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Unlocking the Epigenome from a Single Drop of Blood

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In this week’s Everything Epigenetics episode, I speak with Dr. Toinét Cronjé about what epigenetics can do for the field of epidemiology. 

Epidemiology is the study of the distribution and determinants of health-related states or events in populations and the application of this study to control health problems. By studying epigenetics and epidemiology in tandem, Dr. Cronjé seeks to understand patterns of diseases in populations, identify risk factors, and develop strategies to prevent or control health issues.

More specifically, Dr. Conjé researches epigenetics in understudied populations including the association between DNA methylation and noncommunicable diseases and how DNA methylation clocks perform in these groups.

By making the most of the data we have available at the moment (from high-income countries) and of opportunities provided to researchers like herself to work at leading universities like the University of Copenhagen, she hopes that we will get closer to finding the tools to ease the burden on the research communities in low and middle income countries (LMICs).

If we can truly start to investigate data from LMICs can you imagine the richness of the information we will unearth?

Many of the questions that we are struggling with will be easier to address if we have more diversity in research data sets (e.g. genetics, cultural, dietary, and environmental), as rich (diverse) data sets allow researchers to see more angles to approach their questions from that they might not have been able to see before.

Dr. Cronjé’s hope is to develop blood-based screening tools for a disease. Only then, when disease screening is accessible to all (e.g. through a blood test instead of intensive and invasive procedures) will we actually know what proportion of populations around the world actually suffer from diseases like these.

Using that as a starting block we can finally proceed to addressing stigma and improving care.

In this podcast you’ll learn about:

– Toinét’s unique background
– OMIC epidemiology
– What epigenetics does for epidemiology
– The importance of biobanks
– What we can tell you about yourself when investigating the epigenome using an archived sample from a biobank
– Why it’s important to research understudied populations
– What we can learn from low and middle income countries
– What the research community is missing out on by not studying these groups
– Noncommunicable diseases (NCDs)
– The association between DNA methylation and NCDs
– The urban-rural divide which provides a unique opportunity to investigate the effect of the combined presence of multiple forms of environmental exposure on DNAm and the related increase in disease risk
– Toinét’s study on “Comparison of DNA methylation clocks in black South African men”
– Epigenetic age acceleration in the cardiometabolic disease among migrant and non-migrant African populations
– An editorial Toinét wrote in late November 2021 titled “Could unlocking methylation-based blood cell counts revolutionize epidemiology?”
– The current challenges in epigenetics that should be addressed in future work
– Toinét’s next epigenetic-based project

Toinét Cronjé is an epidemiologist and postdoctoral researcher at the University of Copenhagen’s Department of Public Health. She completed her doctoral training at the Centre of Excellence for Nutrition at the North-West University in South Africa where she investigated the associations of individual and composite DNA methylation markers with cardio-metabolic disease risk factors in an African population. 

Currently, her focus is biomarker discovery in Alzheimer’s disease and related dementias using multi-omic datasets. This work serves her overarching career goal of identifying biomarkers of complex disease risk and progression that are feasible to implement on a global scale.


Héléne Toinét Cronjé

hannah_went (00:01.1)
welcome to the everything epi genetics podcast dr crane i’m excited to have you here today thanks for being here

toin_t_cronj_ (00:08.264)
thank you so much it’s my pleasure to be here and it’s really nice to meet you

hannah_went (00:12.92)
yeah and you have a really unique background i absolutely want to hear more about m and i think our listeners would be excited to hear more about your journey and you know where you got your start and how you ended up where you are now so would you mind giving us a little bit of insight into that

toin_t_cronj_ (00:17.624)

toin_t_cronj_ (00:30.724)
yeah sure i it’s a story of a lot of good mentors and luck i was born in south africa i grew up there that all my studies there and what started out as a focus on psychology and nutrition moved into post graduate work focusing on nutrition and care

ascular disease i got some interesting genetics during that time and that evolved into epigenetics and my thesis and interestingly i was visiting copenhagen right at the end of my thesis and coved block down happened and i got stuck here and i changed the visa guide lines so i was allowed to apply

for post doktor position here and i got one at the university of kopenegan and so now i’m moving a bit more into the prodiomics research area so over all the golden thread is epidemiology an epidemologist i’m looking at non communicable diseases and that is such a wide

field and we will probably talk about that at a bit later but i think the exciting thing about being a researcher right now especially someone newly entering the world science and research is just how incredibly fast pace it is and how you can really jump from one thing to the next and explore everything you can connect with people over the world

even from a small town in south africa you can you can collaborate you can do exciting research and yeah that is how i got here

hannah_went (02:45.54)
yeah that’s that’s great always talk about how amazing it is to have those really great mentors or those connections especially in this research space because it’s not possible for an individual to keep up on all of the research that’s being released right i think that one of michal’s of this podcast everything genetics is to try and bring people together so we can learn a little bit more about what’s out there and maybe that leads to collaboration on very unique data sets or looking at you know

toin_t_cronj_ (02:51.944)

toin_t_cronj_ (03:00.784)

toin_t_cronj_ (03:14.824)

hannah_went (03:15.42)
particular diseases as well so i definitely hear you on on that and you know i know you mentioned on your linked in that you’re an omicepidemiology enthusiast i love that but i want to dig into that you know what are you studying now if you could just explain a little bit of your post doctoral work i know you mentioned at the university of copenhagen n what you’re currently researching

toin_t_cronj_ (03:25.124)
uh uh

toin_t_cronj_ (03:33.764)


so epidemiology is just the term the encompasses investigation of of humans of populations so in contrast to a lot of the people i talk to around here every day i’m not a microphologist or a drug developer but i look at at humans at invade

as in their fullness and that encompasses everything from the molecular parts and the piginom to the exposures around them and how that influences their eno for example or the other omi and then how that relates to risk during their life course and one of the very interesting things about denmark and why it is otentially a very interesting place

research is the availability of archive samples it is all tissues that’s been collected for the past three four decades that they keep stored there’s a single linkage system for all the health records and of course you know with the appropriate data access and the ethics that goes into it the idea

toin_t_cronj_ (05:09.184)
is that you can now have these samples you can go back to the bio bank i can find someone’s liver sample from that time they had the biopsy before they started the treatment twenty years ago and i know what has happened to them since because i have their electronic data so the group that i’m in focuses on pathological bio markers using bi bank samples

and different omes and imaging technology and the ideas really to start comparing some of these methods what is metholican tell us versus prariomics versus image based i and what can be incorporated into canial practice what what is redundant what performs worse than what current they have so that’s

hannah_went (06:09.44)
hat’s great i think we’re going to see this field move in a multioic direction of course i’m bias i love epigenetics will be the first person to admit they can’t do everything right we have to look at at every angle every every omi this idea of the multiomic realm and it’s great that you all have so many access to those bio banks you know i’m not an expert in bio banks whatsoever but i feel like every time i talk to people who are you know in the europe area somewhere you all have so

toin_t_cronj_ (06:09.704)

toin_t_cronj_ (06:14.264)
yeah yeah

toin_t_cronj_ (06:26.724)

toin_t_cronj_ (06:30.364)

toin_t_cronj_ (06:38.664)

hannah_went (06:39.66)
access to them i think that something the us is lacking in is kind of those bio bank samples and in that accessibility which is crucial for doing the research that you’re doing

toin_t_cronj_ (06:40.924)

toin_t_cronj_ (06:46.464)

exactly and especially when when you’re looking at health care system that is so communal where we’re all going to the same place we all have the same system there’s no private and non private it’s just you know and it can all be linked and of course i mean you will know and the listeners hopefully too but i’ll put it out there as a disclaimer it’s not that simple

hannah_went (06:56.56)

hannah_went (07:04.9)

hannah_went (07:09.02)

toin_t_cronj_ (07:18.964)
there are still clutches in the system of course but in terms of sample access data quality just the dhepth of the finatype data that’s available here there’s not a lot of countries there’s some in europe but that’s pretty much it and the point is that until now it’s not really been delved into the samples are just there because we’ve

hannah_went (07:38.28)

toin_t_cronj_ (07:48.984)
not we but people have collected them and you don’t want to destroy them but epigenerics and things that we can do now so relatively new and they know that ten twenty or thirty years ago so the samples are just there and it’s exciting that we get to go back and use them

hannah_went (07:55.14)

hannah_went (08:12.64)
very very and maybe that speaks more volumes about the u s health care system than it does our our viovancinfrstructure so well we won’t get into that but that’s maybe maybe yeah you know it’s great to learn a little bit more about your background and everything you’re doing so what’s zone in on on your research that you’ve done with with p genetics you say a lot of times you know the ability for epigenetics to do things for epidemeology and i just think that’s great

toin_t_cronj_ (08:17.724)

oh it’s a different podcast

toin_t_cronj_ (08:35.664)

hannah_went (08:42.48)
what can epigenetics do for epidemeology

toin_t_cronj_ (08:47.164)
so a key component in in epidemeology like i said is the human and we are biassed and we are falbale and so when we’re doing investigations that include people we rely on question airs a lot we ask them about their alcoconsumption and their smoking and physical activity and and we want to measure their blood pressure all these things

hannah_went (09:06.32)

toin_t_cronj_ (09:17.164)
um and there are a couple of problems when you’re talking about question air data people don’t remember people think you have an agenda and they try and tell you something that they think you want to hear or if you bring it into a global context people speak different languages people not all people smoke the cigarette that you buy in the super market

some make their own or use a different kind of tobacco and so on and so epidemiology is not one size fits and if we’re talking about really increasing diversity in epidmology we need to find buiomarkers that are more one size fits and omits and epigenetics can do that if we find a way like there’s been no

progress in this direction you find a way to accurately quantify lifetime exposure to certain things to pollution to smoking to acol then we don’t need to ask people we can still ask them but we don’t need to fully rely on that so i think that is key and the second thing is if you link to

hannah_went (10:32.1)

hannah_went (10:37.4)

toin_t_cronj_ (10:46.844)
our bank aspect is we’ve got someone with a liver sample a blood sample from thirty years ago and we didn’t think at the time to ask him about specific things that we know are important now but if there’s the n in that sample which there will be then we can measure certain components and we don’t need to ask him or so it’s powerful it’s something i get really excite

hannah_went (11:00.26)

toin_t_cronj_ (11:16.824)
it about because you are able to look at these fine types in an unbiassed way and you also take one sample from a participant and you can get thousands of measures and i don’t have to say okay when you come back i need another blood sample and another one and i can just like the same day and i and i can read so much into it

hannah_went (11:30.6)

hannah_went (11:42.2)
yeah that’s that’s great so i want to stick on that that topic as well and you would need another sample if you want to look at them you know laungitudinally down the line right you wanted update there okay perfect just wanted our listeners to say wait a second um no that’s that’s great so if you investigated my epigno using a blood sample or buckle swab or you know whatever tissue that you had even one that you just mentioned you know the archie bio bank what are some things that you could just tell me about myself

toin_t_cronj_ (11:51.464)
yes yes yeah yeah


toin_t_cronj_ (12:10.124)

hannah_went (12:12.02)
know um kind of in terms of what you’ve investigated so far

toin_t_cronj_ (12:17.444)
so like i just mentioned we can say something about your alchoconsumption um not as accurately as we can with smoking with smoking we can really tune in to exposure over all with alchol we can see whether you are a frequent consumer or not there’s some nuances in the kind of alcho that you’re consuming

hannah_went (12:25.78)

toin_t_cronj_ (12:47.524)
differences in consuming one drink every day versus only seven drinks on saturday but i can tell you if you’re consuming going on i can tell you your age chronological and biological as i know you’ve also discussed on this podcast the idea of biological aging or epitunetic aging in some instances we can look

hannah_went (12:54.48)

toin_t_cronj_ (13:17.584)
drama exposure to drama we can look at risk our future diseases we can identify orstratify between current disease sometimes and again all of this and you won’t know this probably even better than i do but this is not in the public space yet i don’t think you can walk into it

hannah_went (13:45.66)

toin_t_cronj_ (13:47.164)
this office and say here’s my pig telling me everything you can about me because things are moving at such a rapid such a rapid pace and we are just improving these biomarkers and and really trying to to figure out what works for who and what do we actually see and capturing these markers and how reversible they are so we can tell you a lot but with a relative confidence interval

hannah_went (14:17.52)
yeah it makes me so excited as as well i was talking to someone previously in my show and and they stated and i’d love to get your opinion on this as well you know there’s not a stronger signal between anything than there is between methalation and smoking right like you said it’s it’s better than what you’re writing down on you know a paper survey essentially

toin_t_cronj_ (14:34.904)


yeah yeah it is it’s quite incredible

hannah_went (14:47.1)
well you know let’s dive more more into to the work that you do in particular so i know you focus on researching understudied populations and that’s just amazing i think that’s you know very much needed in this space and there’s probably a rather obvious answer to this question but i want to ask you from more of a professional view who you know dedicates their life to this this type of work why is this important you know what can we learn from these low and middle income countries what is the research community missing out on

toin_t_cronj_ (15:10.084)

hannah_went (15:17.04)
not looking at these these populations

toin_t_cronj_ (15:20.684)
yeah i think that’s a really good way to phrase the question because uh as someone that used to be a researcher in those communities there’s often this idea of oh you know it’s the right thing to do to also include these understudied populations but actually i mean yes it might be the right thing to do but it’s also the smart thing to do from researches perspect

if the more diversity you have the better your data set will be now of course if you’ve got if you if you have a limited ability and you can only get a small number of samples then you want to to try and limit diversity because otherwise you won’t find any signal but where we are at this stage is really at a place where we can start including more and moe

a more diverse samples and the research i did was in specific south african population and the complexity of something like smoking we say there’s such a strong association here what about people who need to make a fire in their homes to cook or people that work in a mine or like what is

smoking is it really the cigarette is just the inhalation of smoke in general is it the nicotine things like that you can only start really disentangling when you look at communities that doesn’t smoke in the white european way if i can you know put it as as simply as that and we are dealing

now with health problems of that that’s been in the making in the past ten twenty thirty years that that that came with ourbanization and how our lives changed and we see the consequences of it and there’s a part of the world where the process of orbanization is only just beginning or it’s still happening and so if we

toin_t_cronj_ (17:50.544)
to understand some of the diseases that we’re dealing with in the western world at the moment would be quite wise i think to go to places where it’s still happening and actually investigated as it’s happening um so there’s there’s a lot i saw earlier in the week of study it wasn’t published earlier in the week but i only saw it earlier the week

looking at ethnic differences in in genetics and indian metholation and more than seventy percent of the variation was environmentally driven and not genetically driven and i think that is

toin_t_cronj_ (18:39.284)
i i can’t really say it is surprising but it just goes to show that it’s not enough to say okay but we have african genus what about the exposures what about the life style i think that’s really crucial

hannah_went (18:44.3)

hannah_went (18:49.18)


hannah_went (18:58.06)
and i think looking at those understudied populations before it’s too late right a lot of these may again i don’t know the right word here but disappear i guess or or you know some of these patterns or things it’s just going to be too late so we need to pay attention that way we have a reasoning to take that more targeted approach preventative approach if we want to move this and actually push this into you know doctors offices or make it commercially available for people to learn more about their health

toin_t_cronj_ (19:03.084)

toin_t_cronj_ (19:09.904)

toin_t_cronj_ (19:13.264)

toin_t_cronj_ (19:24.384)

yeah and i mean on that on that note the original idea for my ph d work was to look at to compare a rural and urban population group in south africa and then look over ten years so we had them at an examination two thousand and five and then again at two thousand and fifteen and i went to the rural side where data was collected

hannah_went (19:28.34)

toin_t_cronj_ (19:57.184)
twenty fifteen and this is really like gravel road riding a donkey umslougtering our own animals there’s one kind of kiosk thing that you can buy some fruit from and that is the life style and even there we were rather disappointed to find that it is already

urban it is already too close to urban in terms of exposure in terms of smoking altho consumption p m i in the south african context and of course you have a problem there because i in rural communities you have people traveling to urban sites for their jobs and so you you can’t really disentangle that but we really thought we would see differences and and we couldn’t it’s

ready to urban um so you’re right it’s the clock is ticking and if we want to know more we need to do it now

hannah_went (20:58.64)

hannah_went (21:07.44)
yeah exactly and that was your just two summaries that was your urban and rural divide study that you performed and that was over a ten year period where you were looking at kind of these complex changes and environmental exposure and rapid increase and andnoncommunical diseases was that the study you were mentioning

toin_t_cronj_ (21:23.144)

toin_t_cronj_ (21:26.384)

yeah so that was the original proposal once we saw that we couldn’t actually perform the quantity of investigation of it we wrote quite a large review starting from what we wanted to do and then also just looking at how it could be done better and then we focused some more on the sturdy population that we had but we couldn’t follow them

itudinally so the review that i think you are referring to that that contrast or that talks about the value of the urban world divide was a summary of the available literature and then looking at how what studies are going on at the moment and how they can be used yes

hannah_went (22:23.26)
ah that was the review i think i was was referring to so yeah nice to understand that a little bit um i know a lot of your work backing up some with with the name methalation is going to be looking at just that and then the association with those noncommunical diseases um so i’d love for you to define that just for our audience to link know that in their head and then um yeah we’ll start there

toin_t_cronj_ (22:40.804)

toin_t_cronj_ (22:44.524)

toin_t_cronj_ (22:49.784)
so noncommunical disease s just a disease that is non infectious so we’re talking about your heart your gory vascular diseases cancer diebetis dementia sim disease those kind of diseases and we typically associate them with environmental changes with stress with diet physical activity

sleep those kind of kind of exposures so it’s not it is not infectious like your h i v or very close so yeah

hannah_went (23:32.4)
sure yeah thank you thank you for that just just clearing that up there and then my second half of that that question is going to be i guess you can decide how how broad term you know how far an you want to go here but what is the typical association you see between an metholation and those non communical communicabl diseases and and sis is what now um wister so yeah you want to explain that a little bit

toin_t_cronj_ (23:57.604)
yeah yeah yeah yeah i am whenever i teach classes on pigenerics especially with epitunetic aging i tend to start the class by asking people know what do they do to keep themselves healthy to you know what are the good habits and the bad habits

it’s always something like ow i try and sleep eight hours and i try and just not like the elevator and use the stairs and i try to not smoke and all these things and then we go into the class and we’ll look at the different effects that these expersions have on the methilation and things like ebgneticaging and then we’ll look at the downstream effects of those and my final slide is always something like

you know it turns out your grandmother was probably right like you should do all these things we didn’t know why we just kind of followed her or you know typically in my head it’s the grandmother figured but whoever it is the wisdom comes from and it seems like the more we move forward in this field it just backs up all those you know old wisdom so we

hannah_went (25:01.42)

hannah_went (25:09.36)

toin_t_cronj_ (25:24.444)
see that obesity influences deanmitlation mostly in a way that increases your risk for hyhprotention is cancer and so on we see that obesity associates with pro inflammatory profiles we see that diet an unhealthy diet relates to unhealthy livid profiles and that relates to increase disease risk so it

mostly makes sense i would say and it’s in the direction that you would expect but so far we’ve seen these associations and we don’t really understand how the body responds in the way it does and me going back to the omeepidemiology enthusiast the macs really just provide some of that substance to what we’ve observed for so long

and to you know what our grandmothers told us to do from the start

hannah_went (26:25.46)

hannah_went (26:29.9)
i picture a grandmother figuring in my head too for worth and you’re actually teaching this stuff then right you’re teaching this to students and um classes yeah because i think i may be had like thirty seconds hey this is what p genetic says right in maybe a biology class but that’s amazing to hear that you’re actually teaching this um yeah and you know hopefully informing them on on future career paths

toin_t_cronj_ (26:31.824)
uh yeah

toin_t_cronj_ (26:43.744)

toin_t_cronj_ (26:52.584)

hannah_went (27:00.)
in this work or different research at least and i’m just going to move through some of your other studies here that i’d love to hear a little bit more about dr crone um i know you did one on the comparison of dan metholatian clocks and black south african men can you chat about this study and maybe what you found and give us some insights there

toin_t_cronj_ (27:01.324)
yeah yeah

toin_t_cronj_ (27:18.364)

toin_t_cronj_ (27:23.984)
so we did the study as a way to compare the different clocks that we know work really well in predominantly why predominantly you’re being ancestry samples we wanted to see if they perform as well in africa and over all we saw that our

cohort was consistently younger if generically than they were actually chronologically for for all the clocks and we

strangely observe that the grim age clock which is actually not a measure of age it’s not like your hand or your whole both clocks where you just get an idea of what someone’s biological age is it’s more about what is your risk relative to your age so you have the risk of dying of it’s a big goal sixty year old for example and then we know okay but you are fifty five so this

a problem so that is how the grim age works in a simple way and the grim age gave us the most precise age estimate which was interesting the race really under estimated and when we really dived into the components of these different plugs we found that the grim age probably performed particularly well because of the high

prevalence of smoking and alto consumption in our study group much higher prevalence than in some of the european samples and this is the only clock it was at that stage the only clock that incorporated lifestyle aspect to the clock so it took a metholation it still does it takes a metholation component that reflects lifetime exposed to smoking

toin_t_cronj_ (29:40.124)
for example and we think that a lot of what drives aging in this population is the exposure to smoking be tobacco cigarette smoking or like i mentioned previously having to warm yourself with a fire wouldn’t fire in your home cooking on fire working in mine so on in

hannah_went (30:02.9)

toin_t_cronj_ (30:09.984)
of things like obesity and unhealthy diet so because that is not a problem that we have in this particular code they are all fairly lean fairly fit that do physically active jobs and it’s a cobidret based diet mostly so it was an interesting interesting study

hannah_went (30:19.96)

hannah_went (30:39.72)
yeah definitely so just to clarify that they had higher grim ages you said or lower grim ages

toin_t_cronj_ (30:47.124)
so their grim ages were higher than the other ages but it was the closest to chronological age so it’s the one with the least descriptancy from actual age which is not necessarily what you would expect given ramage goal but that’s what we found yeah

hannah_went (30:53.72)
okay okay

hannah_went (30:59.92)

hannah_went (31:03.9)
no it makes sense when to ask there um you also looked at some epi genetic age acceleration in the cardiometabolic disease um among migrant and non migrant african populations so yeah i thought that was super interesting too so what do you find in that one

toin_t_cronj_ (31:14.544)

yeah yeah


yes and in this study we served out co served as replication cord and the main focus of the study was looking at a population from cana one group of the co or remained in cana and one migrated to europe amsterdam and england and we saw differences

in the way that these the migrants and the non migrants age so we found that the ganians that migrated overseas had accelerated aging and those that stayed in their community did not and then within each community we also looked at some dietary factors so there was an association with

toin_t_cronj_ (32:24.444)
um increased for light for light consumption so viromenbnine and decreased aging but then also there was an association within higher and slower aging which was unexpected because usually we see obesity increases or accelerates age and in vapor there’s quite a lot of

discussion about how in these communities having a higher beam i could be an indicator of

health of socio economic status i mean we’re not talking about obesity what we’re talking about

having adequate reserves having food having you know protecting yourself from from other stresses by having a m that’s a bit higher so we’re not advocating before i reamibut in these groups and in our code in south africa we saw the same thing i was protective

hannah_went (33:14.26)

hannah_went (33:34.78)
yeah there you go know interesting to to say the least and i’ll make sure to link out all of these studies so if someone wants to look a little bit more in depth or read it there very great reads i do recommend looking into them but you’re giving us great um summaries of of those um another published it was more i guess of an editorial that i found of yours that was done i think in late november of twenty twenty one but this was titled could unlock

toin_t_cronj_ (33:41.484)

toin_t_cronj_ (33:48.464)

hannah_went (34:04.62)
metholation based blood cell counts revolutionized epidemiology and we are doing a lot of work with a man sell sub sets right now and i just think you really you know jumped on that idea very very early um so can you summarize what you wrote in that exert for our listeners

toin_t_cronj_ (34:09.424)

toin_t_cronj_ (34:18.824)

toin_t_cronj_ (34:24.604)
yeah so the idea for that came from one of the papers it was part of my p d where we were looking at blood cell counts using metolation data and comparing that to other inflammatory markers o c r p and intrlicn six and c n f alpha and so on and we observed that these blood sell relative pladselcounts or your nutrefol lymphaside ratio

for example just i performed the conventional viomargers of information and if you look at the literature it makes sense that it does it does give you a better idea of relative immune activation and it is used in the clinical setting often and so i started just paying attention to literature and in papers that

read also that and it’s just not something we see in epidemiology that people incorporate blood cell counts and adjust for it and as it turns out the reason for that is because you need to do that in a fresh blood sample that’s why we can do it in a hospital we take your blood it immediately goes to the lab they can do these these analysis with it whereas c p inter six and those we can do in frozen samples

later so we can collect thousands of samples for cord and then years down the line we can we can look at those inflammatory markers and the exciting thing about the nimethulation is we can do the same so we can look at some from ten years ten years thirty years ago and actually quantify relative immune cell proportions in those samples so the idea of that erritorial is just to say that

if we know from an epitimological point of view that these things matter that blood cell count is an important confounded to adjust for it’s an important predictor of outcomes why wouldn’t we start including it the i would think the reason is because it sounds really scary like oh but then i need whole gen d and i methalatian data and its millions of c p g sites

toin_t_cronj_ (36:54.584)
um and the point of the editorial is just to say that at the end of the day after you do your quality control of the nmetlation data you get five you know excell columns that tell you nutrifolenm for sides and so on and it should be no different than having that excel column of c r b or intelican six and we need to com

hannah_went (37:10.9)

toin_t_cronj_ (37:24.364)
indicate that better to the epidemiology world and when we have huge cords that also have methalagian data it is worth in forming researches and say you know i will send you the data said with seropian six would you also like to have these methalagan measures epigenetic age an indication of smoking those kind of things and yeah we should we should use thos

hannah_went (37:45.7)

toin_t_cronj_ (37:54.744)
bbecause they’re valuable

hannah_went (37:55.66)
just that’s another piece to the puzzle right some some further insights that that you can learn so um then we’ll start to unlock kind of you know things we don’t know what we don’t know essentially so trying to learn a little bit more um well you know we have a couple more more questions for you here but we are we are getting to the end you know besides you know people not giving enough attention to these under studied populations what are some other challenges in your work

toin_t_cronj_ (37:58.164)

toin_t_cronj_ (38:06.624)
exactly yeah

hannah_went (38:25.7)
that you face or that you think is a big concern we kind of just mentioned one talking about you know sharing the data and making this obvious as a resource to the epidemioloyologist is there anything else

toin_t_cronj_ (38:34.724)
m yeah

toin_t_cronj_ (38:40.124)
yes is something we’ve been struggling a lot with its just the tissue specificity of it all it is an incredible resource to have by a bank of course but what is methlation of the liver tell us versus the kid neighbors bangers you know versus blood so ideally you want samples at the same time point in the same individ

all that you can compare and we can figure out which tissue is better for which disease and so on but we don’t have that because it’s an ethical and people don’t want to just give you their biopsise but also there’s a bias in by bank ample because there’s a reason i go for live i don’t do it for fun end

hannah_went (39:12.3)

toin_t_cronj_ (39:39.944)
reason is most often that i am ill or something has changed or we saw something on a scan and you can try and narrow down your search by saying i only want the people who went for biopcy and we know that they didn’t have kancsor whatever they were looking for but there’s still a bias in that so i think the next challenge for both the o mix world

but also the epidemeology and methods development world is related to try and quantify the bias and samples like these and better understand who goes for these biopsies and how can you best use the tissue and adjust for the confounding by indication bias

hannah_went (40:35.7)
now that’s that’s a good one and hopefully when that will be addressed as we have that that full profile of the person or know you know why they were in there and why their samples are in that that biobing so i appreciate that answer there um i’m excited to ask this next question you know i know you haven’t published in f genetics in a year or so which is not that long at all but you you men

toin_t_cronj_ (40:48.744)

toin_t_cronj_ (41:02.264)
in evgenticyears it’s very long the field is just running in eve genetic years it’s very long

hannah_went (41:05.7)
what was that

hannah_went (41:09.28)
oh i hears um but you mentioned to me when we were chatting offline you may pursue this genetic space project within the next you know a few months or so and i don’t know anything about it yet so would you be willing to share some insight about that project and maybe what’s next

toin_t_cronj_ (41:21.704)

toin_t_cronj_ (41:28.404)
yeah sure so it’s it is within these bia bank samples and know once once you’ve generated the data you get into that fun phase of writing up and doing the states and all that but before you get to that point what i’ve been doing in the past two years is figuring out which samples

we want what is the question that we want to ask how are we going to ask it getting the biopsies from the bio banks and separately from that i also got a grant from the outsumers association so focusing a bit on dementia and the grant was for prariomics for new prariomics analysis but goal is too

do a multiomic base line profile of these participants and then really look at what we can say about risk in the future and these samples are also a part of clinical trials with different outcomes but with interesting treatment so the idea is also to look at treatment effects and if we can stratify

what dishin based on who will gain most in terms of cognitive function in the long run or at least a delay in cognitive decline in the long run based on these these treatment effects

hannah_went (43:14.1)
well congratulations on the grant um that’s that’s very big um i know that’s that’s not easy um what are you treating those groups with am i able to ask that

toin_t_cronj_ (43:15.904)
thank you thanks yeah

toin_t_cronj_ (43:26.944)
yeah so so this is all again the the gold mine of genetics these are old trials that have so in the u s there’s an incredible resource that i only learned about two years ago bio link so that is all the n i n n i national sorry or the n funded projects

hannah_went (43:36.72)

hannah_went (43:53.04)

toin_t_cronj_ (43:56.744)
that have samples left get stored by the inner age and you can apply for access to some of those samples if it fits within the original scope and that is that is really exciting because if you’ve got a trial that look at blood pressure reduction which is the one that i’m working with you can now take those samples look at follow up data without needing to

hannah_went (44:09.38)
got ya

hannah_went (44:16.36)

hannah_went (44:25.68)

toin_t_cronj_ (44:26.884)
do a new clinical trial and asking people to give new samples or you know go through the process again so when we talk about what can emportunitics bring to pitemiology i think it’s this it’s that we have so much data that we haven’t even started looking at

hannah_went (44:33.88)

hannah_went (44:46.02)
absolutely well that’s great and i’m excited to keep up with all of your studies and in the future i have one last question for you dr crone it’s a curve ball question so nothing related to your research but it’s just it’s just kind of fun so if you could be any animal in the world what would you be and why

toin_t_cronj_ (44:50.564)
thank you

toin_t_cronj_ (44:59.124)
m m

toin_t_cronj_ (45:06.644)
oh any animal who i have to say a lion

toin_t_cronj_ (45:16.324)
and now i have a question for you have you ever seen or yeah seen a lion in a while or in its natural setting

hannah_went (45:27.36)
i haven’t no i want to do the safari i want to go to south africa or africa i want to do it all but i have not and i’m sure it’s beautiful

toin_t_cronj_ (45:32.124)
oh okay

yeah so they are just incredible and they are maybe the reason i so said with them is the way that they can just sleep in the sun and just lay there and have the time of their lives and then in the next moment just get up and be so incredibly powerful and

hannah_went (45:45.)

hannah_went (45:53.44)

hannah_went (46:07.2)

toin_t_cronj_ (46:08.264)
roar in a way that just feels like it’s shaking the earth around you so that that would be my answer but that is agrivbal

hannah_went (46:16.76)
yeah that’s a great answer no one no one s beautiful has a great explanation no one’s given that answer for so um yea i definitely want to go and you see all those animals in the wild so dr crone we’ve come to the end of this amazing podcast interview so for listeners who want to connect with you where can they find you and again i’ll put this in the show notes

toin_t_cronj_ (46:24.264)


toin_t_cronj_ (46:35.984)

toin_t_cronj_ (46:42.304)
so i am most active on twitter i would say so they can find me on twitter they can also connect with me on linked in and then if you go to the university of copenhagen website and you search for me there you will find all my other contact information there

hannah_went (47:04.22)
amazing well you know thanks everyone for joining us at the everything epigenetics podcast and remember you have control over your epi genetic so tune in next time to learn more thanks sector

toin_t_cronj_ (47:13.384)
yes do what your grand do what your grandmother told you i think she’s right thank you so much

hannah_went (47:18.4)
yes that’s the new tag line what your grandmother told you thanks so much


About this Guest Expert

Dr. Toinét Cronjé
Toinét Cronjé, PhD, specializes in biomarker discovery in Alzheimer’s disease using multi-omic datasets, building on her doctoral work on DNA methylation and cardio-metabolic disease risk factors, aiming to identify globally feasible biomarkers for complex diseases.

More About me

Everything epigenetic
Everything epigenetic
Unlocking the Epigenome from a Single Drop of Blood

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