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Nick Norwitz Profile picture
@nicknorwitz
Jan 6, 2023 • 18 tweets • 7 min read • Read on X
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1/18) 🚨NEW PAPER in @AJCN provides evidence supporting #CIM of #obesity

👉 Glycemic Load >>> Calorie Counting for weight loss

👉 Biomarkers of Low carb diet predict weight

👉Insulin hyper-secreters especially benefit fromlow-carb

Video 👉👉
🧵... Image
2/18) First, and foremost, a big congrats to @AdrianSotoMota and @davidludwigmd for an excellent work!

& of course, for those who have the time, I highly recommend reading the full paper, here: doi.org/10.1016/j.ajcn…

But for those who prefer video or TW thread... HERE WE GO...
3/18) What the researchers did in this paper is perform a secondary analysis of pre-existing data from a 12-month RCT: the DIETFITS trial in which 609 adults aged 18-50 without diabetes were randomized to either a 12 m Low-carb diet (LCD) or low-fa diet (LFD).
4/18) Initial data showed LCD led to more weight loss than LFD at 3 and 6 mo, but that the between group diff in weight loss lost significance at 12 months

This was taken to be evidence against the CIM. However, as this paper reveals, there is more nuance to the story... Image
5/18) One important ? is why significance was lost at 12mo?
2 reasons...

i) Participant dropout. Each group lost ~80 participants, diminishing statistic power

AND

ii) Diet convergence: ‘Carb creep’ in the LCD group (132g/d) + carb drop in the LFD group (213g/d) Image
6/18) Even setting aside the dietary convergence, when missing data was imputed, the LCD group did in fact lose more weight at 12 m than the LFD group at all time points. Image
7/18) Moving on, Fig 2 shows a model of predictors of weight loss ➡️ larger circumferences represent better predictors of weight loss

🍽️🍽️Total fat & Calories were poorer predictors of weight loss

🍩🥭Carbs & GI and sugar are the superior predictors

Consistent with the CIM Image
8/18) In Table are 2 models examining the mediators of weight loss

When you add in Glycemic Load (GL) is added to the model in model 2, GL is highly significant (p=5.7x10-5) and calories (p=0.80) LOSE significance!

Let’s expand on this point... Image
9/18) Many think that LCD works bc it just makes you eat fewer calories, but that it’s actually the drop in calorie intake that’s driving the weight loss. This certainly is a contributing factor but...
10/18) These results show that GL is better than caloric intake at predicting weight loss, which may appear counterintuitive BUT can be made intuitive if you think about the components of Energy balance: Calories in & Calories out...
11/18) The CICO model, when taken in CLINICAL practice, usually focuses on CI because accurately measuring CO accurately is next to impossible (think, NEAT, TEF, body temp, etc.)
12/18) By contrast, if GL influences the hormonal milieu of the body, it dictates NOT ONLY hunger and caloric intake (CI) but also homeostatic mechanisms to maintain energy equilibrium, or tip it one way or another, through CO: NEAT, body temp, etc.
13/18) Simply put, one could actually make the argument that the CIM is actually a superior real-life ‘CICO’ model than the standard cal counting CICO model itself!

LOL If that doesn’t make sense, read ^ again and watch video for completeness
14/18) Other cool data presented in this paper consistent with the results already shared is that, in fig 5, a biomarker of low-carb/GL (TG/HDL) was strongly associated with weight loss whereas a biomarker of fat reduction (LDL+HDL) was not. Image
15/18) Finally, and beautifully, the authors put a bold prediction of the CIM to the test which is that those with higher basal insulin secretion would benefit most for GL reduction. Again, this is b/c in the CIM GL influences insulin to cause fat storage.
16/18) So, if someone naturally is an insulin hyper-secreter, the effect of the model is simply going to be amplified. As a result, those who secrete a lot of insulin probably benefit the most from reducing GL. Is that the case? As it turns out yes!
17/18) Clearly see an interaction b/w GL reduction and basal insulin

As you can see in the back left row, these persons who reduced GL most and were the insulin hyper secreters, lost the most weight! Image
18/18) In summary, this paper provides powerful evidence for two prediction of the CIM: (1) GL > Calories as a predictor of weight loss and (2) insulin hyper secreters benefit most from carb reduction.

Video


Paper
doi.org/10.1016/j.ajcn…

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More from @nicknorwitz

Nick Norwitz Profile picture
Nov 20
🚨Discovery of a New Ketone Body Metabolite that Suppresses Appetite

1/5)🧵This thread will review new data, and suggest one reason why some people might lose more weight on #ketodiet than others

The research, publish in @CellCellPress, documents the discovery of a byproduct of ketone body, beta hydroxybutyrate (BHB), metabolism: The BHB-Amino Acids.

At a high level:

👉The enzyme carnosine dipeptidase 2 (CNDP2) combines the ketone body, BHB, with amino acids to make BHB-amino acids.

👉This pathway appears conserved in mice and humans.

👉BHB-amino acids levels increase in response to ketogenic diets, fasting, or exogenous ketones.

👉BHB-amino acids activate different brain regions to reduce food intake and promote weight loss.

Now… for some more details…Image
2/5) Background

The enzyme, CNDP2, is primary expressed in the kidney and gut cells and was previously known as the enzyme that generated the appetite suppressing compound Lac-Phe, a combination of lactate and the amino acid, Phenylalanine, that is thought to mediate the appetite suppressing effects of #exercise the drug #metformin on weight loss.

But this CNDP2 enzyme is “multipurpose,” i.e. it not only combines lactate with amino acids but can also only combines the ketone body, BHB, with amino acids, as shown in the paper, the most prevalent of which is BHB-Phe.

The researchers show that ketogenic diets, fasting and exogenous ketones (ester) each increase levels of BHB-Phe.

(Aside: different ketogenic interventions appear to increase BHB-Phe to different degrees, i.e. the relationship between BHB and BHB-Phe levels may vary depending on 'how' ketosis is induced.)Image
3/5) Although BHB-amino acids are made in humans and present in human blood, to demonstrate causality it’s helpful to use mouse models.

🚨Direct administration of a ketone supplement or BHB-Phe decreased food intake and prevented weight gain.

🚨However – and importantly – mice who had been modified to have the CNDP2 gene knocked out, and thus could not generate BHB-Phe, did not respond to ketone supplementation with appetite suppression.

To reinforce the point, ketone supplementation AND/OR a ketogenic contributed to relative weight loss in animals with functional CNDP2 that could make BHB-Phe. But when this ability to make BHB-Phe was eliminated, so too were the appetite-reducing anti-obesogenic effects of ketones.

This suggests that ketogenic interventions reduce appetite, at least in part, through the generation of BHB-Phe.Image
Read 5 tweets
Nick Norwitz Profile picture
Nov 19
1/4) New Research (Yesterday) in @Nature on the Memory of Your Fat Cells: “Adipose tissue retains an epigenetic memory of obesity after weight loss”

Let’s break it down…

You’re probably aware of the “yo-yo” effect, whereby people who lose excess weight are prone to gain it back.

But is this purely behavioral, or are there deeper metabolic mechanisms at play?

In this study, researchers took cell samples from human patients who were always lean versus those who had a history of obesity but who had lost weight after bariatric surgery, and measured gene expression profiles* from their fat at the time of surgery and 2 years later after substantial weight loss.

🧬They found significant changes in fat cells (adipocytes), as well as their precursors and also in other cell types, like the endothelial cells that line blood vessels.

Overall:
⚡️Fat cells from individuals with a history of obesity showed down-regulation (less expression of) genes relates to metabolic functions
🔥And up-regulation (more expression of) genes relates to inflammation functions

Thus, in the authors’ words, “These results indicate that obesity induces cellular and transcriptional (obesogenic) changes in the [fat cells], which are not resolved following significant weight loss."

Ref. Hinte et al. Nature Nov 18, 2024, doi: 10.1038/s41586-024-08165-7Image
2/4) To get more granular, they did a similar experiment in mice where they fattened some mice using a high-sugar high-fat obesogenic diet, and then normalized their weight through dietary restriction and compared these to mice who never had obesity.

They found, consistent with the human data, persistently gene expression changes, including downregulation of metabolic pathways, such as fatty acid oxidation, mitochondrial signaling, etc., and upregulation of inflammatory pathways.

🔧How it works🔧

I’ll explain how this works at a high level through an analogy.

Your genetic code is like a book… even though all cells in your body contain your full genetic code they are different.

Why?

Because in different cells different pages are opened or shut. This determines the fat or function of cells.

What’s more, cells can “bookmark” or dogear pages for easy access. In the cell these are “epigenetic” changes, where tags are put on to DNA or the protein complexes around which DNA is wound.

This makes it easier (or harder) to access certain pages (certain genes), changing their expression profiles.

Hopefully that makes sense?
And that’s how cells develop a “memory” of past events, including the memory “I was once an ‘obese’ fat cell.” If it’s not too dark to say, think of it like PTSD for fat cells.
3/4) Now, are these changes functionally meaningful with respect to weight regain?

It would appear so. Human observational and clinical data suggest those who have lost weight are more prone to put weight back on.

Although, of course, in free living humans it’s hard to disentangle the effects of behavioral and constitutional (inborn) differences from those imposed from true epigenetic changes brought about by a history of obesity.

However, carefully controlled mouse experiments – which in this case should probably generalize to humans – do indeed strongly suggest that a history of obesity (red vs blue [control]) predisposes fat cells to take up sugar more readily, build up fat stores in response to insulin more quickly, and develop fatty liver more easily.Image
Read 4 tweets
Nick Norwitz Profile picture
Nov 9
🚨Vegan Diet Increased My Cholesterol!🚨

1/5) Since there is talk about Keto and #LMHR, I thought I’d give people something to talk about.

I went from:
🥩Animal-based #carnivore-ish ketogenic diet to a
🌱#Vegan keto diet

And my LDL cholesterol INCREASED! (👀Read On...)
2/5) For this N = 1 experiment, my macro breakdowns were as shown below.

As you can see, despite eating over 4X LESS saturated fat, more fiber, ZERO cholesterol (and more PUFA), my LDL-C increased by 14%.

How could this be?! ...Image
3/5) The explanation is the Lipid Energy Model. In a nutshell (a macadamia nutshell, in this case, which are very hard to crack):

When Lean Insulin Sensitive People go on Very Low Carb Keto Diets, LDL-C increases as part of a lipid triad of:
☝️HIGH LDL-C
☝️HIGH HDL-C
👇LOW Triglycerides
That is the result of shifting from carb burning to fat burning.

The levers that drive how high LDL increases are leanness and activity level.

Thus, when I went to my vegan keto diet, despite the drop in saturated fat and cholesterol and increase in fiber and PUFA, the restrictive (large, acute calorie drop) nature of the vegan keto diet vs the carnivore-ish keto diet drove UP my LDL.

The importance of these factors, especially leanness in determining LDL-C on low-carb diets, is documented in the literature, including our meta-analysis of 41 human RCTs cc @AdrianSotoMota @realDaveFeldman
PMID: 38237807
Read 5 tweets
Nick Norwitz Profile picture
Nov 5
1/5) The hot talk of the week is this new paper in the prestigious journal Science that shows early life exposure to sugar, including including in utero and in the first years of life, can seriously and causally impact a child’s risk of developing diabetes, high blood pressure and obesity later in life.

I’ll have a long-form YouTube video produced in this shortly. But in the meantime, I thought you deserved a breakdown.

First, let me explain what’s special about this study.

Usually, to demonstrate causality for effects that take decades to manifest you can’t do a randomized trial, so you need to rely on animal data and standard observational epidemiological studies, which are riddled with confounders.

However, now and again, real-world circumstances impose a natural experiment. And, in the United Kingdom rationing of Sugar continued post-World War II era, until September 1953.

Cc @ChrisPalmerMD @hubermanlab @foundmyfitness @BenBikmanPhD @RobertLustigMD @FitFounder @DaveEDannaImage
2/5) And after Sugar rationing ended, sugar intake doubled almost immediately – and selectively, with intake of other food stuffs like fats, produce and proteins remaining rather constant.

This presents a natural quasi-experiment, because what you can do is follow cohorts of children – 60,183 children in this study – through their life course, comparing those born just before rationing ended – these are the “rationed babies” – to those conceived and born just after rationing ended – these are the “un-rationed babies” or “sugar babies,” because they were exposed to sugar.

That’s exactly what they did in this study.

And it’s a cool design because it takes advantage of a historical event to control for variables through a sort of ‘randomization’ in time, in a way that would be impossible to control for otherwise.Image
3/5) The researchers found a dose-dependent effect whereby less exposure to sugar during early life led to lower risk of type 2 diabetes, lower risk of hypertension, and lower risk of obesity later in life, particularly starting around age 50.

(Caption: Black is un-rationed (Sugar Babies). Green is rationed in utero. Blue is fully rationed during early life.)

When I say “dose-dependent,” in this case I mean in time, whereby there was a protective effect of not being exposure to as much sugar in utero for kids born just before the end of rationing (e.g. around New Years 1953), and an even stronger effect if the sugar ration included the first year of life because the kids were conceived one year earlier, and even stronger still if rationing included the first two years of life.Image
Read 5 tweets
Nick Norwitz Profile picture
Nov 4
3 SAD and Hilarious Anti- “Animal Based Diet” Studies
🥩🥓🥜🍝

1/4) On request, I just posted a video interrogating the claim that plant-based proteins are better for longevity than animal-based proteins. In thevideo (link at the end), we’ll delve into the nuances. For X, here are three examples of how the methods, data and literature can be misleading...

Ex 1. The “Beef” Diet

This “beef” diet included a breakfast of English muffin with peanut butter and an apple, low fat milk and spaghetti and salad with Italian dressing with lunch, bread rolls, peanuts and beans and fruit with dinner, and chips, hummus and almonds as a snack
2/4) Ex. 2 Lasagna = Steak?

Not much new here, other than to point out studies that use Food Frequency Questionnaires often cluster foods inappropriately.

Here, for example, “meats” can be delivered as a steak or slab of lasagna. They’re the same to the survey, and this isn’t immediately apparent until you do some digging… in this case back to a form from 11 years before I was born.
3/4) Ex. 3 Soy is Animal-Based Now?

This was my favorite!

One of the big holes in the plant-based proteins for longevity argument relates to biological plausibility.

What’s the mechanism?

In a recent study, it’s mentioned in the discussion that animal-based proteins increase IGF-1 relative to plant-based proteins, which is the suggested mechanism… but if you look and their own reference, vegetarians didn’t have lower IGF-1 and … get this … soy protein is clustered with animal proteins because the effect seems to be due to essential amino acids, not the animal/plant nature of the protein.

And if the way you want to craft a narrative around plant > animal protein requires you to call Tofu = “Meat” … well, I’m not sold.

You do you, but I remain unconvinced that tofu and legumes are the thing that will keep my kicking into the 2100s.
Read 4 tweets
Nick Norwitz Profile picture
Oct 14
🔑How Ketosis Really Works!🔥

1/4) This is cool! New Science in @Nature Explains HOW the body triggers ketosis.

AND, I'm going to tell you how I get my ketone levels to the equivalent of a 6 day fast in < 1 day.

⚠️BUT - be warned ⚠️ I will shock you with some SEED OIL talk... & it's not what you expect.

Listen up...

Specifically, these data reveal how fatty acids change the body's metabolism to boost ketone levels and fat burning... pay attention...
#Ketosis #FattyAcids #Metabolism #eIF4E #AMPK #Fasting #KetoScience #MetabolicHealth #CancerResearch
2/4) A new study in @Nature recently characterized the role of a key protein, eIF4E, in the feeding-fasting metabolic transition.

👉What is eIF4E?

eIF4E is already a known player in the “central dogma” of molecular biology, where your DNA 🧬is transcribed into messenger RNA, which are then translated into proteins. Then, the proteins do the work in the body.

The efficiency of these steps determines the overall balance of the >100,000 proteins in the body, and across tissues and organs and overtime. And eIF4E influences the efficiency of translation of specific proteins... thus, eIF4E is a key node in your body’s metabolic network.

👉The Pathway: Fats as Signaling Molecules

Fasting or a ketogenic diet causes a rise in the fatty acids circulating around in the blood go to the liver where they activate an enzyme called AMPK.

Yes, fatty acids can bind directly to AMPK like hormones in their own right. AMPK then acts on a protein called MNK which acts on eIF4E.

If this went over your head a bit, don’t fret.

The punch line is that fatty acids, which are the primary fuel when you’re fasting on keto, are not just fuel but signaling molecules that can bind to pockets on enzymes, setting in motion a cascade of events leading to the change in proteins that “adapts” the body to fat burning mode.🔥

👉In the authors’ words, “Our findings reveal a new signaling property of fatty acids” which are released during fasting or on ketogenic diets.
3/4) ⚠️ This is going to PISS OFF some people⚠️

Different Fatty Acids have different "ketogenic" potential.

Now - here's something CRAZY! I can get my ketone levels to 6.0 mM in <24 hours by shifting to a higher PUFA diet.

I know... I know... people are thinking "SEED OILS!" BUT hang in there.

First, while omega-6/PUFA are more "fragile," in real food forms - e.g. in sesame oil or tahini - they can be protected my natural anti-oxidants.

AND, PUFA are more ketogenic than saturated fats, all things being equal

That's not to put a value judgement on butter vs tahini per se. However, it does emphasize a nuance: CONTEXT matters.

If you're fat-adapted and wanting to boost your ketones, a solid dose of PUFA from real food can be your friend. Hearsay! Or is it?

Would actually love to discuss this matter more with a long list of people
cc @foundmyfitness @theproof @KenDBerryMD @SBakerMD @ChrisPalmerMD @drcateshanahan @TuckerGoodrich @raphaels7 @ChrisPalmerMD @bschermd @biolayne @PlantChompers @realDaveFeldman @AdrianSotoMota

Also, because I know people will ask... I do eat higher PUFA needs and seeds and maintain an omega-6/3 ratio of 1:1 with 17.2% EPA/DHA index.

Also also, I'm not saying LA (18:2) vs PA (16:0) ketogenic potential comes just from AMPK affinity (there was a trend in the paper/spp but is was ns. Still... interesting.

Who wants to have this chat with me in long form?
Read 4 tweets

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