Monday, March 30, 2020

Look after your lysosomes

I was a little cautious about the efficacy vs toxicity of chloroquine and its derivatives in my last post.

George Henderson just retweeted this snippet;

Sadly the narrow line between the degree of raising lysosomal pH to blunt viral replication and that which might release sufficient cysteine to strip the FeS clusters out from complex I can be crossed quite easily, so it appears.

Worryingly Dr Barman appears to have been one of those people with some degree of metabolic syndrome and who might have been someone most likely to benefit from prophylaxis against coronavirus replication.

My own observation during my very rare trips to our local hospital is that medical professionals are far from immune to metabolic syndrome. Couple that with extreme stress, high viral load exposure, severe sleep deprivation and the sort of food/snacks available in hospitals and you have to worry for the health of these people.

None of them want to have metabolic syndrome, a problem which is built in to our public health guidelines. These people are laying their lives on the line to support the lipid hypothesis. Most of their patients are in hospital secondary to the lipid hypothesis. Those developing ARDS in the ITU do so in a large part as a result of the lipid hypothesis.

Just my rather sad view from the sidelines.


Wednesday, March 25, 2020

From Yeasts to Chloroquine

This paper is from Hughes and Gottschling

An early age increase in vacuolar pH limits mitochondrial function and lifespan in yeast

It got a mention in the blog back in 2012 when it was freshly published. The group have gone on to study yeasts, ageing and the lysosome-like vacuole of yeasts. Their core finding is that vacuolar pH controls mitochondrial "health" which controls ageing, at least in their model.

The group has been very busy and earlier this year this paper was published from Hughes' lab:

Cysteine Toxicity Drives Age-Related Mitochondrial Decline by Altering Iron Homeostasis

The paper describes a very long series (way too many to detail here) of experiments aimed at adjusting vacuolar pH upwards and downwards and observing the effect on the survival of mother yeast cells through repeated cell divisions (replicative age rather than chronological age, there are arguments about which matters most).

Bottom line: Acidifying vacuolar pH extends lifespan, reducing its acidity shortens it.

Why should that be?

Their next series of experiments demonstrated that cysteine toxicity was the driver of early mitochondrial functional decline secondary to loss of vacuolar acidity. Cysteine is normally harmless and essential for life. Your cells love it, just so long as it is within the vacuole (or lysosome in humans), not in the cytoplasm. It's kept there by a vacuolar amino acid transporter driven by the vacuole proton gradient. The pH gradient is generated using a vacuolar vATP-ase to pump protons from the cytoplasm in to the vacuole, using ATP. It's related to the mitochondrial ATP synthase but normally runs in reverse.

If, on a long term basis, vacuolar pH rises (ie the vATP-ase fails), cysteine is released from the vacuole in to the cytoplasm where it auto-oxidises, generating much too much hydrogen peroxide. This reacts with the iron-sulphur clusters of complex I and many other crucial enzymes in the mitochondria. In old age cysteine becomes toxic through vacuolar failure.

I've been interested in this for some time because Barja and Sinclair have both intimated that they are tending to avoid animal proteins in favour of low cysteine/methionine plant proteins. Cysteine is the cellular executioner when vacuole pH rises during the old age of yeasts or lysosomal pH rises in ageing mammalian cells. It's interesting because methionine restriction (which reduces cysteine levels) appears to core to the longevity promotion seen with caloric restriction or protein restriction in mice fed on crapinabag.

You have to wonder whether we are looking at this the wrong way round. What if crapinanbag, based on starch and sucrose, causes early onset lysosomal failure which can be ameliorated by removing the cysteine, which is the cellular execution mechanism?

This would make methionine restriction's longevity extension rather specific to glucose based metabolism. My biases would tend to favour this point of view. There's no data, yet.

As an aside:

Now, I have speculated that both influenza and corona viruses need anabolic processes generated by mTOR activation. This requires acute acidification of the lysosome. Blocking acute lysosomal acidification is one technique currently being investigated for treating the life threatening pneumonia which develops in susceptible individuals during the current COVID-19 pandemic. There are suggestions that chloroquine, a suppressor of lysosomal acidification, might be an effective treatment. My guess is because it blocks anabolism.

There is probably a fine line between suppressing anabolism and releasing a mitochondrial-executing concentration of cysteine.

Neither Hughes nor Gottschling were considering therapeutic inhibition of vacuolar acidification as a stratagem for anything. They were more interested in avoiding long term loss of vacuolar acidity to delay mitochondrial function decline. But blunting anabolism without causing catastrophic cysteine release is a current anti-viral/anti-neoplastic therapeutic target.

You can see that the drug chloroquine a) might work and b) might be very toxic in overdose.

It does currently appear that it might work but we should never forget that "clinical experience is no guarantee of therapeutic efficacy".

However it would be great if it really did work.


Tuesday, March 17, 2020

ARDS and linoleic acid

Adult Respiratory Distress Syndrome is topical at the moment. In the comments to the last post I wondered whether omega six fatty acids, especially linoleic acid, might be a driver of ARDS, which is one of the most intractable ITU problems in response to major infection/trauma/inflammatory insults.

Tucker came up with this abstract

Plasma fatty acid changes and increased lipid peroxidation in patients with adult respiratory distress syndrome

and I peeked at the related papers to find this gem:

An increase in serum C18 unsaturated free fatty acids as a predictor of the development of acute respiratory distress syndrome

Again, only an abstract and mostly describing a pilot study. But here is the critical statement:

"Increases in unsaturated serum acyl chain ratios differentiate between healthy and seriously iII patients, and identify those patients likely to develop ARDS".

That is, the more linoleic (and oleic) acid you have as FFAs in your bloodstream, relative to my beloved palmitic acid, the more likely you are to develop ARDS. Which carries a high risk of death.

That was 1996.  The work will have been done before that, so we have known that linoileic acid is bad news for well over 20 years.

If you are a Standard American on the Standard American Diet, or anyone else in the world poisoned by a cardiologist-promoted PUFA based diet, any weight loss through illness will release significant amounts of linoleic acid from your adipocytes. That might just trigger ARDS in the aftermath of a viral pneumonia.

There's a lot of it about.


BTW Steve Cooksey has a rather nice post up citing a lot of the refs featuring how to maintain an effective innate immune system, so as to avoid the viral pneumonia in the first place. It's a good read.

Saturday, March 07, 2020

Cell surface oxygen consumption (4) Influenza

This press release, from 2013, surfaced on twitter (embarrassingly I have again lost the tweeter due a hat tip for this. Mea culpa. Found him, it was resurfaced/retweeted by Guðmundur Jóhannsson).

Glucose: Potential new target for combating annual seasonal flu

which summarises this paper:

Glycolytic control of vacuolar-type ATPase activity: a mechanism to regulate influenza viral infection.

Over the last few weeks I happen to have been immersed in vacuoles/lysosomes, cysteine toxicity, longevity and yeasts. Oh, and mTORC1, which is deeply associated with lysosomes. So I'm in a mindset of how lysosomes/mTOR control longevity/anabolism.

Anyhoo. Influenza A virus uses lysosomes to maximise its survival. My prediction is that it activates mTOR to induce a marked anabolic state and hijacks that anabolic state to generate lots and lots of influenza A virus particles. It will do that, much as a cancer cell might, by aerobic glycolysis working on the basis that glycolysis, while inefficient, is very, very fast at generating ATP compared to OxPhos. This would suggest that the free availability of glucose secondary to hyperglycaemia (or increased access of glucose to the cytoplasm secondary to hyperinsulinaemia) will increase the success of the influenza virus, as found in Kohio's paper.

Which brings us to anabolism and glycolysis. Not only does aerobic glycolysis supply ATP for anabolism faster than OxPhos can but it also supplies phosphoenolpyruvate for amino acid synthesis, plus other anabolic substrates come from glucose via assorted pathways.

However for every glucose molecule which generates a pair of 1-3 bisphosphoglycerate molecules two NAD+ are consumed. If these glycerate molecules are used for anabolism via phosphoenolpyruvate they will not restore the NAD+ balance by converting to lactate. The basic story is in

Cell surface oxygen consumption (2)


Cell surface oxygen consumption (3)

with an introduction to the concept in

Cell surface oxygen consumption (1)

The glycerophosphate shuttle won't do the job because this too is limited to the speed of OxPhos. Cell surface oxygen consumption does fit the bill for rapid restoration of NAD+.

So. Does influenza virus drive cell surface oxygen consumption to facilitate anabolism at a speed fast enough to keep it one step ahead of the innate immune system?

I don't know.

But another standard (primarily rodent) model RNA virus certainly does.

Oxygen uptake associated with Sendai-virus-stimulated chemiluminescence in rat thymocytes contains a significant non-mitochondrial component

I think this will be a basic feature of rapid anabolism, be that viral or neoplasia related.

Will hyperglycaemia and/or hyperinsulinaemia facilitate viral directed anabolism under infection by another, more topical novel human RNA virus?

Personally, I'm not planning on finding out the hard way when I get around to catching the current bug.


Sunday, February 23, 2020


It came up in conversation with Ally as part of the Paleo Canteen podcast that I like coffee but that it doesn't like me.

Over the years before LC my coffee ingestion had stabilised at around 7 or 8 mugs per day. That's quite a lot. At the time I started on LC I did Atkins induction and cold turkey-ed from all methyl xanthines. The headache was tolerable, especially as I knew exactly why it was there and that it would be gone by about seven days in, which it was. The need for an evening stimulant also disappeared because I no longer fell asleep during the hyperinsulinaemic phase of the post prandial period.

For which I was infamous.

Over the years I have reintroduced coffee a couple of times but  stopped it again due to either minor lower GI upsets or worsening of either low back pain or finger arthritis.

I had done a desultory Pubmed search to see if there was any evidence for clear cut, lectin induced GI damage from coffee which might explain my own signs. When the penny dropped that coffee "beans" were actually seeds rather than legume-like beans I sort of gave up hunting.

So I was avoiding coffee and expected to do so long term. My issue was that I quite like the jittery restlessness which comes from an acute large dose.

In the aftermath of chatting to Ally I received an e-mail for Mason about Dr Paul Mason, his local Dr in Sydney. I have a lot of time for Dr Mason and I really enjoyed his lecture from the 2019 conference.

It turns out that Dr Mason is pretty sure there is a lectin in coffee. Not only that but the lectin is heat labile.

If you boil your coffee for 10 minutes you appear to pretty well destroy the lectin.


I can boil down a double strength cafetiere of coffee to the volume and bitterness of a double espresso in 10 minutes.

The caffeine is still there and absolutely produces the desired pharmacological effect.

For myself, drinking two or three double espressos per day produces tachyphilaxis to the caffeine within a week or two. Withdrawal is mild and sensitivity is pretty well restored within about 4-5 days. I have no interest in using caffeine to blunt caffeine withdrawal, so coffee is probably a weekend treat.

Plant poison, undoubtedly. Contains disgusting antioxidants too, no doubt. At the moment I feel that there is an acceptable trade-off.


For those who enjoy confirmation bias and worm studies:

Lifespan Extension Induced by Caffeine in Caenorhabditis elegans is Partially Dependent on Adenosine Signaling

Lard makes hungry mice live longest

Over the past few weeks I've been looking for papers where Barja's group might have run longevity experiments. This does not seem to have been their forte. They have done lots of observational comparative studies looking at long vs short lived species and lots of interventions to modify mitochondrial membrane lipid composition but no hard-core lifespan measuring studies that I can find.

So Barja threw in the rather off comment about avoiding "excessive intake of animal proteins and fats typical of western diets" in his review without obvious direct testing of these variables on lifespan.

I have to leave the mechanism of calorie restriction, aka protein restriction, aka methionine restriction for another day.

What we can do today is to look at Barja's dreaded animal fats. Like lard.

The data are, sadly, only available from CRON fed mice. This is the study:

The Influence of Dietary Fat Source on Life Span in Calorie Restricted Mice

Diets had their fat source modified thus and also had their calories restricted by 40%:

"The modified AIN-93G diets (% of total kcal) each contained 20.3% protein, 63.8% carbohydrate, and 15.9% fat. Soybean oil was the dietary fat in the control group (standard AIN-93G diet). The dietary fats for the CR groups were soybean oil (high in n-6 fatty acids, 55% linoleic acid, Super Store Industries, Lathrop, CA), lard (high in monounsaturated and saturated fatty acids, ConAgra Foods, Omaha, NE) and fish oil (high in n-3 PUFAs, 18% eicosapentaenoic acid, 12% docosahexaenoic acid, Jedwards International, Inc., Quincy, MA). To meet linoleic acid requirements, the fish oil diet contained 1% (w/w) soybean oil".

Here are the survival curves:

The left hand curve of green circles is from (nearly) ad-lib feeding of crapinabag. The yellow squares showing best survival are from feeding the dreaded animal fats from lard, combined with CRON. The fish oil group, full of EPA and DHA, did worst of the three CRON groups with soy oil being intermediate.

I think beef dripping would have done better than lard and beef suet even better still, but then I would think that.

Peter, saturophile.

Saturday, February 22, 2020

Insulin sensitivity makes you fat: growth hormone receptor deletion

TLDR: Excessive insulin sensitivity sets you up to become obese.

I have to apologise for citing Valter Fastingbar Longo, sometimes you have little choice. This paper

GH Receptor Deficiency in Ecuadorian Adults Is Associated With Obesity and Enhanced Insulin Sensitivity

documents the physiology of humans who are homozygous for a large growth hormone receptor gene defect. They make their GH, lots of it. It does absolutely nothing, having no receptor. GH normally works in opposition to insulin on adipocytes, causing both lipolysis and systemic insulin resistance.

Also, in the absence of GH signalling, these people make no IGF-1 so are of dwarf stature. They are exquisitely insulin sensitive. As in here are the OGTT results. Dark lines are the GHR deficient people:

Plasma glucose is comparable to that of controls throughout, matched for BMI (and lots of other things). But just look at that insulin level, peaking at 25microIU/ml vs 80microIU/ml in controls. The dwarves are very, very insulin sensitive.

And very fat.

Despite having a mean BMI of 27.6 (controls are higher at 29.4) the dwarves have 48% of their weight as fat mass compared to 41% in the controls.

Let's put this in to context: The GHr deficient people are fat because they are insulin sensitive. There is no paradox. We are not thinking that their obesity should have caused insulin resistance, it's that their failure to generate one type of physiological insulin resistance has allowed pathological insulin sensitivity to prevail, hence obesity.

Oh, and leptin:

Leptin in the dwarves with 48% body fat is 7.32ng/ml. Leptin in controls with 41% body fat is 10.36ng/ml, p is just over 0.02 if you are wondering or care.

It looks to me as if these excessively insulin sensitive individuals have yet to reach their "ideal" metabolic level of obesity to counteract their lack of GH signalling. Interesting to wonder what determines the level of adiposity at a given age in the absence of GH signalling. That's not simple.

We have no data on RER under fasting or post prandially. But we can be fairly confident that the fasting RER will be low, reflecting high basal lipolysis from distended adipocytes and post prandial RER will be high as insulin action facilitates glucose metabolism and locks lipids in to adipocytes.

A bit like those insulin sensitive pre-obese humans a couple of posts ago. But these dwarves will have to become very, very obese to behave like normal overweight insulin resistant people.


Addendum, not worth a post in its own right but on-topic:

Does Weight Gain Associated with Thiazolidinedione Use Negatively Affect Cardiometabolic Health?

Epic quote of failed perception:

"This review paper discussed the mechanism of action of TZDs on weight gain and the so-called “glitazone paradox”, the phenomenon that TZD-associated weight gain improves rather than exacerbates insulin resistance".

There is no paradox. Insulin signalling improves with glitazones, this makes you fat.

Tuesday, February 18, 2020

CPT1aL479 resurfaces nicely

Originally from Erik Arnesen, via a retweet by Miki Ben-dor:

Inuit metabolism revisited: what drove the selective sweep of CPT1a L479?

as in

Coconuts and Cornstarch in the Arctic?

The P479L gene for CPT-1a and fatty acid oxidation

The abstract looks very nice, I can't wait to get hold of the full text!


Edit: The paper is long and somewhat repetitive. There is a much neater paper from Amber which people might enjoy:

Evidence on chronic ketosis in traditional Arctic populations

End edit.

Monday, February 17, 2020

Insulin sensitivity makes you fat

TLDR: Excessive insulin sensitivity sets you up to become obese. Becoming obese makes you insulin resistant. Eventually excessive adipocyte size will induce systemic insulin resistance. Further weight gain is still possible given a diet which induces systemic hyperglycaemia combined with a pancreas of steel. Here we go.

I picked this paper up from Pubmed while looking for something else:

Insulin sensitivity is increased and fat oxidation after a high-fat meal is reduced in normal-weight healthy men with strong familial predisposition to overweight

It's very interesting.

Over the years I have collected various models, mostly mouse/rat models, which generate obese, insulin resistant rodents.

These mostly involve damaging the hypothalamus in some way and letting the mice eat ad lib until they reach the desired level of obesity, with the associated insulin resistance. There is the ventromedial hypothalamic injury model

Molecular and metabolic changes in white adipose tissue of the rat during development of ventromedial hypothalamic obesity

The MSG injury model:

Decreased lipolysis and enhanced glycerol and glucose utilization by adipose tissue prior to development of obesity in monosodium glutamate (MSG) treated-rats

Late effects of postnatal administration of monosodium glutamate on insulin action in adult rats

The gold thioglucose injury model:

Adiponectin expression is paradoxically increased in gold-thioglucose-induced obesity

What they all have in common is that the models are always more insulin sensitive in the first weeks after injury compared to the non-injured controls. This excess sensitivity persists until a certain level of obesity is achieved. As obesity increases so does systemic insulin resistance increase (a separate mechanism) until it overwhelms the excess insulin sensitivity and rate of weight gain markedly reduces. The model is now insulin resistant.

Inappropriate insulin sensitivity is what generates the obesity. Insulin resistance limits its progression.

Insulin resistance in adipocytes can, undoubtedly, occur but this is not a feature of the adipocytes in the early stages of obesity. They are insulin sensitive. Insulin acts easily. Adipocytes distend.

Back to the paper. It enrolled young, male, non-obese offspring of obese parents. Let's call them pre-obese. Sadly the paper is from 2004, it's now 2020, I would expect the "pre" prefix might nowadays be redundant. Here are the subject characteristics:

To me it is interesting that the pre-obese chaps were carrying more fat mass than the controls. There is a 1.7kg excess, statistically ns but the trend is there. You have to wonder how close to 0.05 the p value might have been.

Here are the fasting metabolic parameters for both groups:

Notice that the fasting insulin is lower in the group with higher fat mass, provided they have obese parents. It's also interesting that their fasting FFAs are higher than those of the folks with slim parents. This difference is also ns but the numbers after the +/- sign are standard deviations, not standard errors, so my guess these too are close to significance (for what that is worth). I also like the ns elevated trigs, I suspect related to repackaging the elevated fasting FFAs. Which are elevated due to increased adipocyte size allowing increased basal lipolysis. All speculation.

Next we have the insulin response to a quite pleasant sounding, mixed macro, highish fat meal:

The fasting insulin is the one from Table 2, p being 0.007 and for a large percentage of the post-meal eight hour period insulin stays significantly lower in the pre-obese group than in the normal-weight parent group. The pre-obese subjects are consistently more insulin sensitive.

Here is the FFA graph for the same eight hours:

Converting the FFA levels to real money terms it appears that the lean parent group had FFAs of 280micromol/l and the pre-obese people had 390micromol/l. I've already speculated that the elevated FFAs in the pre-obese group are from increased basal lipolysis, not insulin resistance. As soon as insulin is released after the meal FFA levels become identical for eight hours. I've not copied the trigs graph but the trend is for chylomicrons to be the same between groups for 4 hours and then lower in the pre-obese as insulin sequesters fat in adipocytes.

Which group will be metabolising most fat under hypoinsulinaemic, near-basal lipolytic conditions? Pre-obese have elevated fasting FFAs and they're oxidising more fat, 1150 vs 740mg/kg FFM/d,  ns but you can see the trend:

However, as soon as insulin rises fat oxidation drops because insulin sequesters fat in to adipocytes at levels way below those which translocate GLUT4s. It will also divert intracellular FFAs in to intracellular triglycerides. Lipid oxidation under insulin drops to 90mg/kg FFM x 8h compared to 163mg/kg FFM x 8h in the more normal individuals. Giving p less than 0.007.

BTW FFAs stay high in both groups because the meal was around 50% fat. I would predict that a high carbohydrate, low fat meal would have produced a marked drop in FFAs and a rise in RER, both more pronounced in the people with obese parents. No data on that one.

I do not think these pre-obese people have an injury to their hypothalamus. It is more likely the problem is with their adipocytes causing the excess insulin sensitivity.

I think we can ignore discussion comments about the influence of medium chain acyl CoA dehydrogenase variation as a red herring because the pre-obese folks are oxidising more fat under fasting conditions, ie when more lipid is available. The leptin receptor comment is lovely because we know that in mice with a complete leptin receptor deficiency that providing less than 5% of calories from PUFA is highly protective against obesity while providing 15% PUFA in the diet is grossly obesogenic (first link in the blog post). Clearly dietary fatty acid composition trumps even gross leptin signalling deficiency.

What were the diets like in the pre-obese participants? All we know from this study is that the ratio of PUFA:SFA was higher in the pre-obese people:

"The polyunsaturated to saturated (P/S) ratio was 0.34+/-0.06 in the group with overweight parents and 0.31+/-0.09 in the control group".

However you try to reverse engineer the limited data from the results it's hardly 5% vs 15% PUFA, but these people have taken around 25 years of eating a slightly heart-healthier PUFA rich-er diet to gain an excess of 1.7kg of fat mass. My biases are willing to accept this as real.

Maybe it is, maybe not. I'm not exactly a bias free source of opinion.


BTW leptin is consistently lower in the pre-obese group carrying excess fat mass. My suspicion is that their fat cells "feel" empty, so are refusing to signal their true state of fullness. Once the adipocytes become full enough then leptin will increase to give a more accurate representation of the absolute fat mass. This will be associated with the onset  of the more expected insulin resistance of obesity.

Saturday, February 01, 2020

Looking in to the future of Low Energy Diets

I think I picked this up from Jan Vyjidak on Faceache but it's done the rounds on twitter too.

Low-energy total diet replacement intervention in patients with type 2 diabetes mellitus and obesity treated with insulin: a randomized trial

"At randomization, participants commenced a 12-week TDR [total diet replacement] formula LED [low energy diet]... followed by 12 weeks of structured food reintroduction and then ongoing followup in combination with an energy deficit diet at 3-month intervals until 12 months. For the first 12 weeks, all meals were replaced with four formula LED products per day (800–820 kcal/day, 57%
carbohydrate, 14% fat, 26% protein and 3% fiber) in addition to at least 2.25 liters of energy-free beverages. A fiber supplement was recommended, if required, to avoid constipation, a common side effect of using a TDR".

For three months patients were starved on 800kcal per day. At 56% carbohydrate that makes carbs come out at around 100g/d. Oddly enough, restricting carbs to this level allowed a drop in insulin usage. Indeed, there was such a marked drop in insulin usage that some patients coming off insulin all together. I wonder what these starvation subjects would think if you told them that they could have had equal reductions in insulin usage just by restricting the carbohydrate content of their diets to that 100g/d, while still allowing fat and protein to satiety... I suspect  that a) no one has told them this and b) they might not be best pleased to find out retrospectively.

For a second three months a little food was added to their diet, but not much. For the final six months patients were kept a little hungry but not so much as in the first six months of the study.

Here is what the abstract says:

"Results: Mean weight loss at 12 months was 9.8 kg (SD 4.9) in the intervention and 5.6 kg (SD 6.1) in the control group (adjusted mean difference −4.3 kg, 95% CI −6.3 to 2.3, p less than 0.001)".

Here is what the results show for the intervention group:

Here is the same graph but simplified in to three red lines representing the three phases of the study:

You can argue the exact slopes of the lines but overall the pattern is correct. Something like this:

Now it is time to look into the future. Usually this is difficult but I think that in this case the general shape of the graph lets us predict the shape of things to come when related to weight gain. Plus, because it becomes obvious in the later months of the study (from HbA1c values) that insulin is going to have to be added back in, at this time the rate of weight gain might actually increase (dramatically), but we can't know that.

Using a simple maintenance of the status quo (best case scenario) we get this, looking forwards to around about the 24 month mark:

Weight gain, in the aftermath of a year of hunger, might not stop at baseline mass either.

I think it is also possible to look in to the future of glycaemia too, by extending the plot of HbA1c with time, working from the published graph in the results. Taken forwards to 16 months or so, it looks something like this:

Maybe I'm being pessimistic. Maybe sudden tolerance of chronic hunger might kick in and reverse the adverse trends in weight and glycaemia clearly present at the end of the study. Maybe subjects might suddenly become slim and euglycaemic.

Maybe not.


Monday, January 27, 2020

Rory Robertson and Protein Restricted Longevity

I looked at this paper when it did the rounds a fair while ago, saw that the only fat source used was soybean oil and decided that living on soybean oil, sucrose, maltodextrin and wheat starch was not a good idea and so I binned it as the junk it is:

The Ratio of Macronutrients, Not Caloric Intake, Dictates Cardiometabolic Health, Aging, and Longevity in Ad Libitum-Fed Mice

I missed the embedded problems which have since been brought to light by Rory Robertson, whose slightly over-the-top concerns are voiced here. I would perhaps disagree slightly with some of his opinions but, overall, he makes a rather good case. The first thing to note is that you have to go to the supplementary data to realise that a significant number of groups of mice were lost (and excluded) due to mortality problems. Table S1 describes all thirty of the diets which the study started out with. Five of these diets had to be discontinued because too many mice either died outright or (I suspect) were ordered to be euthanased on the authority of the supervising veterinary surgeon due to concerns about animal welfare. I'm assuming Oz has a Home Office much as the UK does which requires Named Veterinary Surgeons to be employed to supervise animal welfare in all laboratories.

We know this from the legend to supplementary table S1. Here is the last section of that legend (sorry that the small letter superscripting is lost, that's blogger for you):

"a Diets 2 low energy and 6 medium energy were discontinued within 23 weeks. b Diets 3 low energy, 3 medium energy and 6 low energy were discontinued within 10 weeks of treatment. These diets were discontinued due to weight loss (≥ 20%), rectal prolapse or failure to thrive".

Here is table S1 with the discontinued (and removed) groups outlined in red:

So, they started with 30 diets groups but five of them had such high early death rates that they were excluded from the study. This left 25 groups. Other than the legend to supplementary table S1 I am unable to find any reference to the loss of five diet groups anywhere in the main paper, which gives the distinct impression that 25 groups were all that were included from the start. So 17% of the mice died at under 23 weeks in to the study, many of those within less than 10 weeks, and you have to read the supplementary data to find out.

All of the high mortality groups were eating 5% of calories as protein.

Did you pick that up in the abstract? No, you didn't.

Is there any excuse for failing to discuss this crucial finding in the results and discussion sections of the paper? You can decide that. It's not exactly rocket science.

My feeling is that the authors could argue, if they were convinced that protein restriction was key to longevity (amino acids, cysteine, mTOR etc don'tchano), that studying early life mortality has no relevance to late life longevity. Why not leave early mortality to the paediatricians? That is a potentially arguable position and should, as it involved a huge chunk of the study mice, have been reported and been justified (if possible) in the results, discussion and especially in the abstract.

The other slight hiccup is this line from the main paper:

"Median lifespan was greatest for animals whose intakes were low in protein and high in carbohydrate... (Figure 2A)"

Figure 2A is not in a format which lends itself to simple interpretation and, obviously, excludes all of the mice which died or were euthanased at less than 23 weeks of age, all of which were in low protein groups. Anyway, you might want to see a simple table of median lifespan for each of the surviving groups. Like supplementary table S2. I've high-lighted the group which had the longest median lifespan in red:

Looks to me like the longest median lifespan group might have been eating 42% of it's calories as protein... Hmmmm. Worth repeating:

"Median lifespan was greatest for animals whose intakes were low in protein and high in carbohydrate... (Figure 2A)".

vs Table S2 giving 42% protein for longest median lifespan.


Let's make this crystal clear: The data demonstrating the actual outcomes are, absolutely, present in the supplementary data of the paper. It is also absolutely crystal clear that the paper itself, excluding supplementary information, does not accurately represent the the actual findings in the study.

If you had to summarise the paper in human terms you could say that applying severe protein restriction to your kids while topping up their calories with sugar and soyabean oil would hopefully result in them being taken away from you and placed in to care before they died.

Please don't try this at home.


My thanks to Rory Robertson for his attempts to have this paper retracted and more accurately rewritten and to Grant Schofield for tweeting about his efforts.

Saturday, January 25, 2020

Coronary Artery Calcium Score and Scleroderma

Dr Malcolm Kendrik has a very interesting post over on his blog relating to coronary artery calcium scoring. I think it is fair to say that he is not in favour of the test.

My ears pricked up (metaphorically) when he mentioned myositis ossificans, about which he comments "This does not end well".

I have spent some time in the past thinking about pathological arterial calcification, as applied to the aorta of of patients with familial hypercholesterolaemia. Bear in mind that the dietary advice for patients with FH is about the worst you could possibly imagine and, of course, has no evidence base. My thoughts and assorted links are in an old blog post here. At the time I had never heard of Sci-hub so was unable to access this rather neat diagram of the mechanism of action of insulin, Pi and pyrophosphate:

Back to pathological soft tissue calcification. Clearly the obvious question about myositis ossificans has to be to ask whether it is in part driven by hyperinsulinaemia/hyperglycaemia or both.

As far as I am aware this is not a question which had been asked. It is simply genetic and that's it.

However, a similar question has already been answered in relationship to a serious generalised soft tissue mineralisation condition described as "calcinosis and scleroderma", back in a publication from 1932 (apologies to the person who tweeted the link, I didn't note their name to acknowledge. And twitter is ephemeral). That is too long ago to be listed on Pubmed so if you would like to read it you can go and ask Elsevier how much they would like to charge you for a peek in to the past or you can go to that awful place that none of use ever use to download any paper for free.


"Calcinosis and scleroderm" looks to be one of a family of soft tissue calcification diseases. The case report from 1932 describes the complete remission of this extremely unpleasant condition in a child following a period of time on ketogenic diet of the type used at the start of the last century, before dieticians were invented/summoned from Hades.

Did the ketogenic diet resolve this child's pathological calcification by suppressing insulin levels, glucose levels or both? Does it work by lowering alkaline phosphatase production by cells in/around inflammatory lesions? Or by some other mechanism?

Would it do the same for pathological arterial calcification? Given a tool like the ketogenic diet, perhaps there is some logic to CAC testing?

Unless you feel that tissue calcification is an appropriate part of healing until it gets to scleroderma levels...


Tuesday, January 21, 2020

Barja, an aside

I quite enjoyed Barja's review

The Cell Ageing Regulatory System (CARS)

but found this section a little uncomfortable:

Hmmmmmm. Plant based, healthy fruit and vegetables, bad animal fats. Not my sort of outlook really.

In another of his publications here

Highly resistant macromolecular components and low rate of
generation of endogenous damage: Two key traits of longevity

there is this comment

"It was also found that 6–7 weeks of dietary restriction are enough to decrease MitROS production and 8-oxodG in mtDNA and nDNA in rat liver (Gredilla et al., 2001a )".

Gredialla et al (incl Barja) 2001a is

Effect of short-term caloric restriction on H2O2 production and oxidative DNA damage in rat liver mitochondria and location of the free radical source

Here they found, by eyeball, an approximately 50% reduction of in 8-oxodG in mitochondrial DNA after those six weeks of quite severe caloric restriction:

Now let's compare this with the degree of damage reduction (this time using the term 8-OHdG as the marker rather than oxo-8dG, which appears to be the same thing).

Here's the change in mtDNA damage marker in brain mitochondria using F3666, one of the worst ketogenic diets around:

Just by eyeball I make the drop in mtDNA damage out to be greater than 50% by two days and something like 75% by three weeks. On ad-lib food consumption. No hunger.

Considering that F3666 does not extend longevity in mice (it doesn't shorten lifespan either, despite causing liver damage and it does actually improve health during ageing in rodents) this does, for me, slightly knock some of Barjas core ideas.

Sad but true.


Wednesday, January 15, 2020

Stearic acid again

Better post this one while I have a few minutes. I picked it up while looking for refs for Gustavo Barja's epic The Cell Ageing Regulatory System (CARS) in which longevity is tied to the Double Bond Index of the mitochondrial inner membrane (Thanks Bob!). BTW it is possible to modify the DBI but, with current data, it looks like you cannot alter the saturated or MUFA percentages, it is replacing omega 3s with omega 6s which mimics the mitochondria of long lived mammals!

Anyway, here is the cocoa butter paper:

Differential effects of saturated versus unsaturated dietary fatty acids on weight gain and myocellular lipid profiles in mice

Here are the diet compositions:

The line in red is the total percent of calories from linoleic acid in each diet. Here are the body weight changes:

The bottom two lines are the low fat high carbohydrate diet which happens to come in at just 1% linoleic acid and the cocoa butter diet which comes in at 1.4% of calories as linoleic acid. The high palmitic acid gives the most weight gain as it delivers 4.5% of calories as PUFA. Olive oil is a close second, also with 4.5% linoleic acid. The oddity is the safflower oil diet which is very high in PUFA but only gives intermediate obesity. Quite what is going on here is difficult to say but you have to wonder at what level of omega 6 PUFA that "next level up" signalling (lipid peroxide based) kicks in. No data on that, just a guess/excuse from the Protons perspective. There are a number of other studies showing this phenomenon of limited weight gain with safflower oil.

Still, stearic acid as cocoa butter is still looking pretty good. All of the high fat diets were based around different fat sources placed in to the D1245 background so are equally high in sucrose and starch too, comparable amounts across all of the higher fat diets.


Thursday, January 02, 2020

Protons (53) a formula

A couple of things came up in emails recently. First is that I never mention that I had a chat with Ally Houston on the Paleocanteen podcast. It was fun. I think I sound like me. It's here

Second is that karl asked if there was a general formula for working out the F:N ratio for assorted fatty acids.

Edit: cavenewt pointed out that for people unfamiliar with the FADH2:NADH ratio concept there is a reasonable introduction at Protons: FADH2:NADH ratios and MUFA. PubMed-ing Dave Speijer and CoQ makes good reading too. End edit.

There wasn't but given a few minutes and some algebra it works out like this for even-numbered, fully saturated fatty acids of carbon skeleton length n:

F/N   =   (n-1)/(2n-1)

So stearate (C18) is 0.486

Palmitate (C16) is 0.484

Caprylate (C8) is 0.467

For MUFA/PUFA you just subtract one FADH2 per double bond (db). This doesn't affect the NADH term.

F/N  =  (n-1-db)/(2n-1)

Oleate (db = 1) is 0.457

Oleate is the MUFA of stearate. Saturated fats allow us to resist insulin, MUFA allow insulin to act.

Linoleic acid, also C18 but with two double bonds, gives 0.429

This is lower than stearate or oleate. The switch for ROS generation occurs between roughly 0.486 (high physiological ROS) and 0.457 (low physiological ROS). LA is lower than oleic acid.

Glucose has an F/N ratio, from memory, of 0.2 so LA is the "glucose-like" of the common fatty acids, in Mike Eades' terminology, and so will fail to generate fatty acid appropriate ROS. Which will allow continued insulin action when it should be resisted. That will make you fat, and the loss of calories in to adipocytes will make you hungry. The exact opposite of stearic acid...

Happy New Year all.


Tuesday, December 24, 2019

Stearic acid: Skinny-skinny vs skinny-fat

This paper came up in comments to the last post:

Dietary Stearic Acid Leads to a Reduction of Visceral Adipose Tissue in Athymic Nude Mice

I think we can say that, at least in athymic nude mice (which do not seem to be derived from the C57Bl/6 strain), omega 6 PUFA do not cause obesity when compared to either a low fat or high stearic acid synthetic diet (ie the low fat arm is equally synthetic, not more "food-like" ie not chow). At least when you look at total body weights:

So omega 6 PUFA appear to get a free pass here. The actual composition of the diets is in Table 1 of this previous paper and all four contain generous amounts of starch and equal amounts of sucrose:

Dietary Stearate Reduces Human Breast Cancer Metastasis Burden in Athymic Nude Mice

However if you dexa scan the mice you find that the low fat, corn oil and safflower oil groups all have reduced lean mass (probably muscle) and increased visceral fat mass compared to the stearate group. A picture is worth a thousand words so here are some postmortem images with the size of the inguinal fat pads outline by the authors of the paper (no need for me to doodle on this one!). Fig 3:

I really like these images.

Now, cavenewt questioned the relevance of weight/fat alterations from stearate compared to other potential health effects, particularly its affect on cancer metabolism.

The third paper from this same group is

Prevention of carcinogenesis and inhibition of breast cancer tumor burden by dietary stearate

I've been through all three papers and searched on "insulin". The group appears to have no concept that insulin has anything to do with adipocyte size or cancer progression.

A slight handicap when it comes to insight.

In the stearate-visceral fat paper there is a single measurement made of plasma insulin/glucose. Insulin does not vary between diet groups but glucose is significantly lower in the stearate group. I have been unable to work out if the measures were fasting or fed, or even what time of day the samples were taken (ie when the mice were killed). I think that with glucose values in to 200-250mg/dl range these were probably "fed" glucose and insulin levels. The paper does not give us the measured insulin levels, merely that there was no statistically significant difference between groups. But insulin levels come with such huge standard deviations that getting a p value below 0.05 with small group sizes is not going to happen. A ns result does not automatically mean that there were no differences.

Of course a single insulin measurement at one terminal time point tells us nothing about the long term 24h exposure to insulin of the mice, of their adipocytes or of their cancer cells.

So we have to, once again, look at the significance of the changes in fat distribution to attempt to gain insight in to overall insulin exposure. I spent quite some time looking at visceral fat and its significance early last year in this post:

On phosphorylation of AKT in real, live humans. They're just like mice!

and on how stearate might avoid systemic hyperinsulinaemia here:

Dairy and diabetes

Visceral fat is a surrogate for chronic hyperinsulinaemia, particularly fasting hyperinsulinaemia. While I consider non-inflamed visceral fat to be completely benign, or even beneficial for controlling the hunger of fasting, the insulin which maintains that visceral lipid storage is not benign. Chronically elevated insulin (or, more accurately, insulin signalling) should drive both visceral fat storage and xenograft tumour growth in the mice. Probably in humans too.

Happy Solstice and assorted mid-Winter celebrations. If you live in the northern hemisphere that is. Not that I envy those with a Solstice-on-the-beach-without-wooly-hats-and-gloves situation!


Saturday, December 14, 2019

Protons (52): A correction and a few thoughts on satiety

There has never been a completed concept of the Protons thread. Logic and data have allowed it to emerge and I still have no idea where it will end, but there have been a few mis-steps on the way. A reader recently pointed my incorrect post from 2013 where I was looking to see how fasting or ketogenic diets might blunt insulin signalling. Nowadays my feeling is that it is high physiological ROS generation which achieves this. At the time I clearly got it wrong with:

"We appear to have two basic states of the electron transport chain. There is the situation under fasting or ketogenic dieting conditions. Here delta psi is low, complex I throughput is low and there is plenty of FADH2 input through electron transporting flavoprotein dehydrogenase coming from the first step of beta oxidation of real fats, like palmitic acid. With a low delta psi it is near impossible to generate reverse electron flow through complex I so activation of insulin signalling is rapidly aborted by the continuing action of tyrosine phosphatase".

That does not appear to be the case and, having thought about it, my email reply went like this. We had been chatting about ketones, delta psi, RET and insulin resistance from ketones vs from saturated fats. I may as well copy/paste some of it here, slightly edited for clarity, and place a link within the 2013 post:

"My thinking currently is that ketones do not induce insulin resistance unless, like glucose, there is enough input via complex II to do this. So RET is possible but will only occur when the cell has adequate caloric supply. If you combined ketones with stearic or palmitic acid the long chain fatty acid would undoubtedly input at ETFdh and drive RET, rather than it being the ketones. Incidentally, this probably also represents "cellular satiety". Clearly under physiological conditions ketones will normally be associated with elevated FFAs.

The differential effects of FFAs vs ketones would be that FFAs would then drive insulin resistance in cells which can metabolise them, muscle etc, but ketones would drive far less RET in cells which require some small amount of glucose in excess of the energy supplied by the ketones themselves, ie neurones…

On the adipocytes things look more complex. Undoubtedly both ketones and FFAs exert a negative feedback on lipolysis in addition to any effect of their driving/not driving RET during oxidation. But some degree of insulin signalling is essential to physiology in addition to this negative feedback, otherwise we get diabetic ketoacidosis due to failure of insulin availability to oppose glucagon.

Once you start to think about stearic acid plus glucose you have to differentiate between cellular levels and dietary levels. Simply treating isolated adipocytes with elevated glucose and elevated long chain FFAs will result in ROS. If you set your experiment up correctly (no MUFA, no PUFA, high glucose) the resulting RET will result in apoptosis or necrosis. There is an infinite supply of papers doing this to almost any cell type.

In the whole animal things are different. If physiology is functional the stearic acid will provoke a prompt first phase insulin response and will effectively augment insulin delivery via the portal vein to the liver. Insulin acting in the liver will limit glucose release to the systemic circulation and so limit the need for systemic hyperinsulinaemia to deal with the glucose. Then the animal stays slim as there is minimal systemic hyperinsulinaemia.

If physiology is non functional we are talking DM T2 which is largely the aftermath of chronic PUFA ingestion and things then become even more complex. The low carb approach side steps the problems of failure of correct insulin secretion/hepatic signalling by simply reducing the reliance on any sort of insulin signalling beyond the most minimal needed. Then stearic acid becomes problem free. When (or if) physiology normalises then some degree of glucose consumption by mouth might be acceptable along side saturated fats but by then anyone with any sense will be fat adapted and unwilling to go back to a mixed diet".

This set of thoughts is currently relevant as Brad Marshall has taken the concept of stearic acid as the best physiological generator of adipocyte physiological insulin resistance and converted it in to a moderate carb, highly saturated fat diet with interesting results. You can read about his croissant diet on his blog Fire in a Bottle: Introducing The Croissant Diet. This experiment is based on the PhD of Valerie Reeves where a mixed macro diet based around stearic acid markedly limited weight gain in db/db mice. The db/db mouse is an extremely severe obesity model as it lacks functional leptin receptors. So a complete lack of leptin signalling can be side-stepped, still in the presence of starch, by supplying roughly 40% of calories as predominantly stearic acid. Not low carb. Not ketogenic. It works (from my point of view) by directly manipulating ROS generation (ie increasing it) at the electron transport chain level to signal "cellular" satiety, with appropriate ability to resist insulin's fat storage signal. This will be recapitulated in the brainstem neural circuits which control whole body satiety. Signalling from the ETC is core. It works by generating physiological insulin resistance and clearly over-rides any effect from leptin signalling.

Also in the comments of the last post came this gem from ctviggen, worth a post in its own right. Interesting paper. Limited insights within the discussion but great data!

Dietary Stearic Acid Leads to a Reduction of Visceral Adipose Tissue in Athymic Nude Mice

While all of these ideas were kicking around the concept of fasting as a state of caloric excess emerged. Obviously, not eating makes you hungry. Initially. There comes a point where, when insulin is low enough and FFAs rise to levels approaching over 2000micromol/l (plus ketones), when hunger decreases. Prolonged fasting does not invariably generate ravenous hunger. This is because FFAs (and ketones) represent an energy glut beyond any single cell's imagination and it does not require insulin signalling to access it (there do appear to be other controls on ATP generation). So cells which can metabolise FFAs should behave as it they have more than enough calories so that they should resist insulin. Access to excess metabolic substrate must result in ROS and the appropriate disabling of insulin signalling. Starvation as generator of a caloric excess signal... An interesting concept.

And PUFA, failing to generate adequate ROS, might well lead to glucose "wastage" in to cells such as myocytes which might well result in profound and symptomatic hypoglycaemia, essentially a failure of satiety signalling. Another interesting idea. Which clearly would not happen if metabolism was based around stearic acid...


Wednesday, November 27, 2019

Of mice and men

I usually start from the premise that insulin makes you fat. The most simplistic prediction from this is that eating carbohydrate raises insulin and this insulin is what makes you fat. Over the years I have looked at data from all sorts of places, particularly the extremes such as the Kempner Rice Diet and/or the Potato Diet, which clearly work and which appear to do so (to me!) via lowering the level of systemic insulin acting on adipocytes. In particular I consider that first pass hepatic insulin extraction has a huge effect on the systemic insulin level and the subsequent exposure of adipocytes to that insulin. The carbohydrate-insulin-model of obesity as set up by detractors is simplistic in the extreme.

This paper was published recently:

The carbohydrate-insulin model does not explain the impact of varying dietary macronutrients on body weight and adiposity of mice

Of all of the combinations tested the one which we are interested in is where protein was held constant at 10% of calories and carbohydrate was varied from 10% of calories up to 80% of calories. The remaining calories were made up of fat giving a pure carb vs fat comparison. At the end of the study period we have this graph where I have added in the percentages of calories from fat in red along the x axis:

If you draw a straight line through the data points your weight line slopes downwards as fat percentage drops, pretty well. Fat makes you fat:

Now, clearly, there is a missing data point. That is the bodyweight from a diet group with zero carbohydrate, 10% protein and 90% fat. This combination was not included in the study.

So all else from here forward in this post is now pure speculation.

Help is at hand for the missing data point in this paper

A high-fat, ketogenic diet induces a unique metabolic state in mice

Here we also have C57Bl/6 mice and in this case they were fed F3666 diet which looks like this:

"The proportion of calories deriving from different nutrients was as follows: ... KD:95% fat, 0% carbohydrate (0% sucrose), 5% protein"

This is not a perfect fit as the protein is about half that used by Speakman and there is (obviously) no sucrose, but it's the best anyone can do in the absence of the omitted group essential to complete the graph. The mice which were eventually put on to F3666 were initially made obese with a sucrose/fat combination before being put on to their ketogenic diet. Their weight dropped from approx 37g on the sucrose/fat diet to approx 27g on F3666, ie they ended up about 3g lower in total bodyweight than the control mice fed approx 10% of calories from fat in a carbohydrate based diet throughout. Here's the graph we all know from years ago. Open triangles show the drop in weight when F3666 was introduced at around day 80:

So what might a zero carb, fairly low protein group of C57Bl/6 mice look like? They might well end up slightly below the weight of Speakman's 80% carb group mice, (ie those eating closest to mouse chow), or they might end up slightly heavier due to the higher protein content limiting the total fat percentage which could be provided. I feel a compromise might be to use 35g, the same as Speakman's 80% carb group, the closest chow equivalent.

I've added the zero carb speculative data point to the blue line on the graph at 35g bodyweight which now looks like this:

and now we can curve fit the bodyweights like this:

Ah, that's better. Ketosis at the left, "carbosis" at the right. Nice.

I love rodent studies. You just have to understand that setting them up correctly is essential to obtaining the result you want. You also have to know what you want.


Monday, November 11, 2019

Protons (51) From peripheral cells to the brain

Hunger and satiety. Can these be modelled from a very simple energy availability concept?

This post is a minimally referenced ramble through how I see satiety working.

At the peripheral cellular level energy influx is controlled, to a large extent, via reactive oxygen species. These regulate insulin signalling which controls the translocation of GLUT4 and CD36 proteins to the cell surface and so facilitates the diffusion in to the cell of glucose and fatty acids respectively.

When a single cell has adequate calories it generates ROS, largely from the electron transport chain, which disable insulin signalling. This insulin "resistance" is there to limit excessive ingress of calories. ROS are the signal that no further calories are needed. At the most basic level cellular energy ingress is regulated by the core energy utilising apparatus of the cell. Excess substrate means excess ROS means shut down caloric ingress.

This is a self-contained cellular satiety signal of the most basic type. When the cell has fully adequate supplies of ATP, a high mitochondrial membrane voltage and a deeply reduced CoQ couple then ROS generation becomes almost inevitable.

It is a core, deep level, simple system. How it works is the subject of the Protons thread of posts, as is how it malfunctions.

I find it very, very difficult to envisage that the control of ingress of calories on a whole body basis (hunger/satiety) is not similarly integrated around an ROS generating system within dedicated neurons of the brain, with the hypothalamus being the most likely location.

I've had this as a persistent suspicion for a very long time but you can't get around to reading about everything at the same time. And I have to admit that neurological thinking about hunger and satiety has always struck me as a highly disreputable field. Insulin and satiety smell like cholesterol and the lipid hypothesis.

So yesterday I finally went and had a look for a reasonably recent review of ROS within the hypothalamus and this one came up pretty high in the PubMed listing

Impact of hypothalamic reactive oxygen species in the regulation of energy metabolism and food intake

This gives a flavour:

"Thus, it appears that NPY/AgRP neurons activation is mediated by a decrease in ROS levels while POMC neurons activation is driven by ROS (Andrews et al., 2008). Indeed, icv administration of ROS scavengers induces significantly lower c-Fos expression in POMC neurons and increases food intake during light cycle, observed via an increase of c-Fos expression in AgRP/NPY neurons (Diano et al., 2011). Similarly, addition of H2O2 depolarizes POMC neurons, increases the firing rate, and an icv injection of H2O2 causes significantly less feeding of mice after an overnight fast".

A lot of the work cited is not terribly well performed and no one has the Protons framework to slot their findings in to, but it's a start. What I am looking for is that these cell types do express GLUT proteins and CD36 proteins. I would expect them to be sampling arterial blood or CSF and integrating NADH and FADH2 inputs to their mitochondrial electron transport chain to "decide" whether there are adequate calories to consider that satiety or hunger might be the preferred descriptor of the body's current state.

Whether these cells express insulin receptors to facilitate ingress of substrate is something to be picked at. As I am completely biased against the concept that insulin is a satiety hormone, I would prefer this not to be the case but may be wrong. Time will tell. It looks logical to me that the brain would look at the nutrient levels present in excess of those being disposed of by peripheral insulin in to peripheral cells. As large numbers of peripheral cells become "full" under the influence of insulin, the brain should pick up the rising level of excess nutrients as the signal to call a halt on hunger. Doing this within the brain shouldn't need insulin, merely a set of relatively low affinity transporters to allow glucose and lipid uptake as insulin completes its peripheral function. Satiety should be picked up when enough cells have enough calories, whole body, that they no longer behave as a calorie "sump". The job of the brain is to pick up evidence from the nutrient levels that the sump is full and satiety can be declared.

For hunger, high affinity transporters would allow ROS to be generated easily and falling ROS would signal that energy availability was low.

These signals will come from the neural mitochondrial ETC generating ROS. The best ROS generating nutrients will be the most satiating. Saturated fats spring to mind if you follow the Protons thread.

Obviously there are whole load more hormones which can influence the generation of ROS within neurons. Physiology has applied layers and layers of signalling to maximise reproductive fitness. I have minimal interest in these "higher level" signals. They are there, they will modulate the core process I've been talking about but I see no way that they will do anything fundamentally different from or in opposition to the ROS system.

I'll give the rest of the review a bit of a read and see if it's worth posting about.


Friday, November 08, 2019

Insulin makes you hungry (11) But not in Denmark?

Preamble. The best papers are those which challenge your ideas. When they conflict with what appears to be very hard evidence which support your mindset they become really exciting. Sometimes you just have to shrug, label the new finding as important and put it on the back burner to be ruminated about over the coming months. Sometimes a potential explanation is possible. This post is essentially a fairytale set in Denmark. It may be completely wrong. Or not. Here we go.

This paper came up in the comments to the last post from Gabor Erdosi via raphi. It is from Astrup's group in Denmark and I have to say I have a lot of time for Prof Astrup as he was one of the more influential people who objected to the gross stupidity of Denmark's transient fat tax a few years ago. The fat tax was abandoned quite rapidly as sensible EU dwelling Danes merely popped across their open border and stocked up with un-fat-taxed butter in Germany. Anyway:

The role of postprandial releases of insulin and incretin hormones in meal-induced satiety-effect of obesity and weight reduction

This is the crucial graph

Take 12 lean people, feed them a 600kcal sandwich for breakfast, wait just over three hours then offer them an ad-lib, well mixed pasta salad and see how much of this they eat.

The higher their insulin went after breakfast, the less they ate at lunchtime.

Insulin exposure is clearly associated with reduced subsequent food intake. You might be tempted to assume causality here, but you can't. It's an observational study of a very specific set of people. It can be used to generate an hypothesis, such as insulin suppresses subsequent food intake. But then you would have to test that hypothesis.

You could also simply go back through the literature to interventional studies which actually imposed changes in insulin levels and come to the opposite conclusion. Rodin et al did this here

Effect of insulin and glucose on feeding behavior

which makes that particular hypothesis untenable. Insulin makes you hungry.

Here are the core findings, clamp values first

Here are the hunger ratings

and the amount of liquid food consumed, via a straw, through a screen:

To me personally, his study is very convincing. The principle is simple, logical and comprehensible. I would have been happier if he had also tracked FFAs in the study but we all know what insulin does to FFA levels (in the absence of fat ingestion). My personal view is that the brain looks at the availability of calories. Normoglycaemia with rapidly falling FFAs (the effect of insulin on adipocytes) is going to generate hunger. No one would expect any different. The action of insulin is the inhibition of lipolysis. Much higher levels are needed to facilitate the uptake of glucose.

We have a paradox, excellent. Direct insulin infusion makes you hungry. Insulin response to food makes you less hungry.

That is so cool.

Sooooo. Is it even remotely possible to explain the observation picked up by Prof Astrup in his 12 lean Danes? Starting from the basis that insulin drives calorie loss in to adipocytes with subsequent hunger? Speculation warning.

This group of Danes is very unusual. They have lived, on average, for 34 years in modern Denmark and they are not over weight. They have never counted a calorie, never been to Weight W@tchers, never had an eating disorder. They eat as much as they are comfortable with and eat again when they are hungry. If they pig out at Christmas they don't need to go on a diet in the New Year. They put zero effort in to being lean. That is a very special sort of person. They have normal appetite control.

When we give them a fixed calorie breakfast the insulin response varies. With these normal people I think it is a reasonable assumption that if the 600kcal is high compared to their preferred size of breakfast, the insulin level will go higher. There is more food than needed so more to store, that needs more insulin.

Members of the group who fancied many more than 600kcal for breakfast will have produced a low insulin response to the 600kcal specified by the study.

Now, it gets interesting because you cannot remotely account for a 1200kcal (3000kJ) difference in lunchtime eating by speculating about preferred breakfast size. The effect is too big.

The storage of calories is the simplest of actions of insulin. It does other things too. For these we have to go to the very, very artificial model of Veech's isolated working rat hearts. However some of the findings do have some bearing on real life.

In this paper

Substrate signaling by insulin: a ketone bodies ratio mimics insulin action in heart

we have this snippet:

"Unexpectedly, insulin increased cardiac hydraulic work but decreased net glycolytic flux and O2 consumption, improving net cardiac efficiency by 28%".

Insulin facilitates glucose diffusion in to the myocytes but partitions it in to stored glycogen. Glycolysis actually decreases but there is an increase in efficiency which gives the 28% increase in cardiac work.

Let that sink in. Insulin makes energy production more efficient while diverting calories in to storage. If you wanted to fatten someone up that seems like a good plan.

From a related paper by Veech's group

Insulin, ketone bodies, and mitochondrial energy transduction

we have a slight elaboration:

"The increase in efficiency associated with insulin administration is not readily explained by such a straightforward mechanism [as for ketones]; other factors, such as reduction of the mitochondrial NAD couple or specific effects like covalent modification of mitochondrial membrane protein, will have to be considered as possible factors altering efficiency of ATP synthesis".

Veech's model runs on glucose alone but there will undoubtedly be residual FFAs in the cardiac myocytes. You just have to wonder whether the effect of insulin is to extract these from the mitochondrial uncoupling proteins and covalently bind them in to intracellular triglycerides. An interesting idea and it would certainly tighten the coupling of the ETC.

Bottom line: Insulin, when working as it should, diverts calories to storage but increases efficiency of energy production to allow normal metabolism. I hold that this happens in the elevated insulin individuals of the lean subject group. Recall that all of these people are naturally lean. When the insulin wears off they realise, metabolically, that they have gained a (very) little weight while running a very efficient metabolism. If they have extra stored calories which, being naturally lean, they don't need, why should they eat much at lunch time?

The hypoinsulinaemic lean people get their 600kcal, decide it is way too little to bother storing and partition it towards utilisation. There is no drive towards storage, very little insulin, no insulin mediated increased efficiency. Substrate is available, it gets oxidised. Very little gets stored. This is the low insulin state. When lunch is presented to this naturally weight stable person their metabolism realises that it has not maintained fat stores after the 600kcal breakfast so they eat more at lunch time.

We have a period of high efficiency calorie conservation in the high insulin group and a period of low efficiency calorie wastage in the low insulin individuals. Because these people have that rare gem, a functional metabolism, they simply adjust subsequent food intake to reflect their previous fuel partitioning during the three hours from breakfast to lunch.

It is perfectly reasonable to mistake this scenario as an indicator that insulin is a satiety signal. Easily done. It's incorrect.


The invariable after-thought: Does insulin correlate inversely with reduced food intake in either the obese group at the start of the study or after marked weight loss?

No. Of course not.