Podcasts about lovastatin

This episode is sponsored by Meded101.com/store - Go check out their resources, books, and review courses! They will help you prepare to pass your pharmacology classes and board exams! Lansoprazole is a PPI that can be used for GERD, ulcers, and other GI conditions. B12 and magnesium deficiency are possible long-term mineral and vitamin effects. Augmentin is a combination medication of amoxicillin and clavulanate. It is an antibiotic for infection. Diarrhea is the most common adverse effect. Lovastatin is a cholesterol-lowering medication. It is often not a preferred statin due to CYP3A4 interaction and it is less potent than other medications. Valacyclovir is a prodrug that gets converted to acyclovir. It is an antiviral medication and can treat herpes zoster and herpes simplex infections. Chlorpromazine is a dopamine antagonist that has anticholinergic activity as well. It is a first-generation antipsychotic medication.

New cosmetics technologies - with Dr. Alexandra Bowles! -All about Raynaud's phenomenon -po metformin for CCCA -Lovastatin cream (alone) for DSAP -To sign up for Luke's atopic dermatitis CME activity, go to:impactedu.gathered.com/invite/4QbYEVpbzqWant to donate to the cause? Do so here!
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On this episode of the Real Life Pharmacology Podcast, I discuss lovastatin pharmacology, adverse effect, drug interactions, and more! Lovastatin is broken down by CYP3A4 so drugs like clarithromycin, diltiazem, and others may increase concentrations. Lovastatin is a lipophilic statin and I discuss the importance of this on the podcast. Lovastatin has a very short half-life which means that it is ideal to dose this medication at night for maximal efficacy.

“A diet as good as the famous statins?”This week, Dr Ferghal and I explore the ‘Portfolio Diet'; known for its effectiveness in lowering LDL i.e. ‘bad cholesterol'. This diet is said to be as effective as Lovastatin, which is a cholesterol lowering medication! Support the show (https://www.patreon.com/medheads)

Cardiovascular meds. Cholesterol lowering agents. Hyperlipidemia, Atorvastatin (Lipitor), Fluvastatin (Lescol), Lovastatin,  Pitavastatin (Livalo), Pravastatin (Pravachol), Rosuvastatin calcium (Crestor), Simvastatin (Zocor) Free quiz & full course at https://Simplenursing.com/nursing-school  Pharmacology Master Class - 100 videos not on YouTube - Try it for Free!    Pharmacology Master Class - Try it for Free: https://Simplenursing.com/nursing-school  100 videos not on YouTube    FREE Access to new app + 1,000 videos not on youtube!  https://Simplenursing.com/nursing-school   NCLEX FREE TRIAL:  https://simplenursing.com/NCLEX   STAY IN TOUCH

Today I'm speaking with Dr. Mark Pimentel and of course, he's no stranger to anyone in the SIBO community. He's been really instrumental in many IBS and SIBO studies and a lot of research that's been happening over the last few years.   I learned about Dr. Pimentel through his book, The New IBS Solution, about 10 years ago. He is the executive director of the Medically Associated Science and Technology program at Cedars-Sinai. He's a professor of medicine at Geffen School of Medicine and associate professor of Cedars-Sinai Medical Center in Los Angeles. He's very active in research and has served as a principal investigator or co-investigator for numerous clinical studies. And of course we know him as the developer or discoverer of  the anti-vinculin and anti-CdtB antibodies that predict whether or not you have SIBO or autoimmune IBS. He also discovered the use of Lovastatin for methanogens.   

Today I'm speaking with Dr. Mark Pimentel and of course, he's no stranger to anyone in the SIBO community. He's been really instrumental in many IBS and SIBO studies and a lot of research that's been happening over the last few years.   I learned about Dr. Pimentel through his book, The New IBS Solution, about 10 years ago. He is the executive director of the Medically Associated Science and Technology program at Cedars-Sinai. He's a professor of medicine at Geffen School of Medicine and associate professor of Cedars-Sinai Medical Center in Los Angeles. He's very active in research and has served as a principal investigator or co-investigator for numerous clinical studies. And of course we know him as the developer or discoverer of  the anti-vinculin and anti-CdtB antibodies that predict whether or not you have SIBO or autoimmune IBS. He also discovered the use of Lovastatin for methanogens.   

Jane Ferguson: Hi everyone. Welcome to episode 20 of Getting Personal Omics of the Heart, the podcast brought to you by the Circulation: Genomic and Precision Medicine Journal and the American Heart Association Council on Genomic and Precision Medicine. I'm Jane Ferguson from Vanderbilt University. It's September 2018 and let's dive straight into the papers from this month's issue of Circulation: Genomic and Precision Medicine.                                 We're starting off with some pharmacogenomics. Bruce Peyser, Deepak Voora and colleagues from Duke University published an article entitled, "Effects of Delivering SLCO1B1 Pharmacogenetic Information in Randomized Trial and Observational Settings."                                 Although statins are generally well tolerated, 5-15% of patients taking statins for LDL lowering and cardiovascular protection end up developing statin associated muscular symptoms. Because onset of muscular symptoms associated with discontinuing statin use, as well as increased cardiovascular morbidity, there is a clear need to identify ways to prevent or reduce symptoms in these people. Variants affecting statin related myopathy have previously been discovered through GWAS, including a variant in the SLCO1B1 gene, which also has been shown to relate to statin myalgia and discontinuation of statin use. The risks appear to be greatest with simvastatin, indicating the people at risk of muscle complications may do better on either low-dose Simvastatin or another statin. However, there's still some uncertainty surrounding the risks and benefits of various statins as they pertain to risk of muscular symptoms.                                 The authors have previously shown that pharmacogenetics testing led to increased number of people reporting statin use, but effects of pharmacogenetic testing on adherence, prescribing, and LDL cholesterol had never been tested in a randomized control trial. In this study, they randomized 159 participants to either genotype informed statin therapy or usual care, and then followed them for months to eight months.                                 25% of participants were carriers of the SLCO1B1 star five genotype. The authors found that statin adherence was similar in both groups, but gene type guided therapy resulted in more new statin prescriptions and significantly lower LDL cholesterol at three months, and levels that were lower but no longer significantly different at eight months.                                 In individual's randomized to usual care who then crossed over to genotype informed therapy after the trial period ended, there was an additional decrease in LDL cholesterol. Overall, genotype informed statin therapy led to an increase in re-initiation of statins and decreases in LDL cholesterol, but did not appear to affect adherence.                                 The authors also examined the effects of commercial genetic testing for SLCO1B1 variants in an observational setting by looking at over 92000 individuals with data available in the EHR. They found the people who receive genetic testing results had a larger drop in LDL cholesterol compared to untested controls. Overall, the study indicates that carriers of the SLCO1B1 risk variant may benefit from genotype informed statin therapy, while for non-carriers receiving their results may has limited effects.                                 If you want to read more on this, Sony Tuteja and Dan Rader from UPenn wrote an editorial to accompany this article, which was published in the same issue.                                 We're staying on the topic of statins and LDL for our next paper. This article comes from Akinyemi Oni-Orisan, and Neil Risch and colleagues from the University of California and is entitled, "Characterization of Statin Low-Density Lipoprotein Cholesterol Dose-Response Utilizing Electronic Health Records in a Large Population-Based Cohort."                                 They were interested in understanding what determines variation in statin induced LDL reduction, particularly the genetic component, and they used a large EHR derived data set, the Kaiser Permanente Genetic Epidemiology research on adult health and aging cohort to address this important question. An EHR dataset does have intrinsic limitations, but also has some clear strengths, not only as a readily available and cost-effective data source for large sample sizes, but also because it reflects real world clinical care in diverse individuals, which is not always well represented within the selective constraints of a randomized trial.                                 There were over 33000 individuals who met their inclusion criteria. To account for differences in potency between different statins and doses, the authors generated a defined daily dose value, with one defined daily dose equal to 40 milligrams per day of Lovastatin. The slope of the dose response was similar across statin types and across different sex and race or ethnicity groups. But there were differences by statin type in the response independent of dose, as well as differences in absolute responses by sex, age, race, smoking, and diabetes.                                 Based on these differences, the authors revised the defined daily doses and they highlight how previously defined equivalencies between different statins may not be accurate. They found that individuals with East Asian ancestry had an enhanced response to therapy compared with individuals of European ancestry.                                 The authors identified related individuals within the data set and the estimated heritability of statin response using parent-offspring and sibling pairs. They found only modest heritability, indicating that non-genetic factors may be more important in determining variability in statin response. Overall, this large single cohort study adds to our knowledge on determinants of statin response and raises further questions on the relative effects of different statins and doses within patient subgroups.                                 Okay, so now let's talk about GWAS and Athero. Sander van der Lann, Paul de Bakker, Gerard Pasterkamp and coauthors from University Medical Center Utrecht published a paper entitled, "Genetic Susceptibility Loci for Cardiovascular Disease and Their Impact on Atherosclerotic Plaques."                                 Over the past decade, genome-wide association studies in large cohorts have been very successful in identifying cardiovascular risk loci. However, relating these to subclinical disease or two mechanisms has been more challenging. The authors were interested in understanding whether established GWAS loci for stroke and coronary disease are associated with characteristics of atherosclerotic plaque, the idea being that some of the risk loci may alter disease risk by determining the development and stability of plaque. They identified seven plaque characteristics to study and histological samples, including intraplaque fat, collagen content, smooth muscle cell percentage, macrophage percentage, calcification, intraplaque hemorrhage, and intraplaque vessel density.                                 They selected 61 known loci and examined association of those SNiPA with black phenotypes in over 1400 specimens from the athero express biobank study. Out of the 61 loci, 21 were associated with some black phenotype compared with zero of five negative control loci, which were chosen as established GWAS loci for bipolar disorder, which, presumably, should share limited mechanistic etiology with plaque. They used the software package VEGAS to run gene-based analyses. They also assessed SNiPA relationships with gene expression and methylation in multiple tissues derived from two independence Swedish biobanks, which included atherosclerotic arterial wall, internal mammary artery, liver, subcutaneous fat, skeletal muscle, visceral fat, and fasting whole blood.                                 One CAD locus on chromosome 7q22 that survived correction for multiple testing was associated with intraplaque fat, and was also an EQTL for expression of several genes across multiple tissues. In addition, it was also a methylation QTL.                                 The authors focused on this locus and looked at correlation of expression within the LDL receptor and noted associations with HDL and LDL cholesterol in the global lipids genetics contortion data, which suggests that this locus may have a role in the metabolism. At this locus, the HBP1 gene expressed foam cells may be an interesting candidate as a causal gene in determining plaque-lipid accumulation and cardiovascular risk.                                 So next up, we have a paper that is also about athero and is coauthored by many of the same group as did that previous study. So yeah, this group's productivity is kind of making the rest of us look bad this month. So Martin Siemelink, Sander van de Lann, and Gerard Pasterkamp and their colleagues published, "Smoking is Associated to DNA Methylation in Atherosclerotic Carotid Lesions."                                 Okay. So I think one of the few things we can all definitely agree on is that smoking is bad. But, does smoking exert any of its cardiovascular damage by altering within atherosclerotic plaques? That's the question this group set out to answer.                                 They carried out a two-stage epigenome-wide association study, or EWAS, with discovery and replication of differentially methylated loci with tobacco smoking within carotid arteriosclerotic plaques of a total of 664 patients undergoing carotid endarterectomy and enrolled in the arthero-expressed biobanks study. In discovery, they found 10 CpG loci within six genes that associated with smoking. Four of the CpG loci replicated. These four loci mapping within six genes showed reduced methylation in current smokers compared with former or never smokers.                                 However, there was no difference in specific plaque characteristics based on methylation at any of the four loci. There was also no significant difference in plaque gene expression at these loci based on smoking status. However, a SNiPA at a nearby locus located in the 3' UTR of the PLEKHGB4 Gene was associated with methylation at AHRR, and was a [inaudible 00:09:58] QTL for PLEKHGB4 of expression but not a AHRR expression. The authors speculate that PLEKHGB4 may co-regulate AHRR expression. The authors also examined blood methylation in a subset of the same subjects, and they were able to replicate previously identified CPG sites associated with smoking.                                 This is a really complex area, and it's hard to identify mechanisms and causality from these multiple layers of data, but the authors demonstrate the importance of using disease relevant tissues to start to understand how environmental factors interact with genetics and other underlying physiology to modify methylation and function within the vasculature.                                 Our final full-length research paper this issue from Brian Byrd and colleagues Michigan, is actually the subject of our interview today. So I won't go into too much detail on it right now, but keep listening for an interview with Brian about their paper, "Human Urinary mRNA as a Biomarker of Cardiovascular Disease: A Proof-of-Principle Study of Sodium-Loading in Prehypertension."                                 Our review article this month is about the "Dawn of Epitranscriptomic Medicine" from Konstantinos Stellos from Newcastle University and Aikaterini Gatsiou from Goethe-Universität Frankfurt. In this paper, they're taking us to the next level beyond just RNA, but towards RNA epigenetics. Given the large number of possible modifications that can and are made to RNA during RNA name metabolism, there's huge potential to gain a new biological and mechanistic understanding by studying the RNA epitranscriptome. I think we'll ignore this at our peril. So if you need to catch up on this new field, this comprehensive review will get you right up to speed.                                 Moving on, our research letters are short format papers that allow authors to present focused results. These are also a great avenue to submit findings from replication studies that might not necessitate a full-length paper. So if you have some data from a replication study that you've been procrastinating writing up, a short research letter is a great format to consider.                                 This month, Bertrand Favre, Luca Borradori and coauthors from Bern University Hospital published a letter entitled, "Desmoplakin Gene Variants and Risk for Arrhythmogenic Cardiomyopathy: Usefulness of a Functional Biochemical Assay." The desmoplakin is essential for the cell-cell adhesion complex's desmosomes. Mutations in this gene have been associated with a wide range of phenotypes, including some in skin and hair, but also in heart, which can manifest arrhythmogenic or dilated cardiomyopathy. This protein anchors intermediate filaments, so mutations that alter binding to intermediate filaments may pathogenicity.                                 The author selected seven reported amino acid altering mutations in desmoplakin, and they screened for effects on binding using a novel fluorescence binding assay. They found that three of the seven mutations had a clear impact on binding. This assay is a novel way to assess functional impact of desmoplakin variants, and may be useful to inform the severity of future phenotypes in individuals carrying a desmoplakin mutation.                                 Finally, if you want to stay up-to-date on the genetics of aortic disease and Marfan syndrome, you can find a letter from Christian Groth and colleagues and an author response from Norifumi Takeda and colleagues regarding their previously published paper on impact of pathogenic FBN1 variant types on the progression of aortic disease in patients with Marfan syndrome.                                 I am joined today by Dr. Brian Byrd from the University of Michigan, who is the senior author on a Manuscript published in this month's issue, entitled, "Human Urinary mRNA as a Biomarker of Cardiovascular Disease: A Proof-of-Principle Study of Sodium-Loading in Prehypertension."                                 So welcome Brian. Thanks so much for coming on the podcast. Brian Byrd:          Thank you for having me. Jane Ferguson: So before we get started, could you give a brief introduction of yourself to the listeners and maybe tell us a little bit about how you got into the field? Brian Byrd:          Absolutely. So I am a cardiologist and a physician scientist. I'm an assistant professor at the University of Michigan, where I have a laboratory engaged in clinical investigation. My background is that I did my Internal Medicine Residency at Vanderbilt University. And after I finished residency, I entered Nancy Brown's lab. She's the Chair of Medicine at Vanderbilt, as I know you're aware. And she had a laboratory focused, and still does have a laboratory focused, on the investigation of high blood pressure, with a lot of focus on understanding high blood pressure as it occurs in humans. And I got a Master of Science degree in clinical investigation while I was in her lab, and we did some work on a number of topics related to the renin-angiotensin-aldosterone system, which has been a long-standing interest of mine ever since then.                                 So, at the same time, I was learning how to take care of patients with very complex blood pressure problems, who required three, or four, or five, or six blood pressure medications, in some cases, to control. And it's with that background that I became very interested in the science that underlies treatment-resistant high blood pressure in people and what we might be able to do about that. Jane Ferguson: Wow. Nice. Yeah and I think that background of sort of the combination of clinical and experimental is really nice and really important. I think your paper actually exemplifies that really nicely, so using humans but also some basic science techniques and combining them to really have a very patient focused instead of mechanistic interrogation.                                 So as I mentioned, you just published this really nice manuscript using urine as a source of mRNA biomarkers, which has relevance to hypertension and potentially also to other diseases. But before we get sort of too much into the weeds on the specific details, for any of our listeners who didn't get a chance to read your paper yet, maybe you could briefly summarize what you did? Brian Byrd:          Okay, so the general overview of what we were interested in was that the patients who have treatment resistant high blood pressure tend to have a lot of activation of a receptor in the kidney called the mineralocorticoid receptor. And this receptor helps control salt in bladder in the body. Obviously the amount of salt in the blood stays very, very homeostatic, but we if eat more salt one day then the next and there needs to be a system to help regulate the homeostasis. And so, you waste more or less salt in the urine depending upon how much sodium you're taking in.                                 And one of the functions of the mineralocorticoid receptor is to control this salt and bladder regulation or to fine tune it anyway. And the reason we know that that's an important receptor in patients with treatment-resistant high blood pressure is because of a series of studies done by David Calhoun and Brian Williams and others, showing that mineralocorticoid receptor blockers, or antagonists, are very effective in the treatment of tough to control high blood pressure.                                 And so, we had some insight that there would be something interesting to study there, and one of the things that we knew was that the mineralocorticoid receptor is a ligand activated transcription factor. So when it gets activated by it's ligan which canonically is a steroid hormone from the adrenal gland aldosterone, the receptor, which is in the cytoplasm, ordinarily dimerizes and translocates to the nucleus, where it controls the regulation of a number of genes. We also were aware that cells secrete RNA, and others had the idea that it might be inside vesicles because there's a lot of ribonuclease and biofluids. And you would think it might be difficult to pass the RNA if it were sort of naked as it were.                                 And it turns out that that's right. If you, for example, introduced synthetic RNAs into biofluids, the RNAs will be gone very quickly in a matter of seconds. So, we had this idea that we might be able to look at RNA that was being secreted by cells probably in vesicles, and assay the activity of the receptor potentially. We weren't sure if that was going to be possible or not.                                 One of the things we did was we used part of the available data to look at the transcriptome of vesicles in the urine that had been isolated from 3300 milliliters of urine by ultracentrifugation [inaudible 00:18:57]. Jane Ferguson: So it's a big centrifusion. Brian Byrd:          Exactly. Jane Ferguson: Like you [inaudible 00:19:00] Brian Byrd:          It must have been some project. So that was the work of Kevin Miranda and colleagues, and we were able to compare that transcriptome to the transcriptome of human kidney cortex samples from the GTEx project, which a large consortium focused on human transcriptomics.                                 And that was sort of the first part of what we presented in this paper, and the second thing that we did was we looked within a crossover study in a collaboration with Scott Hummel, one of my close collaborators here at the University of Michigan. We looked at individuals who had been put on a low salt diet activating renin-angiotensin-aldosterone system and causing more activation of the mineralocorticoid receptor. And then, those same individuals underwent saline infusion, so salt loading, and we knew that that would suppress the renin-angiotensin-aldosterone system. And we measured the [inaudible 00:20:02] measures of the renin-angiotensin-aldosterone system, but we also took the urine samples that had been recently banked from that experiment and we centrifuged them to try to palette the cells. We took the supernatant and we extracted RNA after trying to enrich for extracellular vesicles.                                 And with that approach, we measure targets that we thought would be regulated my the mineralocorticoid receptor, as well as some things that we did not think would be regulated by mineralocorticoid receptor. So that's the general overview of what we undertook. Jane Ferguson: Great. Right. So it's very cool. I guess we can break it down into sort of the two different parts, because I think it was a really nice examples of using public data to sort of start addressing your question and then actually doing a human experiment. But so for the GTEx data and the urinary data, you looked at few different tissues, right? And was kidney the one that you were thinking upfront would sort of most likely to correlate, or were you also looking at bladder and other sort of tissues that could potentially be of relevance to urine? But what sort of the ... I guess sort of tell me more about those different tissues that you looked at and what you found and what surprised you or not. Brian Byrd:          Great question. So, the kidney was on our minds from the outset. We knew that Mark Knepper at the National Institute of Health had published in the [inaudible 00:21:25] National Academy of Sciences back in 2004 that there are urinary extracellular vesicles. And he had found proteins that are very characteristic of the aldosterone sensitive distal nephron, that part of the kidney that we're interested in, embedded in the vesicles.                                 So we became quite interested in the idea that it seemed that there was likely a population of vesicles in the urine that is of kidney origin. And that's not to say that there weren't also plenty of vesicles from other origins as well, and there could very well be RNA that is not vesicle enclosed, but is rather ribonucleic protein bound or even bound to other carriers potentially. That could be there as well, and it's possible that the origin of those things could be any number of tissues. I don't really think that we know yet where the possible tissue origins are.                                 But we were curious to know ... I guess the direct answer to your question is we thought from the outset that we probably would find some sort of signal related to the kidney. But we wanted to also consider the possibility that our findings were not very specific to the kidney. And so we thought that the brain would be an interesting negative control. If we say very high correlation with the brain, it would suggest that maybe what we're looking for is a signal that's not really coming from the kidney.                                 And we also wanted to look at the bladder just to try to understand whether or not the signals that we're detecting could be coming from the bladder. It's certainly true that some aspects of the system that we're interested in are present in the bladder, so I wondered whether that might even serve as a signal amplifier for what we were looking for since there's, presumably, quite a bit of bladder tissue right around the urine. It might be contributing vesicles.                                 So that's sort of the rationale for why we looked at those things. Jane Ferguson: And you found mostly enrichment for kidneys. So sort of I guess what you were hoping to find came true? That actually there was sort of evidence that even though there may be contribution from other tissues, that really kidney seem to be the predominant contributor to the expression of the genes in the urine. Brian Byrd:          I think there's a lot of truth to that. One of the things I would say is we found high correlation looking across all genes. But it occurred to us ... As soon as we thought that, we realized, wait a second, that could be driven by ubiquitously expressed genes. Housekeeping genes.                                 So we really wanted to stratify our analysis by things we thought would be expressed in the kidney as well as things that we thought would be ubiquitously expressed to make sure that we could see signals that correlate ... That the transcriptome of the kidney, per se, had a good correlation with those same in terms of the abundance of the gene counts or recounts. They said it was similar to what was in the vesicles.                                 And so, we looked in the literature, and we found that a group had already established a number, 55 genes actually, that were highly kidney enriched as well as over 8000 genes that were ubiquitously expressed. And so we started the analysis from this perspective of the stratification. We thought that was a very important aspect of the analysis. And it's definitely true that if you look at our findings with respect to the kidney enriched genes, as you might expect, they correlate quite well with what is in the urinary extracellular vesicles compared to the kidney cortex.                                 You look at the brain as you might expect the expression of those kidney enriched genes is not well correlated with what's happening in the urine. And then, with respect to the bladder, it's sort of somewhere in between. Jane Ferguson: Okay. Interesting. So I know that some people look at small non-coding RNAs in urine, but you were mostly focused on mRNAs. Is that right? Brian Byrd:          That's right. I thought of this as sort of frontier, something that I knew from some early publications was probably measurable. But I didn't know what it would signify, if anything, with respect to physiology. And I knew that there were quite a few papers about micro RNAs and I wanted to do something a little bit innovated, partly.                                 But the main reason that I was interested in the RNAs was because I could relatively easily tie those to the existing literature from animal models. Preclinical animal models and cell culture studies showing what happens when the mineralocorticoid receptor's activated. That was really the driving reason that I was interested in the RNA. Because if you think about what is the approximate event that might be a readout for activation of a new growth hormone receptor like the mineralocorticoid receptor, it's really the transcriptional events that happen when the receptors translocates to the nucleus and serves its ligan activated transcription factor role. Jane Ferguson: Right. So, [inaudible 00:26:43] sort of the first part of analysis, you saw these really nice correlations between expression and kidney and in urine. And then, a lot of the times when you tried to publish that kind of thing, people are like, "Okay, so what? So you didn't do any intervention. We don't really know what that means."                                 But I like that you took it to the next step and you did sort of a human intervention experimental model. So tell me more about that model and how that worked. Brian Byrd:          Right. Well, I'll just mention also that the work that was done in terms of RNA [inaudible 00:27:14] was done in collaboration with Mark Bertini in Italy as well as Dr. [inaudible 00:27:19]. They were fundamental to getting that work done.                                 With respect to the collaboration with Scott Hummel, one of my colleagues here at the University of Michigan, what we did in that setting was to look at whether or not we could identify within these urinary mRNA signals that are in the supernatant in the urine, whether we could identify changes in physiology. That was the question that was of greatest interest scientifically.                                 And for a very practical or blind perspective, the question was could we detect the activation of the receptor that might determine whether or not people should get a certain medication. Of course, we're not saying that that's an established fact yet, but this is sort of concept, that there's something here to explore further.                                 And so, what we found was that a number of genes that are regulated by the mineralocorticoid receptor, including genes encoding the subunits of the amiloride-sensitive epithelial sodium channel that regulates the salt that I was talking about earlier. We found that those genes changed with sodium loading in terms of their abundance in the expected direction.                                 We also found that several of the assays that we made changed ... I'm sorry. That they correlated with the serum aldosterone concentration. So the concentration of the ligan for the receptor whose readout we were looking for. And we also noticed an inverse correlation with urinary sodium excretion, which is what we would expect if we really identified a readout of the mineralocorticoid receptor's activity.                                 So this study supported the idea that we have identified a way to measure this nuclear hormone receptors activity in living humans. Jane Ferguson: Right. Which is really nice. So there's probably a huge amount of extra things you could do with this, some sort of different ways you could look at it. So how did you pick the time point? So, I suppose when you think about it, I mean the genes, they're transcribed and then that takes a little bit of time, and then it takes a little bit of time for that to sort of make its way into the urine and to be excreted.                                 So how did you decide on sort of what time points to use, and do you think you would see the same things or different things [inaudible 00:29:39] if you did repeated sampling or if you looked at different time points? Brian Byrd:          That's a fantastic question. So this was a study that had already been completed, and I had mentioned to Scott what we were working on. And he said, "You know, we have these samples from this study and it might be possible for us to collaborate."                                 So, we didn't get to pick the timeframes. Jane Ferguson: Right. Brian Byrd:          So, that's a great point. And what I would say is that, as you can imagine, we're very focused on exactly the questions you're asking now. What about sort of signal refinement? What about the chrono-biology of these signals, and how do we understand when we see what in the urine?                                 So, I'm actively pursuing those questions. Jane Ferguson: Right. So, I know as well, there was quite a lot of sort of technical challenges I think to doing this work. Sort of getting to be even able to amplify and get a signal from these RNAs that are really present, sort of pretty low abundance in urine compared to tissues or biofluids that we're used to working with.                                 So tell me maybe a little bit about that process and sort of how much optimization was required to get these essays to work? Brian Byrd:          Great question. So, I had known [inaudible 00:30:58] since 2014 when I took a course on isolation of extracellular vesicles in Heidelberg, Germany. And I had talked to him at a meeting in Washington DC, and I had mentioned what we were trying to do. And he said, "You know, if you were trying to do that, you might want to consider preamplification." You know, using something like 15 cycles of preamplification. And he was willing to share that protocol that he had with me, because they were interested in similar issues. So, I was able to use that protocol to evaluate these gene targets in the urine. And so that was immensely helpful.                                 And the other thing that we did was we used locked nucleic acid probes to try to increase the sensitivity and specificity of our assays. Finally, we just tried to use good logic in the design of the assays. So we were concerned that the RNA might be fragmented, so where it was possible to do so within the design constraints that I'll mention in a second, we made multiple assays per gene target just in case this was fragmented. Which makes the analysis a little more complicated, but I think it was probably the right thing to do, given the state of knowledge that we had then.                                 And one of the other things we did was we made sure that the primers either ... Within a primer, there was an intron or between the primers there was an intron, so that if we actually did try to amplify DNA, abundant amounts of DNA, with those primers just to make sure that our theorizing about the inability to amplify things was actually factual. And that turned out that we couldn't amplify anything at 40 cycles with those.                                 So, we spent a lot of time thinking about how not to get fooled, but also to have adequate signal detection. And have included in the supplement quite a bit of information about the technical merits of the assays and showing how close the technical replicates were. They tended to be very, very similar to one another. We didn't see a signal in every urine sample for every participant at both time points, and I think that was interesting to me about that there tended to be a very binary result, so that you'd either see three technical replicants for the QPCR assays, our QPCR assays that were extremely similar to each other, or you would see no CT value detected.                                 [inaudible 00:33:47] That these were valid assessments of very low copy numbers. Jane Ferguson: Right. And that's probably related to up front of what happens to urine right after it's collected and stored, or during that RNA extraction. But it seems like once you've got RNA, then downstream assays were sort of ... They held through, but I guess ... I mean, and you obviously didn't have necessarily a huge amount of control over how these urine samples were collected. So it's kind of nice that you were able to see something even though these were collected possibly in a way that was not optimized for preserving RNAs.                                 But do you think those ... Are there ways that you could make this even sort of more streamlined and better as far from the get go of how you collect the urine, whether you could be extracting stuff right away? Is that anything you sort of looked into of how this could be improved? Brian Byrd:          That's really been the focus of the labs work since we completed that project, is sort of understanding how would we do this in a prospective study in the best possible way so that the results are highly repeatable, that we get a CT value in everybody so that we're really ... I mean, as you can imagine, that actually has something to do with the input volume of urine that you use. So if you have too little input volume, then you won't be able to detect the targets that you might be interested in every person.                                 However, if you have more, then you can do more with that. But then you have to think about how you're going to deal with the larger volumes of urine. There are lots of questions that we've been interested in related to extract the RNA and the stability of the RNA. And so we have done some experiments of that type, and we continue to work in that area. And I do think that those questions you're asking are the right questions with respect to next steps. Jane Ferguson: All right. So you looked at sort of specific targets, which I think made a lot of sense. Sort of this proof of principle. But do you think this would work on a transcriptome wide level? I mean, could you look at all the genes, or do you think that's just sort beyond the possibility right now given sort of the RNA fragmentation and how you have to sort of amplify it before being able to detect anything? Brian Byrd:          I think it's possible. So the group that had preceded our work with 3300 mils of urine, isolating the vesicles from there, eight have showed that that's something that can be done. The question that's of interest to me is does it actually require such large volumes of urine? And I think the answer to that question is going to be no from what we're overseeing so far.                                 And so, we're thinking along exactly the lines that you are. And certainly some of the feedback we've gotten as we've discussed this project with people is, "Hey, could you look at everything rather than picking targets at [inaudible 00:36:41]."                                 I think there's advantages and disadvantages. I think we chose based on prior knowledge in a way that was rational. But at the same time, it may turn out that there are many things about activation of the mineralocorticoid receptor in humans, especially in the living in-tact human, that don't exactly mirror what's found in rabbits, rats, mice or cells, which are really the systems that have been evaluated the most thoroughly in the past.                                 So I'm very interested in exactly what you're proposing. Jane Ferguson: Yeah. I mean, I think it's exciting because it's obviously relevant for hypertension, but potentially a lot of other conditions, to be able to look at that sort of dynamic change. So I think it's really exciting. It's very cool. Brian Byrd:          And I appreciate your asking about this study. We were excited to do this work and very, very excited to see where we can in the future with this. And I agree with the point you were making, that here we've gone from a rather specific application driven question and we've, I think, made some insights that are probably useful outside the application that we had in mind. And it may turn out that the application where this is the most important is not even the one that we considered in the first place at all.                                 And so I'm pleased by that. I'm pleased by the fact that I think in a sense we're working in what Donald Stokes described as pasture's quadrant, which is a sense that the work is driven both by curiosity and by an intent to use the results. Jane Ferguson: Right. Brian Byrd:          And so that's really what gets me out of bed in the morning, is working that exact space. So that's what we were glad to have done and continue to do. Jane Ferguson: Yeah. No, I think it's grea.t and I feel like a lot of people will read this paper and be like, "Hey, I have urine stored in the freezer. What can I do with this now?" Brian Byrd:          Contact me. Let's talk. We'll see what we can do. But we certainly tried to describe the methods in such a way that people could easily follow in our footsteps if they want to apply these methods. Jane Ferguson: Yeah. Now having read through them, I think that ... Really thorough. I really liked the sort of attention to detail. It was definitely one of those ones where I was like, "Oh yeah. I can see exactly how I could do this if I wanted to. So I think that was great. Brian Byrd:          Thank you. Jane Ferguson: So yeah. Congratulations on the paper. Really nice work and thanks so much for talking to me. Brian Byrd:          Thank you. It was a delight. Jane Ferguson: That's it from me for September. If you haven't had enough yet, you can access all the papers online and you can choose to digest the papers in video format. Available on our website or the Circulation YouTube channel. Thank you for listening and subscribing. I look forward to bringing you more next month.  

  Carolyn Lam: Welcome to Circulation on the Run, your weekly podcast summary and backstage pass to the journal and its editors. I'm Dr. Carolyn Lam, associate editor from the National Heart Center and Duke National University of Singapore. Our feature discussion today is about the validation of a novel biomarker-based stroke risk score for atrial fibrillation, the ABC stroke score. But first, here's your summary of this week's journal.     The first paper provides experimental insights into endothelial nitric oxide synthase uncoupling in endothelial dysfunction. In this paper by first author Dr. Lee, corresponding author Dr. Wong and colleagues from Qilu Hospital of Shandong University in China, authors assessed endothelial function in animal models of hyperglycemia, hyperhomocysteinemia, and a dyslipidemia. They demonstrated that GTP cyclohydrolase 1 is the target of the microRNA-133a and that it's a topic expression and endothelial cells mediates endothelial dysfunction.     Furthermore, Lovastatin up-regulated GTP cyclohydrolase 1 and tetrahydrobiopterin and re-coupled endothelial nitric oxide synthase in stress endothelial cells. These actions of Lovastatin were abolished by enforced micro RNA 133A expression and mirrored by a mir-133a-antagomir. Finally, the beneficial effect of Lovastatin in mice were abrogated by in vivo mir-133A over-expression or by GTP cyclohydrolase 1 knockdown. In summary, this paper offers a mechanistic basis for targeting micro RNA 133A as a therapeutic approach to correct endothelial nitric oxide synthase dysfunction. It also provides further support to the role of statins in combating endothelial dysfunction.     The next study shows us that in hypertrophic cardiomyopathy, calcium mishandling may be the potential link between the primary genetic cause and downstream signaling cascade that leads to hypertrophy and arrythmias. In this study, Dr. Helms and colleagues from University of Michigan analyzed gene expression, protein levels and functional essays for calcium regulatory pathways in 35 human hypertrophic cardiomyopathy surgical samples with and without sarcomere mutations and compared that with 8 control hearts. They found a marked reduction in circa2 abundance, which correlated with reduced circa2 function in hypertrophic cardiomyopathy compared to controlled hearts regardless of the underlying genetic etiology.     However, calcium calmodulin depend protein kinase type 2 or cam2, which is a calcium sensing kinase, was deferentially activated only in the sarcomere gene mutation positive samples. Activation of chem kinase 2 was associated with an increase in phospholamb and phosphorylation in hypertrophic cardiomyopathy. However, neither calcineurin MRNA nor MEF2 activity was increased, suggesting that calcineurin pathway activation was not an upstream cause of increased chem kinase 2 protein abundance or activation.     In summary, this paper demonstrated that calcium mishandling occurs through both genotype specific and common pathways in human hypertrophic cardiomyopathy. Post-translational activation of chem kinase 2 pathway is specific to sarcomere mutation positive hypertrophic cardiomyopathy. While Sarco 2 abundance and sarcoplasmic reticulum calcium uptake are depressed in both sarcomere positive and negative hypertrophic cardiomyopathy. Thus, chem kinase pathway inhibition may improve aberrant calcium cycling in hypertrophic cardiomyopathy. This is discussed further in an accompanying editorial by Dr. Jill Tardiff.     The third study suggests that in patients with a dilated aortic route and trileaflet aortic valve, a ratio of aortic route area to height provides independent and improved stratification for prediction of death. First author Dr. Masry, corresponding author Dr. Desai and colleagues from the Center for Aortic Disease, Heart and Vascular Institute of Cleveland Clinic, studied consecutive patients with a dilated aortic route of greater or equal to 4 centimeters who underwent echocardiography and gated contrast enhanced thoracic aortic computer tomography or magnetic resonance and geography between 2003 and 2007.     A ratio of aortic route area over height was calculated on tomography and a cutoff of 10 squared centimeters per meter of height was chosen as abnormal. In 771 patients with trileaflet aortic valve and concomitant aortopathy, there was incremental prognostic value for indexing aortic route or ascending aortic area to patient height rather than using an unindexed aortic diameter. Incorporation of the ratio significantly and independently reclassified the risk for death and at normal ratio was independently associated with higher long-term mortality while cardiovascular surgery was associated with improved survival. Importantly, a sizable minority of patients with aortic route diameters between 4.5 and 5.5 centimeters had an abnormal aortic route when indexed to height ratio. 78 percent of deaths in this subgroup occurred in those with an abnormal aortic route area to height ratio. Findings were similar when ascending aortic measurements were considered. The take home message is that an aortic route area to height ratio above 10 squared centimeters per meter of height has significant and independent prognostic utility and may be used to re-stratify patients with trileaflet aortic valve and a dilated aorta.     The final study provides pre-clinical data to show that Ticagrelor reduces cardio damage post myocardial infarction to a greater extent than Clopidogrel by an adenosine induced organ protective response. First author Dr. Villaher, corresponding author Dr. Bademan and colleagues from the Cardiovascular Research Center in Barcelona, Spain studied a close-chest swine model of ischemia reperfusion in which myocardial infarction was induced by 1 hour balloon occlusion of the mid-left anterior descending coronary artery followed by 24 hours of re-flow. Prior to occlusion, the animals were randomly assigned to receive either placebo, a loading does of Clopidogrel, a loading does of Ticagrelor or a loading does of Ticagrelor followed by an A1 A2 receptor antagonist. Edema infarc size left ventricular size and left ventricular function were assessed by three T cardiomagnetic resonance imaging. Inhibition of platelet aggregation was the same between the groups receiving a P2Y-12 inhibitor.     Yet, Ticagrelor reduced infarc size to a significantly greater extent than Clopidogrel, reducing it by a further 23.5 percent, an effect supported by troponin eye assessment and histopathological analysis. Furthermore, compared to Clopidogrel, Ticagrelor significantly diminished myocardial edema by 24.5 percent, which correlated with infarced mass. Administration of an adenosine A1 A2 antagonist abolished the cardio protective effects of Ticagrelor over Clopidogrel. At a molecular level, aquaporin 4 expression decreased and the expression and activation of AMP kinase cyclin and COX-2 increased in the ischemic myocardium of Ticagrelor versus Clopidogrel treated animals. In summary, this study shows that Ticagrelor exerts cardio protective effects beyond its anti-platelet efficacy by adenosine dependent mechanisms, which reduce necrotic injury and edema formation. This is discussed in an accompanying editorial by Drs. Gerbel, Jung and Tantry. That wraps it up for the summaries. Now for our feature discussion.     Today, we are going to be discussing the performance of the ABC score for stroke in atrial fibrillation. And as a reminder for all our listeners there, ABC stands for A for age, B for biomarkers, that's NT-proBNP and high-sensitivity troponin, and C for clinical history of prior stroke. And again as a reminder, this risk score was originally derived in the Aristotle trial. However, we have new results about its performance and validation today from first and corresponding author Dr. Jonas Oldgren from Uppsala Clinical Research Center in Sweden. Welcome, Jonas.   Speaker 2: Thank you very much.   Carolyn Lam: We also have today the associate editor who managed this paper, Dr. Sandeep Das from UT Southwestern. Hi Sandeep.   Speaker 3: Hi Carolyn, thanks for having me.   Carolyn Lam: So Jonas, could you start off by telling us why you did this study and what you found?   Speaker 2: We did this study to validate the recently derived ABC stroke risk score. We have had risk scores for predicting stroke in patients with atrial fibrillation derived since the late 1990's and refined later on. But those risk scores have only used clinical markers for risk. We have for several years developed new risk prediction models with biomarkers and now we are combine them in a very simple biomarker based risk score, taking into account age as a clinical variable and the clinical history of prior stroke and only two common used biomarkers. And by that we can predict the risk of stroke with better precision than previous clinical risk scores.   Carolyn Lam: Yeah, I like what you said. I mean it is literally as simple as ABC. So tell us how you validated it and what you found.   Speaker 2: It was derived in a large cohort of patients participating in a clinical trial with new or relapsed coagulant compared to Warfarin and we now validated in almost a full size group participating it another clinical trial. So we have large data sets of very well described patients where we have good outcome data. Very solid data to rely on. Now we can see that the ABC risk score is now validated but the good precision and good collaboration of the discriminatory abilities is high and better than the previously used clinical risk scores.   Carolyn Lam: Could you give us some numbers behind that that are clinically meaningful? Everyone's going to be wondering compared to the chads-vasc score for example, how does this ABC score perform in that validation test set?   Speaker 2: We can adjust that by several different aspects. One is of course to calculate the C index which is a statistical method to see how good we can predict risk and the C indices for the ABC stroke score both in the duration and now in the validation cohort is higher than for the chads-vasc and atrial risk scores. But we can also look at what we have in this paper in circulation ... we can look at predicted outcome rates and observed outcome rates and can see that they clearly overlap both in the duration and validation court. So if you predict a risk that is less than 1 percent per year, it is observed also a risk that is less than 1 percent a year. Does this always ... the thing is when you derive risk or but when you validate it in another cohort, you need to show that it's a similar result.   Carolyn Lam: Yeah, that's true. Sandeep, you are managing this paper. It's very important. How do you think that clinicians should be taking the results?   Speaker 3: I think that clearly using anticoagulation and selected patients at high risk for stroke with atrial fibrillation is one of the best things we do in cardiology. You know in terms of reducing the risk of an important harm to patients. I think there's a fair bit of dissatisfaction out there with currently sort of standard, which is chads-vasc. Especially in people with a chads-vasc ... men with a chads-vasc of 1 or women with a chads-vasc of 1 to 2 where there's a bit of struggling over how to decide. So I think that one real advantage of this score in addition to the fact that it predicts better by the higher C statistic, which is fantastic and pretty uncommon, right? Lars sort of buried the lead a little bit by not emphasizing that it's relatively rare that we're able to move a c statistic by a point of 5 in the modern era.     But the other thing is that it helps give us an ability to come up with good estimates in people at low risk, which I think has been a challenge and something that people are a little concerned clinically. So I think that this is easily available, biomarkers that we routinely check all the time and it doesn't have the sort of gender challenge with chads-vasc where you're trying to figure out whether your low risk woman really needs to be on Warfarin or anticoagulation. So I think that it has a lot of clinical utility right out of the box, which is nice.   Carolyn Lam: Actually, Jonas could you let us know is there any sex differences in the performance of the score?   [00:14:46] Speaker 2:   There are no differences in the performance of the score. So we looked ... the advantage of this score is when we derived it in the original model, we looked at all important clinical and biomarker risk factors and we can see that these were the foremost interesting markers. So we only used those. So we can predict much better and as pointed out so nicely by Sandeep, for patients at the lower end of the risk spectrum, we can find patients or have higher or lower risk even within patients with chads-vasc 1 or chads-vasc 2. And I think it's also important to see what about patients at higher risk despite proper anticoagulation. We did not know how to treat them but in the future we might perhaps tailor treatment also for those patients with residual high risk of stroke despite proper anticoagulation treatment. For instance, if the left atrial appendage occluded devices are shown in the future to be a good option for those patients, we can find them also by this risk score. So both in the higher and lower end of the risk spectrum.   Carolyn Lam: That's a really good point. On that note, I'm just curious. What do you think is in the future? What more knowledge do we need to address before we put this into practice or are you already using this? Or do you think it should enter guidelines for example? Maybe Sandeep, I could ask for your opinion first.   Speaker 3: We see a lot of biomarkers associated with increased risk kind of studies come out in the literature. You know probably every week you see several of these things come out. So what's really interesting about this is that it's obviously methodologically extremely well done but its been derived and validated in two large cohorts, which is pretty much best practice right? You want to see people validate these risk scores in large and distinct cohorts of patients to build up sort of clinical validity to the reader or consumer. So I think, from my standpoint, this is ready for prime time. I'm really intrigued by the fact that biomarkers, especially troponin, are predicting stroke in this population and there have been some observational reports out there that have showed an association between troponin and increased risk of stroke or worse outcomes after stroke. So I'd be really curious as to what Jonas thinks about why troponin would be predictive of stroke in this population.   Speaker 2: We were extremely intrigued by the finding when we first did those single observations of only troponin as a risk marker because we know that troponin is a very specific protein found in the myocardium. But the clinic predicts risk for stroke also and there are several explanations but they are mainly hypotheses about aging and myocardial function really to identify patients of risk. But the clear cut explanation is still not there.   Carolyn Lam: It's likely that these biomarkers are incorporating aspects that we don't fully understand, which is why they are better predictors isn't it? I mean to your point Sandeep.   Speaker 3: Yeah, no absolutely. And I think that's great.   Carolyn Lam: Exactly. It really opens a lot of other questions that need to be answered in the meantime. Jonas, any other last words about how you may be applying this clinically in your own patients?   Speaker 2: We have no solid data supporting the use of this clinical risk score and as already pointed out, which I think is very good, all clinic risk scores should of course be in the best world validated as useful decision support truth and really in clinics trial seeing that they improve outcomes. This is to my knowledge never been down with a clinical risk scores. We have never used them prospectively to guide treatment and to improve outcomes. Actually, we are aiming to do that. We hope to start a clinical trial next year with ABC score guided treatment compared to standard of care. But it's a very huge undertake of course to that we can improve treatment by risk or guided management.   Carolyn Lam: That's excellent. So remember everyone, you heard it right here. A new trial that they're engaging. I really congratulate you first for this study, as well as this future efforts which are clearly going to be very important.     Thank you very much both of you for joining us today and thank you listeners for listening. Don't forget to tune in next week.  

Red Yeast Rice, which comes from fermenting rice with Monascus purpureus, contains the cholesterol lowering monacolins, of which monacolin K (about half of the total monocalins) has been renamed Lovastatin. 10 mg of monacolins (containing about 5 mg of monocalin Continue reading Combining Red Yeast Rice and Berberine for Cholesterol, Triglyceride and Blood Sugar Control – An Interview with Mark McCarty, BA→ The post Combining Red Yeast Rice and Berberine for Cholesterol, Triglyceride and Blood Sugar Control – An Interview with Mark McCarty, BA appeared first on .

Background: Neurofibromatosis type 1 (NF1) is one of the most common genetic disorders causing learning disabilities by mutations in the neurofibromin gene, an important inhibitor of the RAS pathway. In a mouse model of NF1, a loss of function mutation of the neurofibromin gene resulted in increased gamma aminobutyric acid (GABA)-mediated inhibition which led to decreased synaptic plasticity and deficits in attentional performance. Most importantly, these defictis were normalized by lovastatin. This placebo-controlled, double blind, randomized study aimed to investigate synaptic plasticity and cognition in humans with NF1 and tried to answer the question whether potential deficits may be rescued by lovastatin. Methods: In NF1 patients (n = 11; 19-44 years) and healthy controls (HC; n = 11; 19-31 years) paired pulse transcranial magnetic stimulation (TMS) was used to study intracortical inhibition (paired pulse) and synaptic plasticity (paired associative stimulation). On behavioural level the Test of Attentional Performance (TAP) was used. To study the effect of 200 mg lovastatin for 4 days on all these parameters, a placebo-controlled, double blind, randomized trial was performed. Results: In patients with NF1, lovastatin revealed significant decrease of intracortical inhibition, significant increase of synaptic plasticity as well as significant increase of phasic alertness. Compared to HC, patients with NF1 exposed increased intracortical inhibition, impaired synaptic plasticity and deficits in phasic alertness. Conclusions: This study demonstrates, for the first time, a link between a pathological RAS pathway activity, intracortical inhibition and impaired synaptic plasticity and its rescue by lovastatin in humans. Our findings revealed mechanisms of attention disorders in humans with NF1 and support the idea of a potential clinical benefit of lovastatin as a therapeutic option.

Apoptose glatter Gefäßmuskelzellen spielt eine wichtige Rolle sowohl im Rahmen der Pathogenese der Atherosklerose als auch der Restenose nach Ballonangioplastie. Zu Beginn der Arbeit war bekannt, dass glatte Gefäßmuskelzellen in Abhängigkeit von der Zelldichte auf bestimmte Substanzen wie z.B. PDTC oder Lovastatin mit Apoptose reagieren. Bei hoher Zelldichte konnte keine Apoptose induziert werden. Ziel der Arbeit war es, die apoptoseinduzierenden Substanzen PDTC und Lovastatin zu charakterisieren und verantwortliche Mechanismen der Apoptoseprotektion zu identifizieren. Dazu wurden glatte Gefäßmusklezellen in hoher Dichte kultiviert und konditioniertes Medium gewonnen. Dieses konditionierte Medium induzierte Proliferation in glatten Gefäßmuskelzellen und vermittelte einen Schutz vor Apoptose. Durch Immunpräzipitation und Western Blot konnte eindeutig gezeigt werden, dass die verminderte Apoptoseempfindlichkeit glatter Gefäßmuskelzellen in hoher Dichte durch eine autokrine Produktion von FGF-2 vermittlelt wird.

Das multiple Myelom ist eine Erkrankung, bei der terminal differenzierte Plasmazellen das Knochenmark infiltrieren, wodurch das typische klinische Bild eines Myelompatienten zustande kommt. In den letzten Jahren haben sich die Hinweise gehäuft, dass die Bindung der Myelomzellen im Knochenmark an Stromazellen die Chemosensitivität der Myelomzellen vermindert und somit zur „de-novo drug resistance" beiträgt. Das primäre Ziel dieser Arbeit war es, ein Zellmodell zu entwerfen, mit welchem die Untersuchung der Interaktionen von Stromazelle und Myelomzelle und damit der zelladhäsionsabhängigen Zytostatikaresistenz (CAM-DR) möglich ist. Darüber hinaus sollte diese Zytostatikaresistenz charakterisiert und mögliche molekulare Therapietargets identifiziert werden, welche eine Verhinderung von CAM-DR ermöglichen. Da das etablierte Kokulturmodell auf einer Kultur mit der Stromazelllinie HS-5 beruhte, wurde diese zuerst bezüglich der Oberflächenmarker und des Apoptoseverhaltens charakterisiert. Es wurde gezeigt, dass sich primäre Stromazellen aus Knochenmarksspiraten und die Stromazelllinie HS-5 zwar in ihrer Chemosensibilität unterscheiden, sie prinzipiell jedoch gleich reagieren. Beide lösen bei einer direkten Kokultur mit Myelomzellen im selben Maße CAMDR in den Myelomzellen aus. Die anschließende Charakterisierung von CAM-DR bewies, dass CAM-DR nicht zelllinienspezifisch und nicht zytostatikaspezifisch ist. HS-5-Zellen verhinderten nicht nur die Entstehung von später sondern auch von früher Apoptose. Es zeigte sich, dass das Ausmaß von CAM-DR maßgeblich von der Dauer der Kokultivierung abhängt. Des Weiteren stellte sich heraus, dass in diesem Zellmodell die von den HS-5-Zellen sezernierten Zytokine keinen Einfluss auf die Apoptoseinduktion hatten. Konsequenterweise wurden die Oberflächenantigene auf den Myelomzellen und den Stromazellen quantifiziert und teilweise deren Alteration nach einer Inkubation mit Zytostatika festgestellt. Sowohl eine Blockade der wichtigsten Integrine VLA-4 und LFA-1 als die Modulation der wichtigsten Signalwege konnte CAM-DR zwar teilweise, aber nicht vollkommen verhindern. Allein Vertreter der Statine, Simvastatin und Lovastatin, konnten CAM-DR drastisch reduzieren. Wie weiterhin gezeigt werden konnte, lag dies nicht an einer verminderten Expression von Oberflächenintegrinen, einer verminderten Zytokinsekretion der Stromazellen oder einer verstärkten Deadhäsion der Myelomzellen von den Stromazellen, sondern an der Hemmung der Geranylgeraniolpyrophosphatsynthese. Wir wiesen nach, daß Statine in der Kokultur über die Hemmung des HMG-CoA-Reduktase/GG-PP/Rho/Rho-kinase-Signalwegs wirken. Dies wurde in weiteren Experimenten, in denen selektiv die Geranylgeranioltransferase mittels GGTI-298 und die Rho-Kinase mit Y-27632 gehemmt wurden, bestätigt. Die Ergebnisse der vorliegenden Arbeit können als Grundlage für einen potentiellen Einsatz von Statinen in der Therapie des multiplen Myeloms dienen, denn bezüglich des dargestellten Signalwegs wirken die Statine bereits im subtoxischen Bereich. Die weitere Erforschung von CAM-DR und deren assoziierte Signalwege bei anderen Tumorentitäten sowie die Evaluation der klinischen Relevanz der Gabe von Statinen zur Blockade von CAM-DR ergeben sich als wichtige nächste Schritte als Konsequenz der vorliegenden Arbeit.