Podcasts about abcg1

This month on Episode 34 of Discover CircRes, host Cynthia St. Hilaire highlights four original research articles featured in the March 4 and March 18th issues of Circulation Research. This episode also features a conversation with Dr Mireille Ouimet and Sabrina Robichaud from the University of Ottawa Heart Institute to discuss their study, Autophagy is Differentially Regulated in Leukocyte and Non-Leukocyte Foam Cells During Atherosclerosis.   Article highlights:   Pauza, et al. GLP1R in CB Suppress Chemoreflex-Mediated SNA   Lim, et al. IL11 in Marfan Syndrome   Hohl, et al. Renal Denervation Prevents Atrial Remodeling in CKD   Liu, et al. Smooth Muscle Cell YAP Promotes Arterial Stiffness   Cindy St. Hilaire:        Hi and welcome to Discover CircRes, the podcast of the American Heart Association's journal, Circulation Research. I'm your host, Cindy St. Hilaire from the Vascular Medicine Institute at the University of Pittsburgh, and today I'm going to be highlighting articles from our March issues of Circulation Research. I'm also going to speak with Dr Mireille Ouimet and Sabrina Robichaud from the University of Ottawa Heart Institute, and they're with me to discuss their study, Autophagy is Differentially Regulated in Leukocyte and Non-Leukocyte Foam Cells During Atherosclerosis.   The first article I want to share is titled GLP1R Attenuates Sympathetic Response to High Glucose via Carotid Body Inhibition. The first author is Audrys Pauza, and the corresponding authors are Julian Paton and David Murphy at the University of Bristol.   Cindy St. Hilaire:        Hypertension and diabetes are risk factors for cardiovascular disease. And yet, for many patients with these two conditions, lowering blood pressure and blood sugar is insufficient for eliminating the risk. The carotid body is a cluster of sensory cells in the carotid artery, and it regulates sympathetic nerve activity. Because hypertension and diabetes are linked to increased sympathetic nerve activation, this group investigated the role of the carotid body in these disease states. They performed a transcriptome analysis of crowded body tissue, from rats with and without spontaneous hypertension. And they found among many differentially-expressed genes that the transcript encoding glucagon-like peptide-1 receptor or GLP1R, was considerably less abundant in hypertensive animals.   Cindy St. Hilaire:        This was of particular interest because the gut hormone GLP-1 promotes insulin secretion and tends to be suppressed in Type 2 diabetes. Moreover, GLP1R agonists are already used as diabetic treatments. This group showed that treating rat carotid body with GLP1R agonist suppresses sympathetic nerve activation and arterial blood pressure, suggesting that these drugs may provide benefits in more than one way. Perhaps the carotid body could be a novel target for lowering cardiovascular disease risk in metabolic syndrome.   Cindy St. Hilaire:        The second article I want to share is titled Inhibition of IL11 Signaling Reduces Aortic Pathology in Murine Marfan syndrome. The first author is Wei-Wen Lim, and the corresponding author is Stuart Cook and they're from the National Heart Center in Singapore. People with the genetic connective tissue disorder Marfan syndrome, are typically tall and thin with long limbs and are prone to skeletal, eye and cardiovascular problems, including a life-threatening weakening of the aorta. While Marfan syndrome patients commonly take blood pressure-lowering treatments to minimize risk of aortic aneurysm and dissection, there's currently no cure for Marfan syndrome or targeted therapy.   Cindy St. Hilaire:        The cytokine IL11 is strongly induced in vascular smooth muscle cells upon treatment with the growth factor TGF-beta, which is over activated in Marfan syndrome patients. And TGF-beta is also considered a key feature of the syndrome's molecular pathology. This study found that IL11 is strongly upregulated in the aortas of Marfan syndrome model mouse, and that genetically eliminating IL11 in these animals protected them against aortic dilation, fibrosis, inflammation, elastin degradation and loss of smooth muscle cells. Treating Marfan syndrome mice with anti-IL11 neutralizing antibodies exhibited the same beneficial effects. These results suggest that perhaps inhibiting IL11's activity could be a novel approach for protecting the aortas of Marfan syndrome patients.   Cindy St. Hilaire:        The next article I want to mention is titled Renal Denervation Prevents Atrial Arrhythmogenic Substrate Development in Chronic Kidney Disease. The first authors are, Mathias Hohl, Simina-Ramona Selejan and Jan Wintrich, and the corresponding authors also Mathias Hohl, and they're from Saarland University. People with chronic kidney disease have a two to three fold higher risk than the general population of developing atrial fibrillation, which is a common form of arrhythmia that can be life-threatening. Chronic kidney disease is associated with activation of the sympathetic nervous system, which can be damaging to the heart. Thus, this group examined myocardial tissues from atrial fibrillation patients with and without chronic kidney disease to see how they differ. They found that atrial fibrosis was more pronounced in patients with both conditions than in patients with atrial fibrillation alone, suggesting that chronic kidney disease perhaps exacerbates or even drives arterial remodeling.   Cindy St. Hilaire:        Sure enough, induction of chronic kidney disease in rats led to greater atrial fibrosis and incidence of atrial fibrillation than seen in the control animals. Renal denervation is a treatment in which the sympathetic nerves are ablated, and it's a medical procedure that's used for treating uncontrolled hypertension, and it has also been shown in animals to reduce atrial fibrillation. Performing renal denervation in the rats with chronic kidney disease reduced atrial fibrosis and atrial fibrillation susceptibility. This study not only shows that chronic kidney disease induces atrial fibrosis and in turn atrial fibrillation, but also suggests that renal denervation may be used in chronic kidney disease patients to break this pathological link and prevent potentially deadly arrhythmias.   Cindy St. Hilaire:        The last article I want to highlight is titled YAP Targets the TGFβ Pathway to Mediate High-Fat/High-Sucrose Diet-Induced Arterial Stiffness. First author is Yanan Liu and the corresponding author is Ding Ai from Tianjin Medical University. Metabolic syndrome is characterized as a collection of conditions that increase the risk of cardiovascular diseases, such as obesity, hypertension and diabetes. Among the tissue pathologies associated with metabolic syndrome is arterial stiffness, which itself is a predictor of cardiovascular disease incidence and mortality. To specifically investigate how arterial stiffness develops in metabolic syndrome, this group fed mice a high-fat, high-sugar diet, which is known to induce metabolic syndrome and concomitant arterial stiffness.   Cindy St. Hilaire:        After two weeks on the diet, the animals' aorta has exhibited significant upregulation of TGF-beta signaling, which is a pathway known for its role in tissue fibrosis, and the aorta has also exhibited increased levels of yes-associated protein, or YAP, which has previously been implicated in vascular remodeling, collagen deposition and inflammation. YAP gain and loss of function experiments in transgenic mice revealed that while knockdown of protein in the animals' smooth muscle cells attenuated arterial stiffness, increased expression exacerbated the condition.   Cindy St. Hilaire:        The team went on to show that YAP interacted with and prevented the activation of PPM-1 B, which is a phosphatase that normally inhibits TGF-beta signaling and thus fibrosis. Together the results suggest that targeting the YAP, PPM-1 B pathway, could be a strategy for reducing arterial stiffness and associated cardiovascular disease risk in metabolic syndrome.   Cindy St. Hilaire:        Today, Sabrina Robichaud and Dr Mireille Ouimet from University of Ottawa Heart Institute are with me to discuss their study Autophagy is Differentially Regulated in Leukocyte and Non-Leukocyte Foam Cells During Atherosclerosis, which is in our March 18 issue of Circulation Research. So thank you both for joining me today.   Sabrina Robichaud:    Thank you so much for having us. It's a pleasure.   Mireille Ouimet:         Thank you for having us.   Cindy St. Hilaire:        Yeah, and congrats on the study. So we know that LDL particles contain cholesterol and fats, and these are the initiating factors in atherosclerosis. And it's also really now appreciated that inflammation in the vessel wall is a secondary consequence to this lipid accumulation. Macrophages are an immune cell that, in the context of the plaque, gobble up this cholesterol to the point that they become laden with lipids and exhibit this foamy appearance, which we now call foam cells. And these foam cells can exhibit atheroprotective properties, one of them called reverse cholesterol transport, and that's really one of the focuses of your paper. So before we dig into what your paper is all about, could you give us a little bit of background about what reverse cholesterol transport is in the context of the atherosclerotic plaque? And maybe introduce how it links to this cellular recycling program, autophagy, which is also a big feature of your study.   Mireille Ouimet:         Yes, so the reverse cholesterol transport pathway is a pathway that's very highly anti-atherogenic. It's linked to HDL function and the HDL protective effects, in that HDL can serve as a cholesterol acceptor for any excess cholesterol from arterial cells or other cells of the body and return this excess cholesterol to the liver for excretion into the feces. There is also trans-intestinal cholesterol efflux that can help eliminate any excess bodily cholesterol. Mireille Ouimet:         So reverse cholesterol transport is a way that we can eliminate excess cholesterol from foam cells in the vascular wall, and that's why we're really interested in the process. But the rate-limiting step of cholesterol efflux out of foam cells in plaques is actually, they have to be mobilized in the form of free cholesterol to be pumped out of the cells through the action of the ATP-binding cassette transporters. And so the rate-limiting step of the process is the hydrolysis of the cholesterol esters and the lipid droplets, because that's where the excess cholesterol is stored in foam cells.   Mireille Ouimet:         And so for years, people investigated the actions of cytosol like lipases in mobilizing free cholesterol from lipid droplets, although the identity of those lipases are not well-known and in macrophage themselves, but our recent work showed a role for autophagy in the catabolism of lipid droplets. And in fact, in macrophage foam cells, 50% of lipid droplet hydrolysis is attributable to autophagy while the other half is mediated by neutral lipases, which makes it really important to investigate the mechanisms of autophagy-mediated lipid droplet catabolism.   Cindy St. Hilaire:        That is so interesting. I guess I didn't realize it was that significant a component in that kind of rate-limiting step. That's so cool. So really, a lot of the cholesterol efflux studies, and maybe this is just limited to my knowledge of a lot of these cholesterol efflux studies, but to my knowledge, it's been really focused on the foam cell itself, the macrophage foam cell. However, there's been a lot of recent work that has now implicated vascular smooth muscle cells in this process. So could you share some of the research specific to smooth muscle cells and smooth muscle-derived foam cells that led you to want to investigate the contributions of smooth muscle cell-derived foam cells in cholesterol efflux?   Mireille Ouimet:         Yeah, so you're right in the sense that macrophages have always been the culprit foam cells in the atherosclerotic plaques but pioneering work from several groups, including Edward Fisher and Gordon Francis, they've shown that the smooth muscle cells can actually acquire a macrophage-like phenotype becoming lipid-loaded and foamy. And there's been work specifically looking at the ABC transporters, and their ability to efflux cholesterol from these vascular smooth muscle cell-derived foam cells, because as they trans-differentiate into macrophage-like cells, they acquire the expression of ABCA1, but this is to a lower extent, as compared to their macrophage counterparts.   Mireille Ouimet:         And the efflux is defective because there's an impairment in liposomal cholesterol processing of the lipoproteins that's really important to activate a like cell, and the expression of the ABC transporters, so vascular smooth muscle cell-derived foam cells are very poor effluxes.   Sabrina Robichaud:    There's very few studies that look at the vascular smooth muscle cell foam cells, and the very few that did look at it mostly focused on the ABCA1 transporters, and did show that they were poor effluxes. And as we all know, ABC1 is not the only cholesterol transporters that can transport cholesterol out of cells, there's also ABCG1 which is also one of our major findings in our paper.   Cindy St. Hilaire:        Can you tell us a little bit about the models you chose in the study and why you picked them? And also maybe a step back in terms of, what are the pros and cons of using mouse models in atherosclerotic studies?   Sabrina Robichaud:    So we chose to use the GFP-LC3 reporter mouse model because it allows us to track in lifestyle the movement of LC3, which is the main component of the autophagosome which is involved in pathology. So by using this reporter model, we could infer whether or not the cells had high autophagy or low autophagy. And to induce atherosclerosis in these mice, instead of backcrossing them to either an LDLR knockout or an ApoE knockout, we chose to do the adeno-associated virus that encode the gain of function PCSK9 instead to kind of minimize the time for breeding. It did have the effect that we needed in terms of raising plasma cholesterol to induce the atherosclerosis. So that was one of the models that we used in our paper.   Mireille Ouimet:          There's not very many good mouse models to study autophagy flux in vivo and GFP-LC3 is kind of the main one currently. We're working on developing some other tools to track lipophagy in vivo, but these things take time to put in place. So in the future, we hope to have some better tools to track lipophagy in real-time in vivo.   Cindy St. Hilaire:        How difficult is it to measure autophagy flux in vivo? I know there's certain part like LC3 or P62, a lot of people use a western blot and it's like, oh, it's high, it must be active, but it's a flux. So it's a little bit more... There's more subtleties to that, dynamic than that. So how difficult is it to really measure this flux in in vivo tissues?   Mireille Ouimet:         Yes, so now there are more recent mouse models that have been developed more recently to replace kind of the GFP-LC3 is the Rosella LC3. So it has both a red and a green tag, and so two LC3, so when autophagosomes are fused to lysosomes and are degraded, then there's preferential quenching of the GFP first, and then you have the red appearance that predominates so we know that then it's kind of like it a live flux measurements. Because we use the GFP-LC3 mouse, Sabrina treated her cells ex vivo. When we dissected out the aortic arches, digested the cells then we divided those into two components and added bafilomycin so that we can inhibit lysosome acidification to see the changes in the flux. And that's really to get the differences in untreated versus bafilomycin-treated.   Mireille Ouimet:         When we inhibit the lysosome, then we're sure that it is a functional flux or not. But it's kind of an indirect way of measuring it, and it reads very complex when we're talking about P62 and LC3 degradation with or without lysosome inhibition, but you really need that lysosomal inhibition, to show that if you block the degradation of the autophagosomes that fuse in with a lysosome, then you get an increase in the LC3 and the P62, and that's when you know that the flux is you intact.   Mireille Ouimet:         Because you could get an increase in LC3, that's just related to a defect in the breakdown of the autophagosome. But in our study, we've used phosphorylated ATG16L1, which is a now better marker of active autophagy. And I would recommend researchers to begin to use that rather than the combination of P62 and LC3 together with or without a lysosome inhibitors such as- Cindy St. Hilaire:        Oh, interesting. So let's repeat that, phosphorylated ATG-   Mireille Ouimet:         16L1, yes. So there's been an antibody that was developed by a colleague at the University of Ottawa, Dr Ryan Russell, and it's commercially available through cell signaling now, and it really has been a great tool to track active autophagy.   Cindy St. Hilaire:        That's great. I remember my lab was looking at that at one point, and I was trying to explain the flux as... I don't know if people are going to remember this, but there's this amazing, I Love Lucy skit, where her and Ethel are working on a chocolate factory conveyor belt, and it picks up speed. And because she can't get it all done quick, she starts stuffing them in her mouth. And it's like, if you just took a snapshot of that, you would not know whether it's going too fast, or not functioning properly. And so I equate the flux experiments to that. Which are probably aging myself a lot on so.   Cindy St. Hilaire:        All right, so sticking to kind of the autophagy angle, what were the differences you found in autophagy in early and late atherosclerotic plaques? Because I know you looked at those two time points, but also, importantly, between the macrophage foam cells and the smooth muscle cell-derived foam cells?   Sabrina Robichaud:    So surprisingly, there weren't that big of a difference between each time point when we were looking at the individual cell type by themselves. Surprisingly, we did find that the macrophages did have a functional autophagy flux, even at the later stages of atherosclerosis, which was kind of interesting in itself. But when we looked at the vascular smooth muscle cell foam cells, though, that was a whole other story, and we found that these were actually defective at a very early stage and stayed defective up until the very late stage of atherosclerosis.   Cindy St. Hilaire:        And what is the very early stage like? What's that definition with the smooth muscle cell?   Sabrina Robichaud:    So we did a six-week time points in terms of our atherosclerosis study, and then a 25-week time point. So there are far apart, which shows like the very early, early stage and what would be considered the most effective autophagy at that point with the necrotic core and everything. So surprisingly, the two phenotype were quite similar at early and both late stages for both cell types, but were functional in the macrophages but dysfunctional in the smooth muscle cells.   Cindy St. Hilaire:        So you mentioned at one point in the discussion that you observed inconsistent lipid loading of the smooth muscle cells, and you mentioned that a lipase, which is excreted from the foam cells can then be internalized by, I assume kind of neighboring or in the vicinity, smooth muscle cells. And so the question I had it's kind of one of those chicken-and-egg question, and it's, is the smooth muscle cell-derived foam cell an independent process? Does it happen alone or de novo as a function of a smooth muscle-mediated process? Or is it really dependent first on this macrophage foam cell providing this lipid that is efflux that is then internalized by a smooth muscle cell that kind of goes on to become a foam cells. It's kind of a question of like the continuum of an atherosclerotic plaque and what do you think is happening, either based on your data or just kind of a hunch?   Mireille Ouimet:         That's an excellent question. And there's no doubt that macrophages really drive the initiating events of atherosclerosis. So I don't think that without the macrophage there would ever be a vascular smooth muscle cell, or there would be minimal vascular smooth muscle cell-derived foam cells. Definitely the inconsistencies that we observed in our study, were if we added like aggregated LDL on its own to a primary mouse vascular smooth muscle cell, we would get poor lipid loading and a very low percentage of those cells that would become foamy, relative to treating them with cyclodextrin complex cholesterol, for instance.   Mireille Ouimet:         So free cholesterol, that's cell permeable, will go into the vascular smooth muscle cell, no problem, and generate the foaminess and then allow that cell to acquire the macrophage-like phenotype. But aggregated LDL on its own in our hands, just gave very poor loading. And when we treated the vascular smooth muscle cells with aggregated LDL along with macrophage-derived condition media, we got some improvements, but it was still kind of inconsistent. But then we thought if we treat the vascular smooth muscle cells with aggregated LDL in the presence of conditioned media from macrophage foam cells that were preloaded with the aggregated LDL, would that promote their foaminess to a greater extent? And it did.   Mireille Ouimet:         So, there have been studies from Gordon Francis's lab that showed that adding recombinant lysosomal acid lipase to vascular smooth muscle cells that contained aggregated LDL, promoted the lysosomal hydrolysis of the aggregated LDL and to generate the foamy macrophages and allow the lysosomal processing. So we know that that vascular smooth muscle cells take up lysosomal acid lipase, and we know that macrophages undergo lysosome exocytosis and they can secrete lysosome acid lipase and acidify the extracellular milieu.   Mireille Ouimet:         So work from Fred Maxfield group has shown the presence of these cell surface connected compartments that are acidified, containing macrophage-derived lysosomal acid lipase, that even hydrolyze extra cellularly-aggregated LDL for macrophages. So we're not sure whether there's probably a local production of free cholesterol in the plaque by macrophages, this free cholesterol could be taken up by the vascular smooth muscle cell. And also the vascular smooth muscle cells do express some scavenger receptors, whether the expression of these scavenger receptors like LRP or CD36 even goes up when they've taken up a little bit of the free cholesterol. And then that allows the aggregated LDL to come in and then there would be some lysosomal acid lipase secreted by the macrophage foam cells that would promote the lysosomal processing of this aggregated LDL. All of those are very complex questions that will require some addressing in vivo models.     Cindy St. Hilaire:        You also mentioned in the paper that studies... There's a handful of them now. Studies have shown that between 30% and 70% of the cells that are staining positively for macrophage markers, meaning they're foam cells, are of the smooth muscle cell lineage. And so I believe people have seen that in mouse plaques with lineage tracing, but they've also used newer techniques to really see this also in human atherosclerotic plaques. So we know it's not just from a mouse, we know that smooth muscle cells can turn into a macrophage-like foam cell, and it's 30% to 70%, which is a huge range. Cindy St. Hilaire:        So do we know the factors that dictate whether a specific plaque is going to have more or less smooth muscle cell derived foam cells? And I guess more important to what you found in your paper is, how important would it be to know whether a plaque is on the 30% end or on the 70% end in terms of therapeutic strategies?   Sabrina Robichaud:    Yeah, most of these studies, the range can be attributed to the different time points at which these studies have been collected early on will be a little bit more macrophage understanding would be at a later time point. Now of course in terms of therapeutics, as we saw in our paper, metformin actually will positively increase cholesterol efflux in the vascular smooth muscle cell foam cells, but not in the macrophages. So obviously, being able to know at which point there's a majority of macrophages versus vascular smooth muscle cells, definitely going to determine which therapeutic we're going to be able to use.   Sabrina Robichaud:    Ideally, we would be able to find a therapeutic that would work in both foam cell, but from what we've seen, the mechanistic behind the autophagy dysfunction between both cell types are so different, that I'm not entirely sure that that would be possible, we would need some sort of combination therapy. But again, we need to be a little bit more targeted depending on the percentage of the foam cells that are comprising the plaque at that particular moment in time.   Cindy St. Hilaire:        Yeah, so you mentioned there's a function of time there. If you look earlier, there's more macrophage, if you look later, the percent of smooth muscle cell-derived foam cell increases. Is there a point in a very advanced atherosclerotic plaque where it's just mostly smooth muscle cells? Or do those macrophage foam cells stay, and it's just the increasing number of smooth muscle cell-derived foam cells? Do we know?   Mireille Ouimet:         This is an excellent question, and I was going to bring up the topic of clonal expansion of the vascular smooth muscle cells. So it's a very heterogeneous population and understanding that might be some of the differences that we see in different studies. It could be the model has one type of a smooth muscle cell that's expanding more than another, what are the factors that govern that? Does one clone take over at the later stages versus the earlier stages? We don't know.   Mireille Ouimet:         But we were surprised in our studies to see that the macrophages that are present at least on the lumen of the plaques were very active in autophagy. They had the highest staining for the phospho-ATG16L1 in that late stage. So we're not sure if it's newly-recruited macrophages that come in, that are more active and in autophagy, and then have good lysosomal capacity that keeps degrading the lipid present in the plaque and tries to ingest it, but also as a consequence keeps releasing some of the degraded cholesterol into the milieu where the smooth muscle cells that are proliferating are internalizing it and becoming more foamy. So these are really great open questions that need to be addressed in the field.   Cindy St. Hilaire:        So drug-eluting stents are coated with rapamycin or the various chemical compositions that are derived from rapamycin. And rapamycin itself induces autophagy. So while the thought behind using this coating on stents was to prevent smooth muscle cell proliferation, and thus restenosis or ingrowing of the stent, your study suggests that this could also help to promote autophagy in the cells underlying the stent. So has anyone gone in and looked at plaques that have been stented and either failed or not, and investigated the foam cell content or markers for autophagy activity?   Mireille Ouimet:         Not to my knowledge, and this has been something we've definitely... We think that this is what's happening. Some of the protective effects of these drug-eluting stents that have everolimus or sirolimus or the rapamycin or rapamycin analogs, we do believe that some of their protective effect can be attributed to autophagy activation, but this remains to be demonstrated. We think that autophagy activation locally would promote reverse cholesterol transport and would be one of the processes that prevents restenosis because we can promote the efflux of cholesterol out.   Cindy St. Hilaire:        Great. So I guess stemming from my question on the stents, what are the other translational implications of the findings of your study? And what would you like to see come out of this?   Mireille Ouimet:         So one of the things is, as Sabrina mentioned, would be to target both foam cell populations because it seems as though the vascular smooth muscle cell foam cells are very much defective in their autophagy capacity, and they're very poor effluxes, but we could potentially restore autophagy in the cell population to promote reverse cholesterol transport.   And looking at prevention of atherosclerosis is a bit different than looking at regression, because regression is at a later stage where the plaques are more advanced. And if they're mostly vascular smooth muscle cell-derived, maybe then those drugs that we're considering that protect against the development of atherosclerosis are effective on the macrophage themselves early on, but might not be mimicking what we would see in the clinic where the patients that present are older.   Cindy St. Hilaire:        Yeah, it's kind of really reminiscent of like the CANTOS trial and like, where do we want to target the therapy? It's going to be very different if it's an early smaller plaque, versus a late-stage possibly pro close to rupturing type of plaque. Well, Sabrina Robichaud and Dr Ouimet, thank you so much for joining me today. Congratulations again on a wonderful study, and I'm really looking forward to hearing more about this from your group.   Sabrina Robichaud:    Thank you.   Mireille Ouimet:         Thank you very much. And we also want to thank all the co-authors on the study, specifically also Adil Rasheed, who is co-first author on the work and Katey Rayner's group for all the support and involvement in this study.   Cindy St. Hilaire:        That's it for the highlights from the March issues of Circulation Research. Thank you for listening. Please check out the CircRes Facebook page and follow us on Twitter and Instagram with the handle @circres and #DiscoverCircRes. Thank you to our guests, Sabrina Robichaud and Dr Mireille Ouimet Sabrina. This podcast is produced by Ashara Ratnayaka, edited by Melissa Stoner and supported by the editorial team of Circulation Research. Some of the copy text for highlighted articles was provided by Ruth Williams. I'm your host, Dr Cindy St. Hilaire and this is Discover CircRes, you're on-the-go source for the most up-to-date and exciting discoveries in basic cardiovascular research. This program is copyright of the American Heart Association 2022, The opinions expressed by speakers in this podcast are their own and not necessarily those of the editors or of the American Heart Association. For more information, visit ahajournals.org.

Jane Ferguson:                Hello, and welcome to episode two of "Getting Personal: Omics of the Heart". I'm Jane Ferguson, an Assistant Professor of Medicine at Vanderbilt University Medical Center. This Podcast is brought to you by the Functional Genomics and Translational Biology Council of the American Heart Association.                                            If you're a current or prospective member of the American Heart Association but not yet affiliated with our council, I do encourage you to join us. FGTB is a vibrant council with a diverse membership spanning disciplines from basic research to clinical practice, with shared interests in genomics, precision medicine and translational research.                                            You can find out more by going to the AHA professional website at professional.heart.org and selecting FGTB from the list of scientific councils. If you're listening to this, you've obviously already figured out a way to access this Podcast. We do have several convenient options to make sure you never miss a new episode. You can stream each episode and find additional information on links to articles on the Podcast website fgtbcouncil.wordpress.com. You can also subscribe to the Podcast on iTunes or if you are an Android user, you can subscribe via Google Play. Just search for "Getting Personal: Omics of the Heart" and click, Subscribe.                                            In this episode, Kiran Musunuru talks to Erik Ingelsson about research from his group on epigenetic patterns in blood and how these relate to coronary heart disease, which was published in the February 2017 issue of "Circulation: Cardiovascular Genetics".                                            We highlight a recent AHA Science Advisory on merging electronic health record data and genomics, and Naveen Pereira and I discuss precision medicine and whether it can live up to the hype. Kiran Musunuru:             Hello. This is Kiran Musunuru. I'm on the faculty at University of Pennsylvania and it's my pleasure to represent the Functional Genomics and Translational Biology Council of the American Heart Association. Today I have the privilege of interviewing Dr. Erik Ingelsson who is Professor of Medicine in the Division of Cardiology at Stanford University School of Medicine. We're going to be discussing a very nice paper on which he is senior author that was published last month in "Circulation: Cardiovascular Genetics" titled "Epigenetic Patterns in Blood Associated With Lipid Traits Predict Incident Coronary Heart Disease Events and Are Enriched for Results From Genome-Wide Association Studies". It's all right there in the title. Erik, welcome. Erik Ingelsson:                 Thanks. Kiran Musunuru:             It's a pleasure to have you. Maybe you can say a word or two to introduce yourself and your research interests. Erik Ingelsson:                 Yeah, it's a pleasure to be on. Yes, as you said I'm a professor of Medicine at Stanford, an MD, PhD trained really in epidemiology but started to do genetics about 10 years ago. I've been most of my career in Sweden but moved to Stanford now about one and a half year ago. I'm doing broadly studies within omics and molecular epidemiology but also have a translational part where I do [inaudible 00:03:29] and model systems. Kiran Musunuru:             That's great. To the subject at hand, so I think we all appreciate how, with the completion of the Human Genome Project about 15 years ago now, genetics has really taken off. What's interesting is, over the last few years, there's been a bit of a shift in focus from genetics to the layer of regulation that lies right above genetics and that's epigenetics, so modifications of DNA and the proteins that are bound to DNA and how this interacts with genetic expression and then has consequences in terms of clinical traits and diseases.                                            What caught my eye about your study is that you're actually looking at epigenetic regulation of gene expression but not in a very traditional, one locus at a time or one gene at a time fashion, but really in a genome-wide fashion. Whereas, starting in 2005, we started to see genome-wide association studies. Now we're starting to see, just over the last few years, epigenome-wide association studies.                                            Personally speaking, one of my research interests is lipid traits. I thought it was very nice how you were able to apply an epigenome-wide association study to lipid traits and actually find some very interesting things. Why don't I start by asking you simply describe the main goals of your study. Erik Ingelsson:                 As you've already referred to, we wanted to look at variation in DNA methylation, which is one of the ways to look at epigenetics. I think either it's the most common way to look at epigenetics, at least if you want to do it genome-wide. We looked at variation in DNA methylation in relation to circulating lipid levels, and we did this through this epigenome-wide study and in whole blood derived DNA.                                            We did it with about 2,300 individuals from the Framingham Heart Study and from the PIVUS cohort, and then we had an independent external replication in about 2,000 additional individuals.                                            In addition to looking at these DNA methylation associations with lipids, we also wanted to look at these DNA methylation patterns in relation to incident coronary heart disease. We also wanted to integrate all of this with genetic variation, gene expression and also actually with metabolites through metabolomics. The whole idea here is trying to understand genomic regulatory mechanisms that link lipid measures to coronary heart disease risk. Kiran Musunuru:             That's one thing I really liked about this paper, how you really took it all on. It wasn't just one particular type of omics analysis. It started with epigenomics but then you really went the extra mile, I thought, to connect it to genetic variation, and then to disease, and to metabolomics and so it was very comprehensive that way. Why don't we discuss the actual findings. You actually found quite a bit in your analysis, didn't you? Erik Ingelsson:                 Yeah. I think some of it were already actually in the title. We did, as I said, several different layers of things. The first thing was really to look at methylation patterns. We looked at CpG sites across the whole genome, and we identified almost 200 such sites that were different lipid levels in the discovery but then going to the replication stage, we had a little bit more than 30 of them being replicated and 25 of them had never been reported in relation to lipids before. That's one layer, so it is new associations. A lot of the genes that were then enriched they were involved in lipids and amino acid metabolism so it makes a lot of sense biologically.                                            There is the one example of an interesting finding there with ABCG1 that we perhaps can discuss a little bit later. Other larger things that we found was that there was a lot of cis-methylation quantitative triglycerides so that means that there were a lot of genetic variants that were associated with these methylation levels. In fact, actually, 64% of all of the CpG sites that we found, they also had genetic variance determining the level of the methylation. So quite large fraction being genetically determined. We also- Kiran Musunuru:             That's actually quite interesting because typically when you hear it in the lay press or what not about epigenetics, they tend to equate epigenetics with more environmental influences. It's a simple dichotomy or simplistic dichotomy of your genes are what you're born with but then epigenetics is the way that environment actually modifies your genetics in ways. But what you're suggesting from your findings is that it's actually genetic variation itself that could be directly responsible for epigenomic variation, which then would have effects on gene expression. Erik Ingelsson:                 I agree. I think we're seeing a shift a little bit in this field. Again, my background is not really within that genetics field so I'm a little bit on the side here but what I see is that it's come more from an approach or focus really on inherited epigenetic changes so studies in animals, primarily, I guess a lot, but also in some human studies so more on that level to something that had been, as you mentioned, a lot of focus on environment causing methylation changes and now almost more into a focus of gene regulation and then gene expression and that focus.                                            Perhaps the ENCODE project and the Epigenome Roadmap and those projects have moved this field a little bit towards more focus on gene regulation and gene expression and that's kind of a part, a linking variation to gene expression. I think we're seeing a shift a little bit in that field. Kiran Musunuru:             That's very interesting. Can you give an example of a particular locus or particular gene where epigenetic regulation really seems to be playing an important role, not just with respect to lipids but even, perhaps, connecting to disease. I think you'd mentioned ABCG1 very briefly. Erik Ingelsson:                 That's actually a pretty interesting locus. It's been recorded in the past, as well, in relation to methylation but we linked it all together. Basically, we see this intronic variant here where the minor allele is associated with increased methylation at the CpG site in that 5 prime UTR region of this gene of ABCG1 and then so that minor allele leads to increased methylation. It also leads to decreased expression of ABCG1 in blood. I think that makes sense. Quite often in the past, people have recorded that increased methylation should decrease expression.                                            As we see that, we also see an effect on triglyceride levels and HDL levels as well and, interestingly, also, on the risk of coronary heart disease. In addition, also, associations with several of the metabolites, so single myelins and[karomites 00:11:40] which have also been implicated in coronary heart disease in some prior studies. It all comes together quite nicely at this locus where you have a minor allele increasing methylation, decreasing expression, increasing triglyceride levels and increasing the risk of coronary heart disease along with increases in some of the metabolites that also have been linked to coronary heart disease. Kiran Musunuru:             Wow. Fascinating. Erik Ingelsson:                 Yeah, I think it's pretty interesting, actually. We could link it all together in the study. Kiran Musunuru:             That's very nice. Another aspect of this study that caught my attention is that you really did it in a fairly rigorous way. You had your discovery cohorts in which you did the initial screen or the initial association study, but then you also had replication cohorts where you were then able to go independently test your findings and then accrue more evidence or lack of evidence for replication in the ones for which there was evidence of replication, those are, obviously, much more stronger results.                                            I expect that we have among our listeners trainees who might be interested in hearing more about how you were able to assemble so many different cohorts to be able to get this study done. Erik Ingelsson:                 I think that's an important question. I would say that it goes back a little bit to the development that we've seen in genomics in the past 10 years. People coming in from gene studies to GWAS realizing that you really need to work together both because the science is better but also just if you want to establish any robust findings that can be replicated, you need to combine the data.                                            I think we've seen that for GWAS clearly, but I think we're starting to see that also for other [inaudible 00:13:28] approaches as we move forward. Because all of these approaches are prone to false-positives so if you just do your analysis in your own data, then you're more likely to report false-positives and you need replication.                                            I think we're lagging behind a little bit for epigenomics and other omics methods, but we're truly starting to see this happening also in other omics fields. I think, in a sense, the field is prime for collaboration and then I'm talking about the broad, molecular epidemiologist field or the people having cohorts and this kind of data, they're all used to working together from the GWAS era and also realize the need for it. I think for that reason it's usually not that difficult to get people together.                                            Then how do you do it practically? It's easier if you know people, of course, since before and that's probably more common nowadays than it would have been 15, 20 years ago because you always used to work with people in the GWAS era and you can even add a junior level set up these collaborations because you might have been involved in some other collaboration before and know some postdocs in some other labs, etc.                                            That might be one way to go about but the other thing is also that you have an interest in a certain phenotype and then you reached out to people that you think have the data. You can know about either from other publications and other phenotypes or on the same phenotype or just by word of mouth you know it since you've met people at conferences, you've seen some poster on the same phenotype, etc.                                            I would say that people, in general, are very open to collaborations, and I think we've seen that change and shift of the past 10 years. I think we see it now also for other omics methods, and I definitely do think that's the way forward. To report more robust findings, in general. Kiran Musunuru:             In closing, I'd say that seeing your study and seeing the very nice results, it seemed very promising with respect to what we're going to find going forward and doing epigenetic studies. Do you see more of this happening in the near future? Maybe even what happened with GWAS where it just got increasingly larger and larger studies and finding more and more results as these studies became increasingly powered.  Erik Ingelsson:                 Yeah, I think so. I think for epigenomics, as with some other omics, I think we will see the same development that we saw with GWAS, which is the people start to publish in relatively small settings with perhaps a few discovery cohorts, a few replication cohorts, and that parts happen kind of independently of each other. Then the next stage is you're grouping together and you're starting to involve other people as well and these consorts get larger and larger.                                            I think the value of this data can be exponentially increased if you can actually combine it with other data sets. We've seen that in genomics. There's a large return on your investments by collaborating with other people. I definitely do see the same kind of development happening here, as well. Kiran Musunuru:             Well, Erik, thank you so much. That's all the time we have for today but we greatly appreciate your taking the time out of your busy schedule to discuss with us this really nice paper that you and your colleagues published very recently. I would encourage all of our listeners to go take a look at the paper themselves. As I recall, this particular paper is open access so it should be freely available to anyone who is interested. Is that correct? Erik Ingelsson:                 Yes, it's an open access. And thanks, Kiran. It was a pleasure. Kiran Musunuru:             Thank you very much. Jane Ferguson:                An AHA Science Advisory from the FGTB Council published in 2016 focused on the challenges and the potentials in merging electronic health data with genomics data to advance cardiovascular research. Jennifer Hall, John Ryan and colleagues published this on behalf of the Functional Genomics and Translational Biology Council as well as the councils on clinical cardiology, epidemiology and prevention, quality of care and outcomes research and the stroke council.                                            As electronic health records have become ubiquitous in medical practice, there is an opportunity to utilize existing stored data and add new types of data to the EHR to facilitate research through EHR-coupled biobanks and to improve patient care through the use of precision medicine approaches based on genomic and clinical data stored in a patient's record.                                            While logistical and ethical considerations remain, this is an area with great promise. You can read more in the Science Advisory published in the March 2016 issue of "Circulation: Cardiovascular Genetics", which along with all the papers mentioned in this episode, are linked on the Podcast website at fgtbcouncil.wordpress.com                                            This Podcast has the focus of precision medicine, and I saw an interesting back and forth in the JAMA comments section about the hype of precision medicine. I think even those of us who are fond of precision medicine would agree that there's probably a certain amount of hype surrounding it.                                            There was this interesting opinion published in JAMA last October addressing the question of, will precision medicines really have an impact on population health? I think there is some important points that really to improve population health, there may be other options rather than precision medicine, which may be more focused on the individual or on certain subgroups, which may not actually raise the broad population's health.                                            But then there was response to that published in JAMA in January, which was arguing against it. I thought it would be some interesting thing for us to talk about a little to see do we agree? Is this over-hyped? Or is precision medicine really something that could fundamentally change population and individual level of health in the future? Naveen Pereira:              I agree. There seems to be a tension between precision medicine that stresses on the individual and using omic technology and molecular markers to determine individualistic response or characteristics and population health in general, which looks at population trends. Both of them in principle and philosophy appear to be deferring fields. I guess the question is how do we integrate both of them to improve overall, not only individual but large population health? Jane Ferguson:                I think there's probably some disconnect maybe between what people think of as precision medicine and what sort of things it includes because I think our first thought could be that precision medicine is very much based in genetics and genetic risk scores, using genotype as a way to predict an individual's response to a drug or their risk of disease.                                            I think maybe one of the things we have to think about with precision medicine is to encompass all of these additional omic technology. So, yes, genotype alone is unlikely to really affect population health on a broad scale, but when you add in gene expression and proteomic biomarkers, metabolomics and microbiomes, I think then we do start to get to a point where it's mathematically complex but it would theoretically be possible to predict risk and implement precision medicine approaches, even on a large-population scale. Naveen Pereira:              Right. One of the things I've always wondered is should we move away from our traditional classification of disease? For example, hypertension. Is all hypertension the same? We know it's not, it's such a heterogeneous disease process. Are we still stuck in the 19th century where we think of hypertension as blood pressure? Should we move away from that? Should we integrate all this great input from omics technology and phenotype hypertension is a better disease process, which would, perhaps, improve outcomes. Jane Ferguson:                I think that's a great point. Honestly, probably a lot of the challenge in this is just us in thinking about things differently. You're right. We're very used to thinking of hypertension and we recognize it, we treat it. But it really is just ... The underlying causes of hypertension in the individual may be very different and it may need very different treatments.                                            I think a paradigm shift is probably needed in thinking about a lot of these complex diseases. Diabetes is another one where really that's the causes and then the way it progresses in different individuals is probably really distinct subtypes of disease rather than being one broad disease that we can classify as such. Naveen Pereira:              Exactly. And that would enable, perhaps, more dramatic treatment effects, too. I keep thinking of the example in cystic fibrosis where the genetic mutation in the cystic fibrosis gene actually proved that a certain therapy for cystic fibrosis in those patients who carry that gene mutation had a dramatic response. It didn't take tens of thousands of patients to demonstrate that effect but it took several hundred patients. Jane Ferguson:                That's a great point. I think if we're accurately substratifying individuals so that we really are looking at people who really do have the same underlying causes of disease, then I think we will have a lot more power to see effects in smaller numbers of people and we can move away from these huge GWAS of hundreds of thousands of people as being necessary to find effect. Naveen Pereira:              In fact, what we could do is take some of the knowledge from precision medicine and apply it at a population level and, hence, perhaps what we need to do is integrate the two disciplines better and people need to speak to each other more often. What do you think, Jane? Jane Ferguson:                Absolutely. I think that is key. We're used to thinking about our own little narrow field and focusing on that but I think integration and finding good ways for it. The humans to integrate and also to integrate the data mathematically, I think that will be key. I think that certainly caveats, I mean, these approaches may not find everything but I think there's definitely a lot of promise that has not yet been fully exploited. Naveen Pereira:              Absolutely. Jane Ferguson:                Last time we talked, we were talking about a paper that used gene expression profiling in CAD. I think you found a really interesting paper for us to talk about this month looking at gene expression profiling but in the setting of heart transplant and heart transplant rejection. Naveen Pereira:              Yes, Jane. It's interesting to see increasing number of publications now looking at gene expression arrays and profiling for various disease states. In the March 7, 2017, issue of "Circulation", there was a very interesting paper looking at gene expression profiling and complementing the diagnosis of antibody-mediated heart rejection.                                            Just as a background, the two types of heart rejection that heart transplant recipients can have, one, is cellular rejection which we're seeing now less often due to improvements in immunosuppression; the other type of rejection is antibody-mediated rejection most often caused by anti-HLA antibodies that are directed towards the donor or what we call as donor-specific antibodies.                                            This paper, the first doctor is Alexandre Loupy and he is from INSERM Institute in Paris, France and the senior author is Philip Halloran who is from Edmonton, Canada. What they essentially did was look at 617 heart transplant patients from four French transplant centers. Out of these 617 recipients, there were 55 recipients who had antibody-mediated rejection.                                            They did a case control study, the controls being 55 recipients who did not have antibody-mediated rejection. They analyzed 240 heart biopsies in total. Unfortunately, even in this modern era, we still perform heart biopsies traditionally through the internal jugular route and endomyocardial biopsies and these biopsies are then analyzed for features of antibody-mediated rejection.                                            The International Society of Heart and Lung Transplant has standard definitions by consensus as to what is antibody-mediated rejection and their various features histopathologically and by immunostaining. We also use donor-specific antibody detection in the serum to finally make a diagnosis.                                            What this group really did was analyze these heart biopsies by performing expression microarrays and they found a very distinctive pattern in patients who had antibody-mediated rejection by traditional criteria. The gold standard was the traditional criteria, and they used the gene expression pattern to correlate it with the gold standard.                                            They found certain selective gene sets that they call antibody-mediated rejection gene sets. It involved transcripts of natural killer cells, endothelial cell activation, macrophages and interferon gamma. The area under the curve that they found using these gene expression patterns for these four gene sets was greater or equal to 0.8 which is quite good. This gene expression pattern was then validated in a separate cohort of patients from Edmonton, Canada.                                            It's an interesting manuscript, which essentially looks at using gene expression profiling in addition to traditional histopathological determination for a relatively common type of rejection in heart transplant patients to consolidate the diagnosis and give insight into pathophysiology.                                            But some of the questions that arise are we still submit patients to endomyocardial biopsies so this does not supplant the need to perform endomyocardial biopsies because this was looking at expression arrays within heart tissue. We are still struggling with the gold standard, the histological diagnosis of antibody-mediated rejection as to what it really means in patients, for example, who do not have dysfunction of the graft, or a low ejection fraction. Useful in many ways. I think it adds to the overall knowledge of this phenomena, but it may not change clinical practice significantly. Jane Ferguson:                That's really interesting. It's exciting but, you're right, we are subjecting people to heart biopsies isn't necessarily going to be a good way to monitor rejection or be able to predict in advance who is going to suffer rejection versus not.                                            I think it's definitely a very interesting study and I think, the fact that they discovered these genes that which were then validated, may give some additional insight into the underlying biology, which may help us develop new ways to start thinking about treating this unmitigating rejection. Naveen Pereira:              Right and it would be interesting to see how this corresponds to peripheral blood gene expression and whether there's an early, noninvasive way of detecting rejection. I know the Stanford group in the past has looked at circulating DNA from the donor heart, analyzed by peripheral blood, the same thing that's done in efforts to its cancer detection to see if we can pick up rejection by just a blood draw instead of doing endomyocardial biopsies. Jane Ferguson:                Yes, definitely. I wonder if this group collected any blood or is this something they may want to do in the future because I think that would be a really interesting addition to this study. Naveen Pereira:              Absolutely. Jane Ferguson:                Well, it's been great talking to you as always, Naveen, and we want to say special thank you to Rick [Andraysen 00:31:10] for the Mayo Clinic Media Support Services for helping us with this Podcast. Naveen Pereira:              Always does a great job. Jane Ferguson:                Absolutely. We'll thank everybody for listening and we'll look forward to being back with you next month with more topics related to precision medicine and getting personal with omics of the heart. Naveen Pereira:              Lot of excitement next month, Jane. Thank you.

Ein bedeutender Mechanismus zur Prävention und Regression von atherosklerotischen Läsionen ist die Abräumung von akkumulierten extrazellulären Lipiden in der Gefäßwand und deren Einschleusung in den reversen Cholesterintransport durch Makrophagen. Wichtigste molekulare Effektoren sind dabei Scavenger Rezeptoren wie CD36 und Cholesterin-Exporter wie ABCA1 und ABCG1. Deren Expression wird durch spezifische oxidierte Sterole, die die nukleären Transkriptionsfaktoren wie PPARgamma und LXRalpha aktivieren, induziert. Da hochdosierte lipidlösliche Antioxidantien diese regulatorischen Oxylipide beeinflussen könnten, war es Ziel dieser Arbeit am Makrophagen-Modell die Wirkung von hochdosiertem alpha-Tocopherol auf Signalwege und Schlüsselrezeptoren der Cholesterin-Homöostase zu untersuchen. Der Einfluss von alpha-Tocopherol und teilweise auch von gamma-Tocopherol wurde auf regulatorischer, transkriptioneller, translationeller und funktioneller Ebene mittels Realtime RT-PCR, Reportergen-Assays, FACS, Immunoblot und Lipidaufnahme- und Lipidefflux-Assays analysiert. Der LDL-R wurde durch hochdosiertes alpha-Tocopherol nicht beeinflusst, während die Expression des Scavenger Rezeptors CD36, konzentrationsabhängig sowohl auf mRNA-Ebene als auch auf Protein-Ebene durch alpha-Tocopherol beeinträchtigt wurde. Auf funktioneller Ebene verringerte alpha-Tocopherol die Aufnahme von [H³]-Cholesterin markiertem oxLDL durch Makrophagen. Der Effekt konnte ebenso mikroskopisch dargestellt werden. Die verminderte Expression von CD36 durch alpha-Tocopherol konnte zumindest teilweise durch eine dosisabhängige Verminderung der mRNA-Transkription von PPARγ und eine verminderte Aktivierung von PPARgamma im PPRE-Luziferase-Assay auch durch exogene Stimuli erklärt werden. gamma-Tocopherol hatte keinen vergleichbaren Effekt auf die CD36- und PPARgamma-spezifische mRNA, weswegen bereits auch ein direkter transkriptioneller Effekt von alpha-Tocopherol postuliert wurde. Die vermehrte zelluläre Aufnahme von oxidiertem LDL über Scavenger Rezeptoren wie CD36 induziert normalerweise auch eine vermehrte Einschleusung von Cholesterin in den reversen Cholesterintransport durch ABC-Exporter wie ABCA1 und ABCG1, wodurch die Schaumzellbildung zumindest verzögern werden kann. Diese Induktion der Cholesterin-Exporter wird durch oxidierte Sterole vermittelt, die LXRalpha aktivieren. Deshalb wurde ebenfalls eine mögliche Interferenz von hochdosiertem alpha-Tocopherol mit dem zellulären Cholesterin-Export untersucht. In der Tat wurde der Cholesterin-Efflux von Makrophagen auf delipidiertes HDL durch alpha-Tocopherol beeinträchtigt, wodurch der zelluläre Cholesterin-Bestand anstieg. Dieser Effekt zeigte auch mikroskopisch vermehrte Lipidgranula. Die Aktivierung des LXR-Response Elements im Luziferase-Assay durch exogene Stimuli wie 22-OHC oder oxidiertes LDL wurde durch alpha-Tocopherol ebenfalls negativ beeinflusst. Dadurch könnte die Reduktion der Expression von ABCA1 und ABCG1 auf mRNA-Ebene und von ABCA1 auf Proteinebene zumindest teilweise erklärt werden. Mit gamma-Tocopherol konnte nur eine geringe Reduktion auf mRNA Ebene, sowohl für ABCA1 als auch LXRalpha festgestellt werden. Bei der verminderten Expression von ABCA1 und ABCG1 durch hochdosiertes alpha-Tocopherol handelt es sich also wahrscheinlich um einen spezifischen, teilweise durch LXRalpha vermittelten Prozess. Es scheinen aber weitere Signalwege beteiligt zu sein: Unerwarteterweise wurde die Transkription und die Aktivierung von LXRalpha auch durch delipidiertes HDL stimuliert, was durch hochdosiertes alpha-Tocopherol ebenfalls dosisabhängig reduziert werden konnte. Nichtsdestotrotz war ABCA1 in Makrophagen nach Cholesterinverarmung durch delipidiertes HDL supprimiert. Die gefundenen Effekte von alpha-Tocopherol auf Schlüsselrezeptoren der Cholesterin-Homöostase in Makrophagen können zur Erklärung der enttäuschenden Resultate der Preventionsstudien mit hochdosiertem alpha-Tocopherol beitragen: Durch Hemmung des Scavenger Rezeptors CD36 reduziert alpha-Tocopherol zwar einerseits den ersten Schritt zur Schaumzellbildung um den Preis einer verzögerten Abräumung extrazellulärer Lipiddepots, alpha-Tocopherol verlangsamt aber auch durch Hemmung von ABCA1 und ABCG1, den endgültigen Abtransport von Cholesterin aus der Gefäßwand durch den reversen Cholesterin-Transport.

In dieser Arbeit wurde die zelluläre Cholesterin-Homöostase in menschlichen Zellen von Patienten mit der seltenen Tangier-Erbkrankheit (TD) untersucht. Diese Patienten besitzen verschiedene Mutationen im ABCA1-Gen, welches eine zentrale Rolle im Cholesterin-Export spielt, und haben aufgrund des niedrigen bzw. fehlenden HDL im Plasma ein erhöhtes Risiko, kardiovaskuläre Erkrankungen auszuprägen. Es ist jedoch unklar, wieso es trotz der relativ einheitlichen HDL-Defizienz zu völlig unterschiedlichen Identitätsmustern der Arteriosklerose kommt. Ziel der vorgelegten Arbeit war es, Auswirkungen des Funktionsverlustes von ABCA1 auf die Regulation der zellulären Cholesterin-Homöostase zu untersuchen. Dazu wurden Telomerase-immortalisierte Fibroblasten zweier Tangier-Patienten mit verschiedenen ABCA1-Mutationen und unterschiedlich ausgeprägter klinischer Manifestation der Arteriosklerose (TD1 und TD2) mit Fibroblasten eines gesunden Spenders verglichen. Der Cholesterin-Gehalt in TD-Fibroblasten im Vergleich zu Kontrollzellen war 1,4 bzw. 1,5-fach erhöht. Diese zelluläre Cholesterin-Akkumulation führte zur verminderten Expression der an der Cholesterin-Synthese und -Aufnahme beteiligten Gene, HMG-CoA-Reduktase und des LDL-Rezeptors. Daher war die endogene Cholesterin-Biosynthese im Vergleich zur Kontrolle um 27 % (TD1) bzw. 58 % (TD2) reduziert. Die Anreicherung von Cholesterin in den TD-Fibroblasten ging mit der verminderten Expression der Gene einher, die an der Regulation der Cholesterin-Homöostase bzw. dem Cholesterin-Export (ABCA1, ABCG1 und SREBP1c) beteiligt sind. Diese Störung war auch an einem entsprechend gegenläufigen Gehalt an Oxysterolen erkennbar (ein geringer Cholesterin-Export bewirkte einen höheren Oxysterol-Spiegel). Diese Untersuchungsergebnisse deckten jedoch gleichzeitig die Tatsache auf, dass keine strikte Korrelation zwischen einer verminderten Expression des defekten Cholesterin-Export-Gens (ABCA1) und der intrazellulären Cholesterin-Akkumulation existiert. Da die Expression von ABCA1, ABCG1 und SREBP1c laut den Ergebnissen anderer Arbeitsgruppen durch den Transkriptionsfaktor LXR reguliert wird, muß es –auf der Basis der hier vorgelegten Ergebnisse– LXR-unabhängige, aber wichtige Regulationsmechanismen des Cholesterin-Stoffwechsels geben. Die komplexe und unerwartete Regulation der LXR-Zielgene könnte erklären, warum Patient TD2 eine schwere Arteriosklerose aufweist, während Patient TD1 keinen klinischen Befund hat. Weitere Studien sind jedoch notwendig, um diese unbekannten und von Oxysterolen unabhängigen Regulationsmechanismen aufzuklären.

The gene that codes for the ABC transporter ABCG1 is located in a chromosomal susceptibility region (21q22.3) for affective disorders. Genetic variations in ABCG1 have been associated with affective disorders in Japanese males. In this study, we investigated the distribution of a G2457A polymorphism in patients with affective disorders, suicide attempters with various psychiatric diagnoses and healthy subjects, We initially found a trend towards a modest association with affective disorders in males (p = 0.046 for allele frequencies and p = 0.046 for AA versus GG). We conducted a replication study with independent patients and controls, There was no association with affective disorders, either in the replication or in the combined group, Furthermore, we found no association with suicidal behavior, These findings do not support the hypothesis that ABCG1 is a susceptibility gene for affective disorders or suicidal behavior. Copyright (C) 2000 S. Karger AG, Basel.