Amir Shaikh MD David D McManus MDScM Assistant Professor Department of Medicine University of Massachusetts Medical School Worcester MA USA Disclosures David D McManus MD ScM has received research funding from ID: 932874
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Slide1
Role of micro-RNAs in Atrial Fibrillation
Amir Shaikh, MD; David D McManus, MD,ScMAssistant Professor,Department of MedicineUniversity of Massachusetts Medical School, Worcester, MA, USA
Slide2Disclosures
David D McManus, MD, ScM has received research funding from: US Department of DefenseNational Heart Lung and Blood InstituteWorcester
Polytechnic Institute (New Technology Development Grant)St. Jude MedicalPhilips HealthcareSanofi AventisBiotronikOtsuka
PharmaceuticalsAstra Zeneca
Slide3University of Massachusetts Medical School
Slide4Atrial Fibrillation: A Complex Disease with Far-Reaching Impact
Miyasaka
Circulation 2006;11:119
; Go
JAMA
2001;285:
2370American Heart Association
Slide5DD McManus, A
Shaikh, F Abdhiskek, RS Vasan.
Crit Path Cardiol. 2011
A useful phenotype to explore genetic and transcriptomic underpinnings of AF?
Slide6Focal Triggers Initiate AF and Reentry Perpetuates It
Ding Sheng He, MD, PhD
AF requires both a trigger and a vulnerable
substrate
Interplay between intrinsic susceptibility
and
exposures
largely unknown
Slide7Persistent
Paroxysmal
Permanent
Triggers of AF
Substrate for AF
Initiation substrate
AF disease progression
Although all are susceptible to AF, why do many individuals develop it early in life with minimal (if any) exposures?Why do some progress to more persistent forms of the arrhythmia?
Slide8Magnani
…McManus…Benjamin. Atrial fibrillation: current knowledge and future directions in epidemiology and genomics. Circulation 2011.
Slide9Benjamin JAMA 1994;271:840; Lake
Austr NZ J Med 1989;19:321;
Psaty Circulation 1997;96:2455; Sawin NEJM 1994;331:1249;Tsang JACC 40:36, 2002
Slide10Magnani
…McManus…Benjamin. Atrial fibrillation: current knowledge and future directions in epidemiology and genomics. Circulation 2011.
Slide11Genetics of AF
Association with Family HistoryCandidate Gene StudiesGWAS findings
Lubitz, JAMA 2010.
Fox…Benjamin JAMA 2004;291:2851
AF ≥ 1
parent OR
1.9; (P=0.02)
<75yo, w/o h/o heart disease OR 3.2; (P< 0.001)Family History of AF Associated with Increased AF Risk
Slide12Genetics, Genomics and AF
Slide13Candidate Genes Associated with AF
Gene
Variant
Cases
Controls
OR
P value
Replicated?Candidate Gene StudiesConnexin 40-44A, +71G1732321.5< 0.006NoAngiotensinogenM235T2502502.5<0.001NoAngiotensinogenG-6A2502503.30.005NoAngiotensinogenG-217A2502502.00.002NoMink 38G1081081.80.024NoGNB3C825T2912920.460.02NoKCNE597T158960.520.007NoInterleukin 6 -174 G/C26843.250.006NoCETP Taq1B97970.350.05NoKCNE4E145D1422381.660.044NoACED/D512891.50.16NoENOS894T/T512893.20.001NoSCN5AH558R1573141.60.002NoHERG/KCNH2K897T120724751.250.0003YesEllinor Med Clin N Am 2008;92:41
Slide14Associations between Genetic Variants and AF
Lubitz
…McManus…
Ellinor
. JACC 2014
~35% individuals European descent have
≥1 variant
Risk AF OR 1.72, 1.39 /copyGudbjartsson Nature 2007;448:353
Slide15identified
genetic associations of
AF and
future areas of genomic study
Magnani
…McManus…Benjamin.
Atrial fibrillation: current knowledge and future directions in epidemiology and
genomics. Circulation 2011.
Slide16Magnani
…McManus…Benjamin. Atrial fibrillation: current knowledge and future directions in epidemiology and genomics. Circulation 2011.
Slide17Heritability Gap in AF – Moving beyond GWAS
Known unknowns in AF:40% AF risk unexplained by clinical CV risk factors2-fold higher risk of AF in patients with family history of AF90+% of AF heritability unexplained by known SNPs and candidate gene studiesAF triggers contribute to altered atrial gene expression
Could variable gene expression in stress states explain heritability gap?
Slide18MicroRNA in CVD
MicroRNAs (miRNAs) are endogenous, non-coding RNAsmiRNAs are regulators of gene expressionmiRNAs are released by the heart in the setting of an acute MI, heart failure
miRNAs are present in the circulation and provide insights into in vivo gene expression.
McManus, Ambros
.
Circulation
2011
Slide19Animal Models suggests Tissue Levels of Mirnas are associated with AF Susceptibility
Slide20Wang
Card Res 2010
Slide21Altered Cardiac Gene Regulation (e.g., TGF-β)
Atrial Injury
(e.g., from heart failure)
+
miRNAs
secreted or released (e.g.,
exosomes
)Cardiac Remodeling Promotes AFmiRNAs detectable in plasmaDiseased AtriaNormal AtriaAltered atrial miRNA profile- miRNAs degraded or taken up (e.g., platelets)
Slide22High Throughput Technology exists to assess miRNA expression
High-throughput miRNA expression profiling systems allow rapid profiling of miRNAs from numerous samplesUse real-time
PCR, or microarrayPrimers correspond to over 1,000 miRNAs
Accurate, specific and sensitiveCourtesy, Jane Freedman, MD Kahraman Tanriverdi
, PhD
Slide23McManus et al.
Heart Rhythm 2014
miR-328 is up-regulated in the atria of human subjects with AFmiR-328 regulates L-type Ca2+ channel density, shortens the atrial effective refractory periodmiR-328 enhances AF vulnerability in animal models
Slide24Baseline Exam:
Plasma
Prevalent AF (n=122)
1-mo
Post-ablation AF (n=47)
Post-Ablation: Plasma
Atrial Tissue
No AF(n=99)Cardiac surgery (n=31)McManus et al. submitted Circulation. 2014
Slide2521 Plasma mirnas associated with AF
N
Average Expression (delta CT)Multivariable Adjusted***
m
iRNA TotalAFCasesPrevalent AF(n=112) No AF(n=99)Fold ChangeOdds Ratio 95% CIP-value*miR-150-5p206107-3.26-0.962.300.510.41-0.631.5x10-10miR-100-5p205109-1.611.453.070.420.33-0.543.2x10-12miR-122-5p209110-4.81-2.092.720.560.47-0.674.3x10-10miR-125a-5p202106-2.530.853.380.470.38-0.584.09x10-12miR-146a-5p202106-2.190.542.730.380.29-0.517.8x10-12miR-148b-3p198105-1.270.832.100.470.37-0.593.9x10-10miR-21-5p209110-5.82-3.762.060.510.41-0.639.2x10-10miR-221-3p208109-3.30-1.202.090.500.40-0.612.6x10-10miR-223-3p209110-5.88-3.622.270.490.39-0.605.9x10-11AF=atrial fibrillation; OR = odds ratio; miR = miRNA; CI = Confidence Interval; Bonferroni p value cutoff = 0.05/86 miRNAs = 0.0006Fold-change is the difference in miRNA expression between individuals with AF compared to no AFMultivariable adjusted models included age, sex, current smoking, diabetes, prevalent heart failure, and MI21 miRNAs, including several known to regulate genes associated with cardiovascular disease, were associated with prevalent AF
Slide2633 Plasma Mirs change pre- to post-ablation
N
Average Expression (delta CT)
Multivariable Adjusted***
miRNA
Baseline
Post-AblationBaselinePost-Ablation Fold ChangeOdds Ratio95% CIP-value*miR-150-5p4745-3.75-0.693.062.711.85 - 3.983.6x10-7miR-21-5p4747-6.09-2.653.443.071.98 - 4.765.3x10-7miR-122-5p4745-5.41-1.733.682.311.65 - 3.228.2x10-7miR-223-3p4746-6.32-2.643.683.121.98 - 4.931x10-6let-7b-5p4747-6.23-2.673.563.432.08 - 5.661.5x10-6miR-30c-5p4738-1.081.632.713.542.11 - 5.921.5x10-6miR-342-3p4747-2.070.542.614.532.41 - 8.512.7x10-6let-7c-5p4747-4.66-0.953.713.922.21 - 6.973.1x10-6miR-148b-3p4635-1.491.182.672.941.85 - 4.674.9x10-6miR-146a-5p4736-2.240.913.153.21.93 - 5.337.2x10-6miR-125b-5p4738-2.921.484.403.682.05 - 6.611.3x10-5miR-126-3p4744-5.58-1.394.193.812.08 - 6.961.4x10-5miR-100-5p4733-2.071.293.363.952.09 - 7.472.2x10-5miR-125a-5p4736-3.221.484.714.862.12 - 11.161.9x10-4AF=atrial fibrillation; OR = odds ratio; miR = miRNA; CI = Confidence Interval; Bonferroni p value cutoff = 0.05/86 miRNAs = 0.0006Fold-change is the difference in miRNA expression between individuals with AF compared to no AFMultivariable adjusted models included age, sex33 miRNAs changed from pre- to post-ablation14 miRNAs were also associated with AF
Slide27AF vs. No AF in Atrial Tissue
Slide28AF vs. No AF in Atrial Tissue
Slide29Post-Operative AF
Slide30AF vs. No AF
Pre vs. Post-Ablation
miR-10b-5p
miR-24-3pmiR-29a-3pmiR-99b-5pmiR-221-3pmiR-375miR-411-5p
miR-21-5p
miR-30c-5p
miR-100-5p
miR-122-5pmiR-125a-5pmiR-125b-5pmiR-126-3pmiR-146a-5pmiR-148b-3pmiR-150-5pmiR-223-3pmiR-342-3plet-7b-5plet-7c-5p miR-7-5p miR-221-3pmiR-10b-5p miR-320amiR-19a-3p miR-451a miR-20a-5p miR-144-3pmiR-24-3p miR-146b-5pmiR-25-3p miR-29b-3p miR-26a-5p miR-29a-3pmiR-30a-5pmiR-92a-3p miR-106b-5plet-7f-5plet-7g-5pConsiderable Overlap in Highly Variant Mirs and those associated with AF
Slide31m
iRNA
FUNCTION (TARGET GENES)
ASSOCIATED PHENOTYPEmiR-1
Cell cycle regulation; (Ion Channels and gap junction genes,
GJA1
,
KNJ2)Cardiac arrhythmia, cardiac development, downregulation in AFmiR-21Upregulation of the protein sprouty (ERK-MAPK), PDCD4Anti-apoptotic factor, cardiac stress responsemiR-29Inhibition of collagen and extracellular matrix proteins (ELN, FBN1, COL1A1), Pro-apoptosis (Mcl-2)Regulates deposition of intracellular collagenmiR-92aInhibition of neorevascularization (integrin subunit α5 and eNOS)Reduction in cellular apoptosis and improved cardiac function miR-122fatty acid beta-oxidationContributes to endothelial dysfunction miR-150(c-Myb), H2O2-induced cardiac cell deathAtherosclerosis, cardiac hypertrophy, heart failure, myocardial infarction, and myocardial ischemia/reperfusion injurymiR-320Pro-apoptosis (HSP20 levels); Increases expression of insulin-like growth factor-1Down-regulated after ischemia reperfusion injury; down-regulated in AF miR-92aInhibition of neorevascularization (integrin subunit α5 and eNOS)Reduction in cellular apoptosis and improved cardiac function Gene Targets associated with Significant MIRNAsMcManus et al. submitted Circulation. 2014
Slide32Olson,
Nature 2010
Slide33MiRhythm Findings
We observed associations between AF and plasma miRNAs linked to gene regulatory pathways responsible for cardiac remodeling Overlap was observed between plasma miRNAs
associated with AF and those changing after ablation Studies are needed to explore gene regulatory pathways implicated in susceptibility to AF and to examine the role of miRNAs as circulating biomarkers of diagnostic or prognostic importance in AF
McManus et al. submitted Circulation. 2014
Slide34Future DirectionsExploring functional significance of miRNA
dysregulation in animal models of AFComplete echocardiographic phenotyping of LA structure in FHS and look at genomic and transcriptomic profiles of LA-EF, LAVILeverage AF Registry and Biobank
Slide35BU/FHS
-Vasan Ramachandran MD-Emelia Benjamin MD,
ScM-Jared Magnani, MD, MPH-Shuxia Fan
-Susan Cheng, MD MS-Honghuan Lin, MDMGH-Patrick Ellinor MD, PhD
-Steven
Lubitz
, MD
UMMS-Nada Esa, MD-Raghava Velagaleti, MD-John Keaney MD-Robert Goldberg PhD-Victor Ambros, PhD-Jane Freedman, MD-Kahraman Tanriverdi, PhD-Rosalind Lee, BS-Jeanine Ward, MD PhD-Iryna Nieto, MD-Divakar Mandapati, MD-Stanley Tam, MD MBA-Okike N. Okike, MD-Timothy Fitzgibbons, MD-Donna Suter, RN-Amir Shaikh, MD-Menhel Kinno, MD-EP ColleaguesA special thank you to the 650+ AF patients who have entrusted their care to us and participated in the Umass AF Registry, AF Biobank, and InRhythm!
Slide36Thank you for your attention!