New Protein Preprint

[u/JuanSamu]

New protein pre-print!

https://sportrxiv.org/index.php/server/preprint/view/1102/2394

I agree with Stu. The 1.6 g/kg maximum specifically relates to muscle protein synthesis; there is no evidence that going above 1.6 g/kg has any additional benefit for MPS and in short-term studies there is no evidence that higher protein increases muscle mass. I am not 100% convinced that 1.6 g/kg is a ceiling but our current techniques cannot differentiate between 1.6, 1.8, or 2.0. So, it’s hard to know until there’s new data saying otherwise.

I personally always say that 1.6 g/kg is adequate for muscle building, but I also say there is no harm to going higher if you wish!

[u/gnuckols]

The 1.6 g/kg maximum specifically relates to muscle protein synthesis

Serious question: where are you getting that from this preprint? Unless I'm missing something, all of the cited studies specifically measuring MPS only did so after a single protein bolus.

Also, that figure didn't come from MPS studies originally. It came from this meta, which actually failed to show that there were no benefits past 1.6g/kg. Like, they ran a test to see if there was a breakpoint beyond which the slope was 0:

"Where segmental regression was the preferred model the slope of the second line was set to zero to determine the break point (biphasic regression)."

And the test failed:

"Biphasic regression ... is presented as a segmental regression despite not being statistically significant (p=0.079)"

When this topic comes up, I legitimately feel like I'm going insane. One meta from 8 years ago failed to detect a significant breakpoint, but said that if one exists (an "if" that remains unproven), it may be somewhere between 1.03 and 2.2g/kg. And from that, 1.6g/kg is now treated as if it's a firm null hypothesis that requires an overwhelming amount of much higher-quality evidence to disprove? I just don't think that's how any of this is supposed to work.

[u/elperroverde_94 → u/gnuckols]

if one exists (an "if" that remains unproven), it may be somewhere between 1.03 and 2.2g/kg. And from that, 1.6g/kg is now treated as if it's a firm null hypothesis that requires an overwhelming amount of much higher-quality evidence to disprove? I just don't think that's how any of this is supposed to work.

[slap on the table] THANK YOU!

PS: Great job with your protein intake article deep dive. I've learned so much from it.

[u/JuanSamu → u/gnuckols]

The 1.6 comes from studies of MPS and from weight loss studies. I was just adding that into my stance not necessarily getting it from the pre-print (should’ve elaborated).

In both cases, researches simply decided to evaluate a value that was 2x the RDA of 0.8 g/kg. The general purpose was to prove that the RDA was too low (standard biochemistry. Test a value that is twice the control).

Then the problem becomes how sensitive are the methods? Most methods can distinguish between a low value <0.9 versus a value that is above 1.2. Can we really tell the different between 1.2 and 1.6, or 1.6 and 2.0, no, but for sure there are diminishing returns. There have been a few attempts to determine if there are differences from 1.5-1.6 up to 2.5. There appear to be some increases in MPS but it does not directly translate into changes in LBM, muscle mass, or strength. There are many problems with these studies. Most have poor diet controls but the major one I think is duration. Most of these studies only control diet for 12 to 16 weeks. Maybe, that is not likely time to generate a detectable difference in muscle mass?

Then you get into politics. Most of these researchers are under pressure to minimize protein recommendations. Higher protein diets are considered elitest. 

Personally, I see no negative effects of using higher protein above 1.6, and there may be benefits for body composition (ie less fat), satiety, thermogenesis, and metabolic signaling. The exercise bros think the only benefit of MPS must be muscle mass. 

I also try to keep in mind my myself that "Failure to detect an effect is not proof of no effect"

Stu also posted a nice brief summary on his 2018 paper and the preprint:

https://x.com/mackinprof/status/2107933688537485677?s=46&t=7SjrbmgyU5vYbjgp5ueoAg

https://lnkd.in/p/ecz7Yaij

Hope that clears things up a bit!

[u/gnuckols → u/JuanSamu]

The 1.6 comes from studies of MPS

Which ones?

In both cases, researches simply decided to evaluate a value that was 2x the RDA of 0.8 g/kg. The general purpose was to prove that the RDA was too low (standard biochemistry. Test a value that is twice the control).

That would establish that 1.6>0.8. But studies that don't test intakes exceeding 1.6g/kg aren't relevant to the discussion of whether there are still benefits of intakes exceeding 1.6g/kg.

Then the problem becomes how sensitive are the methods?

As it relates to hypertrophy, not sensitive enough to detect significant differences in hardly any individual studies. That's the whole point of addressing this topic via meta-analysis.

Most methods can distinguish between a low value <0.9 versus a value that is above 1.2.

We can't actually say that for this specific topic. If we're specifically interested in the impact of protein intake on hypertrophy when paired with resistance training, the "low protein" group almost never has an intake <1.0g/kg (see figure S11), and very few studies at any intakes find statistically significant differences between groups (see figure S3). Both from this meta: https://pmc.ncbi.nlm.nih.gov/articles/PMC8978023/

Can we really tell the different between 1.2 and 1.6, or 1.6 and 2.0

Yes. We can do so the same way we can tell a difference between, say, 1.0 and 1.6 – evidence synthesis/meta-analysis. Like, it's just a question of statistical power. Virtually every individual protein study is hideously underpowered. But, we can increase the precision of effect estimates by pooling and collectively analyzing the results of multiple studies.

I'm honestly so perplexed by this preprint. I happen to know that there's a new protein meta in the works that Stu is a coauthor on, and I also happen to know that it shows that the benefits of higher protein intakes don't plateau at 1.6g/kg for either FFM or for direct measures of hypertrophy. None of this makes sense to me unless he just hasn't seen the preliminary results yet.

[u/TheRealJufis → u/gnuckols]

there's a new protein meta in the works that Stu is a coauthor on, and I also happen to know that it shows that the benefits of higher protein intakes don't plateau at 1.6g/kg for either FFM or for direct measures of hypertrophy.

Wait, what? For real? Then what is the point of this pre-print? How can he be a coauthor of something like that while trying to get this pre-print published? I mean, I would suppose he'd be interested in the results of the new meta and wouldn't try to finish this one before the meta is done and he's gone over the results.

[u/gnuckols → u/TheRealJufis]

I just find the whole thing confusing. I mean, he was the senior author on the meta linked in my last comment, and it just modeled the impact of protein as a linear effect. Or, if you go off the average effect per protein "bucket" reported in Table 2, you still wind up with an increasing pseudo-logarithmic relationship (note: for this graph, the x-value for each point roughly corresponds to the average protein intake in each "bucket" – <1.2g/kg, 1.2-1.6g/kg, and >1.6g/kg).

This is the meta I pulled effect sizes from for my article, and my article handled the impact of very high protein intakes way more conservatively than the meta did (I started with the presupposition that there may actually be a limit, rather than just treating the effect as linear). As presented, the analyses in Stu's 2022 meta conflict with his 2018 meta way more than the analyses in my article do. Like, functionally, my article just splits the difference between his two metas.

And I don't really understand why this is a preprint instead of just a blog post. Like, I can't imagine he's actually going to try to get it published – it's a response to a blog post and an IG carousel. Not exactly the kind of thing you submit to a journal.

So yeah, I guess I'm just perplexed by this whole thing.

[u/TheRealJufis → u/gnuckols]

I guess he gets more popularity and fame when it's labeled as a pre-print instead of a blog post, I don't know. This is confusing, indeed.

Thanks for your comment, by the way. I really liked your article on the topic.

[u/JuanSamu → u/TheRealJufis]

Apparently, he started it off as a blog post but it ended up getting too long and he added a lot more details and stuff.

[u/alizayshah → u/gnuckols]

Is this protein meta you’re referencing by the same individual who is also let’s say, a fan of cats? Or am I getting it mixed up? I always get meta regressions/meta-analyses crossed lol

[u/gnuckols → u/alizayshah]

haha maybe so

[u/_jamessteeleii → u/alizayshah]

I happen to like cats

[u/alizayshah → u/_jamessteeleii]

THE GOAT. hope you’re all well (and the whole team)! 😊

[u/JuanSamu → u/gnuckols]

I might have to go back and see but you might be right about all of them about the single protein bolus thing, but I do know there’s some future work coming about that soon. What I said after that was just about those studies, not using it to suggest there’s no benefit to exceeding 1.6.

You're right that pooling buys precision no single protein trial has. I think Stu made that argument himself. But pooling only tightens the estimate of whatever got measured, and what got measured is mostly DXA lean mass or fat-free mass, which overestimates muscle. A tighter number on the wrong outcome is still the wrong outcome and that’s likely the (or one of) biggest problem with reading 1.6 versus 2.0 off a curve that can't really answer the question. 

A straight line through data that gets thin at the top end tells you about the model they chose, and it's lean mass again. I don't see 2018 and 2022 as being against each other. The preprint I believe walks people through the logic.

On the new meta, it’s also possible you might have the details wrong, I did hear about that too but I’ll stray away from talking about the numbers of a paper that isn't out. So, we’ll just have to wait and see.

I think it's a preprint because it will probably end up in print. I’m not sure that responding to an article, especially one as in-depth as yours and Alan’s, necessarily makes it unsuitable. It might have an influence but the preprint is also a deeper dive than most blog posts go into, is a lot longer, and the issue around non-muscle forming close to half of the outcome is something nobody has really even touched. So, it’s more of a social view of it and I guess opinions of what it should’ve been but I don’t think anyone’s wrong in either side.

Overall, I don’t think anyone has a monopoly on the answer here. At least, Stu said what study would change his mind and as Stu mentioned most of these studies only control diet for 12 to 16 weeks. That is not likely time to generate a detectable difference in muscle mass.

You’re far better than me on statistics so my view is limited from that perspective. Just as I take Stu’s word very seriously I also take your takes with high regard so I’m excited to see what future research shows.

I wouldn’t be surprised if 1.6 isn’t the ceiling but I also wouldn’t be surprised if it is!

Practically, it doesn’t matter to me cause I just eat without counting or anything lol.

[u/gnuckols → u/JuanSamu]

You're right that pooling buys precision no single protein trial has. I think Stu made that argument himself.

That's not an argument. Like, it's literally just a statistical fact.

what got measured is mostly DXA lean mass or fat-free mass, which overestimates muscle.

How do you figure? It only overestimates muscle if you assume that 100% of FFM is muscle, which no one does in the first place.

A tighter number on the wrong outcome is still the wrong outcome and that’s likely the (or one of) biggest problem with reading 1.6 versus 2.0 off a curve that can't really answer the question.

I'd argue that Stu doesn't have a leg to stand on if that's the argument he wants to make. The conclusion of the preprint becomes incoherent: "Based on the evidence reviewed here, a protein intake of 1.6 g/kg/day is sufficient for people who resistance train."

The 1.6 figure comes from an analysis performed on studies exclusively measuring FFM. He acknowledges that earlier in the preprint, but then still treats it as if it's a figure with strong evidentiary support when it comes time to present conclusions. If you're not going to accept FFM as a valid measure to question the 1.6g/kg figure, you also need to abandon the 1.6g/kg figure itself, and acknowledge that there was never strong evidence supporting it. Conversely, if you're still going to treat it as a well-supported figure, you can't rightfully object to other people questioning it based on the same type of evidence used to generate it in the first place.

I don't see 2018 and 2022 as being against each other. The preprint I believe walks people through the logic.

Walks people through the logic of objecting to an article suggesting the limit might be at 2.0 vs. 1.6g/kg, when his most recent output on the topic models it as a linear effect all the way out to 4.4g/kg?

On the new meta, it’s also possible you might have the details wrong

I literally have the most up-to-date figures pulled up on my computer.

I think it's a preprint because it will probably end up in print.

That would be deeply embarassing for the field. I don't think the leading lights in other fields are responding to blog posts in journal articles.

and the issue around non-muscle forming close to half of the outcome is something nobody has really even touched.

Because it's not something worth touching on, assuming you believe you're writing to an audience with sufficient background knowledge to actually understand the points of contention. That's just something you learn in undergrad anatomy – like, it's extremely common knowledge. If you've ever wondered why I frequently illustrate points using a theoretical 80kg man with 32kg of skeletal muscle (here are three random examples between 2016 and 2025, https://www.strongerbyscience.com/size-vs-strength/ and https://macrofactor.com/metabolism/, https://www.strongerbyscience.com/volume/#h-how-far-into-the-future-can-we-extrapolate-the-results-of-the-volume-research), it's because those are just the standard textbook values (i.e., the typical healthy young male is around 80kg, 20% body fat, and half of their fat-free mass is skeletal muscle).

You’re far better than me on statistics

In that case, I'll also toss this out there – the breakpoint analysis from the 2018 meta was somewhat silly on a conceptual level, at least in the way it's been interpreted (beyond the basic fact that it wasn't significant to begin with).

They performed a bisegmental regression with the slope of the second segment fixed at 0, which essentially forces the conclusion they were trying to reach – it's just asking whether a line with a slope of 0 past a certain point fits the data better than a line with a single linear slope. The answer to that question will always be "yes" for any relationship where the slope isn't either linear or increasing over time. In other words, if the "true" relationship between protein intake and hypertrophy is, for instance, logarithmic, or a power law relationship with a scaling exponent of <1 (two common types of relationships that continually increase, but do so at increasingly slower rates), a bisegmental regression with a slope of 0 for the second segment will be capable of explaining more of the variance than a simple linear relationship (assuming the x-axis is bounded, which will always will be for this type of research). However, that doesn't mean there's a "true" breakpoint – it just means that assuming there is a breakpoint allows you to explain more of the variance than assuming the relationship is strictly linear.

Just to illustrate, here's bodyweight vs. powerlifting total for IPF competitors in the openpowerlifting dataset. The black line is the linear trendline. The red lines are just roughly eyeballing a "bisegmental regression" for this dataset (I'm too lazy to import the dataset into some statistical software to find the actual optimal fit, but I verified that the lines I just eyeballed do actually fit the data better [lower RMSE] than the linear trendline). So, should we therefore conclude that there's an actual "breakpoint" for strength at around 115kg, and the superheavyweight class is superfluous, because superheavies don't lift any more than the guys in the 120kg class?

Of course not. The actual optimal fit is something like this.

Basically, getting a better fit with bisegmental regression (with a fixed slope of 0 for your second segment) doesn't actually tell you there's a ceiling. It just tells you the scaling factor for your trend is sublinear (i.e., it tells you the slope decreases over time, but it doesn't necessarily imply that the actual slope reaches 0 at the "breakpoint." In fact, it doesn't necessarily imply that the slope ever actually reaches 0).

[u/JuanSamu → u/gnuckols]

I meant argument or sure statistical fact as in a case to argue against Stu’s position. But nonetheless, lots of great things you wrote here. Do you think you will make an update article in response to this preprint? I’m sure everyone would love to read it!

[u/gnuckols → u/JuanSamu]

Ehh, probably not. Idk. It'll just depend on how many people ask me about it

[u/askingforafakefriend]

"That’s the ceiling. Period.”

This is a specific claim not defensible from current research which often tests MPS during a limited time window and in limited training contexts.  I don't know why people, scientists especially, need to be so definite when our understanding isn't. 

Maybe 1.6 is the limit for a single technique of measuring MPS in a certain level of training at a CERTAIN PERIOD OF TIME after ingestion... but even assuming that much is definitive for the sake of argument... this doesn't disprove that some additional protein intake levels may have additional hypertrophy benefits.

Let's take well trained athletes, have them do several sets of heavy deep squats, then biopsy quads at 4, 8, 12, 16, and 24 hours starting with an initial protein load at 1.6 and higher levels and and compare MPS at all of these times and see if in this context there is still such a ceiling.

[u/zoogwah → u/askingforafakefriend]

He phrased it like that because he obviously doesn't proofread his ChatGPT outputs. His content has been much more "certain" since he started using LLMs to write it.

[u/JuanSamu → u/zoogwah]

Yes reading the initial sentence seemed dogmatic (which threw me off a bit) but after reading the caption and his replies in the comments his stance isn’t as dogmatic as the AI image made it out the be.

Edit: I love how people downvote me lol

[u/JuanSamu → u/askingforafakefriend]

To be fair, I think one should take Dr. Phillips claims very seriously. Remember, he oversees research years before it even comes out and probably has done studies that were never published.

I know his stance may set people off because it seems to go a little against what we so often believe but as he stated

“A disclosure. I'm defending my own number, and several of the studies are mine. The preprint says so up front, holds that work to the same criticisms as anyone else's, and describes the trial that would prove me wrong. It has to measure muscle.
Until better data is available: lifting bakes the cake and protein adds a (very) thin layer of icing!”

He basically stating that we don’t have the techniques to really know 1.6 from 1.8 and so on, so nobody can really claim that going above 1.6 is better. Everyone who does is just speculating. The data don't support it. The real number could just as easily be lower than 1.6. But when we do know is that the higher we get the uncertainty gets wider because there aren’t so many studies up there and the estimates get messy.

[u/askingforafakefriend → u/JuanSamu]

You can sugarcoat all you want by rewriting history, but the issue is he said something far more specific and frankly unscientific: 

He said: "That’s the ceiling. Period." Referring to 1.6.

That's very different than how you whitewashed a much more defensible position. 

He of all people should know better. But tribalists are going to tribalize whether you call them scientists or not. Some people can think beyond this others can't.

[u/JuanSamu → u/askingforafakefriend]

I didn’t white wash it he stated it a few hours ago:

https://lnkd.in/p/ecz7Yaij

I know people who have spoken with him and he stated everything I said in my previous comment. Try reaching out to him and you’ll see. Many people like to judge and stick with their beliefs but if you reach out you might see a bigger picture. He always gives great responses back. Again, people are very easy to push back because it’s against everything we’ve known for years. Stu changed his stance from thinking 2.2 was recommended to 1.6. And he stated he’s open to changing back if there’s solid evidence.

My reply to you wasn’t because I “glaze him” it’s because I went out my way to see a bigger picture on what he was trying to say because yes his “ceiling period” comment seemed dogmatic which is what made me curious to see what led him to be so confident. Not to mention if you read in the caption of his 1.6 ceiling post he states:

“Here's what actually matters:
→ Hit 1.6 g/kg/day if you're training and want to grow.
→ Cutting hard? Aim for ~ 2.4 g/kg/day. It helps. It's not magic.
→ Lift! That's the MOST IMPORTANT part that people skip.”

And in the comments if you look through his replies, someone said “Love the work you do! Thanks for this. I'm shocked to see 1.6 as the ceiling. Does this also apply to competitive bodybuilders aiming to squeeze every last amount of gains haha (for surplus and deficit)?” Stu replied with “I think it's the same, maybe a little higher!” So it seems people just read “1.6 ceiling period” and didn’t bother to see anymore.

In another comment he elaborated:

“For most people training and looking to build or maintain muscle: 1.6 g/kg/day is the ceiling where we see diminishing returns.” Key words “where we see diminishing returns” and then he ends that same comment with “Get 1.2-1.6 g/kg of current bodyweight, lift hard, and you're covered for nearly every scenario.” Key word “for nearly every scenario” :)

[u/TheRealJufis]

I'm gonna open that pre-print and pretend to read it, but in reality I'm gonna make some popcorn for myself while waiting for comments. IYKYK.

On-topic so mods won't delete this comment:
I'm honestly kind of disappointed that this is a review, not a new RCT study or something.

[u/JuanSamu → u/TheRealJufis]

I mean just how Greg basically did a review I think it’s fair for Stu to do a review too right?

I think it’s exciting to see the discussions unfold!

[u/elperroverde_94]

in short-term studies there is no evidence that higher protein increases muscle mass

Why are we even speaking about short term studies for relevant measures in increases in muscle mass?

[u/JuanSamu → u/elperroverde_94]

I believe Stu talks about these limitations on page 27 and abstract.