Personalized Nutrition by Prediction of Glycemic Responses

“please stop asking gurus how many carbs you need to optimize health”


bananas cookies

An interesting paper came out recently by Zeevi et al. (2015), showing, in part, that we’re all unique snowflakes (in some contexts).





Mini-rant: this study is in line with a lot of my beliefs about individuality in human biology.  We don’t know all the mechanisms, but we do know that some people respond better to some interventions than others.  We learn a lot from studies on diet, light, sleep, physical activity, etc., but the findings rarely/never apply equally to everyone (and some people experience completely opposite effects; eg, see studies where individual data are reported).  LIGHT exposure can improve sleep quality in some but cause agitation in others.  Low carb diets can help weight loss in some people but low fat is better for others.  Dairy, wheat, protein, the ‘biome, and fibre/resistant starch all fall into this category.  Sleep ‘requirements’ vary by person, season, geography, etc., etc…  there’s no QED answers in many of these contexts.

anecdote: some people say they’ve never had better blood glucose than when they were having a few servings of beans/legumes per week; others just report bloating & farts (no bueno).

End rant.

Background reading:

  1. The Atlantic ran a decent piece on this study (certainly more colorful than my take)
  2. Reddit AMA with some of the people involved in the study


In this particular study (video summary below): they continuously monitored the blood glucose responses in 800 people to all of their meals for a week, including a variety of test meals.  Main result: many different responses, even to the same foods!  An oversimplified example: some people had smaller relative postprandial glucose excursions after 50g carbohydrate from rice compared to 50g carb from potatoes, and other people responded oppositely.  And friggin’ tomatoes?!

Translation: need to move beyond recommending #IIFYM.

Some foods were universally well-tolerated [in this population] in the context of mixed meals, like quinoa and salmon; other foods did the opposite, like chocolate chip cookies and sushi.  And lastly, some foods like cottage cheese and hummus were good for some people but others.


bananas cookies[participant 445 is winning]


*In general, I don’t believe in labeling foods as categorically good or bad, which is pretty much confirmed by this study, but some patterns emerged wrt postprandial glucose excursions in this population…



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So the theory goes: high carb meal -> blood glucose spike -> insulin spikes a little too hard -> hypoglycemia -> hunger, so you eat to replenish blood glucose.

In the original theory of hangry, hypoglycemia was a core component, although as Jane Plain pointed out, it could be the relative, not absolute levels of blood glucose that count (&/or free fatty acids, but that’s a story for another day).  This could be true, in part because:
1) symptoms of hypoglycemia rarely correlate with actual hypoglycemia;
2) many episodes of actual hypoglycemia are asymptomatic; and
3) hunger isn’t even one of the main symptoms of hypoglycemia.


Tl;dr: hangry might be a real phenomenon, but there are little/no data to support it, and much to the contrary.


The low carb brigade says “LCHF = no hangry.”
Turns out, the same can be said by the high carb brigade (in some contexts), so does it really matter? (see below)


What we know: obese insulin resistant patients undergo a spontaneous reduction in appetite upon initiating a carbohydrate-restricted diet.  FACT (P<0.05).  Low carb, high protein meals also induce more satiety than high carb meals in acute scenarios…

Imho, hunger and satiety are complicated biological phenomena that can’t be so easily simplified into cute concepts like “hangry.”


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Epigenetics & Circadian Biology: Prader-Willi

I came across a recent study on a mouse model of Angelman Syndrome (an epigenetic disorder), and wasn’t surprised to learn there’s a strong circadian component to it.  Epigenetics are one of the main ways circadian rhythms are programmed.

In this case, the circadian connection is more direct.

Angelman Syndrome (AS): you inherit 2 pairs of each gene, one from Mom and one from Dad.  In some cases, one of the copies is silenced via epigenetics and you’re basically just hoping the other one is in good shape.  In the genetically relevant region in AS, the paternal copy is silenced and the maternal copy does all the heavy lifting, but in AS, the maternal copy is mutated or absent, so none of the genes in this region are expressed.

Interestingly, scientists found that one of the genes, Ube3a (an ubiquitin ligase), is involved in regulating Bmal1, a core circadian gene (Shi et al., 2015) . And mice with a silenced paternal Ube3a and mutant maternal Ube3a exhibit many of the same circadian symptoms of children with AS. They don’t mimic all of the symptoms as there are many other genes in this region.  But both show circadian abnormalities.

Prader-Willi Syndrome (PWS) is the epigenetic opposite: same region of DNA, but silenced maternal copy and mutant or absent paternal copy. This disorder is characterized by massive obesity and low muscle mass (among other things).




While reading about this disorder, I was taken aback with how the obesity was explained.

“Insatiable appetite” (Laurance et al., 1981), although from what I can gather, these children would develop massive obesity even if they were fed cardboard.  Some studies even showed no change in food intake and/or energy expenditure (eg, Schoeller et al., 1988), which led some researchers to publish entire papers about how these children must be lying and/or stealing food (eg, Page et al., 1983) .

Further, other researchers even explained their obesity was due to an inability to vomit (Butler et al., 2007).



When these kids gain weight, it’s nearly all fat mass; when they lose weight, it’s nearly all muscle [shoulda been a BIG hint]… this even led some researchers (who detected no change in fat mass after significant weight loss) to conclude that their techniques to assess body composition must not be valid in this population because: surely, they must’ve lost some fat mass like normal people do.


It was actually painful to read: these kids are being accused of stealing food and not vomiting because that’s the only way to explain it.


They can be forced into losing fat while maintaining some muscle with an extreme protein-sparing modified fast (eg, Bistrian et al., 1977)…

A few research groups have considered the possibility it’s a hormonal disorder, and some fairly long-term studies with GH replacement have shown promising results (eg, Carrel et al., 1999).


Prader-Willi Food Pyramid. Wait, wut? O_o

Prader-Willi Food Pyramid.
Wait, wut?


Some have even speculated involvement of leptin (eg, Cento et al., 1999), although this hasn’t been followed-up on.



Disclaimer: I don’t know the cure or best treatment modality for Prader-Willi, although given the strong circadian component in its sister condition, Angelman’s Syndrome, I strongly believe this avenue should be explored (in combination with the seemingly necessary hormonal corrections, which have been the only successful interventions yet).  “Diet” doesn’t work; these kids aren’t obese because they’re stealing food or failing to vomit.  Interventions strictly targeting CICO have massively failed this population.

Side note: in the Angelman Syndrome mouse model, *unsilencing* the paternal copy worked… maybe the same could work in PWS (and/or other forms of obesity)…?


Evidence supporting potential circadian-related treatment modalities for PWS:

A Prader-Willi locus IncRNA cloud modulates diurnal genes and energy expenditure (Powell et al., 2013)

Symptoms of Prader-Willi associated with interference in circadian, metabolic genes.

Magel2, a Prader-Willi syndrome candidate gene, modulates the activities of circadian rhythm proteins in cultured cells (Devos et al., 2011)

Circadian fluctuation of plasma melatonin in Prader-Willi’s syndrome and obesity (Willig et al., 1986)


And the connection with LIGHT:

Artificial light at night: melatonin as a mediator between the environment and the epigenome (Haim and Zubidat, 2015)

Circadian behavior is light re-programmed by plastic DNA methylation (Azzi et al., 2014)





PWS is much worse than just nutrient partitioning (seriously, just spend a few minutes on any Prader-Willi support forum or this; maybe it is an appetite disorder, but given the data on weight gain [mostly fat mass] and weight loss [mostly muscle mass], it seems far more likely a circadian disorder of nutrient partitioning),
but that component jumped out at me; more specifically, despite the only positive results coming from non-dietary interventions, researchers were still all “#CICO.”

“Lean meat, sugar-free Jello, and skim milk”

Circadian biology, hormone replacement [where appropriate], and figure out if any specific diets help.  PMSF/CR doesn’t work unless “refrigerators and cabinet pantries are locked shut.”

Maybe this applies to other forms of obesity, too.


calories proper



The “Insulin Index”

Similar to the glycemic index, which is an estimate of the rise in blood glucose after eating a particular food, the insulin index is an estimate of the rise in insulin after eating a particular food.  In general, these indices are obvious: processed carbs have high glycemic and insulin indices, whereas whole foods are lower.  Some exceptions are things like dairy and lean meat, which induce more insulin than you’d expect given to their low carbohydrate content…




When some protein-rich foods were discovered to induce insulin secretion, people thought this information might help type 1 diabetics more accurately calculate their insulin dose.  Interesting rationale, worth testing.

Tl;dr: it didn’t work very well.

More of the protein-derived amino acids may have been incorporated into lean tissue, but the extra insulin load ended up causing hypoglycemia more often than not.  Hypoglycemia is acutely more harmful than hyperglycemia, and is still quite harmful in the long-term.  Some studies on incorporating the insulin index for type 1 diabetics are mixed, ie, increased or no change in risk of hypoglycemia, but no studies show it reduces the risk.


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“Insulin Dynamics”

This one has a bit for everyone.


Relationship of Insulin Dynamics to Body Composition and Resting Energy Expenditure Following Weight Loss (Hron et al., 2015)


I think study was actually done a few years ago, originally published here (blogged about here), and re-analyzed through the eyes of Chris Gardner.  I think. (But it doesn’t really matter as the study design appears to be identical.)


Experiment: give someone an oral glucose tolerance test (75 grams glucose) and measure insulin 30 minutes later.  Some people secrete more insulin than others (a marker of insulin resistance); these people also have a lower metabolic rate after weight loss = increased propensity for weight regain.  However, if these people follow a low carbohydrate diet, then the reduction in metabolic rate is attenuated.  Some people who don’t secrete a lot of insulin after a glucose load may do better in the long-run with a lower fat diet.


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Some nuances of Intermittent Fasting

Intermittent fasting (IF) is not a universal panacea, regardless of whether you’re not eating anything at all for a few days each week/month or just restricting your feeding window to a few hours per day.

Some protocols, eg, 20h fasting every second day, significantly improve insulin sensitivity in adipose tissue (Halberg et al., 2005). This is expected to make fat gain easier, and while this wasn’t meant to be a study on body composition per se…


body composition


After just a few weeks, things weren’t changing in a good way (NS).


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Hall et al., THE FIRST SIX DAYS (update)

Some people say the study design was rigged to favor the Low Fat diet (LF), which is dirty business but not exactly criminal; sometimes, this happens in science.

The claims go something like this: baseline diet was so high in carbs that they were locked into making unreasonable adjustments to formulate isocaloric low fat and low carb diets; eg, fat was too low in the low fat diet and carbs weren’t low enough in the low carb diet.

The biggest finding was “Fat Imbalance,” which favored LF.  Here’s why I don’t think the baseline diet mattered very much.

Tl;dr: drastically cutting fat intake (LF diet) is much more effective than upregulating fat oxidation (LC diet) to create a large Fat Imbalance in an acute setting, ie, THE FIRST SIX DAYS.


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A brief explanation of Hall et al., ie, THE LOW CARB WAR

“Examination of acute shifts in energy balance by selectively reducing calorie intake from one macronutrient.”

Intro (1/2): please don’t read this study with the media headlines in your mind.  Don’t even pay any attention to the study’s title, abstract, intro, and discussion.  In no way did this study put low carb proper on the chopping block, regardless of what you’ve seen online or elsewhere.  Mmmkay?


Intro (2/2): if you want a lesson (or refresher) in Advanced Nutrition, check out the Supplemental Information: in formulating his mathematical models, Dr. Hall seemingly reviewed every single biochemical pathway and physiological variable ever invented.  Read it, for science.  Really.


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Ketosis is a hack: here’s why

There are multiple distinct flavors of diabetes/obesity, as evidenced by the fact that some people have: 1) impaired glucose tolerance (but normal fasting glucose); 2) others have impaired fasting glucose (but normal glucose tolerance); and 3) others have both.  This means there isn’t a linear relationship between these phenomena*.  There are also: 4) obese patients with normal glucose metabolism; and 5) lean patients with type 2 diabetes.

*I think the great Dr. Kraft may have missed some of the nuances here.

There is not 100% overlap among these, suggesting [confirming] distinct diabetes/obesity phenotypes (and probably causes & best treatments).





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Many pre-diabetic, diabetic, and insulin resistant people have used the low carbohydrate diet to successfully manage their blood glucose levels.  It just plain works.  FACT (P<0.05).

However, a small subset of this population fails to achieve normal fasting glucose.  This is likely due, in part, to a type of circadian mismatch induced by aberrant meal timing and excess exposure to artificial light at night.  For an extensive list of citations supporting the former, see “Afternoon Diabetes;” stay tuned for evidence of the latter.  In brief, a combination of delaying food intake for as long as possible after waking in the morning (“skipping breakfast”) and consuming most calories at night = no bueno.  These behaviors can also promote a circadian mismatch and phase delay.  Hint: eat when the sun is up; sleep when it is down.


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