Rebuttal of 14 claims about metabolism, genetics, paleoanthropology & stable isotope analyses in Hardy et al.’s 2015 paper “The Importance of Dietary Carbohydrate in Human Evolution”


The evolutionary selective pressures which drove human encephalization are passionately debated, largely because the brain’s function accounts for much of our ill-defined and ever-changing ‘human uniqueness’. Apportioning individual contributions from the multitude of factors ranging from climate change to food and socialization dynamics requires a truly multidisplinary approach encompassing evolutionary biology, genetics, medicine, archeology, chemistry, physics, climatology and many more scientific fields. It is with this wider perspective that evidence for how food contributed to human encephalization is assessed. Clues from human metabolism, anatomy and food web positioning in addition to stable isotope analyses do not generally support the hypothesis that cooked starches were a major driver of human encephalization. Land and marine life as wells as birds and insects seem to have contributed substantially more to it. 11 points on metabolism, 1 on genetics, 1 on paleoanthropology and 1 on stable isotope analyses are individually rebutted.

In their paper, The importance of dietary carbohydrate in human evolution, Hardy, Brand-Miller, Brown, Thomas and Copeland argue for the importance of dietary carbohydrate (mainly in the form of cooked starches) in human evolution and particularly encephalization. One way they do this is by drawing an association between the supposed advent of controlled fire use (cooking) by hominims with increases in AMY1 copy numbers. Neither the timeline for the emergence of cooking or the AMY1 copy number increase are supported by their citations or by more recent evidence discrediting this purported association. Much of their argument is thus based on genetics, paleoanthropology and both general and specific claims of human metabolism as well as stable isotope anlayses, all of which can be individually rebutted.

Stable istope analysis

Hardy et al. severely misquote a 2009 paper by Richards and Trinkauss – in which stable isotope analyses of Oase 1 humans and Neanderthals were performed – because it is used to support the notion that human diets likely included substantial amounts of starch given the variations in  δ15N and δ13C ratios.

[1]“a wider range of isotopic values have been observed in contemporary Middle Pleistocene H. sapiens (Richards and Trinkaus 2009), indicating that considerable differences in the levels of starch consumption existed between these two species”

The 2009 paper by Richards & Trinkauss actually found that “early modern humans (~40,000 to ~27,000 cal BP) exhibited a wider range of isotopic values, and a number of individuals had evidence for the consumption of aquatic (marine and freshwater) resources […] The other early modern humans all have δ13C values < –18.5‰ (see Fig. 1 and Table S2), which indicate that their protein came from terrestrial C3 (or freshwater) foods, yet many of them have high δ15N values, at or above the highest Neanderthal values”. It is unequivocal that the δ15N and δ13C variations refer to the dietary apportioning of land versus marine protein, not to the ratio of dietary carbohydrate versus fat. In fact, the authors clearly state that “The Oase I δ15N value is also above those of the hyena (11.1‰), and the highest wolf value (11.5‰) from the same site and dating to about the same time”. This also unequivocally contradicts the notion that starches were a significant dietary contributor for these hominins given that this evidence suggests that they were more carnivorous than Neanderthals, hyenas and wolves as evidenced by their Figure 2 represented here.

Isotope Analysis of Oase 1 humans & Neanderthals vs other animals


Hardy et al. cite 2 papers to substantiate the claim that the copy number increase of AMY1 occured less than 1 million years ago despite neither paper supporting it.

[2]“it [multiplication of the AMY1 genes] is thought to be less than 1 million years ago (Samuelson et al. 1996; Lazaridis et al. 2014)”

  • The first paper from 1996 by Samuelson et al. gives no specific date concerning the emergence of AMY1 copy number increase since it was not the objective; their objective was to “infer the structures of common ancestors and trace the evolution of the modem human amylase promoters”. The second is a 2014 paper by Lazaridis et al. which also does not mention a date for AMY1 copy number increase since it is focused on issues of lineage by studying 7-8kya Neolithic skeletons from La Braña (Spain), Motala (Sweden) & Loschbour (Germany). Only once does Lazaradis et al. briefly reference a hypothesized association between AMY1 copy number increase and high starch diets by citing Perry et al. 2007. Interestingly, the latter reference contradicts Hardy et al.’s purported timeline for AMY1 gene copies increase as, in their words, it was mosty likely of “a relatively recent origin that may be within the timeframe of modern human origins (i.e., within the last ∼200,000 years”.
  • Irrespective of when the when copy numbers of AMY1 increased, the significance of this is still unclear. It has been hypothesized that more copies of the AMY genes would improve glucose homeostasis on higher starch diets and protect against obesity (1, 2, 3). Nevertheless, Nature Genetics in June 2015 published a study by Usher et al. where the authors did “not observe even a nominal association between obesity and the copy number of any amylase gene (P = 0.70 for AMY1)” nor did they in diabetic cohorts where “AMY1 copy number did not associate with BMI in any group (P = 0.31 for GoT2D controls, P = 0.24 for GoT2D cases and P = 0.53 for InCHIANTI samples)”. Usher et al. explain why previous studies may have found associations that were not there given the use of ”lower-precision molecular methods, such as RT-PCR and array comparative genomic hybridization (CGH), or lower-precision analyses of whole-genome sequencing data to measure copy number”. It would be prudent to first understand the significance of the AMY genes in humans before using them as a mechanistic foundation in arguments relating to the evolution of humans and their encephalization.
  • In June 2015 Perry et al. avoided using “lower-precision molecular methods […] to measure copy number”, unlike Carpenter et al.’s group in March of that same year. This improved copy number assessment enabled Perry et al. to confidently conclude that “AMY1 gene duplications are likely human-specific and that they occurred following the divergence of our lineage from the Neandertal/Denisovan lineage ~550-590 kya”, contradicting Hardy et al.’s less than 1 million years ago timeline.


Hardy et al. correctly cite the only paper to date supporting their view of hominim cooking emerging less than 800kya. However, the natural event confounding the interpretation provided by this paper and more recent evidence to the contrary are not mentioned as a counterbalance. Furthermore, Hardy et al. do not provide the reader with a representative view of the balance of evidence which currently is heavily biased towards the hypothesis of fire emerging 400-300kya.

[3]”Gesher Benot Ya’aqov, in Israel, which dates to around 780,000 bp, has charcoal, plant remains, and burned microartifacts in concentrations that the excavators believe suggests evidence for hearths (Alperson-Afil 2008)”

  • A 2008 paper by Alperson-Afil is cited as evidence of when hominin cooking emerged 780kya as evidenced by the Gesher Benot Ya’aqov (GBY) site in Israel. It does in fact conclude that “as the scenario of a natural fire is unlikely, we conclude that the concentrations of burned flint microartifacts in the different occupational surfaces of GBY represent phantom hearths, i.e. remnants of hominins’ use of fire”.
  • This conclusion is probelmatic for 2 major reasons. The first is addressed by Shimelmitz et al. in 2014, where it is explained that “consistent evidence for fire is found not just in the Tabun sequence but at every Acheulo-Yabrudian cave site where good information is available. The near-absence of burnt flints in the lower 8m of the sequence at Tabun (composed of 19 layers) also indicates that the scarcity of fire evidence before 350 kya is not just a matter of spotty preservation, or cave sites versus open air-sites (e.g., Gowlett and Wrangham, 2013). Rather, the negative evidence from the early layers is genuine, and there is a significant and permanent increase in the frequency of evidence for burning between 357 and 324 kya […] our best estimate for the onset of regular fire use at Tabun is between 357 and 324 kya”.
  • The second problem is that lava probably invaded the GBY site, as correlated with the Matuyama-Brunhes chron boundary event taking place 781kya. This occurence further substantially confounds Alperson-Afil’s interpretation. Evidence for this event at GBY stems from “artefacts in fluvial conglomerates, organic-rich calcareous muds and coquinas that accumulated along the shorelines of the palaeo-Hula lake (Goren-Ibar et al. 2000)”.


A lot of Hardy et al.’s argument for the important role of dietary carbohydrate in human evolution and the spectacular encephalization is based upon claims about metabolism. These 11 points are at best taken out of context or at worse entirely false.

[4]“There is debate on whether dietary carbohydrates are actually essential for human nutrition”

  • Micronutrients and macronutrients have been defined as essential when their absence causes a deficiency syndrome. No such ‘carbohydrate deficiency’ has been found to date and, to the best of my knowledge, nor has any suggestive evidence surfaced in the last century.
  • The 1999 report by the IDECG Working Group, led by DM Bier, recognizes that “the theoretical minimal level of carbohydrate (CHO) intake is zero”, before following on about its importance in human biological function.
  • Glucose is essential for cells to function but it does not have to originate from dietary sources due to an evolved gluconeogenetic capacity capable of providing 150 grams per day for CNS functions. This lack of reliance on dietary glycose has been validated since at least 1975 by Cahill and Owen’s 2 month starvation experiment. Depicted in their Figure 1, they found that the human brain always requires at least 35% of its energy from glucose (not necessarily of dietary origin).brain usage of glucose & ketones
  • In 1972 Drenick et al. stress-tested human reliance on endogenous glucose showing that “after fasting 2 months, administration of weight-adjusted doses of insulin […] no insulin reactions nor significant rises in catecholamine excretion occurred despite equal extent and rate of glucose fall. Glucose concentrations as low as 0.5 mmoles/liter (9 mg/100 ml) failed to precipitate hypoglycemic reactions.”
  • When dietary carbohydrates are avoided entirely and protein is moderated the human brain will use ketone bodies as its primary energy substrate. In such a metabolic state, Vanitalie and Nufert say that “although these data need confirmation, they suggest an increase in the metabolic efficiency in human brains using ketoacids as their principal energy source in place of glucose”.

[5]“a more realistic recommendation is that at least one-third of dietary energy should be supplied from carbohydrates (Bier et al. 1999)”

  • For this Hardy et al. quote, the 1999 report by the IDECG Working Group, led by DM Bier, does not identify a carbohydrate deficiency syndrome but advises at least 150g per day for “practical reasons”.
  • Dr.Eric Westman summarizes his findings about carbohydrates being non-essential saying “although there is certainly no evidence from which to conclude that extreme restriction of dietary carbohydrate is harmless, I was surprised to find that there is similarly little evidence to conclude that extreme restriction of carbohydrate is harmful.”

[6]“Glucose is the only energy source for sustaining running speeds above 70% of maximal oxygen consumption (Romijn et al. 1993)”

  • Brook et al., who developed the Cross-Over Point hypothesis, did not state that glucose was the only energy source above 70% VO2 max, only that it and glycogen were the main sources and free fatty acids the minor source. Hardy et al. essentially describe a binary change in energy substrate use when in fact the change is quantitative.
  • It is an unproven assumption that carbohydrates of dietary origin are necessary to use glycogen and glucose as the predominant substrate for instances of near maximal VO2. Even if it were true that glucose use always predominates across all individuals at >70% VO2 max, this does not automatically imply that dietary glucose is the necessary fuelling strategy for sustaining such intense efforts. These are separate claims.
  • In 2015 Hetlelid et al. showed that well-trained runners performing high intensity training at 85% VO2 max, nearly one third of the total energy expenditure comes from fat oxidation. Furthermore, the lower intensity, steady state equations of indirect calorimetry used here and elsewhere overestimate carbohydrate oxidation and underestimate fat oxidation.
  • In 2014 Noakes, Volek and Phinney characterize this quantitative change in energy substrates according to effort intensity, saying “some highly adapted runners consuming less than 10% of energy from carbohydrate are able to oxidise fat at greater than 1.5 g/min during progressive intensity exercise and consistently sustain rates of fat oxidation exceeding 1.2 g/min during exercise at ∼65% VO2max, thereby providing 56 kJ/min during prolonged exercise. The remaining energy would comfortably be covered by the oxidation of blood lactate, ketone bodies and glucose derived from gluconeogenesis”
  • Preliminary results from Volek et al.’s soon to be published FASTER study (Fat Adaptated Substrate Oxidation in Trained Elite Runners) have been reported at Maximal fat oxidation rates higher above 1.54g per minute with 1 subject reaching 1.8g were shown. Classic sports physiology literature performed in non-ketogenic dieters with sub-optimal fatty acid oxidation capacities previously found maximal fat oxidation rates of only 1g min. These findings will, quite literally, require re-writing text books.
  • Elite ultra-runner and FASTER study participant Zach Bitter shared his personal data. At 75% VO2 max he used 98% fat and 2% carbohydrate. At 84% VO2 max he used 76% fat and 24% carbohydrate. Finally, at 96% VO2 max he was still using 23% fat and 77% carbohydrate.

[7]“In an evolutionary context, large stores of glycogen must be generated in order to provide sources of glucose for periods of sustained fasting or hardship. To build these reserves, the diet must consistently provide energy surplus to basal metabolic requirements”

  • The human gluconeogenetic capacity mentioned above disqualifies this imperative statement. Red blood cells, immune cells and the brain, as well as the more extended CNS, all function properly with glucose solely of endogenous origin.
  • The average lean male has tens of thousands of stored calories available to him in adipose tissue in contrast to his glycogen storage capacity of approximately 15 g/kg. Furthermore, his adipose tissue contains all the glycerol precursors required for endogenous production of glucose when combined with amino acids.

[8]“The diets of traditional Arctic populations are sometimes given as examples of successful high-protein diets (Lindeberg 2009)”

  • It is a common mistake to assume that the Inuit ate high-protein diets or it may simply be a misnomer arising from its association with the consumption of animal protein. In humans, high-protein diets lead to protein poisoning, otherwise known as ‘rabbit starvation’ (4, 5). The protein ceiling is 35-40% of calories or 200-300g of protein a day. The Inuit ate high-fat diets and their protein intake was moderate. Unlike the livers and kidneys of lions or wolves, human livers have substantially lower functional hepatic nitrogen clearances (FHNC) and urea nitrogen synthesis rates (UNSR) (6, 7).

[9]“15–20% from carbohydrate principally in the form of glycogen from the meat they consume (Ho et al. 1972)”

[10] “Meat frozen soon after slaughter will retain much of its muscle glycogen (Varmin and Sutherland 1995)”

  • Points 9 and 10 can be addressed together. The citation for point 7 should be “Varnam and Sutherland 1995”.
  • Greenberg et al. recognize the Inuit diet as one of “80–85% fat, 15–20% protein, and, apart from a little muscle glycogen, almost no carbohydrate” by citing Phinney’s 2004 paper.
  • Ho et al.’s 1972 study conduced in Point hope, Alaska, does not provide evidence of how this estimate is arrived except that it is based off of a 3,000-4,500kcal diet. Presumably, the reported glycogen levels are those of live animals.
  • Raw meat from a dead seal contains 0 grams of carbohydrate. In fact, in 1995 Varnam and Sutherland themselves explain that “if meat is frozen before ATP and glycogen levels are depleted post-mortem glycolysis is suspended. On thawing, however, the meat undergoes severe contraction with associated toughening and loss of large quantities of drip (thaw rigor)”. Simply stated “in response glycogen, the main energy store in the muscle, is converted to lactic acid by anaerobic, post-mortem glycolysis”. Momentarily and drastically slowing post-mortem glycolysis by flash-freezing meat will not stop glycolysis from depleting glycogen when the meat is finally thawed for consumption. The resulting lacate is a glucose element but is not counted into the percentage of dietary carbohydrate in a diet.
  • Flash-frozen meat does not contain glycogen levels anywhere near those necessary to support Hardey et al.’s statement. In 1976 Hamm explains how “the regulatory enzymes which control ATP metabolism and glycolysis in the living tissue are still active in the muscle postmortem, but these enzymic mechanisms are not able to maintain the ante-mortem levels of ATP and glycogen because the oxygen supply of the cell is stopped as soon as the blood circulation is interrupted by death of the animal. The lack of the aerobic ATP synthesis from ADP in the muscle mitochondria results in an anaerobic depletion of glycogen and consequently in a disappearance of ATP within a few hours p.m.”
  • In 1936 Sharp related glycogen’s conversion to lactic acid over time as a function of temperature (°C) saying that “in fish-muscle in the frozen state the maximum rate of glycogenolysis occurs in the interval -3.2° to -3.7 [and] freezing at -2° and lower temperatures for a period of 4 hours causes injury to the muscle, resulting in very rapid lactic acid formation on thawing. Freezing at 1.6° has no such effect, and on thawing the normal rate of lactic acid formation is resumed.” Figure 2 and 3 from his paper graphically illustrate this relationship.Lactic acid & glycogen in frozen muscle

[11]“the derived A-allele [CPT1A gene] has been shown to associate associate with hypoketotic hypoglycemia and high infant mortality […] suggests that it is an important adaptation to high meat, low- carbohydrate diets”

  • The association between hypoketotic hypoglycemia and high infant mortality with the CPT1A allele is from Clemente et al.’s 2014 paper which references a 2009 paper by Greenberg et al. entitled “The paradox of the carnitine palmitoyltransferase type Ia P479L variant in Canadian Aboriginal populations” in which 3 familes for a total of 7 patients were studied. The conclusion was that “severe clinical effects have been observed in only some, but not all, infants and young children [and] the occurrence of hypoglycemia, the main initial clinical effect of CPT-I deficiency, is dependent upon many environmental factors, including infection, feeding history and long-chain fat content of the diet, glycogen stores in the liver, and perhaps even climate“.
  • Clemente et al. found “strong evidence in favor of selection from a de novo mutation P(SDN) = 0.98, as opposed to selection on standing variation”. In simple terms, this means it was strongly positively selected for in high latitude populations eating very high-fat diets. Clemente et al. characterize these CPT1A mutations as “strong deviations from mutation-drift equilibrium”. Interestingly, Greenberg et al. describe the CPT1A mutations as ‘a paradox’ whilst Clemente et al. as ‘deleterious’. Patient 2 in the study of the former, for example, was most likely on a Westernized, relatively high carbohydrate diet described as a “regular diet and skim milk”. Such a diet underpins many ‘diseases of civilization’ and most likely contributed to the hypoketotic hypoglycemia and high infant mortality that is associated with these particular alleles.
  • Neither Hardy et al. nor Clemente et al. considered the evidence of compensatory mechanisms paralleling the drop in ketogenesis provided in Greenberg et al.’s paper. Veterinarian Petro Dobromylskyj from the Royal Veterinary College explains it best, saying “there is also evidence that the mutation decreases the inhibitory effect of malonyl-CoA on fatty-acid β-oxidation in mitochondria, thereby partially compensating for the drop in ketogenesis associated with reduced CPT1A activity”.
  • Finally, Greenberg et al. mention their “results of detailed β-oxidation studies in family C showed that oxidation was low at 37°C and were further decreased when measurements were conducted at a higher temperature”. These mutations may well be an adaptation to the freezing temperatures of the environments in which they arose.

[12] “high levels ketones in the blood, which can compromise reproductive function (Kim and Felig 1972)”

[13] “larger infants are born to women with higher blood glucose (Butte 2000), while a link has been made between maternal gestational ketonemia and a reduced off-spring IQ (Rizzo et al. 1991)”

  • Points 12 and 13 can be addressed together. Hardey al. quote a 1972 study by Kim and Felig that studied metabolic responses in pregnant women fasting for 84-90hrs. Specifically, their interests lay in the interplay between amino acids, glucose and insulin. They describe their interest saying “the influence of pregnancy on the changes in plasma glycine, threonine, and serine during fasting are of interest in as much as these amino acids are unique in demonstrating a delayed increase during prolonged starvation of obese nonpregnant subjects”. In fact they recognize the importance and adequacy of gluconeogenesis saying “maternal hepatic gluconeogenic mechanisms are capable of responding to increased substrate [amino acids] delivery during starvation in pregnancy”. Nowhere in their paper are ketones suggested to compromise reproductive function. This study looked at the effects of multi-day fasts – not ketogenic diets – in the context of gestation.
  • In another paper from 1972, Kim and Felig also note that in pregnant mothers, “starvation resulted in significant hypoglycemia and hyperketonemia and in an elevation of free fatty acid and glycerol concentrations. In 13 of 18 fasted subjects, blood glucose levels fell below 50 mg/100 ml. No specific symptoms or signs of hypoglycemia were noted.” Furthermore, the evidence was suggestive “that ketones may become an important fetal fuel during maternal caloric deprivation”.
  • In a 2015 retrospective cohort study of 906 pregnant mothers, Deschamps et al. found that “infants from mothers with a FBG [fasting blood glucose] >95 mg/dL were fatter both in relative (18.7 vs. 14.9%; p<0.05) and absolute (803 vs. 543g; p<0.01) terms. Further, over 50% of infants from mothers with FBG >95 mg/dL had a %fat greater than the 90th %fat percentile”. Increased adiposity may partially account account for the higher birthweight infants of mothers with higher blood glucose levels. This casts a less positive light on Butte’s findings from 2000 than Hardy et al. have.
  • In a 1980 study of calorie-restricted diabetic pregnant mothers, Coetzee et al. found that “neonates born to diabetic mothers with ketonuria had no fetal distress or asphyxia neonatorum [and] positive Ketostix tests in urine samples do not indicate toxic levels in the blood”.
  • It appears that Hardy et al. are confusing the pathological state of diabetic ketoacidosis – a simultaneous and excessive rise in the blood of both glucose and ketones – with simple nutritional ketosis. The latter arises naturally as a result of restricting carbohydrates and moderating protein (or simply fasting).  Hardy et al. quote papers by Nancy Butte and by Rizzo et al. who both looked at gestational diabetes and ketoacidosis, not nutritional ketosis. Rizzo et al. concluded that “the associations between gestational ketonemia in the mother and a lower IQ in the child warrant continued efforts to avoid ketoacidosis and accelerated starvation in all pregnant women”. Butte recommend avoiding ketonemia from her study of gestational diabetes mellitus, not ketogenic dieters. In fact, she recognizes how “the ADA states that the percentage of carbohydrate in the diet is dependent on individual eating habits and that the effect on blood glucose and percentage fat depends on assessment and treatment goals”. She also goes on to emphasize how “the lower percentage of carbohydrate blunts the postprandial hyperglycemia”.

[14] “can also be obtained directly from other dietary sources, or it can be synthesized from other fatty acids such as α-linolenic acid (ALA), which is present in oils from ocean fish, eggs, seed oils, and various leafy plant foods”

  • It is suprising that Hardy et al. do not mention how inefficiently humans convert α-linoleic acid (ALA) into the bioavailable long chain forms, eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA). In 1998 Gerster H. used radioisotopes to show how adults “with a background diet high in saturated fat conversion to long-chain metabolites is approximately 6% for EPA and 3.8% for DHA. With a diet rich in n-6 PUFA, conversion is reduced by 40 to 50%”. Western diets are excessively rich in omega-6 polyunsaturated fatty acids. Consequently, specifically targeting plant foods as a meaningful source of EPA and DHA is not recommended, especially in light of the 2006 estimate by Simopoulos whereby people eating a Westernized diet have a 15:1 to 16.7:1 ratio of omega-6 to omega-3 (EPA and DHA) fatty acids.

Gut Microbial Metabolism Drives Transformation of Msh2-Deficient Colon Epithelial Cells

The great question posed in Belcheva et al.’s study “What is the nature of the interaction between our microbiota, colorectal cancer and inflammation?” has produced results that can help RECONCILE CONFLICTING EVIDENCE regarding the fiber-colorectal cancer question [CRC = colorectal cancer].

Generally speaking, epidemiological studies on the matter have only provided hints for generating hypotheses that are oftentimes more confused than the questions they’re trying to answer. In Good Calories, Bad Calories, Taubes’ position on fiber is echoed in a New England Journal of Medicine randomized controlled trial that he refers to. It concludes that “adopting a diet that is low in fat and high in fiber, fruits, and vegetables does not influence the risk of recurrence of colorectal adenomas […& that…] two previous trials [Toronto Polyp Prevention Trial & Australian Poly Prevention Project] also found that dietary changes had no effect on the overall risk of recurrence of colorectal adenomas”. This is damning evidence – damning evidence against adopting a modern day, grain-derived, sugar heavy & fat devoid ‘fibrous’ diet.

Ass cancer or Chipotle - that is the question.

Ass cancer or Chipotle – that is the question.

Buyer beware. Yes, yes, yes – the authors do unfortunately disenchant themselves by stating “Nor should we overlook the abundant data indicating that a diet low in saturated fats and rich in fruits, vegetables, and whole-grains has a favorable influence on the risk of chronic disease and mortality”. That statement is incorrect and frankly stupid in 2014. Let’s not waste time over it.

Now that we know consuming lots of fiber according to the ‘modern eating model’ is pretty useless – not only for preventing CRC – let’s do away with a whole load of variables and look at cellular mechanisms up-close to see what different kinds of murine (mouse) epithelial colon cells think of fibre. Let’s dive into Belcheva et al.’s study . Their message is essentially positive about butyrates’ effects on CRC, but cautions (at least in principle) against blind application.

Genes often affected in CRC

  • Adenomatous Polyposis Coli (APC) genes = tumor suppressing
  • DNA mismatch repair (MMR) genes (self-explanatory name)

The researchers approached their awesome question, keeping in mind the “role of inflammation in producing a niche for specific microbes to elicit their oncogenic effects” all the while recognizing that “the etiology of most CRCs does not have an inflammatory component”. Furthermore, “a comprehensive meta-analysis found a positive association of total carbohydrate intake with CRC”.

Bullshit aside - where's the CRC?

Bullshit aside – where’s the CRC?

To TEST their hypothesis, they make:

  • a mouse model [APCMin/+ (multiple intestinal neoplasia)] of human adenomatous polyposis
  • & cells with a “Mutation in or inactivation (via silencing) of MMR genes, such as MutS homolog 2 (MSH2)

They give an APCMin/+ mouse MSH-deficient cells and observe the growth of many more polyps.

Naturally, the question “Does the microbiota affect the #/growth of polyps?” arises. Well, lets see what happens when you take their microbiota away: “Polyp incidence is not reduced in germ-free APCMin/+ mice (Dove et al., 1997), indicating that gut microbes have little to no role in disease progression in this background.”

Ok – so what about antibiotics?

  • oral antibiotics dramatically reduced CRC specifically in APCMin/+MSH2-/- mice”

OK – since carbs “feed” bacteria and antibiotics “kill” ‘em, what’s up with carbs on the #/growth of polyps?

  • “a diet reduced in carbohydrates can phenocopy this effect and show that gut microbes stimulated CRC development through the production of carbohydrate-derived metabolites such as butyrate

INTERESTING. That which feeds our microscopic partners going back eons & eons is also implicated in feeding CRC. Hhhmm…if it’s not on already, tightly fasten your skeptic helmet.

The researchers elaborate further:

  • “The fact that antibiotic treatment led to a reduction in grade 1 polyps, which include aberrant crypt foci, argues that gut microbiota in APCMin/+MSH2-/- mice act at an early stage in the formation of CRC, perhaps even as a tumor initiator […with the caveat that…] not all members of the gut microbiota contribute equally to CRC development in this animal model”.

A hint as to possible mechanisms (or the elimination thereof):

  • “the mutation frequencies were similar between colon epithelial cells from untreated or antibiotic-treated MSH2-/- mice”

But how does the mice microbiota contribute to CRC formation?

  • “gut microbiota induce CRC through a mechanism that is independent of both inflammation and DNA damage.” So we know what mechanisms AREN’T responsible but still don’t know which one(s) IS/ARE.

Carbs as a function of microbial depletion – what happens in that paradigm?

They checked by setting up “Three-week-old APCMin/+MSH2-/- mice [who] were given a normal or low-carbohydrate diet (Table S1). Approximately 58% of the calories provided with the normal diet derived from carbohydrates, compared to 7%

2 things surfaced:

  • “Strikingly, the low-carbohydrate diet reduced polyp numbers in the small intestines and colons of APCMin/+MSH2-/- mice”
  • no additive effect on polyp number by combining the low-carbohydrate diet and the antibiotic treatment (Figures 3B & 3C) suggesting that both treatments function by the same mechanism

It is reasonable to think: maybe the decreased metabolite levels (i.e. poop from fermenting fiber/resistant starch) resulting from carb restriction is the deterministic factor in tipping the balance towards CRC? The authors think so:

  • “reducing either gut microbiota or dietary carbohydrates resulted in the reduction in both Ki-67 and β-catenin expression in APCMin/+MSH2-/- mice led us to hypothesize that bacterial metabolites might fuel the aberrant hyperproliferation of colon epithelial cells in these mice”.

So now we need a better mouse model to tease out the (potential) effect of metabolites (i.e. butyrate) on polyps (as a CRC proxy marker):

  • Previous mouse model = inadequate. It was MMR-deficient AND DDR-deficient (MMR also works via a ‘DNA Damage Response’ pathway)
  • New mouse model, succinctly named MSH2G674D/G674D = adequate ===because===> they have a functional DDR mechanism but CANNOT carry out other MMR functions (this is called controlling for variables).
    • ==> ‘what mechanisms do what’ can now be narrowed down via a process of elimination.

MSH2G674D/G674D mice revealed “the only SCFA that was statistically reduced by all antibiotic treatments and by the low-carbohydrate diet was butyrate”…Specifically, these treatments led to the reduction of three families within Firmicutes, namely Clostridiaceae, Lachnospiraceae, and Ruminococcaceae (Figure 6C), that are known to produce butyrate”.

From their controlled 2nd mouse model they remark on the plausible mechanism of butyrate’s **apparent** proliferative properties in murine epithelial colon cells

  • “butyrate modulates canonical Wnt signaling (Lazarova et al., 2004) and has been shown in some studies to promote CRC (Freeman, 1986; Lupton, 2004)”
  • Canonical Wnt signaling = regulates gene transcription, cell size and calcium levels inside the cell; all majorly important factors determining if cells live or die…so yes, of prime interest in cancer.

This is the CRUX of the study ===> “To TEST whether butyrate directly affects polyp formation in APCMin/+MSH2-/- mice, antibiotic-treated mice were fed a diet enriched in tributyrin, a stable form of butyrate that breaks down into three butyrate molecules in the gastrointestinal tract

  • 50 mM and 0.5mM of sodium butyrate, which represent concentrations of butyrate found in the distal part of the colon (Donohoe et al., 2012a), stimulated proliferation of colon epithelial cells in APCMin/+MSH2-/- mice but NOT in controls
  • AND “high concentrations of sodium butyrate (i.e., 10 and 100mM) did NOT increase colon epithelial cell proliferation in APCMin/+MSH2-/- mice

KEY POINT: I’m underlining “in APCMin/+MSH2-/- mice” like it’s going out of style because the study should not be extrapolated as saying

  • ‘butyrate = horrible for humans via mouse proxy’
  • but rather that ‘if certain cell repair mechanisms are non-functional, butyrate (through no fault of its own) can still fuel dastardly clever murine mutant epithelial colon cells
    • In technical speak: “because deregulated β-catenin signaling is a marker of early neoplastic changes of intestinal epithelium (Van der Flier et al., 2007), our results suggest that MSH2-deficient colonic epithelial cells are highly predisposed to transformation
  • And consequently, the authors say the “gut microbiota plays a key role in CRC by providing metabolites such as butyrate that ’fuel’ the transformation of murine APCMin/+MSH2-/- colonic epithelial cells” [into an “aberrant hyperproliferation phenotype”]

So, we’re left with:

  • Our study supports the carbohydrate-cancer link by showing that a diet reduced in carbohydrates resulted in reduced polyp formation in APCMin/+MSH2-/- mice
  • YET…”butyrate has been shown to modulate canonical Wnt signaling, and depending on the status of β-catenin activity, colon epithelial cells respond differently to butyrate (Lazarova et al., 2004)” ==> i.e. the butyrate paradox. It is not a paradox, just that the dose-response curve is not linear but rather U-shaped (as so often is the case) & dependent on the particular cellular metabolic milieu. OF COURSE this matters.

What to conclude? Let us think about these 2 points:

  • The authors’ conclusion of “a diet reduced in carbohydrates as well as alterations in the intestinal microbial community could be beneficial to those individuals that are genetically predisposed to CRC
  • A paper referenced by Belcheva et al.’s group states that “The Warburg effect dictates the mechanism of butyrate-mediated histone acetylation and cell proliferation”] and explains how butyrate metabolism is impaired in cancer cells. It remarks on the fact that “butyrate has opposing effects on cell growth: it inhibits cancer cell proliferation as an HDAC inhibitor but stimulates the proliferation of noncancerous cells (and cancerous cells when the Warburg effect is blocked) by being oxidized as an energy source
    • More details about 2 histone-base mechanism butyrate uses in its **seeming** flip-flops:
      • Colonocytes near the base of crypts receive tiny amounts (uMs) of available butyrate and so makes us of the acetyl-CoA/HAT mechanism for histone acetylation (inhibiting aberrant proliferation). The “acetyl-CoA/HAT mechanism involves metabolism of butyrate in the mitochondria followed by the subsequent ACL-catalyzed production of acetyl-CoA.”
      • Luminal colonocytes however receive more available butyrate (maybe in mM quantities) and thus uses another histone-based mechanism (for inhibiting aberrant proliferation), HDACinhibition, where higher levels of butyrate surpass the oxidative capacity of the cell, causing it to accumulate butyrate within.
  • NO FLIP-FLOP, just AWESOMENESS: “our transcriptome profiling results indicate that they upregulate different targets, with the former (acetyl-CoA/HAT) enriched for cell-proliferation genes and the latter (HDAC-inhibition) being enriched for apoptotic genes
  • THE GOLD: “These changes in gene expression are consistent with the lower doses of butyrate stimulating cell proliferation, while higher doses inhibit proliferation and increase apoptosis. These findings lead to a model whereby butyrate facilitates the normal turnover of the colonic epithelium by promoting colonocyte proliferation in the bottom half of each crypt while increasing apoptosis in those cells that exfoliate into the lumen

I conclude that our bodies really like fat as a fuel. Being the opportunists that we are, we do have long-term bacterial friends that can give us that oh-so-good fatty-fat-fat we love if we give them carbohydrate. Redundancy & mechanistic diversity are true evolutionary treats.

Taken together, it seems like a good idea to feed your colon cells plenty of butyrate and lower your total ‘sugar burden’. You can ingest sources of fiber that will not (usually) induce mutant cell genotypes. Not all sources are equal. Your colon cells like a high-fat diet and so do other cells in your human body. Fiber does and probably should play a role in a high-fat diet. How big a role? No idea. You probably can include quantities that satisfy your taste as a starting point.

Lastly, ketogenic diets are NOT synonymous with fiber poor diets. They fact that people implement them as such says more about their lack of understanding than what a ketogenic really is or can actually be when done properly.

TL;DR A varied and nutrient dense ketogenic diet combining evolutionarily concordant foods (for the most part), including vegetation feeding colon cells butyrate (& other metabolites) by bacterial proxy seems not only reasonable, safe and tasty but also a good strategy for avoiding god damn ass cancer.