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Tuesday, 17 January 2017

Will a ketogenic diet increase the risk for malignant melanoma?




It's well-known that ketogenic diets reduce the growth of some cancer types in humans. These are early days for learning which cancer types are most vulnerable, which diet is best, and what the mechanisms are; Warburg had a clue, but the Warburg effect is far from the whole story.

On the other hand, there are cancer types that may not respond to a ketogenic diet. Prostate cancers seemed a likely candidate, because there is an inverse correlation with type 2 diabetes, but in animal models a ketogenic diet improves survival.[1]

But recently some U.S. researchers have provided evidence that acetoacetate accelerates the growth of an important type of malignant melanoma, cells with a BRAF V600E mutation.[2]

We recently reported that the ketone body acetoacetate selectively enhances BRAF V600E mutant-dependent MEK1 activation in human cancers. Here we show that a high-fat ketogenic diet increased serum levels of acetoacetate, leading to enhanced tumor growth potential of BRAF V600E-expressing human melanoma cells in xenograft mice. Treatment with hypolipidemic agents to lower circulating acetoacetate levels or an inhibitory homolog of acetoacetate, dehydroacetic acid, to antagonize acetoacetate-BRAF V600E binding attenuated BRAF V600E tumor growth. These findings reveal a signaling basis underlying a pathogenic role of dietary fat in BRAF V600E-expressing melanoma, providing insights into the design of conceptualized “precision diets” that may prevent or delay tumor progression based on an individual’s specific oncogenic mutation profile.



I have some issues with this - firstly, that "Dietary fat promotes ketogenesis to enhance BRAF V600E tumor growth." Dietary fat will only do this in a ketogenic diet. It doesn't take much carbohydrate and/or extra protein to stop it. Fasting or a very low calorie diet will promote ketogenesis too; the rate of oxidation of fat when you skip carbohydrate and restrict protein is exactly the same as when you don't eat, except that ketone levels stay lower over the longer term. So if ketone bodies from fat oxidation promote melanoma, fasting should be worse than a ketogenic diet.

Obesity and type 2 diabetes are conditions that suppress ketogenesis and make it hard to get into ketosis. They are the opposite of fasting. They should be protective against malignant melanoma; they're not. However, the relationship is weak and inconsistent, which might show some effect, countering the usual pro-cancer mechanisms in these conditions. 
Type 1 diabetes is a condition that frequently exposes people to high ketone levels. Type 1 diabetes seems to be inversely, but non-significantly correlated with melanoma in Sweden, standardized incidence rate of 0.8 (0.5 to 1.1).[3] 



This evidence doesn't refute the ketone-melanoma link in humans, and it doesn't relate to ketogenic diets, but it does show that there are many influences on melanoma (deficient vitamin D3 and hyperleptinaemia, and glutamine as a fuel, appeared in a cursory search) that might swamp the ketone effect.

One of the findings in the latest study was that cholesterol increased in the mice on the ketogenic diet. This is presumed to deliver more lipid to cells. Prostate cancer cells upregulate the LDL-receptor to take in more lipid. and the function of this is to take in more omega-6 fatty acids to make prostaglandins which promote tumour growth.[4] This is relevant to the present case because polyunsaturated fatty acids are especially ketogenic; however, the fat used in this experiment was a mixture of 1 part corn oil to 6.5 parts Primex, which is "pure vegetable shortening, a mixture of partially hydrogenated soybean and palm oil". None of these are fats that anyone on a ketogenic diet would use, and all, it turns out, are contaminated with carcinogens. However this would have had little effect in the context of this experiment.

This dodgy version of a ketogenic diet did not increase tumour size in the mice with the alternative malignant melanoma mutation.


It may be that polyunsaturated fatty acids can promote ketogenesis more easily than other fats in cells that don't normally produce ketones:

This paper summarizes the emerging literature indicating that at least two polyunsaturated fatty acids (PUFA; linoleate, alpha-linolenate) are moderately ketogenic and that via ketone bodies significant amounts of carbon are recycled from these fatty acids into de novo synthesis of lipids including cholesterol, palmitate, stearate and oleate. This pathway (PUFA carbon recycling) is particularly active in several tissues during the suckling period when, depending on the tissue, >200 fold more carbon from alpha-linolenate can be recycled into newly synthesized lipids than is used to make docosahexaenoate. At least in rats, PUFA carbon recycling also occurs in adults and even during extreme linoleate deficiency.[5]

We have many thousands of people around the world using various types of ketogenic diets or fasting, some for a very long time (lifetimes in the case of some people with pediatric epilepsy), and a large proportion of them nowadays are relatively sceptical about sunscreen. There are no case studies of melanoma in such people that I could find, and I have come across no reports in many years on social media.
This is not to say that a ketogenic diet or fasting is a treatment option for 
BRAF V600E melanoma, this is I think good enough evidence to decide that it's probably not. However, it's likely that other benefits of keto diets and fasting, viz. improved insulin and leptin status, decreased inflammation, lower glutamine, improved vitamin D status, hormetic antioxidants, avoidance of refined oils and a good omega 3:6 ratio, etc. decrease all the other changes that lead to a tumour's appearance in the first place.
Edit 20-01-17

The research I cited here has received ample funding from an impressive array of sources, but not all ketone-and-cancer research receives public funding. Thus E.J. Fine and R.D. Feinman are now crowd-sourcing funding for a simple experiment, certainly much less expensive than the one above, which is testing the effect of acetoacetate on a variety of different cancer cell types and looking at the metabolic pathways associated with response and non-response, specifically those that control ROS generation and cytotoxicity.

Our 28 day pilot human trial of 10 subjects with advanced cancers on a very low carbohydrate ketogenic diet (KD) was publilshed in Nutrition (Elsevier) in 2012. Patients with the greatest extent of ketosis had stable cancers or partial remission, while those with the least ketosis showed continued progressive cancer.
In cell culture studies we published that ketone bodies (KB) inhibited growth of 7 different cancers from 20-50%, leaving normal cells unaffected.
Despite a favorable editorial & the Metabolism Award, our proposal to scale up to 65 patients & extend our cell culture work was rejected by the NIH/NCI, as they are committed to drug therapy. We appeal now to people who are interested in supporting promising dietary cancer research.

You can donate here https://experiment.com/projects/part-2-can-low-carbohydrate-ketogenic-diets-inhibit-cancers or support the project by buying a cool T-shirt here.
https://www.booster.com/support-research-on-ketogenic-diets-for-cancer2


[1] Masko EM, Thomas JA, Antonelli JA, et al. Low-Carbohydrate Diets and Prostate Cancer: How Low Is “Low Enough”? Cancer prevention research (Philadelphia, Pa). 2010;3(9):1124-1131. doi:10.1158/1940-6207.CAPR-10-0071


[2] Siyuan Xia, Ruiting Lin, Lingtao Jin, et al.  Prevention of Dietary-Fat-Fueled Ketogenesis Attenuates BRAF V600E Tumor Growth. Cell Metabolism (2016), http://dx.doi.org/10.1016/j.cmet.2016.12.010

[3] Zendehdel K, Nyrén O, Östenson C-G et al. Cancer Incidence in Patients With Type 1 Diabetes Mellitus: A Population-Based Cohort Study in Sweden. JNCI J Natl Cancer Inst 2003; 95(23): 1797-1800.
[4] Chen Y, Hughes-Fulford M. Human prostate cancer cells lack feedback regulation of low-density lipoprotein receptor and its regulator, SREBP2. Int J Cancer. 2001; 91(1):41-5.



[5] Cunnane SC. Metabolism of polyunsaturated fatty acids and ketogenesis: an emerging connection. Prostaglandins Leukot Essent Fatty Acids. 2004: 70(3):237-41.




Monday, 2 January 2017

Scientific Fraud, in the Abstract

Someone posted this scare story from November in the Low Carb and Paleo group on Facebook.
Luckily I missed it at the time as I was busy with arguably more important things, but being on holiday now I think it warrants a little attention.
It was an abstract - that's all for now - presented at a conference of the American Heart Association, based on data from the WHI study (Womens' Health Initiative - the follow-up from the huge, long-term study where lowering saturated fat in the diets of women seemed to cancel out all the expected benefits from improving carbohydrate quality and reducing trans fat intake).

It generated headlines like 

Mostly meat, high protein diet linked to heart failure in older women (AHA)
American Heart Association Meeting Report – Presentation: 627 – Session: EP.RFO.28

NEW ORLEANS, Nov. 14, 2016 — Women over the age of 50 who follow a high-protein diet could be at higher risk for heart failure, especially if much of their protein comes from meat, according to preliminary research presented at the American Heart Association’s Scientific Sessions 2016.

Researchers evaluated the self-reported daily diets of 103,878 women between the ages of 50 and 79 years, from 1993 to 1998. A total of 1,711 women developed heart failure over the study period. The rate of heart failure for women with higher total dietary protein intake was significantly higher compared to the women who ate less protein daily or got more of their protein from vegetables.

While women who ate higher amounts of vegetable protein appeared to have less heart failure, the association was not significant when adjusted for body mass.

High-protein diet linked to heart failure in older women (CNN)

and so on.

None of these press releases (there were others) linked to any paper, but a bit of searching brought up the actual abstract in a doc.x format.


It says 
Results: Among 103,878 women in the study sample, 1711 women developed HF through 2005. Incremental biomarker calibrated dietary protein consumption was associated with an increase in the risk for Heart Failure. An inverse association was found between higher intakes of energy adjusted vegetable protein and HF although this association wasn’t statically [sic] significant if the association was adjusted to BMI and diet quality.




But what you find here is also that (a) the non-significant association mentioned above was no longer even inverse once fully adjusted, and (b) - in my words -
"An inverse association was found between higher intakes of energy adjusted animal protein and HF, although this association wasn’t statically [sic] significant, if the association was adjusted to BMI and diet quality."





Protein intake was verified with biomarkers, but these were incapable of distinguishing between animal and vegetable protein. The amount of vegetable protein in each quintile, if this study is typical, would have been about 1/3 the amount of animal protein in the corresponding quintile, with the amount of vegetable protein consumed by even the upper quintile being insufficient to support life, so a valid comparison of this sort is not possible. This difference alone is enough to explain the variance in the unadjusted results.

What about total protein? This set of results is not adjusted for BMI 

This matters because heart failure, as a disease of ageing, may be associated with poor appetite, which would tend to increase the protein percentage of the diet. The same is true of heavy drinking, a known cause of cardiomyopathy and heart failure. Overweight also increases the risk of heart failure, as shown by this Mendellian randomisation study.

The results show that an increase of one unit of BMI increases the risk of developing heart failure by an average of 20 per cent.

If that's so, then a high protein, low carb diet would reduce the risk. Mechanistically I can't think of a reason why protein would cause heart failure, and none is mentioned in the abstract. Ketone bodies, a product of protein metabolism even on a high carb diet, are the preferred fuel of cardiac muscle.

In any case, adjustment for BMI is essential, and so is adjustment for diet quality (especially the B vitamins essential for the metabolism of amino acids). Vitamin deficiencies are associated with heart failure, which makes sense mechanistically, and the AHEI 2010 score is one of the diet quality algorithms, confounded by concepts of virtue (it would be better if it focussed on essential nutrients in this case).
Do that, and there's obviously nothing to see.


But even when there's nothing to see, there are plenty happy to report it, as long as it fits the plant-based bullshit bias of the health-reporting media and the AHA.


Friday, 4 November 2016

The HDL correlations in CANHEART probably don't mean what the druglords will want them to mean



The CANHEART study findings on HDL have made a big splash, supposedly debunking the idea that raising HDL is a good idea. Of course, raising HDL with drugs by sticking a spanner in the works at some point has never been an effective strategy, and there are genetic polymorphisms that give elevated HDL of little worth, but healthy diet and lifestyle changes that are reasonably expected to extend life always raise HDL a bit. Is this meaningless?
In CANHEART very high HDL cholesterol was actually associated with higher non-cardiovascular mortality.[1]
Especially levels over 90 mg/dl (2.33 mmol/l), but also over 70 mg.dl in men (1.81 mmol/l).
These are very high HDL levels, I don't remember seeing levels this high in non-drinkers on LCHF diets, no matter how much coconut oil they eat.






The most obvious question is, what about alcohol? Alcohol elevates HDL but at high intakes promotes secretion of useless and atherogenic HDL subtypes. Ko at al claimed to have adjusted for excess alcohol intake, which was highest in those with highest HDL;

"Heavy alcohol consumption, as defined by the use of 5 or more drinks on 12 or more occasions per year was also included in the model for non-cardiovascular non-cancer death."

Newsflash - drinking 6 drinks 13 times per year will not raise your HDL. You really need to be a chronic alcoholic. In 2012, approximately 5 million Canadians (or 18 % of the population) aged 15 years and older met the criteria for alcohol abuse or dependence at some point in their lifetime, but how many at any one time qualify as chronically alcoholic is unknown.


Even so, this adjustment was far from perfect.

"Since the use of smoking and alcohol was not available in entire CANHEART cohort, we imputed smoking status and heavy alcohol use for those with missing data based on the characteristics of the respondents to the Canadian Community Health Survey. Multiple imputation using complete observations and 10 imputation datasets was conducted. Smoking status was available for 5,093 individuals and alcohol use was available for 5,077 individuals who completed the survey."

This was a tiny fraction of the 631,762 individuals in the study - less than 1% - and presumably was either restricted to a single geographical area, or a few especially obliging subjects.
Alcohol intake is known to be misreported in dietary surveys by a factor of 2-3. Alcoholism is probably under-reported to health professionals to a much greater extent, especially in countries where health insurance is a major factor in access to care.

Another confounder is the effect of genetic hyperalphalipoproteinemia. One genetic cause of very high HDL is a CETP defect.

"...the in vitro evidence showed large CE-rich HDL particles in CETP deficiency are defective in cholesterol efflux. Similarly, scavenger receptor BI (SR-BI) knockout mice show a marked increase in HDL-cholesterol but accelerated atherosclerosis in atherosclerosis-susceptible mice. Recent epidemiological studies in Japanese-Americans and in Omagari area where HALP subjects with the intron 14 splicing defect of CETP gene are markedly frequent, have demonstrated an increased incidence of coronary atherosclerosis in CETP-deficient patients. Thus, CETP deficiency is a state of impaired reverse cholesterol transport which may possibly lead to the development of atherosclerosis."[2]


Ko et al do not mention the likelihood of such conditions affecting their analysis. Even if we assume that both chronic alcoholism and hyperalphalipoproteinemia are rare conditions, men with HDL over 90mg/l were less than 0.3% of the study population, and of these few men, only a few dozen died during the study. The exact number isn't clear because the only mortality data given is for adjusted age-standardized rates per 1,000, but from total deaths and these rates I estimate it to be (at the very most) 70-80 deaths, of which 30-35 were non-cardiovascular and non-cancer deaths, out of about 2240 men. The majority of alcohol-related such deaths in Canada are due to alcoholic liver disease, motor vehicle accidents and alcohol-related suicides. Had Ko et al given a breakdown of non-cardiovascular causes of death for the highest HDL categories, it would have been relatively easy to tell how many of these were due to alcoholism.

Overall, people in the high HDL categories exercised more, had lower triglycerides, less diabetes, lower LDL, more ideal BMI, and ate more fruit and vege than people in the middle and lower ranges.
Did these things cause them to die at a higher rate?
Here's an alternative explanation - the baseline characteristics represent only the vast majority of people in each category.  The vast majority of people in each HDL category, even the highest, didn't die. The people who died in the high HDL categories tended to be the people with alcoholism and poorly-managed genetic hyperalphalipoproteinemia, and their baseline characteristics, had they been isolated, would have been quite different. These are the people for whom high HDL is not protective, and, as their numbers increased in categories of increasing HDL, the usual dose-response relationship between HDL and cardiovascular disease and cancer, seen in better-controlled populations, was lost.


A criticism is that Ko et al have misrepresented the lipid lowering trial data to support their thesis.
They say "Several contemporary studies have shown a lack of significant association of HDL-C levels and outcomes for patients on higher-intensity statins, with coronary artery disease, or who had undergone coronary artery bypass graft surgery (12,13,15)."
However, reference 12 states

"In 8901 (50%) patients given placebo (who had a median on-treatment LDL-cholesterol concentration of 2.80 mmol/L [IQR 2.43-3.24]), HDL-cholesterol concentrations were inversely related to vascular risk both at baseline (top quartile vs bottom quartile hazard ratio [HR] 0.54, 95% CI 0.35-0.83, p=0.0039) and on-treatment (0.55, 0.35-0.87, p=0.0047). By contrast, among the 8900 (50%) patients given rosuvastatin 20 mg (who had a median on-treatment LDL-cholesterol concentration of 1.42 mmol/L [IQR 1.14-1.86]), no significant relationships were noted between quartiles of HDL-cholesterol concentration and vascular risk either at baseline (1.12, 0.62-2.03, p=0.82) or on-treatment (1.03, 0.57-1.87, p=0.97). Our analyses for apolipoprotein A1 showed an equivalent strong relation to frequency of primary outcomes in the placebo group but little association in the rosuvastatin group."[3]

In other words, people in the top quartile for HDL and ApoA1 on placebo had the lowest vascular risk, and these people got no extra benefit from LDL lowering with a statin. And because we are looking at quartiles, not isolating a small number of people who have freakishly high HDL for some reason, there is a true dose-response effect of HDL between quartiles in the placebo arm.
This effect has been seen in multiple trials. Drug trials are likely to exclude alcoholics and binge drinkers.
All these 3 references tell us is that the predictive value of HDL is excellent, but is lost when people are undergoing intensive treatment for coronary artery disease, a classic case of Goodhart's law, "When a measure becomes a target, it ceases to be a good measure." We see this again and again with intensive drug treatment of metabolic markers.
Thankfully, it doesn't seem to apply to diet and lifestyle interventions.


References

[1] Ko DT, Alter DA, Guo H, et al. High-Density Lipoprotein Cholesterol and Cause-Specific Mortality in Individuals Without Previous Cardiovascular Conditions: The CANHEART Study. J Am Coll Cardiol. 2016;68(19):2073-2083. doi:10.1016/j.jacc.2016.08.038.

[2] Yamashita S, Maruyama T, Hirano K, Sakai N, Nakajima N, Matsuzawa Y. 
Molecular mechanisms, lipoprotein abnormalities and atherogenicity of hyperalphalipoproteinemia.
Atherosclerosis. 2000 Oct;152(2):271-85.


[3] Ridker  P.M., Genest  J., Boekholdt  S.M., et al; for the JUPITER Trial Study Group. HDL cholesterol and residual risk of first cardiovascular events after treatment with potent statin therapy: an analysis from the JUPITER trial. Lancet. 2010;376:333-339.

Sunday, 25 September 2016

Animal Protein vs Plant Protein - the illusion of scale in diet epidemiology.

This graph appeared in Jason Fung's excellent Intensive Dietary Management blog here. I don't really want to disagree with Jason's statement that animal protein raises insulin more than plant protein, as I haven't looked into the evidence for that or what it means - I merely want to point out that this graph, and the paper it comes from, do not by themselves provide evidence that eating animal protein is associated with a higher risk of developing type 2 diabetes than eating plant protein.


The paper, by Sluijs et al, is titled "Dietary Intake of Total, Animal, and Vegetable Protein and Risk of Type 2 Diabetes in the European Prospective Investigation into Cancer and Nutrition (EPIC)-NL Study" and states 
"During 10 years of follow-up, 918 incident cases of diabetes were documented. Diabetes risk increased with higher total protein (hazard ratio 2.15 [95% CI 1.77–2.60] highest vs. lowest quartile) and animal protein (2.18 [1.80–2.63]) intake. Adjustment for confounders did not materially change these results. Further adjustment for adiposity measures attenuated the associations. Vegetable protein was not related to diabetes. Consuming 5 energy % from total or animal protein at the expense of 5 energy % from carbohydrates or fat increased diabetes risk.
Diets high in animal protein are associated with an increased diabetes risk. Our findings also suggest a similar association for total protein itself instead of only animal sources. Consumption of energy from protein at the expense of energy from either carbohydrates or fat may similarly increase diabetes risk. This finding indicates that accounting for protein content in dietary recommendations for diabetes prevention may be useful."
Leaving aside the implausibility of the finding for the moment, there's an inconsistency in this abstract. If vegetable protein isn't "related to" diabetes, why is total protein a problem?
I knew from reading Song et al recently that the quartiles for vegetable protein actually represent quite small amounts. In the graph above, the upper quartile of vegetable protein is eating 33g/day, while the lower quartile of animal protein is eating 35g/day. So if you want to compare similar amounts of these proteins, you need to compare upper quartile vege with lower quartile animal, and they have exactly the same association with diabetes. And total protein (meat and vege combined) actually had a stronger association with diabetes than animal protein (1.67 in model 3, vs 1.58 for animal protein).

In real life, most people were eating both sorts of protein. Across the animal protein quartiles in Table 1, vegetable protein stayed very constant (people ate much the same amount of wheat). Unfortunately, there is no baseline data that tells us how much animal protein the quartiles of vegetable protein ate.

But let's take a common-sense approach to this data. Model 3, which I cited earlier, isn't adjusted for BMI and waist circumference. The highest protein quartile reports eating fewer total calories than the others, but has significantly greater BMI and waist circumference. And when these are adjusted for (Model 4, Table 2), voila, the association between protein and diabetes disappears from the quartile calculations; only the per 10g association remains. And this, though small, is greater for total protein (1.16) than for animal protein (1.13).
Amount of total protein across quartiles is 64g, 72g, 79g, and 88g. This range hardly seems excessive. Why it would be associated with diabetes at all is, frankly, a mystery. And what would happen if this population ate 64g, 72g, 79g, or 88g of plant protein is completely unknowable.

EDIT: some afterthoughts

The abstract of this paper only reports the completely unadjusted HRs. That is, not even age or sex adjusted. "Attenuated" really means "Disappeared".

The upper protein quartile ate fewer calories, were more active, and had significantly higher BMI (2 points) and waist circumference (4cm).
In other words, either this study breaks the sacred rules of diet thermodynamics, or diet was not reported accurately.
The quartile who ate least vegetable protein had to have eaten more animal protein than the others, just to survive. So why is their risk of diabetes so low?

Monday, 19 September 2016

Court of last appeal - the early history of the high-fat diet for diabetes

It's a long story, and not a proud one. Seeing an email in my inbox from the Journal of Diabetes & Metabolism, which seemed like the title of a journal I'd investigated earlier, I impulsively sent off a draft of my history of Louis "Harry" Newburgh and the Michigan diet. I just emailed the unformatted pdf to them, and never engaged any portal or website.
The journal replied, in terrible English, that my article would be accepted with changes requested by one of "two reviewers" supplying a short paragraph each. This request was that I shorten and focus the abstract, and format references.
At this stage I realised this was an OMICs journal, of predatory reputation. I sent off the formatted article with no change but a small edit to the abstract to see what would happen.
The next thing I knew, I was sent an author proof. And an invoice for US$4,000. For some reason the illustration of Newburgh had been titled as being of Frederick Allen, a name which appears in the text but was never attached to any picture. I corrected this and received an authorproof with errors corrected.
Here is this proof, which I consider to be an accurate version of the paper, albeit I believe it was not properly peer-reviewed.

https://www.dropbox.com/s/l3pxp9lazyu5v04/2155-6156-7-696_Authorproof.pdf?dl=0

I never paid the fee, and received numerous reminders, not all addressed to me. I still receive emails from other OMICs journals requesting my input. I was never asked to sign a COI declaration of any sort, nor any other agreement (the work is Open Commons). I had read a thread on researchgate in which an author describes seeing their work published despite not paying the fee.
https://www.researchgate.net/post/Can_I_trust_OMICS_publishing_group

So I searched for my paper online and found it here.
http://www.omicsonline.org/open-access/court-of-last-appeal--the-early-history-of-the-highfat-diet-for-diabetes-2155-6156-1000696.php?aid=78354

Not only is the picture of Newburgh captioned Frederick Lewis Allen 1932, the references in the HTML version (but luckily not the pdf) are imported from some other paper, probably from a different journal.
I feel like this is a punishment to make an example of defaulting authors!

Anyway, the history of Newburgh is published, which is the main thing, but I feel ethically unclean, and whether anyone can ever now cite this article in a proper paper is uncertain. At least OMICs have not claimed exclusive rights in the matter, so republication is not out of the question. But then, if I'd thought this necessarily detailed history would be easy to publish in a proper journal, it would never have ended up in the hands of OMICs.

I'd like to thank Ash Simmonds
 and Zooko for introducing me to the work of Prof Newburgh.

Tuesday, 23 August 2016

Evidence of cardiovascular benefits of LCHF diets, despite no change or increase in LDL, from drug trials

A recent meta-analysis of low-carb diets and cardiovascular risk factors found, predictably, that low carb diets decrease triglycerides (TG), increase HDL, and - significantly, on average, but not consistently, and only by a small amount - elevate LDL.
The authors argued that this was not evidence of cardiovascular safety. "Low-carbohydrate diets increase LDL-cholesterol, and thereby indicate increased risk of CVD."
Other cardiologists disputed this (including  Axel F. Sigurðsson of the Doc's Opinion blog), citing evidence that TG and HDL are better markers of cardiovascular health than is LDL.[1]
The authors responded with a narrowly focussed argument [2] -

1) Mendelian randomisation shows the genes associated with LDL are associated with CVD, whereas genes associated with HDL are not, and those with TG only slightly.


I think this is faulty logic. Genes are the things we cannot change, so the association of TG and HDL with CVD risk, seen in the baseline characteristics of participants in drug trials (those with high HDL and low TG have low CVD risk in placebo arm and get no extra benefit in LDL-lowering arm  - links to those studies in this post), is probably due to diet and lifestyle factors, as Mendelian randomisation seems to rule out a strong genetic influence; but it does suggest that these factors are downstream markers of some other, more proximal "root cause" factor.


2) Drugs that elevate HDL have no effect on CVD risk, whereas statins, which lower LDL, do have some effect.


As with their point 1), these authors simply did not look deeply enough into the literature. There are many drugs that have lowered LDL with no or harmful effects on CVD outcomes, which seem to have been ignored in this argument. As for HDL, alcohol, for example, is a drug that elevates HDL and decreases CVD risk, see e.g.[3]

However, this link is observational. Better data comes from the trials of a new class of drugs, the SGLT2 inhibitors. Empagliflozin elevates both HDL and LDL. "in T2DM patients with high CVD risk empagliflozin compared to placebo reduced the primary major adverse cardiac event end point (CV death, nonfatal myocardial infarction, nonfatal stroke) by 14%. This beneficial effect was driven by a 38% reduction in CV mortality with no significant decrease in nonfatal myocardial infarction or stroke. Empagliflozin also caused a 35% reduction in hospitalization for heart failure without affecting hospitalization for unstable angina."[4]
Empagliflozin was also shown to be renoprotective, significantly reducing the incidence of worsening nephropathy, by 39%. This is interesting because nephropathy is a vascular pathology of diabetes.

SGLT2 inhibitors mimic the effect of low-carbohydrate ketogenic diets over a wide range of metabolic parameters (increased sodium excretion, decreased extracellular volume, increased HDL and LDL, reduced requirement for insulin, increased ketogenesis). The doctors are still arguing about the mechanism of benefit.

However, we note that 48% of the subjects were receiving insulin at baseline (median daily dose 54 units) and 43% were using sulfonylureas (which increase insulin secretion). During the EMPA-REG trial the rate of addition of new medications was (drug vs placebo) 5.8% vs. 11.5% for insulin and 3.8% vs. 7.0% for sulfonylureas, consistent with studies in which SGLT2 inhibitors decrease insulin requirements in type 1 diabetes.[5]

Are there other drug trials that support this model? The STOP-NIDDM study tested acarbose for the prevention of diabetes in a group of patients with impaired glucose tolerance. Acarbose inhibits the digestion of starch, and side effects of diarroeah  and flatulence limited compliance (how much simpler it would be to simply resist starch).

"211 (31%) of 682 patients in the acarbose group and 130 (19%) of 686 on placebo discontinued treatment early. 221 (32%) patients randomised to acarbose and 285 (42%) randomised to placebo developed diabetes (relative hazard 0.75 [95% CI 0.63-0.90]; p=0.0015). Furthermore, acarbose significantly increased reversion of impaired glucose tolerance to normal glucose tolerance."

Less carbohydrate entering the bloodstream from the gut = less progression of pre-diabetes to diabetes (and hence less CVD risk). It's not rocket science, unless you work for a pharmaceutical company in some capacity.

Acarbose doesn't alter LDL or HDL, but it does decrease triglycerides (thus improve the TG/HDL ratio) and VLDL. It also reduces the atherogenicity of LDL particles.
"The density gradient lipoprotein separation and disk polyacrylamide gel electrophoresis analyses showed that acarbose reduced the amount of small dense LDL, a more atherogenic and oxidatively susceptible form of LDL. We also found that the fatty acid composition of LDL changed after the treatment: polyunsaturated (omega-3) fatty acid, a beneficial substance for preventing cardiovascular disease, was significantly increased, whereas saturated fatty acids and triglyceride were decreased in the LDL of the acarbose-treated group."[7]
Decrease in sdLDL and serum SFAs is also an effect of low carb diets.

Does acarbose lower CVD incidence? You bet it does. In a meta-analysis of 7 RCTs of acrabose vs placebo in patients with T2DM, "The treatment significantly reduced the risk for ‘myocardial infarction’ (hazards ratio=0.36 [95% Cl 0.16–0.80], P=0.0120) and ‘any cardiovascular event’ (0.65 [95% Cl 0.48–0.88], P=0.0061)."[8]

In an experiment in fructose fed rats, there was no difference in blood glucose, but fructose increased, and acarbose subsequently reduced, insulin levels.[9]
In a double-blind, placebo-controlled, randomised cross-over study in subjects (n=10) with type 1 diabetes, "Acarbose produced a statistically significant reduction in mean insulin requirement over a 3-hr period following the meal compared with placebo (5171.7+/-2282.6 mU vs 8074.5+/-3045.4 mU; p=0.003). The level of blood glucose control over the same period was similar in the two groups.".


We measure fasting glucose, HbA1c, and OGTT glucose response to diagnose type 2 diabetes because these are easy and cheap to measure, but if we could measure the insulin response as easily and cheaply we would have a better guide to risk of complications and CVD and to the type and stage of diabetes.

This is because most of the pathologies of type 2 diabetes - cardiovascular disease and vascular disease in particular, but also, probably, the progression of beta-cell failure - are driven by elevated insulin levels.[11]
On the other hand, drugs that reduce both glucose and insulin (secretion or requirement) by restricting uptake or increasing excretion of glucose - i.e. acarbose or SGLT2 inhibitors (EMPA-REG trial) - significantly reduce the risk of cardiovascular disease and vascular pathologies.
What of statins? These have some lesser effect on the incidence of cardiovascular and vascular disease, despite the potential for increased blood glucose.
Statins inhibit the synthesis of cholesterol in cells, and the synthesis of excessive cholesterol, which disrupts mitochondrial function, is driven by excessive insulin concentrations.
"β-Hydroxy-β-methylglutaryl coenzyme A reductase activity in rat liver increased 2 to 7-fold after subcutaneous administration of insulin into normal or diabetic animals. Reductase activity began increasing after one hour, rose to a maximum in two to three hours, and then declined to the control level after six hours. This response was elicited during the time of day when the normal diurnal variation in reductase activity approached a minimum. It was also elicited when animals did not have access to food. This stimulation of reductase activity was completely blocked when glucagon was administered in conjunction with insulin. The increase in reductase activity after insulin administration was accompanied by a proportionate increase in activity for the conversion of acetate to cholesterol."[12]
What therapy lowers the secretion of or requirement for insulin, but does not increase and will usually lower blood glucose?
A low carbohydrate, high fat diet.
Q.E.D.

[1] Thomas R. Wood, Robert Hansen, Axel F. Sigurðsson and Guðmundur F. Jóhannsson (2016). The cardiovascular risk reduction benefits of a low-carbohydrate diet outweigh the potential increase in LDL-cholesterol. British Journal of Nutrition, 115, pp 1126-1128. doi:10.1017/S0007114515005450.


[2] Nadia Mansoor, Kathrine J. Vinknes, Marit B. Veierød and Kjetil Retterstøl (2016). Low-carbohydrate diets increase LDL-cholesterol, and thereby indicate increased risk of CVD. British Journal of Nutrition, 115, pp 2264-2266. doi:10.1017/S0007114516001343.


[3] Roles of Drinking Pattern and Type of Alcohol Consumed in Coronary Heart Disease in Men

Kenneth J. Mukamal, M.D., M.P.H., Katherine M. Conigrave, M.B., B.S., Ph.D., Murray A. Mittleman, M.D., Dr.P.H., Carlos A. Camargo, Jr., M.D., Dr.P.H., Meir J. Stampfer, M.D., Dr.P.H., Walter C. Willett, M.D., Dr.P.H., and Eric B. Rimm, Sc.D.
N Engl J Med 2003; 348:109-118January 9, 2003DOI: 10.1056/NEJMoa022095


[4] SGLT2 Inhibitors and Cardiovascular Risk: Lessons Learned From the EMPA-REG OUTCOME Study.

Muhammad Abdul-Ghani, Stefano Del Prato, Robert Chilton and Ralph A. DeFronzo.
Diabetes Care 2016 May; 39(5): 717-725.

[5] https://www.wikijournalclub.org/wiki/EMPA-REG_OUTCOME


[6] Lancet. 2002 Jun 15;359(9323):2072-7.

Acarbose for prevention of type 2 diabetes mellitus: the STOP-NIDDM randomised trial.
Chiasson JL1, Josse RG, Gomis R, Hanefeld M, Karasik A, Laakso M; STOP-NIDDM Trail Research Group.

[7]  Acarbose ameliorates atherogenecity of low-density lipoprotein in patients with impaired glucose tolerance.

Inoue I, Shinoda Y, Nakano T, Sassa M, Goto S, Awata T, Komoda T, Katayama S.
Metabolism. 2006 Jul;55(7):946-52.

[8] Drugs Exp Clin Res. 2005;31(4):155-9.

Acarbose, an alpha-glucosidase inhibitor, improves insulin resistance in fructose-fed rats.
Nakamura K, Yamagishi S, Matsui T, Inoue H.

[9] Diabetes Nutr Metab. 2000 Feb;13(1):7-12.

Influence of acarbose on post-prandial insulin requirements in patients with Type 1 diabetes.
Juntti-Berggren L, Pigon J, Hellström P, Holst JJ, Efendic S.

[10] Acarbose reduces the risk for myocardial infarction in type 2 diabetic patients: meta-analysis of seven long-term studies

M. Hanefeld, M. Cagatay, T. Petrowitsch, D. Neuser, D. Petzinna, M. Rupp.
European Heart Journal. Volume 25, Issue 1. Pp. 10 - 16

[11] Exposure to excess insulin (glargine) induces type 2 diabetes mellitus in mice fed on a chow diet.

Xuefeng Yang, Shuang Mei, Haihua Gu, Huailan Guo, Longying Zha, Junwei Cai, Xuefeng Li, Zhenqi Liu and Wenhong Cao.
Journal of Endocrinology (2014) 221, 469–480

[12] Stimulation by insulin of rat liver β-hydroxy-β-methylglutaryl coenzyme A reductase and cholesterol-synthesizing activities.

M.R. Lakshmanan, Carl M. Nepokroeff, Gene C. Ness, Richard E. Dugan, John W. Porter. Biochemical and Biophysical Research Communications. Volume 50, Issue 3, 5 February 1973, Pages 704-710



Thursday, 18 August 2016

Glucokinase mutations, diabetic complications, and cardiovascular disease

This is a very interesting study that was posted by Richard Lehman on his BMJ blog a few years ago. It contains much food for thought.
People with this mis-sense mutation in the gene that encodes glucokinase (GCK), part of the pancreatic beta cell glucose sensor, basically have their sugar thermostat, their glucostat, set too high. They don't produce insulin in response to blood glucose in the pre-diabetic range. In this study, average HbA1c is 6.9%. But the incidence of insulin resistance, obesity, dyslipdaemia, and hypertension in this population is the same as in the normal controls, who have average HbA1c of 5.8% here.
So basically we are looking at mild hyperglycaemia without hyperinsulinaemia and its sequelae.
I think this is a good model for people with type 2 diabetes who have reversed the disease to a pre-diabetic level on a low carb diet, lost weight, and corrected hypertension. No carbs = low insulin, so how much of a problem is mild hyperglycaemia if it persists?
Also, do some people diagnosed with T2DM or prediabetes who go low carb have the GCK mutation without knowing it, meaning they will not get normal blood sugars?


JAMA. 2014 Jan 15;311(3):279-86. doi: 10.1001/jama.2013.283980.
Prevalence of vascular complications among patients with glucokinase mutations and prolonged, mild hyperglycemia.
Steele AM, Shields BM, Wensley KJ, Colclough K, Ellard S, Hattersley AT.

IMPORTANCE:
Glycemic targets in diabetes have been developed to minimize complication risk. Patients with heterozygous, inactivating glucokinase (GCK) mutations have mild fasting hyperglycemia from birth, resulting in an elevated glycated hemoglobin (HbA1c) level that mimics recommended levels for type 1 and type 2 diabetes.

OBJECTIVE:
To assess the association between chronic, mild hyperglycemia and complication prevalence and severity in patients with GCK mutations.

DESIGN, SETTING, AND PARTICIPANTS:
Cross-sectional study in the United Kingdom between August 2008 and December 2010. Assessment of microvascular and macrovascular complications in participants 35 years or older was conducted in 99 GCK mutation carriers (median age, 48.6 years), 91 nondiabetic, familial, nonmutation carriers (control) (median age, 52.2 years), and 83 individuals with young-onset type 2 diabetes (YT2D), diagnosed at age 45 years or younger (median age, 54.7 years).

MAIN OUTCOMES AND MEASURES:
Prevalence and severity of nephropathy, retinopathy, peripheral neuropathy, peripheral vascular disease, and cardiovascular disease.

RESULTS:
Median HbA1c was 6.9% in patients with the GCK mutation, 5.8% in controls, and 7.8% in patients with YT2D. Patients with GCK had a low prevalence of clinically significant microvascular complications (1% [95% CI, 0%-5%]) that was not significantly different from controls (2% [95% CI, 0.3%-8%], P=.52) and lower than in patients with YT2D (36% [95% CI, 25%-47%], P<.001). Thirty percent of patients with GCK had retinopathy (95% CI, 21%-41%) compared with 14% of controls (95% CI, 7%-23%, P=.007) and 63% of patients with YT2D (95% CI, 51%-73%, P<.001). Neither patients with GCK nor controls required laser therapy for retinopathy compared with 28% (95% CI, 18%-39%) of patients with YT2D (P<.001). Neither patients with GCK patients nor controls had proteinuria and microalbuminuria was rare (GCK, 1% [95% CI, 0.2%-6%]; controls, 2% [95% CI, 0.2%-8%]), whereas 10% (95% CI, 4%-19%) of YT2D patients had proteinuria (P<.001 vs GCK) and 21% (95% CI, 13%-32%) had microalbuminuria (P<.001). Neuropathy was rare in patients with GCK (2% [95% CI, 0.3%-8%]) and controls (95% CI, 0% [0%-4%]) but present in 29% (95% CI, 20%-50%) of YT2D patients (P<.001). Patients with GCK had a low prevalence of clinically significant macrovascular complications (4% [95% CI, 1%-10%]) that was not significantly different from controls (11% [95% CI, 5%-19%]; P=.09), and lower in prevalence than patients with YT2D (30% [95% CI, 21%-41%], P<.001).

CONCLUSIONS AND RELEVANCE:
Despite a median duration of 48.6 years of hyperglycemia, patients with a GCK mutation had low prevalence of microvascular and macrovascular complications. These findings may provide insights into the risks associated with isolated, mild hyperglycemia.

BAM! as they say. Without high insulin, glucose at this level doesn't damage the blood vessels any more than "normal" BG does in a population with "normal" insulin responses to carbohydrate.
It does damage the eyes (but not the nerves), probably because the polyol pathway is insulin-independent, but the rate of retinopathy is already high, at 14%, in the "normal" population. Neuropathy has both a glycotoxic and a microvascular pathology, so is more dependent on hyperinsulinaemia than retinopathy.

A feature of GCK mutation is that blood glucose is highest in the most overweight individuals; this seems to show increased FFA flux boosting gluconeogenesis, or some extra effect of NAFLD increasing insulin resistance.

This is from a paper comparing a sample with the GCK mutation with their normal, non-diabetic family members.[1]
"In subjects with the mutation, beta cell function was impaired, being geometric mean 63 % (normal-100 %) compared with 126 % in the subjects without the mutation (p less than 0.001) measured by HOMA and in a subset assessed by CIGMA 59 % and 127 % (p less than 0.01 ), respectively. There was no difference in fasting insulin concentrations, insulin sensitivity, lipid concentrations or blood pressure between the groups. The haemoglobin A was raised (mean 6.5 % compared with 5.5 % in the subjects without the mutation), but microvascular and macrovascular complications were uncommon."

The authors of the first paper think this is a model for glycaemic control that attains recommended HbA1c targets for T1D and T2D. I don't think this can be the case if extra insulin or sulfonylureas are being used to meet these targets because the diet is still high in carbs. It is a model for the early stages of dietary control of diabetes, with reduced insulin levels or requirements and HbA1c trending down, and weight and blood pressure normalising.

The mechanisms that cause vascular disease in diabetes, including smooth muscle cell dysfunction and impaired eNOS signalling, are the same ones that are supposed to initiate atherosclerosis, whatever the role of lipoproteins in its development. Say it again - it's the insulin stupid.

[1] Diabet Med. 1995 Mar;12(3):209-17.
Clinical characteristics of subjects with a missense mutation in glucokinase.
Page RC1, Hattersley AT, Levy JC, Barrow B, Patel P, Lo D, Wainscoat JS, Permutt MA, Bell GI, Turner RC.