4X worse than LDL | Heart Disease expert explains

We've all heard of LDL, but there's something else  that also causes heart disease and might actually  

be worse, nastier than LDL. Four times worse if  we compare them one to one, same units. I spoke  

about this with Dr. Elias Bjornson who researches  heart disease at the University of Gothenburg in  

Sweden. Here's our conversation and stay tuned  for the recap in the end. In the world of risk  

factors for cardiovascular disease there are a  couple of different risk factors but the main  

category of risk factors, or main categories,  are lipoproteins, and simply speaking you can  

categorize atherogenic lipoproteins, that is,  lipoproteins that can cause atherosclerosis, heart  

disease, into three different types. These three  different types all contain a protein called ApoB.  

So they all contain ApoB but they are slightly  different from each other. So the first one that  

people may have heard of is the LDL particle that  contains that apoB. The second one has many names  

but one name is remnant, is a remnant. It's also  called a VLDL. It's kind of like an LDL particle,  

but it contains more triglyceride and it actually  contains a little bit more cholesterol as well  

for a particle, but it's sort of like a bigger  version of an LDL. And the VLDL can actually  

become an LDL. And then you have the third type  of particle which is called lipoprotein little A,  

but we'll keep that by the side for this moment.  So when focusing on remnants versus LDL, there  

has throughout the years been some speculation  but there has never been very solid evidence  

on how atherogenic these lipoproteins are. One  hypothesis is basically that they are equally  

atherogenic for a particle. So, doesn't matter if  you have one remnant or one LDL, they both crash  

in the artery of wall and cause atheroscerosis. A  competing hypothesis has been that these remnants  

are more atherogenic per particle. Why would they  be that? Well, one idea is that since they do  

contain more cholesterol per particle, that could  be a reason. It does contain other kind of lipids  

in and on the surface of the lipoproteins as well.  So that could be more atherogenic in some other  

ways than an LDL. So, but there has never been a  clear consensus and very solid evidence because  

there has never been very good randomized control  trials where you can draw these kinds of causal  

inference on the relative atherogenicity. So  that's the backstory. So that's the background to  

try and figure out how dangerous is this particle  compared to LDL. Maybe I should stop there. That's  

sort of the backstory to the whole method, to  the whole question and then we can move into  

the methodology which is a much bigger question.  Yeah. Just to clarify just in case some people,  

most of my viewers I think have heard the basic  terminology, lipoproteins and these things  

but just in case there are some people who are  watching this who haven't heard of these things,  

can you briefly describe what a lipoprotein is?  Yeah so in our bloodstream we need to transport  

both water-soluble stuff but also fat-soluble.  So in order for us to do that, since the blood  

actually mostly contains water, fat will not  like to be in water. So, however, if you package  

fatty stuff within an envelope of something called  phospholipids, you can sort of make it into a ball  

and protect it from the aqueous solution and you  can transport it that way. So, you can think of,  

often an idea is like tennis balls. They kind  of look like tennis balls. The tennis ball  

has a surface protecting the core from the outer  environment and these particles travel throughout  

the bloodstream. They can be produced mostly by  the liver but also from the intestine. and they  

are removed by various tissues in the body but  they are primarily removed by the liver as well.  

What what's their purpose? Well there are actually  no clear consensus of exactly the purpose. There  

may be many different purposes of lipoproteins.  One purpose maybe to transport fat-soluble  

vitamins. Other purposes may be to transport  cholesterol itself. Although that may or may  

not be the primary purpose of lipoproteins. One  purpose could be for the liver to actually get rid  

of excess lipids, otherwise you may develop fatty  liver and so on, may end up with trouble doing  

that. Well, if you can't produce lipoproteins, the  liver may be sick by that, so they are produced,  

they get into the blood, they get cleared somehow.  However, they can also crash into the artery wall  

and produce what we call plaques which can then  lead to cardiovascular disease. Got it. Yeah. So,  

they're like these vehicles to transport fats,  lipids and fat and the types of vitamins for  

example that are fat soluble. all these things  that would clump up in the blood because the  

blood is aqueous, these serve as vehicles like a  submarine or a car or whatever vehicle you have  

in mind, an Uber that transports these fats back  and forth in the bloodstream. And so these are  

the lipoproteins. And then you talked about the  different classes. people might be wondering about  

HDLs which are also types of lipoproteins. We  left those out because we're focusing on the ones  

that are atherogenic. So the ones that cause this  atherosclerosis type of heart disease and coronary  

disease but HDLs will be the other kind of big  family and then within these the atherogenic  

ones that are the apoB carrying lipoproteins as  you explained, we then have these categories,  

we have LPA which we've talked about in other  videos, we have the LDLs and then we have these  

this big family of sometimes called triglyceride  rich lipoproteins but yeah there's all these,  

these remnants and all this stuff. Do you guys  normally just call them, what do you guys call  

them in the lab or what's like the quick name? I  usually call them remnants. That's my remnants is  

remnants is the favorite to go to because it's  sort of easy to say. It's but technically it's  

more technically precise to call them triglyceride  rich lipoprotein. So, TRLs, we say sometimes you  

can think of LDLs and TRLs that if you want to an  abbreviation, that's the go-to abbreviation for  

me. If you want just say it out loud, it's easier  to say remnants instead of TRLs. So, I usually say  

that. Yeah. For some reason, DLDDLS hasn't caught  on. so not many people refer to to them as DLDDLs,  

but that's right. that that if you like an  abbreviation that's a good abbreviation as well  

right when I think of TRLs or or TGRLs or however  you want to say triglyceride rich lipoproteins  

this whole family in my mind it includes the VLDLS  it includes the IDLs as well and but let me know  

if that's not correct the the chylomicrons I think  you mentioned that briefly that come from the  

intestine those are and then the remnants we're  basically talking about when those guys start  

delivering ing their cargo, their triglycerides  to different tissues and they become smaller and  

smaller. They're still technically VLDLDLs or  kyomicrons, but sometimes we start calling them  

VLDL remnants or kyomicron remnants to distinguish  from the original big, the OG particle with all  

the cargo. is that correct? Yeah, that's correct.  So you mentioned IDL as well, which is good. You  

you can think of it just instead of categorizing  you can think of it as just a continuous  

uh continuous distribution of particle size. So  the liver and the intestine they tend to output  

just when it's a newly produced particle then it's  not a remnant then it's just the the pure newborn  

particle that's a very fatty lots of triglycerides  in in that particle then uh lipases begin to  

metabolize that those triglycerides and then it  starts to shrink. So then technically the first  

triglyceride that is hydrayed from the lipolyized  from the particle then it becomes a remnant  

because it's not the OG the original particle it's  a shrunken version of of the OG particle. So then  

it shrinks down. Uh if you classify it density, it  will be a VLDL technically for quite some time and  

then for a kind of a brief period of time it will  become an intermediate density lipoprotein IDL as  

you mentioned before it becomes you could  say the ultimate remnant the LDL particle.  

M that's just a continuous lipolylis step and then  it shrinks shrinks down shrinks down and then it  

ultimately becomes an alium right and people might  be wondering because yeah it's a it's a good point  

that this is somewhat arbitrary because it's a  continuum in practice the these divisions are  

somewhat artificial but there is a difference in  terms of composition as you said in terms of how  

much triglyceride and how much cholesterol is  in there there's also a difference in terms of  

the proteins on the surface, right? So they there  are some differences physiologically between these  

things. It's not just a complete continuum  of the same thing bigger and smaller. No,  

you're right. So there there are distinct even  though something continuously changes sometime  

at some point it changes enough for it to become a  distinctly different type of particle. And one way  

to also kind of uh differentiate that I use in my  mind is that uh what is the clearance pathway if  

if it can be cleared if it can be lipol lipolyized  for example if it contains enough uh triglycerides  

for it to be a good substrate for LPL lipoprotein  libase then it's a triglyceride rich lipoprotein  

right because LP lipoprotein lip basease likes  that as a substrate. When enough trigger has uh  

been removed, LPL doesn't like it anymore. Then it  needs to be then it's a on the other hand a good  

substrate for the LDL receptor. then it becomes ah  now the LL receptor try become it shrinks enough  

for it to be recognized and then it can be removed  that way. So it's the cat catabolism the catabolic  

pathways differ depending on the size and the  lipid composition. Yeah that makes sense. So the  

yeah the so the question you guys were attacking  was this question of this family of of TRLs or  

remnants however people want to call them all are  they just as nasty as LDL are they less nasty are  

they more are they nastier and there and it was  kind of controversial some people thought they  

were equally atherogenic and some people thought  there might be differences there and so how did  

you guys go about testing this yeah so just  as a as a as a background hypothe hypothesis.  

I don't believe anyone thought that the remnant  or the fragrin was not agogenic. I I do believe  

that everyone thought that it was agogenic at  some degree. So therefore, hence maybe equally  

as an LDL or maybe even higher. So those were the  two plausible options before before our research.  

so how did we what what did we do to answer this  question? Well, we used a methodological approach  

called mandelian randomization. now that's a  big word and it's not easy to grasp just the  

first time you hear it. but you can you can make  actually um a comparison to a randomized control  

trial. So in a randomized control trial, you  randomize people to a drug or no drug or maybe  

one drug versus another drug, something  like that. And everything else between the  

subjects is just randomly there are no systematic  differences between the groups. So if you do that,  

you can actually say if something changed in that  group that I gave it that drug, it's likely that  

the that was actually caused by the drug. Now  there's an analogy in mandelian randomization  

and that is that some people inherit genetic  varants. back in the days we call them mutations.  

We don't call them that anymore. uh we call them  snips, single nucleotide polymorphisms or genetic  

variants. So maybe some people just by pure chance  happen to have a genetic variant that makes them  

have lower LDL cholesterol for example or higher  LDL cholesterol or lower remnant cholesterol or  

higher remnant cholesterol. So you see where I'm  getting at. So we specifically looked for genetic  

varants that affected either LDLs up or down or  remnants up or down. And we we used uh uh the  

UK bio bank data for this which is roughly half a  million uh British uh citizens that were genotyped  

and followed for 12 13 14 15 years at this point.  so what you can do is that you can look for uh  

genetic variants that either affect as I said LDLs  or RAMs and then you can classify. So basically  

we found over a thousand of these genetic  variants that had some effect on either LDL  

and or remnants. But what we then tried to do was  to categorize the genetic variants into those that  

predominantly or almost exclusively affected LDL.  We try to look for if you keep everything constant  

but you move LDL or vice versa the other type of  snip category genetic variant that changed remnant  

levels without affecting LDL. So in practice this  is quite difficult because many snips change them  

both a little bit in in between. So they have had  this sort of uh both both uh remnant and and LDL  

effect but there is enough variation it turns out  in nature. So there does exist genetic varants  

that predominantly affects remnants and those  that predominantly affect aliens. And then you can  

utilize this information actually to uh to  work out mathematically how risky is is it if I  

uh move LDL up or down or how risky is it if I  move remnants up or down? Um, so specifically what  

we do is um I I may or may have not mentioned it  in the in our in our uh little lipoprotein school  

here but um all both LDLs and remnants contain  exactly one copy of this protein called apple B.  

So LDL have one apple B rand have one exactly  apple B. So now if we if we now have these genetic  

variants we can actually relate if you change LDL  apple B so LDL particle number by a fixed amount  

what change in cardiovascular risk do you get? We  can answer that question and then of course we can  

answer the question if you use the other types of  snips that predominantly affect remnants or the  

same given increase now in remnant apple. How does  that relate to cardiovascular risk? Uh change in  

cardiovascular risk and is is that delta in risk  the same for LDL or for randoms and the take-h  

home message is that it does not appear to be  same. So for the same unit increase in Apple B you  

get a certain risk uh increased by LDL but you get  maybe a roughly a three or four fold higher risk  

increase if you change remnant particle number  the same amount. Uh so hence our sort of take-h  

home message that remnants are probably around  around fourfold as agenic per individual particles  

as LDL to be. Mhm. uh as my understanding is  you guys looked at uh LDL cholesterol and um  

triglyceride rich lipoprotein cholesterol and then  instead of looking directly at the particle number  

that's I think because the UK bio bank does  not have the metric of measuring lipoproteins  

uh is that correct or not and if so how do you how  do you get from the lipids to the lipoproteins?  

Yeah, that's a very very good question and this  question is very uh difficult to explain if you're  

not very versed into into the nitty-gritty of  this mandelian randomization methodology. But  

first what we can do and what we did do is  that to relate the risk change in terms of  

cholesterol units as you say. So we can quantify  LDL cholesterol in UK bio bank and we can quantify  

remnant cholesterol in UK bio bank. So what you  can uh start by doing then forget about particle  

number now we're just thinking about cholesterol  content. So you can do exactly the same one unit  

for example 1 mill mole per per liter of LDL  cholesterol how does that uh causally affect uh  

risk of cardiovascular events are the same 1 mill  per liter unit uh increase in remnant cholesterol  

how does that relate to risk and the answer is  that in that type of analysis if you do it per  

cholester we get a roughly threefold something two  and a half to three and a half fold um higher risk  

or one unit remnant cholesterol than one unit LDL  cholesterol. So but this is not per particle now  

but uh as you say we those measures are actually  measured in UK bio bank. we can quantify them and  

and relate them to the to risk. And if we do find  that remnant cholesterol per uh unit cholesterol  

is higher then it must mean that per also per  number of particle it will be higher simply  

because remnants are actually as I mentioned  before not cholesterol they actually contain more  

cholesterol per particle. So if you think about  that for a second. So if we have one particle  

that contains more cholesterol per particle and  another particle contains less cholesterol per  

particle and you relate cholesterol to risk and  you get a higher per cholesterol unit for remnants  

then you can definitely infer that. Now you can  say okay then then the the factor that we get  

which is maybe a three-fold it must be at least  threefold higher per particle uh since it contains  

more cholesterol per particle. So I I will let  that sink in for for a second because then we  

come to the the second step of doing it per number  of particles and that's another uh another type of  

analysis that that we employed then. Mhm. So do  you want me to go into that or should we linger  

on the per cholesterol results first? I think the  the main question for me and I imagine for viewers  

who are following along and have seen some of my  content previously and are kind of familiar with  

the basics here is that uh when we see a change  in cholesterol level, yes, it could reflect a  

change in particle number, but it could also just  reflect particles that are richer or or poorer in  

cholesterol content. So that if we see an increase  in cholesterol, it could just be that the particle  

has become richer in cholesterol or a mix of both.  So yeah, I think the general question is how do we  

how do we get from the lipids to the the particle  number? I understand that there's a level of  

uncertainty always if we don't have a measure of  the particle number. Um but how do you u reconcile  

that and how do you think of of that issue in  terms of this this leap? Yeah. So mandelian  

randomization analysis can only estimate the  average particle. it cannot say anything about uh  

if if a particle is more or less cholesterol rich.  So this is an important point. Our results is only  

relating an average type of remnant particle to an  average type of LDL particle. We say nothing about  

what happens if the cholesterol to apple ratio  changes within the particle. But that's just by  

the very nature of of the medal randomization  methodology. We deal with population averages.  

We can say how's an average particle relate to  risk. We don't say anything about then it can  

absolutely as you say be that there may be more or  less risky types of remnants. There may be more or  

less risky types of LDLs, but an average remnant,  at least uh according to our results, is more  

uh astrogenic than an LD than an average LDL. Mhm.  Um yeah. Yeah. Yeah. So uh the the regarding your  

other first question, how can we relate particle  number something that is actually not measured in  

UK bio bank to to risk? Well, first of all there  is actually uh uh measured particle uh numbers and  

we have that done that analysis as well uh using  NMR uh NMR data. So there is available NMR data  

in UK bio bank. So you can get a measured VLDL  particle number and you can relate VLDL P to LDLP  

and you can redo the same as medular randomization  analysis as I just said uh before but for  

cholesterol. So we of course did that as well but  we didn't publish that but we got the expected  

results namely that per per NMR estimated particle  remnants are several fold more autotogenic oh  

interesting but then there's a third version  methodology you can triangulate even further  

and that is when you when you find a genetic  variant that changes LDL cholesterol. So let's  

say we we find a genetic variant that only affects  LDL cholesterol and nothing else. Then we can say  

aha. So it doesn't change remnants. It doesn't  change alpha little A. It only changes LDL.

Then we can actually quantify how much is apple  B plasma apple B changed by that very genetic  

variant. Mhm. So that delta in plasma apple B must  be LDL apple B because nothing else has changed.

Probably probably I'm following the logic.  Yeah, I think I think it's likely that that  

the changes mainly coming from LDL unless  it's a more complicated scenario where  

uh you had a you had a in the in the remnants uh  the the number of remnants changed in the same  

proportion or something like that to the LDLs. Um  yeah, it' just be a more complicated uh scenario,  

but I I understand what you're saying. It's the  most likely cases that only LDLs have changed.  

Yeah. Yeah, I mean as you say there there  is a very you can make it a very complicated  

uh story up as or why that delta apple B  does not reflect LDL apple B uh but then  

it must involve that that genetic variant also  affects the composition uh of maybe LDL and or  

remnants so in fact it doesn't show any effect on  remnant cholesterol but maybe it actually changes  

remnant cholesterol to apple B ratio or  something like that, right? But then that has  

to be systematically true for several hundreds of  snakes, right? Which is extremely unlikely. So the  

the most you know or gams raer type of explanation  is that those several hundred of snips that  

predominantly affect LDL cholesterol. If you look  at the apple change there that will in average  

uh reflect an LDL apple B change. And then you do  the same with snips that predominantly affect the  

remnants. uh that change in apple B uh it probably  reflects remnant apple B change and then you  

uh relate that delta apple B to cardiovascular  risk compare that to the LDL apple B uh to  

cardiovascular risk and then in the context of  the NMR based analysis and the cholesterol-based  

analysis and we did did several other types of  sensitivity analysis using polygenic scores as  

well. All of those analysis paint exactly the same  uh picture and if you get uh if you do that that  

let the apple be based analysis you get a roughly  a four-fold uh difference in agenic potential per  

particle per apple. So ju just to summarize this  to make make sure that I understand in the main  

analysis that was published you did have you did  have the apo B measurement uh right not just you  

had the lipids and the Apo B just not the complete  NMR panel and so you're looking at these changes  

of the lipids and you know how much Apo B is  changing and you're taking the average basically  

uh if one snip for example changes LDL cholesterol  uh let's Say to make it simple all let's say once  

in one snip all of the changes in LDL cholesterol  and none in VLDL in in the remnant cholesterol and  

then you have a a certain change in Apo B you're  assuming for the purposes of the analysis that  

they all the change in Apo B is coming from the  change in LDL particles and that amount is going  

to be then using the LDL cholesterol change and  vice versa. uh and then in proportion if you  

have change of both lipids you're assuming that  that the same proportion is going to apply to the  

April B change. Uh but then but you also then have  this other analysis that you mentioned that was  

not published uh that is seems more seems like a  a good confirmation step where you look at actual  

NMR data at actual measurements of particles  and there you get rid of this this margin of  

error of the assumption of the lipids to to the  particle number and there it sounds like you you  

got a roughly the same uh result. Yeah, that's  true. So the I think the the reason why we didn't  

publish the NMR data results was that uh not to  overload the paper and uh we did that analysis to  

to really do all the diligence we can to be very  confident in the results before we publish because  

uh we know that these results may appear to be um  surprising or controversial for some people maybe  

not for others. Mhm. Uh so we we triangulated  using different uh different assumptions,  

different techniques. Um we used the polygenic  risk score methodology as well which is  

uh separate from the the main analysis. So we  we do we did all the all the type of sensitivity  

analysis that we could do over a period of  maybe 18 or 24 months something like that.  

We tried really really hard to to to kill kill  the results and uh uh but but no matter how we  

did the analysis the results came out pretty much  the same. If we used NMR it came out the same. If  

you use per cholesterol it came out as expected.  If you used perapp it came out as expected. If  

you use polygenic risk score approach it came  out as expected. actually which we also didn't  

publish was that if we used observation purely  observational data not median randomization data  

we get exactly the same results as well. Uh so  then we sort of draw drew a line that we said that  

uh when you get these kind of consistent results  we have to publish and we we just have to make  

sure that we do all the as I said all the due  diligence that we can given the data that is  

available. Yeah. Uh, no, I think it's really  interesting and and it's an interesting also  

exchange with uh with Al with Alan Sniderman and  the the piece that he wrote kind of uh kind of  

giving a counterpoint of he he's I think he's  a little bit skeptical uh of this effect of the  

of the remnants being substantially more  ethoggenic than LDL's. And I think he he  

presents some interesting counterpoints,  some some interesting counterarguments.  

uh and I and then I think there's he also  puts forward this idea that maybe this is  

true but it's for a percentage of people that is  relatively small or for very specific populations  

and so maybe that explains all the observations  why you guys see this reproducibly and then it  

doesn't match other findings that we have. He's  he's trying to reconcile everything which I I  

think is is what we have to do. Um so I don't  know if you I I I agree. Yeah, I agree. I mean  

uh I we need to uh not use o only our evidence.  We need to use all the types of evidence that  

is available in the literature so far to try and  triangulate and come up with a plausible scenario.  

What what I will point out is that um I personally  do not believe that our results uh will will  

change clinical practice you know substantially or  or um simply because of the reason that remnants  

are much less abundant than LDLs. So yes,  they may be more athogenic per per particle,  

but they are literally 10 times as common in the  in the bloodstream for an average person. So for  

every 100 particles uh only around 10 of them  are remnants. So it will not in terms of risk and  

clinical practice that's a different story. Uh and  you shouldn't take our results and now say that oh  

now all the risk is on remnants no that's not the  case still a ma major a majority of all risk is on  

on the LDL particle because it's vastly much more  abundant I think this is a key the key point uh  

for people to understand that one thing is risk  per particle so for the same number of particles  

your data indicates whether it's a specific  context of of a specific population or not is  

is up for grabs. But um you guys are are showing  that in this context at least the same number of  

particles of remnants or triglyceride rich  lipoproteins is riskier than the same number  

of LDLs but in the vast majority of people they  have a lot more LDLs present in the blood. So  

it would still be the the total amount of risk  that's coming from L the LDL population is still  

much higher than the total amount of risk coming  from the um the remnant population. Um but then it  

gets interesting depending on the exact individual  right if people if this balance changes and uh in  

specific populations uh I don't know if what are  your thoughts like people with diabetes or people  

on statins where do you think this becomes more  relevant? Yeah. So uh most people on on that that  

have diabetes they may also have hypertralmia. So  particularly if there is a population I wouldn't  

state yes diabetes but more as a proxy for the  hyper trialmia. So I would say that people who  

have maybe are in the top uh 10th percentile uh  or so the top n 90th percentile or higher in the  

population uh maybe they have triglyceride level.  So if they have a plasma transistor level of maybe  

3 mill per liter something like that or above then  it starts to become our the the inference from our  

results is that for those levels you start to  really you can't ignore the remnant risk then  

it becomes a major player in all your risk. So as  an example, let's say um let's say for a top top n  

for a 90th percentile plus individual who have who  has hypertrigusmia maybe 20% of all particles are  

remnants uh compared to LDL. Let's forget about  L for for a second. So, so you let let's just  

look at some numbers. So, let's say let's say you  have 100 particles uh 20 of those are triglyceride  

rich lipoproteins and 80 are LDLs. So, if let's  take our headline results. So, try proteins are  

four times as agroenic. Then we can multiply that  20 20 particles by four. Then we have 80 sort of  

risk equivalent units. And how many LDLs did we  have? Well, yes, we had also 80. So then we're  

talking risk equivalent basically 5050 of your  risk may be uh carried by remnants versus LDLs.  

But but again that's for that's a relatively  uncommon individual. Yes it may be one or one  

in 10 or higher. Uh so it's not a non-issue.  It is important for that population. Uh whereas  

for the general population it's less of an issue  that you really have to clinically look at. Uh so  

uh you also mentioned uh if you're if you're let's  say type two diabetic taking a statin. Yes, it  

is true that um let's say you're a hyper trialmic  individual taking a statin, you have reduced your  

LDL particle number quite a bit, but maybe you  still have elevated remnants. Not that's uncommon  

in practice. Then it may be the case that maybe  60 70% of your agenic risk is carried by remnants.  

uh it mind you that that is simply also a result  for the lowering of the LDL. So you're taking down  

the LDL risk what risk is remaining uh then  is disproportionately or kind of relatively  

looks relatively high in terms of um uh for the  remnants. However, if you are really interested  

in reducing your total risk, this sort of  residual risk could be a major the remnants  

could be a major source of this residual risk in  this context. So, it's you should certainly not  

neglect that and every means necessary to reduce  rem proteins will uh certainly be helpful in that  

context. One little caveat though is that many  people do not realize that statins also lowers  

remnant cholesterol. So the the benefit you get  from statins is not only isolated to LDLs. So  

let's say for example you you lower you take a  statin that lowers your LDL cholesterol by 50%.

that actually also typically lowers your  remnant cholesterol by maybe 25%. Something  

like that. And so statins themselves also do uh  contribute a little bit to reducing your residual  

remnant related risk. So that it's just it's just  something that many people forget. But uh when um  

um when it's a little bit like um ECSK9 inhibitors  that has has this benefit of reducing alkal as  

well maybe 20 30% something like that has has this  sort of extra boost by reducing grounds a little  

bit and you should neglect that. Yeah. So these  are these are important points and and just to  

reiterate um so statins will reduce all of these  apo lipoproteins but they are they are better at  

reducing the LDL fraction than the than the the  VLDLDL fraction or the the remnant fraction. So,  

uh, what we what we're talking about when residual  risk is people on a statin have brought their LDLs  

down, so they're not at significant risk from  that anymore, but sometimes these remnants are  

still higher because the statins aren't aren't  as good as bringing them down. And so, there's  

this remaining cardiovascular risk that hasn't  been addressed. And a portion of that is coming  

from these these particles. Uh and so that's  that's a context where well where where this  

um this factor of the increased ethogenicity of  uh of the remnants comes into play because yeah  

you you have these particles that remained and  it seems like they're a minority but they are  

also nastier particle for particle so um they  become more more of a of a big deal. Um yes I  

I should mention an analogy in that uh sense is  that let's say you have high alkalate A and you  

take a statin or a PC inhibitor you will reduce  LDL a lot and statins a little bit or remnants a  

little bit in addition maybe a little bit extra  LPA but those risk uh bars now you shrunk LDL a  

lot but what is still remaining if you have high  LP little A is the alkalith a related risk. So  

your residual risk if you're have high alkala  will be uh in large part due to alkala then so  

and just to put these numbers a little bit further  into context that maybe a typical person has  

u somewhere around 200 nanom per liter or 150  to 200 nanom per liter of remnant particles.  

And according to our research we have done we  have applied the same methodologies to L as  

well. And we what we can say is that the genetic  evidence seem to support the role that the remnant  

and alle are roughly equally aogenic. So now  you're in a situation where you have 200 maybe  

nanom per liter of remnants and then maybe you  have 200 nanom per liter of alkalith as well.  

If you're that kind of person, uh those two two  will be two big risk contributors, especially if  

you have lowered LDL uh quite a lot. Maybe you're  on a PC9 inhibitor or something like that. So,  

it's all it's all just a numbers game. How um how  many LDLs do you have times how astrogenic they  

are? How many remnants do you have times how  estrogenic they are? How many healthy little  

A's do you have times how astrogenic they are?  And depending on uh what person you have, those  

numbers came may come out differently. But having  said that, LDL for most people is the absolute  

dominant risk factor. Yeah. I guess when when  these things become more crystallized and more  

uh demonstrated and and accepted across the board,  uh when we have specific numbers that everybody  

agrees with, I mean, people will come up with  um calculators where you just enter all these  

numbers and it gives you your your risk, which is  a pretty simple formula, but it's still kind of  

controversial. What's the the exact contribution  of the remnants and all the and all this stuff.  

Um and so on that on that point um had a couple  questions here. One is just to get an idea of  

the prevalence of this. Do you know in a western  population let's say typical like a US population  

or something like that because it's a typically a  pretty sick population. What's the prevalence of  

uh of people who would have uh the this this  concentration of remnants that's high enough  

that's um um you know causing a substantial  risk coming from the remnants? Well, I guess  

that that's uh depends on where you draw the the  line of substantial risk. So, but I would say  

um I would say that um okay, I I I'll just take  you the typical the typical western person first.  

So uh the typical person just a medium person  maybe has as I said maybe 150 to 200 nanom per  

liter of remnants so so let's let's say 150 so  150 and that typical person maybe has 10 times  

as many LDLs of 1,500. So 1,500 150. All right.  And the median person has very low elk A. So you  

can almost ignore L in that context. So if our  genetically predicted results are correct then  

the implication for a median person is that maybe  25% 30% of your total Applebee risk uh is by is  

carried by remnants and you know the rest 75 70  to 75% is carried by LDL. Mhm. Now, where would  

you say that remnants are a substantial risk  contributor? Maybe you would draw the line at  

50/50. So, if remnants contribute half of your  entire risk, I would say that's a substantial  

risk contributor. And where do you get that? Well,  you get that typically if you have a I would say a  

plasma triglyceride level of three millol per  liter or above then my guess and this applies  

to UK by bank. So maybe one in 10 people have  that kind of level. M so the average Joe maybe  

a quarter of the risk would be on remnants quarter  to a third uh the one in 10 individual maybe has  

half of of of their risk on remnants uh I remember  from the from the study and I think we talked  

about this on Twitter that there seemed to be sort  of a cut off but I don't know if I'm remembering  

this correctly that it was about 20 to 30% of the  total uh remnants had to be no 20 to 30% of APOB  

had to be remnants for the risk of remnants to be  measurable or significant. Is that correct? Yeah.  

Yeah. You're you're remembering correctly. So what  what we did in our this is a little bit difficult  

to explain but what we did in our mandela  randomization analysis is to quantify the risk  

uh depending on how many percent of now here  comes another difficult term nonHDL cholesterol  

is uh constituted by remnant cholesterol so I  will just what the heck is non HDL cholesterol  

Non HDL cholesterol is simply called LDL  cholesterol plus remnant cholesterol. So a typical  

person maybe has 15% of of the non-HDL cholesterol  being renant cholesterol and the rest 85% being  

uh LDL cholesterol. uh but if you in our mandelian  randomization analysis we we ch we chose genetic  

variants that change this uh risk this uh  sorry cholesterol uh ratio within nonHDL so  

for a given increase in nonHDL if it was uh 10%  uh of the nonHDL was remnant cholesterol 15 20 25  

etc. And we actually found genetic variance that  per one unit increase in non-HDL cholesterol,  

twothirds of it was remnant cholesterol. So that  is a strong genetic variant that not only affect  

remnants but almost only affect romance. And then  on the other end of the spectrum, we found genetic  

variance that of the non-HDL cholesterol  change 95% was LDL cholesterol. So only 5%  

uh was uh remnant cholesterol that gave us this  dynamic range enough variation that we needed for  

our analysis to quantify the relative aogenicity.  Uh and if you plot if you plot the risk uh per the  

same given increase in particle number depending  on what percentage you have on by uh remnant  

cholesterol as a percentage of nonHDL cholesterol  you can sort of see a breaking point uh at 25  

something% it's a little bit fussy but uh Then  um Alice Sniderman in his uh in his uh editorial  

rightly pointed out that not many individuals are  above this breaking point. So the point being that  

therefore non-HDL cholesterol is a good enough  measure. Uh not many people have like 50% of  

their nonHDL cholesterol as remnant cholesterol.  That almost never happens. And he's writing that  

he's writing pointing out that but the reason why  we did this graph is is to basically fundamentally  

try to quantify the particleity and then it's a  totally separate question as I mentioned before  

to to try and infer the clinical utility of that  and Alan Sniderman is right and I've just said it  

here that most people are pretty similar in their  nonHDL cholesterol LDL to remnant cholesterol  

ratio. So yes, it is true even though remmons are  morogenic if everybody has the same then you you  

can just if everyone by definition has had the  same ratio you can just measure LDL cholesterol  

and that would be a great risk marker. So it  um that however I would say that this does not  

mean that if you are below this this uh breaking  point where we saw clearly that uh that uh the  

the particleity really rose uh then then remnants  will not contribute to your risk at all. That's  

not actually the inference you can draw from that  graph. So, uh, RAM will contribute to risk at any  

level above zero and then it's just a matter of  defining what's high enough. What is a substantial  

risk contribution? So, okay. So, it it's not zero.  It's not all or nothing. Uh, so what's the the 20  

to that that 20 to 30% uh cut off? What does that  determine? Is it like a jump in the ethogenicity?  

Well, it's just that if you um um the statistical  preision or power uh that we had to detect the  

difference uh uh is let's say if you if we find  a genetic variant that by 30% or more affects  

run cholesterol then we can stay with uh that  with statistical uh confidence that ah it that's  

that infers a higher risk. Okay, we're sure about  that. And luckily we did find genetic variants but  

many hundreds of them that were like 35 40 50 55  even 68% uh risk. So we had plenty of statistical  

power to determine the isogenicity if there was  the difference. If there wasn't a difference,  

you should have just uh expected a flat line.  So regardless of your composition of nonHDL,  

you should get the same risk. There shouldn't be  a gradient. There just should be a flat line like  

that. Yeah. So under 25 to 30% uh you couldn't  pick up a statistically significant increase.  

So it's it might still still be there or not. We  don't know. TBD, right? Yeah. Yeah. So if we if it  

turned out that we there were no genetic variants  that affect change the ratio uh as substantially  

as as uh as as they turn out to do. So let's  say you could we only have genetic varants that  

change the ratio from 20 to or let's say from 18  to 22%. Mhm. Something like that. That would not  

be enough variance for us to make an inference  about the particle estrogenicity. Then we could  

just say ah we give up we can't we can't infer  this. uh but uh luckily there was this range  

uh and that allowed us to make the quantification  with good statistical power. But to reiterate,  

you shouldn't draw the conclusion that therefore  uh that has huge clinical implications. That's not  

the inference. Mhm. The inference is that this  has clinical implications only if people differ  

in their composition of non-HDL. So let's  say remnants were 100 times more asoggenic  

but everyone just had a very very low level of  remnants and no one had high then it would just  

simply be an academic interesting question but  it wouldn't be a practically relevant question.  

uh the the the remnant cholesterol there is a  simple way to to calculate but I don't know how  

accurate that is but if you just take total  cholesterol minus LDL cholesterol minus HDL  

cholesterol that gives you the remnant cholesterol  is that right is that accurate yeah uh but there's  

a big caveat so if you have calculated LDL  cholesterol for example by the freedom formula  

then mathematically if you do that calculation as  you just said mathematically you will calculate  

triglycerides. So the the result you get when you  do that right will be a onetoone correlation with  

plasma triglycerides. Mhm. But if you if you use  any method that directly measures LDL cholesterol  

you can do that calculation and that is indeed uh  what we found in in UK bio bank. So in UK bio bank  

they had a direct measure of LDL cholesterol. So  we can actually quantify quantify by calculation  

the the remnant cholesterol. Mhm. So uh this is  a big u I mean this is a big question now if if  

remnants are are remnants worthwhile quantifying  separately if so what method should you use right  

so should should you use a an essay uh for it  there are I would say there are assays but they  

there is no very cheap easy to use essay that  is widely accepted yet. So I would say that  

that method method that if you have quantified  LDL cholesterol directly and not calculated  

uh you can absolutely use that calculation uh  to to calculate gon cholesterol that will work  

otherwise you're stuck with plasma triglycerides.  Mhm. So if somebody does have the direct LDL and  

uh do you think it's it's this is worth  calculating uh how should people think  

about this in general out there? Uh should they  look at this number? What are what number should  

be what range should they be shooting for? What  can they do about it like in actionable terms?

Well, depends on how pragmatic you want to be. Um,  

I mean, if you only have a standard lipid  panel, let's say we live in that world.

I would be happy to quantify risk.  I would look at non-HDL cholesterol.  

But I will however make a caveat that if you have  very high triglyceride levels let's say it's well  

any level I I want my trigger size below one so  below one that's a or the lower the better but  

below one that's that that's good many people are  not below one many people are between one and two  

maybe 1.5 1.6 6 1.72 something like that then it's  just a matter of degree. If you're getting up to  

2 and a half three then this I would say that the  nonHDL cholesterol as a risk measure will start to  

break down a little bit. Uh so yes look at nonHDL  cholesterol from the standard lipid panel. Keep  

a little extra eye on the triglyceride number as  well. If it's super high, then non HDL cholesterol  

will not tell you the whole risk story. Mhm. In  other words, if your triglyceride is not mega  

high, the non-HDL cholesterol, which is a kind  of a the poor man's April B, right? It's kind  

of a a reflection of April B. Um, so the non HDL  cholesterol is going to give you a pretty good  

readout of risk. If your if your triglycerides are  extremely high then that indicates and three mill  

mole per liter is what like probably like 250  milligrams per deciliter something like that.  

Yeah. So it's Yeah. 250. Yeah. Something like  that. 250 275. Yeah. Yeah. So if somebody has  

like super high triglycerides uh that indicates  that the number of those remnants is abnormally  

high as well. And so that total risk might be even  higher than the non-HDL cholesterol would suggest  

because the composition of the nonHDL cholesterol  is abnormally enriched in remnants. Is that fair?  

Exactly. Yeah. Okay. That's uh that's exactly  right. And uh you also mentioned that uh non  

HDL cholesterol would be the poor man's apple B  measure and this is a whole separate discussion  

uh but I you would believe from from do from our  research that I would favor nonHDL cholesterol  

actually between if the choice is apple B or  nonHDL cholesterol you you can't measure anything  

else you only have apple B or only managed as like  as I mentioned in in the in the start of of this  

presentation or talk we remnants are actually more  cholesterol enriched per particle. So they have  

more cholesterol per particle meaning per apple  be than LDLs do. that will make that will favor  

nonHDL cholesterol as a better risk measure than  apple B because it will more closely approximate  

uh the risk compared by remnants but let let's  say a simple example let's say let's say remnants  

were four times as cholesterol enriched compared  to an LDL and they are four times more aoggenic  

Then the cholesterol measure will capture all the  risk because it's four times more cholesterol,  

four times more risk. Then per cholesterol it  will be the same risk, right? So then nonHDL  

is a great measure. We don't quite live in  that world. So remnants are not four times  

more cholesterol enriched. But comparing measuring  only the apple be content to comparing measure the  

cholesterol content then the cholesterol content  will reflect risk better than apple. Mhm. However,  

so if that was the only factor on the table,  you would choose nonHDL cholesterol over apple,  

which is surprising. But that's not the only  fact on the table actually. So it turns out  

that the cholesterol to apple B ratio  of LDL particles when when that is off  

uh the risk tends to track with the number of LDLs  rather than the cholesterol content of the LDLs.  

So if that is true, which it does seem  to be definitely from the literature and  

uh from my own investigations in in UK bio bank  that will favor Apple B as a risk measure. So you  

have these opposing forces. One force saying ah  remnants more esogenic then ah cholesterol content  

uh then then that should favor non-HDL. On the  other hand you have the discordance type of effect  

uh which will favor Apple B as a risk measure.  Where do we come out in the end? My best guess  

so far is that I would actually favor in a perfect  world, I would favor Apple B as the risk measure  

because I believe this discordant type of effect  is actually stronger to rule to to rule over the  

effect of the um nonHDL cholesterol composition  thing. However, I do think it's almost a wash. U  

both of these measures are good risk measures for  a majority of the population. Yeah, it's probably  

but but as as someone as if anyone is first in L A  they will know that ah if you only measure apple B  

and you have a high alp [Music] is not many many  particles. So then you will uh miss risk from the  

apple measure if you only measure apple without  measuring alp right. So what's the best version?  

Well, of course, measure everything. So measure L+  A, measure apple B, measure non HDL cholesterol,  

measure remnant cholesterol, uh preferably find a  method that measures remnant apple B if it's NMR  

or some other method. Uh but we also unfortunately  have a limited brain capacity to take all of these  

measures into account simultaneously. Hence a a  kind of a simple message to boil down is if you  

have apple b that's a that's a good measure. If  you have non HDL cluster that's also a pretty good  

measure. Yeah, they're they're both pretty close  and I I suspect you will depend on the population  

on the specifics of the population you might see  and I think we see that in some analyses Ap comes  

out on top and then others non HDL cholesterol  comes out a little bit on top. Um but yeah,  

I try to look at both and try to keep them both  in the healthy range and that way uh I'm I'm safe,  

I guess. Um yeah, add one last thing uh because I  think Allan makes really interesting points in the  

in his uh commentary in his his editorial. One  thing that he he points out is that the trials  

uh looking at fibrates for example uh so for  example if we look at prominent which is one of  

the most recent ones uh they use the fibrate that  lowers triglycerides by a lot by like 30%. and  

lowers VLDLDL cholesterol. But then Apo B there  wasn't much difference. I think it was an increase  

of 5%. And risk mace no significant change. So  he's arguing that that argues against this this  

uh increased aogenicity of um of remnants because  presumably these fibbrates are reducing remnants  

but they're increasing LDL. So if if remnants were  that much that much nastier we should see lower  

risk. What's your what are your thoughts on that?  Yeah. Yeah. Uh this a excellent question Gil and  

uh basically the short version is that what  happened what the hell happened in prominence and  

uh as you say uh LDL uh remnant cholesterol was  reduced by not 30% but 26%. Okay. So depending on  

how you measure, oh sorry, triglyceride levels  were reduced by 26%. Remnant cholesterol was  

reduced by roughly 18%. Okay. Okay. So that's  that's good. That's looks good. Uh on the other  

hand, we saw an increase in LDL cholesterol by  12%. [Music] And an accompanying in increase in  

apple B plasma apple B by 5%. So what has happened  in prominent? Well, if you do the maths, uh for  

every remnant particle you reduce in prominent,  you roughly gain back two or even three LDL  

particles. Oh, I see. So, okay. But that's just  for every remnant particle you reduce Uhhuh. you  

get two or three back, right? So if if remnants  are four times more asoggenic then actually it  

should even in the end result in a slight risk  reduction. Mhm. But uh that that um I mean uh the  

power for prominent was it was powered for a 16%  risk reduction which is then uh the predicted risk  

reduction you would get from uh if you only go  on the mandela randomization results is maybe 6%  

five six% risk reduction something like that and  it was way underpowered for for that unfortunately  

completely you can't draw any conclusions  from prominent. It's consistent with multiple  

explanations. That's a terrible conclusion from  prominent. Yeah. Yeah. Yeah. Uh yeah. He says that  

there are some some meds that are coming out  that are either being developed or are being  

starting to be trial that mainly reduce remnant  cholesterol and don't change April B much or don't  

don't change LDL cholesterol much. And those will  be uh maybe the tiebreaker. Yeah. So I think so  

too. So I think uh even uh I think the proof is in  the randomized control trial. So you can you can  

do all the academic exercises you want with the  genetic data and that's good. You should do that  

if you have the available genetic data and we have  these mandelian randomization methodologies. You  

should absolutely do that. However, in the end,  what is practically relevant for people is do we  

find something that reduces remnants and therefore  reduces risk. And that all depends on can you find  

any drugs that do that? and can you reduce  it enough to lower risk and is that clinically  

relevant? Is it costly and so on. So that is  a completely the practical relevant  

um evidence that you in the end need. and  there are companies doing that now. For example,  

Arrowhead is developing an silencing RNA  drug that targets ApoC3. so if you look at  

the data from coming out on from those phase  two trials it looks like remnants remnant  

cholesterol plasma triglycerides is reduced quite  a bit so it has a nice big effect size and no  

effect on LDL so it doesn't seem to have this  unexpected or unfortunate LDL increasing effect  

that prominent had. So I think the results  from that arrowhead trial which I believe is  

hopefully coming to fruition.  that trial is at least being planned. that  

would be fantastic for the field just for  for academic reasons and for practical reasons.  

If you have a few key messages, don't forget  that one key message is still that LDL is the  

major risk factor. I keep emphasizing this  point because if you don't emphasize the point,  

people will take the research and do their own  interpretation wrongly of it. So I think that's  

important. people do tend to do that on social  media. They will look at a study or they will find  

what they want to find by hook or by crook. They  will bend everything. Oh yeah. Yeah. Sounds good,  

man. I appreciate  the putting things in context. Okay,  

quick recap of everything. Remnants are  large lipoproteins. They're related to LDL,  

but they're much larger and there's some other  differences. And they also cause heart disease.  

particle for particle they seem to be about four  times worse than LDL for heart disease risk. Now,  

most people have a lot more LDLs than remnants in  circulation. So LDL is still going to be a larger  

component of risk but in people who have very high  triglycerides, indicating that they have a lot of  

remnants, or in people who have lowered their  LDL, remnants can become a larger component of  

their risk. Elias gave this cut off of 3mg/L triglycerides or about 250-  

260mg/dL where people have so  many remnants that they become a major component  

of risk and can even trump LDL for overall risk  if triglycerides are high enough, if the number  

of remnants is high enough. This can happen  for example in people who are very overweight,  

who are obese, who have diabetes. In those groups,  the number of remnants tends to be elevated. This  

is especially true, for example, people who have  type two diabetes, they often get prescribed lipid  

lowering medication because their risk of heart  disease is higher. And so that tends to lower  

the LDL fraction. So now that's lower, but their  remnants are higher. And so in those individuals,  

remnants can become a major component, even the  major component of their cardiovascular risk. And  

so in those individuals, you might look at your  blood work and go, "Oh, my LDL is really low."  

And your doctor might look at it and go, "Great.  You have very low LDL." Cool. But let's not forget  

that there are multiple things that cause heart  disease risk. Let's not become one-trick ponies.  

Some people who have low LDL can still  have problems. For example, if the number of  

remnants is very high, if their LPA is very high,  there's a number of factors. We call that residual  

risk. The risk that still remains after the LDL  fraction of lipoproteins is handled. Okay. So,  

what can we do about it? Well, one thing is  we can calculate our remnant cholesterol. That  

gives us an idea of how we're doing in terms  of remnants. And you can do that with your  

basic lipid panel. No special tests needed.  It's total cholesterol minus HDL cholesterol  

minus LDL cholesterol. Now, caveat, that only  works if your LDL cholesterol is measured,  

not if it's calculated. And in your lipid panel,  it should say under your LDL cholesterol level,  

it should say if it's calculated or measured.  You can also get a sense of your remnants by 

your triglyceride levels. So if your triglycerides  are not very high, if they're under 100 or there  

about, not mega high, then your ApoB and your  non-HDL cholesterol are good estimates of risk.  

NonHDL cholesterol is just total cholesterol minus  HDL. And if you don't have an APOB, it's a good  

alternative. And you want it under 130 mg/dL. under 100 better, but under 130,  

good start. So in a lot of people, those are  good measures. ApoB, non-HDL cholesterol. But  

if your triglycerides are very high, 250, 300,  something like that, then it is possible that  

your APOB or your non-HDL may underestimate your  risk because it looks at total particles, but you  

may have a lot of remnants and the risk of those  seems to be higher than LDLs, for example. So,  

good to be aware if you have low LDL, but very  high triglycerides, might be a red flag. might  

be something to look into. I know that all these  names, all these formulas, these calculations  

are a huge pain in the rear end. This is going  to get better with time because measurement of  

the actual lipoproteins and the actual particles,  because that's what causes risk, and measurement  

of that is going to become more mainstream and  more default. So, this is going to get easier  

with time. And I want to make a website at some  point for you guys with all these calculators in  

one place and you can just enter your basic lipid  panel and it can spit out all of these results for  

you. So that's work in progress. In the meantime,  for a lot more information on how to lower your  

triglycerides in a healthy way with lifestyle,  check out this video and I'll see you in there.