Author Archives: Bill

AMYLIN

Brief background reading: amylin (according to Wikipedia)

 

In a study by Hollander on type II diabetics, the synthetic amylin analog pramlintide was tested (Hollander et al., 2003).  In this year-long RCT, over 600 patients were treated with placebo or up to 120 ug pramlintide BID (twice per day).  On average, these subjects were obese (BMI 34), diabetic for ~12 years, and had an HbA1c of 9.1%.  After one year, HbA1c declined 0.62% and they lost about 1.4 kg… not very impressive.

 

But it’s not all bad news; after viewing those relatively negative results (3 lb weight loss over the course of 1 year), another group of researchers led by Louis Aronne and Christian Weyer believed amylin had yet to be tested proper.  So they designed a better study; it was shorter, used higher doses of pramlintide, and they enrolled obese yet non-diabetic patients (Aronne et al., 2007).  They opted for higher doses of pramlintide (240 ug TID [three times per day]) because in dose-escalation studies, the incidence and severity of adverse drug reactions was consistently low at all doses tested.

 

They chose to study obese-er subjects (BMI 38, compared to 34 in the Hollander study) because obese subjects lose fat more readily than lean people, so if the study is designed to measure fat loss, then it is better to select a population of subjects where more fat loss is predicted.  They selected non-diabetic subjects for a similar reason; diabetics must regularly inject insulin which promotes the accumulation of fat mass — this could counteract any fat reducing effects of pramlintide.
In other words, it was a more powerful and better designed study.

 

After 16 weeks, pramlintide-treated subjects lost an average of 3.6 kg (~8 lbs), or about half a pound per week.  30% of patients lost over 15 pounds (1 lb/wk)!  Importantly, the weight loss didn’t appear to have reached a plateau by week 16, so it would have most likely continued along a similar trajectory had the study been longer.  There were no side effects, and a battery of psychological evaluations showed that the patients receiving pramlintide felt it was easier to control their appetite and BW, they didn’t mind the daily injections, and overall well-being increased.  At the very least, these evaluations meant the subjects weren’t losing weight because of nausea or malaise.  In fact, it was quite the opposite.

 

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Ketone supps

1st Generation: ketone salts.  Only problem is the huge dose of salt limits how much you can take without adverse effects… but these are the ones on the market.

 

2nd Generation: ketone esters.

Advantage: no salt, and probably “slow-release.”

Disadvantage: gonna be WAY more expensive than the salts (which are still pretty expensive).

 

 

~40 grams of (R)-3-hydroxybutyl (R)-3-hydroxybutyrate (a ketone ester) (from Clarke et al., 2013):

 

ketone ester

 

They did this thrice daily, so some people were getting up to 170 grams.

ONE HUNDRED SEVENTY GRAMS

 

[keep that number in mind]

 

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Tissue-specific fatty acid oxidation

Does it matter where fatty acids are oxidized, liver or skeletal muscle?  Of course, they’re oxidized in both tissues (quantitatively much more in the latter), but relative increases in one or the other show interesting effects on appetite and the regulation of fat mass [in rodents].

Warning: a lot of speculation in this post.

A LOT.

It’s known that LC diets induce a spontaneous decline in appetite in obese insulin resistant patients.  Precisely HOW this happens isn’t exactly known:  the Taubes model?  improved leptin signaling?  probably a little bit of both, other mechanisms, and possibly this one:

 

Exhibit A. Oxfenicine

 

oxfenicine

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Muscle growth sans carbs

1.  net muscle growth = synthesis – breakdown

2.  need =/= optimization

3.  #context

 

muscle sans carbs

 

I’m totally cool with keto, honestly!  but still don’t really like seeing stuff like the above graphic and people interpreting it to mean “KETO IS MUSCLE-SPARING.”

 

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Random thoughts on the ‘biome

If you’re healthy, no major complaints, then you probably won’t benefit from tweaking your ‘biome.  Ymmv.  But if you’re gonna do it anyway, here are some tips (mostly my opinions).

 

microbiome

 

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New low carb protein bars

Warning: this post isn’t #Paleo Certified.   It’s more about convenience, choosing the lesser evil.

Quest Nutrition led the charge in low carb, high protein, fibre-rich bars.  “Fibre-rich” is really the key in allowing a bona fide “low carb” bar with shelf-stability and decent texture.  Sugar alcohols have also been used in some, but due to the high incidence of maltitol-induced GI discomfort, ymmv.  But in general, you need one or the other to provide bulk and keep it together (except Epic Bars, which use black magic).

For the most part, the new bars have basically copied Quest’s formula with some new flavors.

 

Disclaimer #1: I’m a whole foods guy.  Not really #Paleo, but when it comes to people’s actual lifestyles, I recognize convenience is a huge factor… and selecting the lesser evil is frequently the best option — eg, you can store a couple LC protein bars in your office, car, etc.; not so much with hard-boiled eggs or other protein-rich foods… and these options are WAY better than many other snacks or “fast-foods” out there.

Disclaimer #2: yeah, I keep a few of these bars in my office, just in case…

Quest recently switched from isomaltosaccharides to soluble corn fibre (SCF), which will likely impact GI effects.  YMMV!  Isomaltosaccharides are cool, but I’m not prepared to say they’re superior to SCF for everyone, in every #context (personally, for the ‘biome, I prefer brassicas, alliums, the gristly bits, galactooligosaccharides, et al.).
[it’d awesome if Bi2Muno would collaborate with one of these companies]

 

In these n00bs to the protein bar market, some of the biggest differentiating factors are cost, net carbs, ratio of fibre to sugar alcohols, flavor profiles, etc.

 

With no further ado, here are the newcomers:

[or just skip to the chart at the bottom]

 

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Personalized Nutrition II

More on Zeevi et al. (2015) (this is a follow-up to part 1)

I like this study a lot, or at least the fundamentals… or new tools that it might bring to the table.  Like, we know sleep and physical activity are important, and we know all calories aren’t created equal.  This study is the next level, showing there are even big differences in specific carb-rich foods depending on who’s eating them.

And more interestingly, if I’m interpreting the results of the intervention study correctly (which may not be the case), gut microbial responses to specific foods were very individualized… and predictable!

But first, the main part of the study — standardized meals (after overnight fast): 50g carbs from glucose, white bread, bread and butter, bread and dark chocolate, and fructose.  All repeated at least once (except fructose).  Everyone responded pretty similarly to fructose (little to no blood glucose spike), but a wide range of responses to glucose.

PPGR = PostPrandial Glucose Response

 

glucose and fructose

 

Bread:

 

bread

 

The range of PPGR to bread was ~15 to 79!

Again, here are some of the findings I found most interesting (besides the huge range in glycemic response to bread):

 

 

banana and cookie

 

Participant #468 has a consistently higher response to glucose than to white bread.  Participant #663 is the opposite.  And participant #445 is still winning.

I truly wonder if there’s a gut microbe (or something) that’s involved here…

 

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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).

 

#context

#context

 

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…

#context

 

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HANGRY!

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).

Prader-Willi

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).

THEY’RE OBESE BECAUSE THEY’RE NOT BULEMIC.

AYFKM?

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.

THEY FAILED TO CONSIDER THIS IS AN EXTREME CIRCADIAN MISMATCH DISORDER IN NUTRIENT PARTITIONING

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.

NO IT’S NOT, SCIENCE.

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?
O_o

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”
FFS

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.
Maybe.

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calories proper