Noncoding RNAs in Cardiovascular Disease – Potential as Biomarkers and More

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Information about Noncoding RNAs in Cardiovascular Disease – Potential as Biomarkers and More

Published on June 1, 2016

Author: QIAGENscience

Source: slideshare.net

1. Sample to Insight Noncoding RNAs in cardiovascular disease – potential as biomarkers and more Ali Bierly, PhD allison.bierly@qiagen.com April 19, 2016

2. Sample to Insight Legal Disclaimer 2 QIAGEN products shown here are intended for molecular biology applications. These products are not intended for the diagnosis, prevention or treatment of a disease. For up-to-date licensing information and product-specific disclaimers, see the respective QIAGEN kit handbook or user manual. QIAGEN kit handbooks and user manuals are available at www.QIAGEN.com or can be requested from QIAGEN Technical Services or your local distributor.

3. Sample to Insight Agenda 3 1. Introduction to cardiovascular system and diseases 2. Introduction to noncoding RNAs (microRNA and lncRNA) 3. Noncoding RNAs in cardiovascular diseases – what’s known, and new research 4. Tools for total RNA research (mRNA, miRNA and lncRNA) 5. Additional resources

4. Sample to Insight Cardiovascular diseases 4 Diseases of the heart and blood vessels Coronary artery disease High blood pressure Congestive heart failure Cardiac arrest Arrythmia Peripheral artery disease Stroke Top cause of death globally – includes diseases of the heart and blood vessels Behavioral risk factors:  Tobacco use  Diet/obesity  Physical inactivity  Excessive alcohol use Early detection and management is key to successful control* * Source: WHO Cardiovascular diseases (CVDs) fact sheet

5. Sample to Insight The cardiovascular system 5 Image CC BY-SA 2.1 JP http://creativecommons.org/licenses/by-sa/2.1/jp/ Primary responsibilities:  Blood circulation, leading to:  Nutrient transport, such as amino acids  Oxygen transport  CO2 transport  Hormone circulation  Blood cell circulation  Primary organs/vessels involved:  Heart (pumps blood to body and lungs)  Lungs (pulmonary circulation, oxygenates blood)  Arteries (deliver oxygenated blood)  Veins (return blood to the heart)  Capillaries (connect arteries and veins) Blood component of the circulatory system, which also includes the lymphatic system

6. Sample to Insight Major cardiovascular diseases 6 Vascular diseases Coronary artery disease (can lead to myocardial infarction) Peripheral arterial disease Cerebrovascular disease (including stroke) Renal artery stenosis Heart diseases Cardiomyopathy – diminished ability of heart muscle to contract Hypertrophic cardiomyopathy – the above, due to thickening of myocardium Hypertensive heart disease – complications of high blood pressure; left ventricular hypertrophy, atherosclerosis, congestive heart failure, atrial fibrillation Heart failure – heart can’t pump enough anymore, can result from a number of CVDs Valvular heart disease Question: Can noncoding RNA biomarkers help us detect CVD early?

7. Sample to Insight Noncoding RNAs – microRNA overview 7 microRNA (miRNA)  Naturally occurring, ~22-nt noncoding RNAs  Mediate post-transcriptional gene regulation  Circulating miRNAs are detectable in serum and plasma – good potential biomarkers  Detectable by qPCR, sequencing or microarray or a discovery-verification combination of sequencing followed by qPCR  Involved in many biological pathways, including apoptosis, cell differentiation and development and immunity, as well as diseases from cancer to cardiovascular to diabetes

8. Sample to Insight 8 microRNA biogenesis Noncoding RNAs – microRNA overview  Transcribed by RNA polymerase II as long primary transcripts (pri-miRNAs), which may contain more than one miRNA  In the nucleus, pri-miRNAs are processed to hairpin-like pre-miRNAs by RNAse III-like enzyme Drosha  Pre-miRNAs are then exported to the cytosol by Exportin 5  In the cytosol, RNAse III-like Dicer processes pre- miRNAs into mature miRNAs  Mature miRNAs are incorporated into RISC  miRNAs with high homology to target mRNAs lead to mRNA cleavage  miRNAs with imperfect base pairing to target mRNAs lead to translational repression and/or mRNA degradation

9. Sample to Insight 9 Long noncoding RNA (lncRNA)  Noncoding transcripts >200 nt (some may code for “micropeptides”)  Not strongly conserved across species in general, but some strongly conserved elements  Involved in regulating gene transcription, post-transcriptional regulation and epigenetic regulation Noncoding RNAs – lncRNA overview

10. Sample to Insight 10 lncRNAs are a novel class of RNAs larger than 200 nucleotides Noncoding RNAs – lncRNA overview Martin, L., Chang, H.Y. (2012) Uncovering the role of genomic "dark matter" in human disease. J Clin. Invest. 122, 1589

11. Sample to Insight What’s currently known about ncRNA in CVD research? 11 Acute coronary syndromes Coronary artery disease Heart failure diagnosis Upregulated miR-1, miR-21, miR-30a, miR-30c, miR-34a, miR-122, miR-126, miR- 133a/b, miR-134, miR-145, miR- 146a, miR-155, miR-186, miR-195, miR-198, miR-199, miR-208, miR- 208b, miR-223, miR-320a, miR- 328, miR-370, miR-423-5p, miR- 433, miR-485-3p, miR499 Upregulated miR-21, miR-25, miR-92a, miR-106b, miR-122, miR-133a, miR-135a, miR- 140-3p, miR-146a, miR-155, miR-182, miR-186, miR-208b, miR-370, miR- 451, miR-490-3p Upregulated miR-18b*, miR-21, miR22, miR-29b, miR-30a, miR-92b, miR-122, miR-129- 5p, miR-133a, miR-142-3p, miR-200b, miR-210, miR-320a, miR-423-5p, miR- 499, miR-519e*, miR-520d-5p, miR-622, miR-675, miR-1254, HS_202.1 Downregulated let-7b, miR-29a, miR-122, miR- 125b, miR-126, miR-155, miR-223, miR-320b, miR-375, miR-663b, miR1291 Downregulated miR-21, miR-29a, miR-31, miR-125b, miR-147, miR-181a, miR-214, miR- 320b Downregulated miR-30b, miR-103, miR-107, miR-125b, miR-126, miR-139, miR-142-3p, miR- 142-5p, miR-342-3p, miR-497 Information from Romaine, S.P.R. et al. (2015) microRNAs in cardiovascular disease: an introduction for clinicians. Heart doi:10.1136/heartjnl-2013-305402 microRNAs with differential expression in cardiovascular diseases

12. Sample to Insight 12 * Information from Uchida, S. and Dimmeler, S. (2015) Long noncoding RNAs in cardiovascular diseases. Circ. Res. 116, 737. ** Information from Kataoka, M. and Wang, D.-Z. (2014) Non-coding RNAs I including miRNAs and lncRNAs in cardiovascular biology and disease. Cells 3, 883. What’s currently known about ncRNA in CVD research? lncRNAs that have been associated with cardiovascular diseases Acute myocardial infarction: HIF-1 AS*, MALAT1*, KCNQ1OT1*, MIAT**, ANRIL NR_003529* Cardiac hypertrophy: CHRF (induces hypertrophy by acting as a sponge for miR-489, de-repressing its target MyD88)*, Mhrt (downregulated after pressure overload, protective of heart function when overexpressed)* Coronary artery disease susceptibility: ANRIL** Many more are being investigated by RNA-seq and greater characterization is yet to come.

13. Sample to Insight Recent advances in noncoding RNA biomarkers for CVDs 13 microRNAs in circulating HDL help predict vulnerability of coronary artery disease patients Niculescu, L.S. et al. (2015) miR-486 and miR-92a Identified in Circulating HDL Discriminate between Stable and Vulnerable Coronary Artery Disease Patients. PLoS One 10, e0140958. Aim: Determine if there’s any relationship between the microRNAs associated with circulating lipoproteins and stability or vulnerability in CAD patients

14. Sample to Insight What is coronary artery disease? 14 Cause: Buildup of plaque in the arteries (atherosclerosis), restricting flow of oxygen-enriched blood to the heart by narrowing the arteries. Plaque breaking up can result in blood clot formation on top of the ruptured plaque, blocking blood flow. Possible consequences:  Angina (chest pain)  Myocardial infarction (heart attack, death of heart muscle due to lack of blood flow)  Arrhythmias  Heart failure What is a stable vs vulnerable plaque? A vulnerable plaque is at risk for rupturing, causing blood clots and driving patients toward heart attack. A key goal in the CAD field is to find an early detection method for vulnerable plaques / vulnerable patients in order to help prevent coronary events. Image: Blausen.com staff. "Blausen gallery 2014". Wikiversity Journal of Medicine. DOI:10.15347/wjm/2014.010. ISSN 20018762. Used under Creative Commons Attribution 3.0 Unported license. Question: Can microRNA biomarkers help identify vulnerable CAD patients?

15. Sample to Insight Niculescu et al.’s approach: qPCR and statistical analysis 15  Four groups of subjects: stable angina (SA), unstable angina (UA), 1 month post- myocardial infarction (MI) and healthy controls  Isolated serum for biochemical and microRNA analysis, and generated 3 independent pools for each group of subjects.  Profiled serum parameters (cholesterol, triglycerides, fasting glucose, etc.)  Isolated/characterized serum lipoproteins (IDL, LDL, HDL, HDL2, HDL3) by ultracentrifugation  Isolated and analyzed miRNAs from sera and lipoprotein fractions  Used miRNeasy Serum/Plasma Kit for isolation  Screened serum miRNAs in a pool of sera from 8 random individuals per group with Human CVD miScript miRNA PCR Array  Used individual miRNA TaqMan assays for 7 microRNAs in all 111 (95 CAD, 16 control) subjects  Used binary logistic regression model to determine predictive value of the microRNAs for vulnerable CAD patients

16. Sample to Insight Findings and relevance – miRNA biomarkers in CAD 16  From the array, they found 48 upregulated miRNAs in serum of SA, 38 in UA and 38 in MI – MI group’s microRNAs were considered top-rank  The highest ranked were miR-486, miR-92a and miR-122, and the group analyzed them with individual qPCR assays as well as 3 others due to previous literature (miR-146a, miR-125a and miR-33a)  No significance in differences between SA and UA serum in the larger cohort for these microRNAs; small & significant increase for miR-122, miR-146a and miR-125a in MI vs SA  The 6 selected microRNAs were mostly associated with HDL, varying by subfraction  HDL from CAD patients showed highest levels of miR-486 and miR-92a (predominantly associated with HDL2 and HDL3, respectively)  miR-486 was much higher in HDL2 from UA and MI compared to SA  miR-92a in HDL3 was higher in UA and MI compared to SA miR-486 and miR-92a associated with HDL can distinguish between vulnerable and stable CAD patients – may warrant further study along with a combination of these miRNAs with apolipoprotein levels, PON1 activity and HDL/LDL ratio (data not discussed here)

17. Sample to Insight Recent advances in noncoding RNA biomarkers for CVDs 17 microRNA biomarkers identify diffuse myocardial fibrosis Fang, L. et al. (2015) Circulating microRNAs as biomarkers for diffuse myocardial fibrosis in patients with hypertrophic cardiomyopathy. J. Transl. Med. 13, PMID: 26404540 Aim: To find circulating biomarkers for myocardial fibrosis to alleviate the problems of traditional cardiac magnetic resonance (CMR) imaging techniques for diagnosis.

18. Sample to Insight Diffuse myocardial fibrosis and hypertrophic cardiomyopathy 18 Hypertrophic cardiomyopathy (HCM):  Thickening of the myocardium that damages cardiac muscle function and can lead to heart failure or unexpected cardiac death.  Usually asymptomatic  Genetic component – can be inherited (often a mutation in the beta myosin heavy chain or the cardiac myosin binding protein C gene) or de novo mutation in beta myosin heavy chain gene Diffuse myocardial fibrosis:  Early feature of HCM  Associated with poor prognosis  Difficult to diagnose Image: Blausen.com staff. "Blausen gallery 2014". Wikiversity Journal of Medicine. DOI:10.15347/wjm/2014.010. ISSN 20018762. Used under Creative Commons Attribution 3.0 Unported license.

19. Sample to Insight Fang et al.’s approach 19  Used cardiac magnetic resonance (CMR) imaging and postcontrast T1 mapping time to identify diffuse myocardial fibrosis in HCM patients  Collected blood samples from the same patients prior to CMR and isolated RNA from plasma using the miRNeasy Mini Kit.  microRNA was surveyed with the miScript Serum & Plasma miRNA PCR Array  Individual miRNA assays were used to follow up the array results on dysregulated miRNAs  Receiver operating characteristic (ROC) curve was used to determine how individual miRNAs could diagnose fibrosis, and a logistic regression model was used to determine probabilities.

20. Sample to Insight Findings and relevance: biomarkers for diffuse myocardial fibrosis 20  Identified 14 miRNAs that were increased in patients with diffuse myocardial fibrosis compared to healthy controls in the initial screen of 8 HCM patients and 4 controls  12 of these were confirmed by individual qPCR assays in a larger cohort of 55 HCM patients  AUC for all 14 miRNAs, the 12 validated miRNAs from the screen plus miR-29a-3p and miR-133-3p, was 0.87 for prediction of diffuse myocardial fibrosis  The logistic regression model with backward stepwise method narrowed this down to 8 miRNAs, still with an AUC of 0.87 miRNAs identified as potential biomarkers for myocardial fibrosis miR-18a-5p miR-30d-5p miR-21-5p miR-193-5p miR-10b-5p miR-296-5p miR-29a-3p miR-15a-5p This microRNA signature might someday be developed into an alternative diagnostic option that is less expensive and more available than CMR, with no contraindications for renal dysfunction or implanted cardiac devices.

21. Sample to Insight Recent advances in noncoding RNA biomarkers for CVDs 21 High plasma expression of microRNAs in coronary artery disease Zhou, J. et al. (2016) miRNA 206 and miRNA 574-5p are highly expression [sic] in coronary artery disease. Biosci. Rep. 36, e00295 Aim: Identify key microRNAs in CAD that could be turned into diagnostic biomarkers in the future.

22. Sample to Insight Zhou et al.’s approach: 22  Isolated blood from CAD patients and healthy controls (defined as individuals with no coronary stenosis or atherosclerotic vascular disease)  Initial screening of microRNAs was done via microarray  Individual microRNA assays (miScript Primer Assays) were used to follow up by qPCR  Used statistical analysis to determine the strength of the microRNAs’ predictive ability for CAD

23. Sample to Insight Findings and relevance: high miRNA expression in CAD 23  Identified 33 microRNAs differentially expressed in CAD patient plasma (3 samples)  2 microRNAs were selected for analysis in a larger sample group, miR-206 and miR-574p – they were upregulated very strongly compared to controls (8.74-fold and 29.53-fold) and their targets were possibly related to CAD development  miR-206 and miR-574p were confirmed as consistently upregulated in CAD via qPCR assay in 67 CAD patients and 67 healthy controls  ROC curve analysis showed a 0.607 AUC value for miR-206 and a 0.696 value for miR- 574-5p These 2 microRNAs are possibly promising for development of early biomarkers for CAD

24. Sample to Insight Technologies for total RNA discovery – Isolation 24 Total RNA isolation – miRNeasy Kits FFPE KitMicro KitMini KitSerum/Plasma Kit  Purify total RNA 18 nt and up, including mRNA, miRNA and lncRNA  Can also purify separate miRNA-enriched fraction and total RNA >200 nt fractions (Mini/Micro kits)  Products are suitable for quantitative RT-PCR, Northern blot and microarray analysis  Automatable on QIAcube  Use with up to 200 µl serum or plasma  Internal normalization control available  Visit webpage for more info  Animal cells/tissues, including difficult-to-lyse tissues  Visit webpage for more info  Works with small amounts of cultured cells (1 x 106 cells)  Works with small amounts of animal/human tissue (≤5 mg)  Visit webpage for more info  Lysis buffer efficiently releases  RNA while avoiding degradation  Subsequent incubation at 80°C reverses formalin crosslinking  Visit webpage for more info

25. Sample to Insight Technologies for total RNA discovery – mRNA expression 25 RT2 Profiler PCR Arrays and Assays  Available for 13 species  Lab-verified assays  Multiple arrays for CVD-related pathways, with gene lists selected by our experts:  Endothelial cell biology  Atherosclerosis  Lipoprotein signaling & cholesterol metabolism  Angiogenesis  VEGF signaling  Cardiotoxicity  Hypertension  View the full list Preamplification  Optional for small samples – RT2 PreAMP cDNA Synthesis Kit and Primer Mixes

26. Sample to Insight 26  Profile 84 different genes using one array  Appropriate controls for  data normalization  sample quality  reaction performance  Lab-verified assays for guaranteed performance Gene expression profiling – RT2 Profiler PCR Arrays & Assays Technologies for total RNA discovery – mRNA expression

27. Sample to Insight Technologies for total RNA discovery – microRNA expression 27 microRNA expression profiling and functional analysis qPCR arrays and assays miScript microRNA PCR Arrays and Primer Assays CVD-related arrays:  Cardiovascular Disease  Apoptosis  Cell Differentiation & Development  Serum and Plasma  miFinder Full miRNome arrays:  Through miRBase V21 for human and mouse  Leading coverage for dog, rat, rhesus macaque and cow Functional analysis  miScript miRNA Mimics  miScript miRNA Inhibitors  miScript miRNA Target Protectors qPCR reagents and preamplification  miScript PreAMP PCR Kit and Primer Mixes (optional step for small samples)  miScript II RT Kit  miScript SYBR Green PCR Kit

28. Sample to Insight 28 Technologies for total RNA discovery – microRNA expression  Profile 84 different miRNAs using one array  Appropriate controls for  data normalization  sample quality  reaction performance  Lab-verified assays for guaranteed performance miScript miRNA PCR Arrays

29. Sample to Insight 29 microRNA list for the Human Cardiovascular Disease miScript array Technologies for total RNA discovery – microRNA expression Myocardial Infarction: Up-Regulated: let-7e-5p, miR-122-5p, miR-126-5p, miR-133b, miR-145-5p, miR-146a-5p, miR-15b-5p, miR-208a, miR-208b, miR-223-3p, miR-320a, miR-499a-5p. Down-Regulated: miR-1, miR-107, miR-130a-3p miR-133a, miR-143-3p, miR-155-5p, miR-16-5p, miR-195-5p, miR-21-5p, miR-214-3p, miR-22-3p, miR-24-3p, miR-26a-5p, miR-26b-5p, miR-494. Cardiac Hypertrophy: Up-Regulated: let-7b-5p, let-7c, miR-103a-3p miR-125b-5p, miR-140-5p, miR-142-3p, miR-146a-5p, miR-18b-5p, miR-195-5p, miR-199a-5p, miR-208a, miR-208b, miR-21-5p, miR-214-3p, miR-221-3p, miR-222-3p, miR-224-5p, miR-23a-3p, miR-23b-3p, miR-24-3p, miR-25-3p, miR-27a-3p, miR-27b-3p, miR-31-5p, miR-424-5p. Down-Regulated: miR-1, miR-126-5p, miR-133a, miR-133b, miR-149-5p, miR-150-5p, miR-181b-5p, miR-185-5p, miR-29a-3p, miR-29b-3p, miR-29c-3p, miR-30e-5p, miR-451a, miR-486-5p, miR-93-5p. Regulated: miR-182-5p. Cardiomyopathy: Up-Regulated: let-7c, miR-100-5p, miR-103a-3p, miR-10b-5p, miR-125b-5p, miR-140-5p, miR-145-5p, miR-146a-5p, miR- 181b-5p, miR-195-5p, miR-208a, miR-208b, miR-21-5p, miR-210, miR-214-3p, miR-221-3p, miR-222-3p, miR-23a-3p, miR- 328, miR-342-3p, miR-423-3p, miR-499a-5p. Down-Regulated: miR-1, miR-125a-5p, miR-126-5p, miR-133a, miR-133b, miR-143-3p, miR-29b-3p, miR-365a-3p, miR-378a- 3p, miR-7-5p, miR-92a-3p. Differentiation/Development: Up-Regulated: let-7a-5p, let-7b-5p, let-7c, let-7d-5p, let-7f-5p, miR-1, miR-133a, miR-143-3p, miR-144-3p, miR-145-5p, miR- 17-5p, miR-181a-5p, miR-206, miR-208a, miR-21-5p, miR-24-3p, miR-26a-5p, miR-27a-3p, miR-27b-3p, miR-30a-5p, miR- 30c-5p, miR-30d-5p, miR-378a-3p, miR-93-5p, miR-98-5p, miR-99a-5p. Down-Regulated: miR-124-3p, miR-125b-5p, miR-183-5p, miR-302a-3p, miR-302b-3p.

30. Sample to Insight Technologies for total RNA discovery – lncRNA expression 30 qPCR arrays and assays RT2 lncRNA PCR Arrays (link): Four pathways, available in human and mouse  lncFinder Cancer PathwayFinder  Cell Development & Differentiation  Inflammatory Response & Autoimmunity Custom lncRNA PCR arrays (link):  >25,000 human lncRNA assays available  >10,000 mouse lncRNA assays  Can combine lncRNA with mRNA assays Individual lncRNA qPCR assays (link)  Designed against combined NCBI RefSeq and Ensembl GENCODE database  Compatible with RT2 First Strand Kit and RT2 SYBR Green Mastermix

31. Sample to Insight Cardiovascular Diseases Research Portal 31 Visit the research portal here Links to 24 ebiology stores on CVD-related topics, such as:  Angiogenesis  Apoptosis  ECM and adhesion molecules  Hypertension  And many more Includes tools for:  mRNA profiling  microRNA profiling  lncRNA profiling  NGS  Reporter assays  Methylation arrays  RNAi

32. Sample to Insight Cardiovascular system pathway maps at GeneGlobe 32  500+ downloadable, editable pathway maps  Multiple maps related to cardiovascular system and diseases:  Cardiomyocyte differentiation  Factors promoting cardiogenesis  Angiopoietin-TIE2 signaling  C. pneumoniae infection in atherosclerosis  Embryonic cell differentiation into cardiac lineage  NFAT in cardiac hypertrophy  VEGF pathway  Many more

33. Sample to Insight For more information, visit… 33 Biomarker Insights blog – news and opinions about life science research QIAGEN webinar calendar – complimentary seminars from our experts Visit the blog! Check out the webinar calendar! QIAGEN Life Sciences LinkedIn showcase page – the latest updates on QIAGEN content QIAGEN Life Sciences Twitter – real-time updates on QIAGEN and life sciences news QIAGEN Slideshare – presentations, infographics and more for viewing and download

34. Sample to Insight Thank you for attending today’s webinar! Contact QIAGEN Call: 1-800-426-8157 Email: BRCSupport@qiagen.com qiawebinars@qiagen.com Questions? 34 Ali Bierly, Ph.D. allison.bierly@qiagen.com

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