Manage episode 190558032 series 1581590
Jane Ferguson: Hi Everyone. Welcome to Getting Personal: Omics of the Heart, your podcast from Circulation Cardiovascular Genetics. I'm Jane Ferguson, an assistant professor at Vanderbilt University Medical Center and an associate editor at Circ Genetics. This is Episode 9 of the podcast from October 2017.
This month we were on the road and traveled to sunny Orlando, Florida for the annual Scientific Sessions of the American Society of Human Genetics. While there, I had the chance to talk to some of the researchers presenting posters in the sessions on cardiovascular genetics and genomics, which you'll hear in just a moment. While at ASHG, we had the chance to organize a CRISPR-Cas9 genome editing boot camp. Those of you who attend a JR ATVB/PVD Scientific Sessions might have had the chance to participate in a boot camp in previous years, and this is the first time we were able to offer a boot camp at ASHG. These boot camps are based on a flipped classroom model in which the participants do some preparatory learning in advance of the meeting, and then have the chance to do hands on activities with immediate guidance from the onsite instructors. It's a really nice way to learn more about a topic, so if you're attending AHA meetings in the future, look out for the option to sign up for a boot camp while you're registering.
If you haven't been able to attend a boot camp but are interested in CRISPR-Cas9 genome editing, you can access video and slide materials on the Circ Gen website at http://bit.ly/CRISPRbootcamp and the CRISPR is capitalized, so capital C-R-I-S-P-R boot camp.
Moving on to the virtual poster session from ASHG, you may notice a little more background noise than usual, which will hopefully make you feel like you were right there with us at the poster session.
First up, Dr. Gemma Cadby is a research fellow at the University of Western Australia and she presented a poster with data from her ongoing research into heritability of lipid species, measured through lipidomic analyses and their relationship with cardio metabolic risk traits, including blood pressure and HDL/LDL and total cholesterol.
I'm here with Gemma Cadby, whose poster is entitled "Genetic Correlation of Human Lipidomic Endophenotypes and Cardio metabolic Phenotypes in the Busselton Family Heart Study". Hi Gemma, can you tell us a little about your poster?
Dr. Cadby: Sure. So what we've done is we've taken about four and a half thousand people from an epidemiological study called the Busselton Health Study, so that's a group of people from Busselton in western Australia who were recruited initially in 1966 and they've been followed up every couple of years, and their blood was taken in 1994 and 1995. So the great thing about the Busselton Health Study is that there are a lot of related individuals, so it wasn't recruited as a family study but because it's a small town, a lot of people are related. So we didn't want to exclude those people from our analysis.
Jane Ferguson: Right.
Dr. Cadby: And because we don't really trust family records, because the study wasn't recruited as a family study, what we've done is we have empirically derived their relationship using the LDAK software.
Jane Ferguson: Okay.
Dr. Cadby: And then what we've done is we have performed targeted lipidomic profiling to quantify 530 lipid species and those are from 33 lipid classes.
Jane Ferguson: And that's all from plasma samples?
Dr. Cadby: Yes. And then what we did is we estimated the heritabilities. At this stage we've just done the heritabilities of the total of the sort of, of the 33 lipid classes, so those 530 species break down ... sort of can be combined into 33 classes. So we estimated the heritability of those, and then we also looked at the genetic correlation between those lipid classes and some cardio metabolic phenotypes. So, we found that 98% of our lipid species was significantly heritable, so those of the individual 530 species, and those heritabilities ranged from .12 to .52 and all of our lipid classes were also significantly heritable, with heritabilities between .15 and .5.
Jane Ferguson: How does the LDAK software work? Do you put in genotypes, like were these subjects all genotypes-
Dr. Cadby: So, they were genotypes on the Illumina ... Was actually on two different chips, the 610 and the 660, but we checked them in a batch of facts, and we combined them into one sample-
Jane Ferguson: Mm-hmm (affirmative)-
Dr. Cadby: Yep, and then LDAK adjusts for linkage between the variants, and then we used that to estimate their relatedness. And what we also did is we removed any relationships that were ... We said any relationship less than .05 to 0 so that ... With the idea being that the snips on the chip should estimate the whole genome relationships, but anything less than .05 might just be due to sort of, chance.
Jane Ferguson: Right, right. Okay.
Dr. Cadby: So we ran the genetic correlation between nine cardio metabolic phenotypes and the 33 lipid classes, and we found 155 of these genetic correlations who were statistically significant. Probably not surprisingly, so dystonic blood pressure wasn't genetically correlated with any lipid class, but we did find that systolic blood pressure was genetically correlated with eight of our lipid classes.
Jane Ferguson: Did you notice any difference between the highly-heritable lipids and the non ... like the less-heritable lipids and their association with phenotypes?
Dr. Cadby: Surprisingly, the most heritable lipid class was [asoplanetine 00:06:09] and that wasn't genetically correlated with any of our cardio metabolic phenotypes, which was quite surprising to me.
Jane Ferguson: Right. So your next steps would be data-
Dr. Cadby: So, what I've actually done, but is not showing on this poster, is I've now run the genetic correlation between each of the 530 lipid species and their cardio metabolic phenotypes to see whether the genetic correlations we observed were just due to, sort of a subset of lipids within that class or whether it was across all of the lipids species in that class.
And we've also, I guess the exciting part, we've also got 500 whole genome sequences that we've just performing QC on at the moment. So then what we want to do is we want to see if we can use our lipid species to try to identify any genetic variance that are coarsely associated with the lipid endophenotype and then ... which would then go on to be associated with cardiovascular disease outcomes.
Jane Ferguson: Cool. Very interesting. Have you published this or are you working on a manuscript now?
Dr. Cadby: No I just working on it at the moment. We only got the lipidomic data in maybe June. So it's been sort of a quick ... just trying to get it done at the moment.
Jane Ferguson: Thank you.
Next I talk to Doctor Sylwia Figarska post doctorate fellow at Stanford University. She presented her research on proteomic profiling in several Swedish cohorts using the Olink platform and looking at the association of cardiovascular risk proteins with triglycerides, HDL, LDL, and total cholesterol.
So I'm here with Sylwia Figarska from Stanford who has a poster entitled, "Associations of Circulating Protein Levels with Lipid Fractions in the General Population".
Hi Sylwia. Thank you for agreeing to this. I would love to hear a little bit more about your poster.
Dr. Figarska: Yeah, so I work with a Dr. Erik Ingelsson at Stanford and we were interested in pathways of association between circulating proteins and lipid levels to better understand [inaudible 00:08:30] of cardiovascular disease. Because both protein biomarkers and lipids are associated with cardiovascular disease, which is main cause of death world-wide. And so, in this study we investigated association between protein biomarkers and triglycerides, cholesterol, LDL, and HDL levels in population based cohorts.
So as we study population, I used a Swedish cohort, [Epi Health - inaudible 00:09:04] cohort. So the cohort size is a little bit more than two thousand individuals. Associations at the p value collected for [FDR - inaudible 00:09:19] lower than five percent. We tested in a validation step, which was [inaudible 00:09:29] cohort also, turning a population based Swedish based cohort, and associations at P value lower than 0.05. We considered my results.
Jane Ferguson: Okay, so what kind of things did you find?
Dr. Figarska: Yeah, so we tested 57 proteins and 42 of them were successfully replicated for association with at least one lipid fraction. So, we found 55 blood associated with triglycerides. 15 proteins associated with cholesterol. 9 protein associated with LDL cholesterol and 24 with HDL. And then we were interested in overlap between protein biomarkers and lipid fractions. And indeed we have found some proteins that were associated with all of the lipid fractions or with, for instance, HDL cholesterol and triglycerides, because this is ... and we also looked at the parting of these associations, so this is a hit mark showing them directions of association. It's because some older proteins will associate with increase of triglycerides and at the same time will lower HDL, which is kind of expected pattern ...
Jane Ferguson: Right.
Dr. Figarska: ... and also this increase triglycerides and decrease HDL level is a phenotype that also is associated with insulin resistance, another phenotype I'm interested in. Yeah, so far good finds. Some interesting associations and further studies are needed to have a closer look at these patterns.
Jane Ferguson: Right. So do you think ... are you going to follow it up with more functional analyses with these proteins to see sort of what are the functional relationships between these proteins and the lipid traits?
Dr. Figarska: Yeah, yeah. We also might look at genetic background of these to see, which part of genetics will determine both of these proteins and lipid levels.
Jane Ferguson: Right, interesting. So have you published any of this yet or are you working on a manuscript?
Dr. Figarska: No, I'm working on a manuscript right now. So it's not published yet. It's new data, the results.
Jane Ferguson: Yeah, very interesting. And I guess ... so tell me a little more about this Olink platform? So is this ... was this selected specifically for proteins that are known to be involved in cardiovascular disease?
Dr. Figarska: Yeah, yeah. So, Olink is a Swedish company that offers partners to test protein levels and it's highly sensitive and specific assay. So for each panel you might test 92 proteins and using one microliter of blood sample, which is [inaudible 00:12:48]. Efficient and as I said it's very specific and sensitive method. And Olink effects panels of 92 proteins and for this study we used cardiovascular panel one and cardiovascular panel two and three. So, it means proteins that were like expected to be related to cardiovascular disease. And because significant panels were used in different cohorts, for this study we used those that were overlapping between these three panels to ... because then we could check them. We could check the ... validate the result.
Jane Ferguson: Thank you.
Dr. Marketa Sjogren is an associate researcher at Lund University in Sweden and spoke to me about her project investigating genetic risk scores for coronary artery disease could predict overall hospitalization burden and mortality in over 23,000 individuals from the Malmo Diet and Cancer Study.
So I'm here with Marketa Sjogren from Lund University and her poster is entitled, "Elevated Genetic Risk for Coronary Artery Disease Increases Hospitalization Burden and Mortality".
So, Marketa, I'd love to hear a little bit more about your research.
Dr. Sjogren: So what we have done here is to take about 28,000 or 23,000 individuals from a study called Malmo Diet and Cancer Study, which has been previously published [inaudible 00:14:33]. And we constructed a way to genetic risk score consisting of 50 snips for coronary artery disease as a risk.
Jane Ferguson: And was this from previously published studies?
Dr. Sjogren: Yes, those are from previously ... those are GWAS identified and previously published for different stuff. So these are basically at that time up to date, I think. There are some more to be included now, but at that time this was up to date.
What we have done is to look whether we can, in a population based study, that is prospective study, whether we can predict if this genetic risk score, increased genetic risk score, could predict hospitalization and/or mortality. And what we see is that, that actually higher genetic risk score. So if you are in the top quintile of a genetic score, your risk of every being hospitalized for any reason increases by about 10% ... actually about 30% when it comes to cardiovascular causes. At the same time we also can see that increased genetic risk actually increases your risk to die both of any causes and particularly of cardiovascular mortality. And the strength of our study, I think, is that we actually have electronic health records, which include 100% of the population. So that we are actually sure that these people were increased and we also have the good sort of diagnosis for those, because those are hospital diagnosis.
Jane Ferguson: Right, right. Interesting. So, even ... so for people who were hospitalized for CAD but did not have a high genetic risk score, where you able to sort of tease that out? So people who had CAD but didn't have ... had a low genetic risk but got CAD anyway?
Dr. Sjogren: Yeah. No, we haven't actually quite look at that, but that's an interesting question because that would of course be interesting to see what else to they have and what are the environment factors that would influence the low genetic risk. Because, of course there are people with low genetic risk that will also ...
Jane Ferguson: Yeah, they must exist. It's probably relatively small numbers.
Dr. Sjogren: Yeah, they are probably smaller and the risk is lower, but I'm guessing that when you combine these genetic risks you can actually see quite strong with the risk of ever getting C-A-D, or CAD, or any of those other ... or any cardiovascular complication increases.
Jane Ferguson: Yeah, interesting. So what are you hoping to do next with these data?
Dr. Sjogren: What are we hoping to do next? Well, publish of course. That's our first step. That's the first part. And now we are actually looking into other kinds of genetic predisposition for different cardiometobolic traits. So we are currently proceeding with BMI and also type two diabetes and related phenotype. So that's our next thing, to sort of explore what kind of ... maybe what kind of hospitalization for the different cardiometobolic traits are most common for individuals for different genetic risk.
Jane Ferguson: Yeah, yeah. That'll be interesting. That's probably people who have increased risk for genetic CAD, they also have increased genetic risk for related things, like ...
Dr. Sjogren: Yes.
Jane Ferguson: ... obesity and type two diabetes.
Dr. Sjogren: That will probably be a huge overlap. But even if you look at them separately, because we have quite a big data, so you can distinguish those [inaudible – pieces]. Of course, we haven't actually looked what happen if you would, which would also be interesting to see sort of a combined cardiometobolic genetic risk. That would be an interesting challenge.
Jane Ferguson: Right. Plenty of work to do.
Dr. Sjogren: Yes, always.
Jane Ferguson: Alright, thank you.
Dr. Jessica Van Setten is an assistant professor at University Center Utrecht. Studying the genetics of rejection of heart transplant. She presented novel genetic loci from donors and recipients associated with acute rejection. As Jessica mentions, she's actively building a resource of data for transplant donors and recipients. So if you have access to data or samples and are interested in furthering the efforts of the International Genetics and Translational Research and Transplantation Network Consortium, you can find more information at wwww.iGeneTRAiN.org or by contacting Jessica directly.
I'm here with Jessica Van Setten from Utrecht and her poster is entitled, "The Effect of Genetic Variation in Donors and Patients on Rejection After Heart Transplantation".
So, Jessica thanks for talking. I would love to hear a bit more about your research.
Dr. Van Setten: So, yeah, we are a ... I'm part of iGeneTRAin, which is an international consortium in which we try to collect as many transplants cohorts as possible that may or may not have genetic data. And so for we have genotyped over 40,000 samples of which 12,000 full donors and recipient pairs. So this means we have DNA of the donor and of the recipient. So we can actually do ... we can check how this matches.
Jane Ferguson: That's a really cool resource.
Dr. Van Setten: Yeah, I think it's really exciting. It's one of the very first things I think in the world that actually does this type of research and we do need large samples size in people studies and other studies.
Jane Ferguson: Right.
Dr. Van Setten: So, I'm really excited to be able to show now our very first results of GWAS actually in donors and we ... so last year we have also shown the very first results of the GWAS recipients and we are working on loss of function study. So this means we are interested in genes that are absent in the recipient but are present in one or two copies of the donor.
Jane Ferguson: Okay.
Dr. Van Setten: So we can see if this actually ... if this specific genes pose rejection after transplantation.
Jane Ferguson: Interesting. Okay, so what kind of things did you find?
Dr. Van Setten: So this is actually very novel. These analyses were run only like one or two weeks ago. So, these results are the reason I didn't put the gene names here. Right now we have only a thousand donors [inaudible - in pairs for hearts].
Jane Ferguson: Okay.
Dr. Van Setten: But we aim to have another at least 500 pairs by the end of next year. We will use another 600 for replication probably later this year. So what we find so far is basically a bunch of common snips that associated with rejection at year one.
Jane Ferguson: So do you only included pairs where there was rejection at some point? Then you excluded pairs where there was a successful transplant?
Dr. Van Setten: No, no. So this is ... actually I think we are doing pretty good at transplantation. So we have on average less than 30% rejection across all cohorts. And what we do is in this case for disposition we did genotype association to see if there was rejection at year one. Like within the first year after transplantation yes or no. And then it was basically a case control study between those.
So what we aim to do in the near future is also do time to first biopsy to rejection and hopefully get more powerful analysis there. Because then you get actually time to advance as your outcome.
Jane Ferguson: Yes, interesting.
Dr. Van Setten: Yeah. We're really excited about it.
Jane Ferguson: Yeah. Yes, so it looks like you found, you know, like a number of signals that genome-wide significance.
Dr. Van Setten: We do. Yeah and that's only with a thousand samples. So, of course we do need replication to see if they are actually true, which I think is really nice. And what we aim to do after is our next sequencing experiments to see if it actually, you know, these things are expressed in the heart. So for this we have ex-plant hearts of the recipients but we also have the heart biopsies of the donor. So I work at Utrecht and there we do regular biopsies. So the first few months is actually almost every week and then it's once ... I think every six months. So we can also use those for our next sequencing experiments.
Jane Ferguson: Wow. So they can look at like the changes in expression over time.
Dr. Van Setten: Exactly.
Jane Ferguson: And sort of do like as a temporal EQTL to look at its genetic predictors of expression over time.
Dr. Van Setten: Yeah, so there is so many very nice things we can do with this. And we need a consortium, we're not the only ones doing this but we are also working on other markets like cell-free DNA and protein expression in the blood to see if we can have markers for rejection there. So we can hopefully in the future, even weeks before you can actually see the rejection in a biopsy, already prove that it's going to happen based on blood. So you don't need those invasive biopsies, you can just take a little bit of blood and check that and then say, okay, we actually need a bit more immunosuppressive drugs. Or you know, it's all fine. Maybe you can lower it a little bit and see where that ends.
Jane Ferguson: Right, right. That's really cool. So was this done mostly in European ancestry populations or is this ...
Dr. Van Setten: Yeah, it's mostly European. We used mixed models and we just included all we have. Because we only have such a limited sample size we decided to just go for everything and use mix models.
Jane Ferguson: Right.
Dr. Van Setten: So I think about the thousand samples, it's probably about 700 European samples. And the others mostly African-American ancestry and then a few Asian and other ethnic populations.
Jane Ferguson: Yeah, really cool. So you probably ... this is like hot off the press so it's not published yet. Are you planning to write it up soon and ...
Dr. Van Setten: Yeah. No, we are planning to write it up soon. So we may want to combine this with our loss function results and we really hope to have everything ready before, let's say, the first of January and then write it up.
Jane Ferguson: Very cool.
Dr. Van Setten: Yeah.
Jane Ferguson: Anything else you want to say?
Dr. Van Setten: Well, I do ... this is also on my poster, we really want to invite other people who may have transplant data, even if you only have phenotypic data data. You know, you have large transplant cohort collected over the years, but you don't have genotype data yet. Please do contact us, because we are always in need of more samples. Especially for heart, because right now we only have a thousand. And even if ... like in the Netherlands we were one of the largest transplant centers but we only do 12 to 15 transplants a year, heart transplants a year. So we know how difficult it is to get higher numbers of samples and we know how it must be the same for all other cohorts. So we really hope with these types of collaborations we can actually start doing genetic studies in heart transplants.
Jane Ferguson: Interesting. Okay, so can people go to iGeneTRAiN.org ...
Dr. Van Setten: Yes.
Jane Ferguson: ... and then find your contact details?
Dr. Van Setten: For sure.
Jane Ferguson: Or maybe email you directly and ...
Dr. Van Setten: That's also fine. Yeah. So you can email me on firstname.lastname@example.org.
Jane Ferguson: Awesome. Alright, thank you Jessica.
Dr. Van Setten: Yeah.
Jane Ferguson: I'd like to give a special thanks to all the poster presenters who agreed to share their unpublished research with you via this podcast. And I'd like to thank you for listening. Talk to you next month.
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