting out and don't have many tools at all. It means we should treat sceptially all studies, including WFPB studies, because ultimately we're all individuals. The study may, or may not be applicable to you. Call it trivial, but it's not trivial given potential outcomes down the road. We should still acknowledge the limitations of population based studies when attempting to address a particular individual.
  21. mccoy

    Jeanne Calment was a fraud?!!

    Right, thanks for reminding. Also, one point that pretty much baffled me (discussed in the exercise and blood glucose thread) is that it appears that it isn't so easy to lower post prandial glucose peaks, even with exercise . So the advantage of wanting to lower BG with its peaks at all costs may be dubious (too much time and energies required and a choice of foods which is not undisputably healthier). It remains pretty controversial as a topic though. I'd like to underline that I'm eating plenty carbs right now, simple and complex but I'm ready to intervene should my fasting BG cross consistently the prediabetic borderline (100 mg/dl).
  22. According to the above metanalysis by Burgers et al., 2011, Low levels of IGF-1 are bad for either CVD risk and cancer risk. High levels are bad for cancer risk. My doubt is that the optimum range for minimum cancer risk seems to be pretty narrow, let's say in the 100-125 ng/ml interval. Keeping the IGF-1 constantly within this range would probably be very hard. Also, the whole range stands below Longo's optimum value of 140 ng/ml- The takehome lesson is pretty clear though. CR practitioners should check that IGF-1 is not too low, resulting in increased all causes mortality. Conversely, non CR practitioners should check that it is not too high. Dr. Fuhrman's 100-150 optimum range seems to be relatively accurate but maybe too excessive in the higher end of the interval , according always to the Burgers et al. metanalysis.
  23. These are the podcast notes in the PA-Rhonda epipsode. Some optimum values for IGF-1 are displayed. source: J Clin Endocrinol Metab. 2011 Sep;96(9):2912-20. doi: 10.1210/jc.2011-1377. Epub 2011 Jul 27. Meta-analysis and dose-response metaregression: circulating insulin-like growth factor I (IGF-I) and mortality.
  24. Ron, I agree, the genotype A/A exhibits the lowest IGF-1 range in males with age > 85, whereas other genotypes do not exhibit such a drop, so maybe study of the A/A genotype in males > 85 years might be of relevance to longevity. Not a big takehome lesson, nothing immediately applicable by ourselves methinks. And back to the IGF-1 plot, I really don't see any correlation even in the non linear fashion. Besides, the values are so scattered and there are such montruos outliers that no practical conclusions can be reached. I believe so far the only scheme we could agree upon is to take as a reference Valter Longo's 140 ng/mL, check our values, try to comply by adjusting our protein and especially methionine intake. If the values are pretty far from Longo's optimum, then there might be some particular issue to figure out.
  25. Daidzein and genistein have differential effects in decreasing whole body bone mineral density but had no effect on hip and spine density in premenopausal women: A 2-year randomized, double-blind, placebo-controlled study. Nayeem F, Chen NW, Nagamani M, Anderson KE, Lu LW. Nutr Res. 2019 Jul 3;68:70-81. doi: 10.1016/j.nutres.2019.06.007. [Epub ahead of print] PMID: 31421395 Abstract Soy isoflavones are potentially beneficial phytoestrogens, but their tissue-selective effects in women are poorly understood. We tested the hypothesis that soy isoflavones affect bone mineral density (BMD), which may be influenced by individual differences in isoflavone metabolism and serum calcium levels. Ninety-nine healthy premenopausal women were randomized to isoflavones (136.6 mg aglycone equivalence) and 98 to placebo for 5 days per week for up to 2 years. BMD, serum calcium, and urinary excretion of daidzein and genistein were measured before and during treatment. In 129 adherent subjects, we found that isoflavone exposure, determined by urinary excretion levels, but not by dose assignment, interacted with serum calcium in affecting whole body BMD, but not hip and spine BMD. The regression coefficient was -0.042 for genistein excretion (GE) and 0.091 for the interaction between GE and serum calcium (all P < .05). Daidzein excretion had similar but marginal effect. Genistein significantly decreased whole body BMD only at low normal serum calcium levels but increased whole body BMD at higher serum calcium levels. Comparing maximum to minimum GE, mean changes in whole body BMD were +0.033 and -0.113 g/cm2 at serum calcium levels of 10 and 8.15 mg/dL, respectively. These associations were not evident by intention-to-treat analysis, which could not model for inter-individual differences in isoflavone metabolism. In summary, soy isoflavones decrease whole body BMD only when serum calcium is low. Isoflavones are dietary substances that may influence calcium homeostasis by releasing calcium from bone while sparing the common fracture risk sites hip and spine. KEYWORDS: Bone metabolism; Calcium homeostasis; Daidzein; Genistein; Hormone receptor modulators; Isoflavones A Prospective Study of Dietary Meat Intake and Risk of Incident Chronic Kidney Disease. Mirmiran P, Yuzbashian E, Aghayan M, Mahdavi M, Asghari G, Azizi F. J Ren Nutr. 2019 Aug 14. pii: S1051-2276(19)30265-1. doi: 10.1053/j.jrn.2019.06.008. [Epub ahead of print] PMID: 31422013 Abstract OBJECTIVE: The aim of the present study was to investigate the association of different meat intake and substitution of them with risk of incident chronic kidney disease (CKD). METHODS: At the baseline, habitual dietary intakes of 4881 participants of the Tehran Lipid and Glucose Study who were free of CKD were assessed by a valid and reliable food-frequency questionnaire. Logistic regression, adjusted for age, sex, smoking, total energy intake, triglycerides, body mass index, physical activity, hypertension, and diabetes, was used to assess the relationship between major protein sources of food (total red meat, unprocessed red meat, and processed red meat) and incident CKD. Odds ratios (ORs) and 95% confidence intervals (CIs) for the CKD were estimated for substituting one serving of total red meat with one serving of low-fat dairy, nuts, whole grains, and legumes. RESULTS: The mean ± standard deviation age of participants was 40.1 ± 12.8 years. After adjustment for confounders, compared with the lowest quartile of total red meat intake, OR of incident CKD in the highest quartile was 1.73 (95% CI: 1.33 to 2.24; P for trend <0.001) in the final model. OR for participants in the highest compared with that in the lowest quartile of processed red meat was 1.99 (95% CI: 2.54 to 2.56; P for trend <0.001). In the substitution analyses, replacing 1 serving of total red meat and processed meat with 1 serving of low-fat dairy, nuts, whole grains, and legumes was associated with a lower risk of incident CKD. CONCLUSIONS: Higher consumption of total red meat and processed meat was associated with increased risk of incident CKD. Furthermore, substitution of total red and processed meat in the diet with other sources of dietary protein was associated with lower CKD risk.
  26. AlPater

    Al's CR updates

    Effects of long-term intermittent versus chronic calorie restriction on oxidative stress in a mouse cancer model. Cicekdal MB, Tuna BG, Charehsaz M, Cleary MP, Aydin A, Dogan S. IUBMB Life. 2019 Aug 19. doi: 10.1002/iub.2145. [Epub ahead of print] PMID: 31424629 https://sci-hub.tw/10.1002/iub.2145 Abstract Calorie restriction (CR) is one of the most effective methods to prevent many diseases including cancer in preclinical models. However, the molecular mechanism of how CR prevents cancer is unclear. The aim of this study was to understand the role of oxidative stress (OS) in the preventive effects of different types of CR in aging mouse mammary tumor virus-transforming growth factor-alpha (MMTV-TGF-α) female mice. Mice were enrolled in ad libitum (AL), chronic CR (CCR, 15% CR) or intermittent CR [ICR, 3 weeks AL (ICR-Refeed, ICR-RF) and 1 week 60% CR (ICR-Restriction, ICR-R) in cyclic periods] groups started at the age of 10 weeks and continued until 81/82 weeks of age. Blood samples were collected to measure malondialdehyde (MDA), glutathione (GSH), catalase (CAT), and superoxide dismutase (SOD) levels. There was no significant difference for MDA levels among the dietary groups although the chronic calorie restriction (CCR) group had lower MDA levels compared to intermittent calorie restriction (ICR) and AL group at different time points. There was also no change in MDA levels of CCR group with aging. On the other hand, the CCR group had higher CAT and SOD activity compared to ICR-R, ICR-RF, and AL groups. Moreover, GSH level was higher in CCR compared to ICR group at week 49/50 (p < .05). CAT and SOD activities were also positively correlated (p < .05). Here, for the first time, the long-term (72 weeks) effects of different types of CR on OS parameters were reported. In conclusion, moderate that is, 15%, CCR is more likely to be protective compared to the same overall calorie deficit implemented by ICR against OS that may play role in the preventive effects of CR. KEYWORDS: MMTV-TGF-α mice; breast cancer; energy restriction; intermittent calorie restriction; mammary tumor; oxidative stress
  27. Dean Pomerleau

    Jeanne Calment was a fraud?!!

    As you noted on the other thread about personalized nutrition, it isn't clear that preventing transient rises in blood glucose after meals is necessary for good health, and it is clear that it isn't ALL that's necessary for good health. But focusing narrowly on blood glucose for the moment. There is no doubt that people's post-meal glucose response to different foods varies substantially. But Tom and these researchers/entrepreneurs pushing personalized nutrition seem to assume that these variations are due to intrinsic differences between individuals, although paradoxically pointing out that genetics has very little to do with it. Instead they seem to attribute it largely to differences in microbiome from person to person. But there is a lot of research to suggest that microbiome differences are caused by the diets we eat. So it seems to me a very credibly hypothesis that the glucose response differences are merely an artifact of eating an unhealthy diet that leads to an unhealthy gut microbiome and insulin resistence. As a corollary, my hypothesis would suggest that if people ate a healthy, whole food plant-based diet, with time their gut microbiome and insulin resistance would improve, glucose responses would settle down, obviating the need for "personalized nutrition". In other words, I haven't seen any evidence that a WFPB diet won't work for everyone if followed consistently for a a year or two to get your weight, gut microbiome and insulin sensitivity in order. I'm happy to acknowledge that getting to this point of health from the poor state many people are in as a result of a lifetime of bad diet and lifestyle choices may require some personalized tweaks along the way (e.g. temporarily avoiding even certain healthy carbs for diabetics). But in the steady, healthy state, it seems to me that we haven't seen any evidence that personalized nutrition is required. --Dean
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