Hyperlipid by Petro Dobromylskyj
16 September 2021You need to get calories from somewhere, should it be from carbohydrate or fat?
This post has been waiting around for some time so I thought I'd just put it up before settling down to readbut I'm also looking atHyperphagia in Rats with Experimental Diabetes Mellitus:A Response to a Decreased Supply of Utilizable Fuelsand this one is pure Protons and ruminantsditto this
Effect of supplementation with corn oil on postpartum ovarian activity, pregnancy rate, and serum concentration of progesterone and lipid metabolites in F1 (Bos taurus x Bos indicus) cowsand there might be at perhaps two more post on canagliflozin. Maybe.
When on earth I'll get to post on these I have no idea. Working on it!Anyhoo. Back to today:I thought it might be interesting to very, very crudely apply Kevin Hall's mathematic model to a much more interesting study. This one came my way via Jacob in comments quite a few weeks ago.
Response of body weight to a low carbohydrate, high fat diet in normal and obese subjects
This graph is an example of one single individual out of a total of five people in 1973, so we are talking about near-anecdotal data, but fascinating never the less.The diet contained a fixed 168g/d of carbohydrate and 64g/d of protein plus a variable amount of fat over time. This is the weight change curve for subject "1", as far as I can make out:This person lost around 2kg in the first 10 days on the diet then regained just a small amount over the following 25 days. For comparison if we now go on to look at Table 3 from Hall's
How Strongly Does Appetite Counter Weight Loss? Quantification of the Feedback Control of Human Energy Intake
we can see that a standard "lifestyle intervention" (Weight Watchers and exercise perhaps????) established an enforced caloric deficit of around 700kcal per day, which was eroded by hunger ("appetite") at something like an exponential rate, approaching the re establishment of baseline caloric intake with persistent ongoing hunger:In the first month or so this caloric deficit triggered something around 2kg of weight loss. So if we took the graph for subject 1 at the top of the post we might reasonably assume an initial deficit of in the region of 700kcal with a rapid onset of hunger which would try to erode this weight loss effort. Something like:Absolute CI decrease + CO increase = hunger, ie real life.Except the subject in the graph at the top of the post was not in a weight loss study. He/she was in an overfeeding study. Carbohydrate and protein were kept fixed (and non-ketogenic) and progressively more fat was added to the diet, in steps, every five days. Here is the graph with the calorie intakes illustrated for this particular individual.Yes, that is just under 6000kcal/d at a stable reduced weight.Two things come to mind.First is that it is stated that all subjects consuming over 2700kcal/d of fat felt warm all of the time and sweated easily. Second is that DLW measurement of TEE would certainly pick this up perfectly well and estimate a massive "calories out". Those would be as heat. Reversing-engineering weight loss to estimate changes in food intake is clearly completely out of its depth here. What happened?The fat was corn oil.Linoleic acid -> 4HNE -> activates uncoupling to blunt insulin signalling and causes insulin resistance per se -> hot, sweaty weight loss.It takes a significant amount of linoleic acid to do this, well in excess of that needed to augment fat storage.This effect appears to apply just as well to humans as it did to those mice in The ginger paradox (3), even when overfeeding is exogenously enforced. Clearly the mice which actively lost weight "effortlessly" (ie mice never do the human "appetite" battle unless they are exogenously semi-starved) on safflower oil used uncoupling to blunt insulin signalling and so increase lipolysis and adipocyte derived calorie supply.Subject 1, on corn oil, had a peak of around 84% of calories from fat which put the linoleic acid percentage in the region of 40% of 6000kcal, well in to uncoupling levels. Corn oil in the 1970s was suggested to be around 45% LA.Now, what would be expected to happen if we massively over fed with a lower LA, less uncoupling fat? The estimate for LA in olive oil in the 1970s was 7%. In this next graph the maximum LA percentage was 6% of calories, which is more akin to an obesogenic dose than to an uncoupling dose. Overfeeding olive oil does this:That is 9kg weight gain in 40 days, and still going.Now, what might we expect if we tried the same thing with beef fat? My expectations:Weight gain would be even greater.Metabolic syndrome would develop rapidly.It should be much harder to sustain a 6000kcal diet of mostly beef fat than it was from either an uncoupling or an obesogenic fat source.The group didn't try overfeeding beef fat, sensibly.There are a number of studies which I have picked up over the years which suggest that the uncoupling effect of double bonds kicks in at essentially all levels of their metabolism. At low levels the effect is over-ridden by the effect of failing to limit insulin signalling in adipocytes as per the Protons concept, leading to weight gain ie insulin still signals perfectly well and it does so more than is physiologically appropriate, especially in the immediate post prandial period. As uncoupling comes to predominate the ability of a low mitochondrial membrane potential to markedly suppress ROS generation becomes progressively more and more dominant, so insulin signalling becomes profoundly blunted. It will never get to high enough levels where insulin-induced insulin resistance should have kicked in, so the Protons concept becomes irrelevant. Under uncoupling, mitochondrial metabolism is functionally hypoinsulinaemic, it should resemble that of reduced insulin gene dose mice in Jim Johnson's lab where reduced insulin signalling was simply the end result of reduced insulin production, 24/7. It should also resemble ketogenic, hypoinsulinaemic eating.Whether it is via 4-HNE/UCPs or 2, 4-dinitrophenol, high enough levels of uncoupling will absolutely blunt insulin signalling, with subsequent increase in access to adipocyte calories and consequentially suppressed hunger, leading to adipose tissue loss without increased food intake, with a few small caveats thrown in.Peter
It is quite possible to make a very reasonable estimate of how many calories a given person has consumed over the previous few weeks by estimating their total energy expenditure (TEE) using doubly labelled water (DLW), estimating the calories supplied from fat in adipose stores using the changes measured by DEXA scanning and applying a little arithmetic:TEE (by DLW) - Fat mass change (by DEXA) = Food derived caloriesNice and simple. And very, very expensive.Quite a few years ago Kevin Hall's group had the idea that you might be able to reverse engineer the intake of food calories simply from the change in weight over time using a mathematical model. They validated this against a two year conventional diet study where weight, TEE by DLW and fat mass changes by DEXA were repeatedly measured. They produced this paper:Validation of an inexpensive and accurate mathematical method to measure long-term changes in free-living energy intake
Their model is pretty good within certain limits. You could trip it flat on its face pretty easily but that's not today's post. Just assume it works in the above study and also in this one:How strongly does appetite counter weight loss? Quantification of the feedback control of human energy intake
The second study piggybacked on a diabetes study using canagliflozin, a sodium glucose co-transporter inhibitor which increases urinary glucose excretion. Canagliflozin produces the loss of around 90g/d of glucose, ie around 400kcal/d. This loss is insensible, other than via counting the number of trips to the bathroom. There was no specification within the study protocol to lose weight or to restrict calories.
Long-term efficacy and safety of canagliflozin monotherapy in patients with type 2 diabetes inadequately controlled with diet and exercise: findings from the 52-week CANTATA-M study
The interesting questions are whether this silent caloric loss produces weight reduction, what does it do to caloric intake and what mechanisms might be at work.Here are the weight changes:So. Obviously losing 400kcal/day does produce weight loss. Or is that genuinely obvious? Surely, if the hypothalamus wants to "see" a certain number of calories to run metabolism, shouldn't it immediately increase calories eaten to counter that 400kcal deficit? Yes, it should. Immediately. Except...Here is what happened to the energy intake. The solid black line is Hall's model which does not include the starting point at time zero with weight change zero. I've added the red curve to include this and roughed in the rest of the data points as well as a curve in powerpoint can manage:It's quite clear from the data points that there was an initial drop in total energy intake to a nadir, somewhere within the first three weeks. DLW is an averaging technique so the location of the nadir is an unknown but it must have happened, to explain the data points generated where week three is below time zero. The effect is more marked in the placebo group and probably represents simply being in the trial and tidying up, in both groups, the worst of the normally execrable diabetic diet prior to starting the study.The effect is blunted in the canagliflozin group, presumably because of those 400kcal/d down from day one and their hypothalamus will have noticed this and have kicked their cortex in to doing something about it (hunger). By 15 weeks the extra calorie intake estimate (around +350kcal/d) is getting pretty close to the urinary calorie loss estimate (around -400kcal/d).But for the first 15 weeks calorie intake was estimated to be well below urinary calorie loss. Food was ad libitum. Why any weight loss?That's interesting.Also, despite increasing food calories to match urinary losses, weight remained stable at over three kilograms below baseline, with no suggestion of weight regain at the end of a year.That's interesting too.Hall goes on to treat the changes in weight as an engineering control system, a bit like a black box, without any attempt at integrating any basic physiology. A quick search of the text shows no mention of insulin in the whole paper. Not surprising, given the stance taken by Hall over the CIM of obesity.But even the most basic, strawman-facilitating version of the CIM of obesity has no problem explaining the results in some depth. It takes about 30 seconds on PubMed to ascertain what canagliflozin does to the insulin requirement of people with DMT2.It drops the requirement.Addition of canagliflozin to insulin improves glycaemic control and reduces insulin dose in patients with type 2 diabetes mellitus: A randomized controlled trialFor patients still using their own pancreas for insulin this seems very likely to simply be reflected in a spontaneous fall in plasma insulin, triggered by the loss of 90g/d of glucose which exits through the bladder rather than requiring insulin to stuff it in to storage within the body.If we assume insulin drops by a fixed amount in proportion to 90g less of glucose, and stays at this reduced level for as long the canagliflozin is given, there will be an acute rise in lipolysis which will supply adipocyte derived calories to partially make up for the urinary loss.As the hypothalamus monitors energy status it will see 90g/d of glucose as absent but being replaced by, initially, roughly a kilo of fat from adipocytes over three weeks. More arithmetic:400kcal glucose x 21 days = 8400kcal deficit from glycosuria.Weight loss of 1kg over three weeks = 9000kcal of fat from adipocytes.I would suggest that fat loss comes as a direct response to lowered insulin levels and will easily at least partially replace the glucose loss, certainly initially. The fat loss can be described as "calories-in" without actually eating them. So people with an acutely lowered insulin level eat less than you would expect.Let's look at this the correct way round. An all-glucose caloric deficit of 400kcal/d was acutely established which directly resulted in rapid drop in plasma insulin levels. Lipolysis was acutely increased which largely offset the glycosuric calorie deficit. Because over several weeks lipolysis gradually slowed to an appropriate level determined by the the new insulin levels, food calories had to increase in proportion, to maintain an adequate energy flux to keep the hypothalamus happy. Eventually extra food-in will equal urinary glucose-out giving stable weight. But with lower insulin levels this will occur at a lower total fat mass.The weight loss/calorie intake deficit were both caused, directly, by a fall in insulin levels. Utterly simplistic CIM.Kevin Hall is a great source of data. Of insight?Not so much.Peter
Hi all.Life is back to a semblance of normality now. I've de-spammed/approved the comments on older posts and will try to read all of the comments as soon as practical.
As a brief update, Brian Sanders and I had a chat which is now up on the Peak Human website. It was fun. Nothing too detailed in the way of biochemistry and lots and lots of "I don't know about....." or "I don't have a framework to integrated that into..." sort of statements.
As life should be.
Peter from Hyperlipid on Are medical professionals giving the absolutely wrong advice?
The other thing which happened just before our vacation was a chat with Amber O'Hearn. She is really interested in sleep and diet, as in
The therapeutic properties of ketogenic diets, slow-wave sleep, and circadian synchronyand it was a great privilege to throw in some ROS derived ideas which might have been helpful towards her presentation at AHS21
Does dietary mismatch affect us via sleep?Very interesting. I have previously been sent a paper by a reader (long time ago) where death from sleep deprivation is an ROS phenomenon, largely centred on ROS damage to the gut. But, while fascinated, it didn't make a lot of sense to me until Amber filled in a lot of gaps. It still doesn't completely make sense but time and some thought might help with that!I have to say, adenosine looks to be a very interesting molecule too, even if not directly ROS controlled...Peter
Brief one-liner:There was a question in comments about what tweaks people might apply to themselves to minimise the risk of severe COVID-19 when they get around to being exposed to the SARS-CoV-2 virus, as we all will.For subtleties anyone could do a great deal worse than follow George Henderson on Twitter.For myself I rather like his tweet related to the Virta Health intervention:which has been reinforced by this AI facilitated mining operation of the morass of published "risk factors" for severe COVID-19, with thanks to James for the link:
A Machine-Generated View of the Role of Blood Glucose Levels in the Severity of COVID-19
Clearly in 2021 DMT2 is currently due to either a lifestyle choice or to a lack of (accurate) information.So for COVID-19 my specific medical advice to minimise serious illness is still the same.
Try not to be elderly. Try not to be diabetic.Peter
Lots of posts part written but currently I'm getting camping gear ready for our family holiday with kayaks, hills and tents. At the same time the essential big car is in the garage getting it's rear differential fixed/replaced and I'm not sure we would all fit into the MX5...
Normal service will be resumed when I get some time!Peter