Rapid Fire Session

Session: Rapid Fire Session 5: Valvular Heart Disease and Myocardial Disease (Monitor 11)

Using the myocardial transcriptome to explore cardiac imaging phenotypes in patients with severe aortic stenosis

Saturday, February 7, 2026

10:22 AM - 10:29 AM

Location: Galapagos / Aruba / Ilhabela (2nd Lower Level)

Presenting Author(s)

Marilena Giannoudi, PhD, MSc

Academic Clinical Lecturer in Cardiology
University of Leeds
Leeds, England, United Kingdom

Primary Author(s)

Marilena Giannoudi, PhD, MSc

Academic Clinical Lecturer in Cardiology
University of Leeds
Leeds, England, United Kingdom

Co-Author(s)

MC

Marcella Conning-Rowland

Phd Candidate
University of Leeds, United Kingdom
Nicholas Jex, PhD

Cardiologist
University of Leeds
Leeds, England, United Kingdom
HP

Henry Procter, MBChB

Cardiology research fellow
University of Leeds
Leeds, England, United Kingdom
SK

Sindhoora Kotha, BSc, MB

Cardiology Clinical Research Fellow
University of Leeds, Multidisciplinary Cardiovascular Research Centre and Biomedical Imaging Science Department, Leeds Institute of Cardiovascular and Metabolic Medicine, LS2 9JT, United Kingdom
Leeds, England, United Kingdom
AM

Anna McGrane

Phd Student
University of Leeds, United Kingdom
AM

Amanda MacCannell

Post Doc
University of Leeds, United Kingdom
DB

David Beech, PhD

Professor
University of Leeds
Leeds, England, United Kingdom
Peter P. Swoboda, PhD

Consultant Cardiologist
Leeds Institute of Cardiovascular and Metabolic Medicine
Leeds, England, United Kingdom
Peter Kellman, PhD

Senior Scientist
National Institutes of Health
Bethesda, Maryland, United States
Sven Plein, MD, PhD

Professor of Cardiology
Leeds Institute of Cardiovascular and Metabolic Medicine
Leeds, England, United Kingdom
MK

Mark Kearney

Professor of Cardiology
University of Leeds, United Kingdom
LR

Lee Roberts

Professor of Molecular Physiology & Metabolism
University of Leeds, United Kingdom
KG

Kathryn Griffin

Clinical Academic
University of Leeds, United Kingdom
EL

Eylem Levelt

Academic Clinical Lecturer
Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds
Leeds, England, United Kingdom
RC

Richard Cubbon, PhD

Associate Professor
University of Leeds
Leeds, England, United Kingdom

Background: Severe aortic stenosis(AS) is associated with myocardial remodelling, which can be quantified with cardiac magnetic resonance(CMR) imaging. While CMR provides detailed functional and structural data, the molecular correlates of CMR-defined phenotypes are poorly understood. We hypothesised that myocardial gene expression (the transcriptome) correlates to CMR phenotypes.

Methods: Patients with severe-AS underwent CMR, performed on 3.0Tesla MR system (Prisma, Siemens, Erlangen, Germany) pre-(Visit 1) and post-(Visit 2) aortic valve replacement surgery(SAVR). The CMR protocol consisted of cine imaging, pre- and post-contrast T1 mapping (MOLLI), quantitative dual sequence adenosine stress and rest perfusion imaging with automated inline myocardial blood flow(MBF) analysis, and late gadolinium enhanced(LGE) imaging. RNA was extracted from right atrial appendage(RAA) collected during SAVR. Bulk RNA-sequencing(RNA-seq) of single-end reads was performed using Illumina NextSeq 2000, followed by alignment to the human genome. Principal component(PC) analysis was used to extract the largest signals in overall RNA-seq data, allowing us to correlate CMR variables with RNA-seq. The data guided differential gene expression(DEG) analyses to identify genes of interest.

Results: Thirty-four patients were enrolled (74%male; mean age 68[66–71] years). Demographic and imaging characteristics are in Table 1. Over 40,000 genes were quantified by RNA-seq. We extracted the first 10 PCs, which accounted for >65% of gene expression variance between patients. To illustrate the strength of associations between these PCs and CMR characteristics, correlation(Eigencor) plots were generated. Figure 1 illustrates this for pre-operative CMR data(Visit 1). Here, PC3 demonstrated strong negative correlations with left atrial ejection fraction(LAEF) and left ventricular ejection fraction(LVEF), and modest positive correlations with indexed left ventricular end-systolic volume(LVESVi) and with both rest and stress endocardial-to-epicardial myocardial blood flow(MBF) ratios(Endo:Epi) (Figure 1). DEG analyses were used to explore these associations in more detail. For example, expression of 44 genes differed between patients in the upper and lower quartiles of LAEF. PC analysis was also performed using Visit 2 CMR data. PC1 showed a mild positive correlation with global longitudinal shortening(GLS). PC2 was mildly negatively correlated with LAEF and GLS, whereas PC3 exhibited a strong positive correlation with LAEF and a mild negative correlation with global rest MBF ratio(Figure 2), illustrating that pre-SAVR gene expression associates with post-operative cardiac remodelling.

Conclusion: RAA gene expression patterns correlate with CMR phenotypes before and after SAVR, offering insights on myocardial remodelling in response to AS and its treatment. These data can be used to define specific genes associated with CMR metrics, further exploration of which may help to understand CMR traits and develop blood biomarkers.

Table 1: Demographic and CMR findings of All Groups

Variable	V1 n= 34	V2 n= 28	P value
Demographics
Age, y	68 (66, 71)	70 (68, 73)	0.2749
Female, n (%)	9 (26)	6 (21)	0.6446
BMI, kg/m²	29 (27, 31)	29 (27, 31)	0.6621
Heart rate, bpm	71 (66, 75)	67 (61, 74)	0.3839
Systolic BP, mmHg	133 (127, 140)	134 (125, 144)	0.9019
Diastolic BP, mmHg	78 (74, 82)	80 (75, 84)	0.5332
Creatinine, umol/L	77 (72, 82)	81 (74, 87)	0.3619
Haemoglobin, g/L	145 (140, 149)	143 (139, 148)	0.7219
TG, mmol/L	1.6 (1.2, 2.1)	1.6 (1.2, 1.9)	0.9252
HbA1c, mmol/mol	40 [36, 43]	41 [37, 45]	0.4332
Glucose, mmol/L	5.2 [5.0, 5.9]	5.4 [4.9, 6.0]	0.7989
NT- proBNP, ng/L	294 [155, 1048]	387 [204, 838]	0.4351
AS Clinical Details
TTE Vmax, m/s	4.5 (4.2, 4.7)	2.5 (2.3, 2.8)	< 0.0001
6 min walk test, m	412 (367, 455)	453 (423, 483)	0.1371
Cardiovascular Past Medical History
T2D, n(%)	9 (26)	5(18)	0.4195
Stroke TIA, n(%)	1 (3)	1 (4)	0.8888
(P)AF, n(%)	6 (18)	6 (21)	0.7076
Hyperlipidemia, n (%)	14 (41)	12 (43)	0.8938
CMR Results
LV end-diastolic volume indexed to BSA, mL/m²	76 (71, 80)	67 (62, 71)	0.0054
LV end-systolic volume indexed to BSA, ml/m²	28 (24, 31)	25 (21, 28)	0.2218
LV mass, g	153 (138, 169)	123 (112, 135)	0.0040
LV mass indexed to BSA, g/m²	75 (68, 82)	61 (57, 66)	0.0015
LV mass to LV end-diastolic volume, g/mL	1.0 (0.9, 1.1)	0.9 (0.8, 1.0)	0.1168
LV stroke volume indexed to BSA, ml/m²	48 (45, 52)	43 (40, 46)	0.0212
LV ejection fraction, %	64 (61, 67)	63 (59, 68)	0.7550
LV maximal wall thickness, mm	14.1 [12.7, 16.0]	13.0 [11.0, 14.7]	0.0924
LA biplane end-diastolic volumes, mL	99 (80, 118)	94 (75, 113)	0.7304
LA biplane end-systolic volumes, mL	69 (50, 89)	68 (48, 88)	0.9282
Biplane LA EF, %	39 (33, 45)	35 (26, 43)	0.3517
GLS, %	15 (14, 16)	18 (16, 20)	0.0165
Native T1, (ms)	1299 (1284, 1315)	1315 (1287, 1343)	0.3112
Extra cellular volume fraction, (%)	0.23 [0.21, 0.24]	0.24 [0.23, 0.27]	0.0037
LGE, (%)	1.8 [0.8, 5.0]	1.2 [0.0, 3.4]	0.1234
Stress MBF, ml/min/g	1.4 [1.1, 1.8]	1.7 [1.1, 2.2]	0.3068
Endo MBF Stress, ml/min/g	1.2 [0.9, 1.6]	1.6 [1.0, 2.0]	0.2723
Epi MBF Stress, ml/min/g	1.5 [1.2, 2.0]	1.8 [1.1, 2.4]	0.6063
Endo/Epi MBF Stress Ratio	0.8 [0.7, 0.9]	0.9 [0.8, 1.0]	0.0166
Rest MBF, ml/min/g	0.6 [0.6, 0.7]	0.6 [0.5, 0.7]	0.1810
Endo/Epi MBF Rest ratio	1.0 [1.0, 1.1]	1.1[1.1, 1.1]	0.0002
MPR	2.3 [1.8, 2.7]	2.8 [2.0, 3.5]	0.0749
Endo MPR	1.9 [1.5, 2.2]	2.3 [1.7, 3.0]	0.0536
Epi MPR	2.4 [1.9, 2.9]	3.1 [2.1, 3.9]	0.1346
Increase in RPP, %	22 (16, 28)	22 (15, 30)	0.9755

AS, aortic stenosis; y, years; n, number; bpm, beats per minute; BMI, body mass index; BP, blood pressure; TG, triglycerides; HbA1c, glycemic hemoglobin; NT-proBNP, N-terminal-pro hormone b-type natriuretic peptide; TTE, trans-thoracic echocardiogram; V max, peak aortic forward flow velocity; T2D, type 2 diabetes; TIA, transient ischemic attack; (P)AF, (paroxysmal) atrial fibrillation.

LV indicates left ventricle; BSA, body surface area; SV, stroke volume; LA, left atrial; LA EF, left atrial ejection fraction; GLS, global longitudinal shortening; LGE, late gadolinium enhancement; RPP, rate pressure product; MBF, myocardial blood flow; Endo, endocardial; Epi, epicardial; MPR, myocardial perfusion reserve.

Normally distributed continuous variables are expressed as mean (±95% confidence intervals); nonparametric continuous variables are expressed as median [IQR]; and categorical variables are expressed as counts (percent).

P signifies p value for comparisons across the groups with ANOVA for normally distributed datasets and Kruskal-Wallis test for non-parametric tests.

Figure1: Eigencor plot showing the correlation between principal components (1-10) on the x axis and cardiac MRI parameters from patients’ baseline study visit on the y axis. Colours indicate the strength and direction of the correlation, with red representing positive correlations and blue representing negative correlations. The scaled bar on the right represents correlation coefficients, and significance levels are denoted by asterisks (*p < 0.05, **p < 0.01, ***p < 0.001). PC, principal component; LVEDVi, indexed left ventricular end diastolic volume; LV Mass EDV, left ventricular mass to end diastolic volume ratio; LVESVi, left ventricular end systolic volume indexed; LVEF, left ventricular ejection fraction; GLS, global longitudinal strain; Atrial EF, atrial ejection fraction; MBF Stress, stress myocardial blood flow; MBF Rest, rest myocardial blood flow; MPR rest global, global myocardial perfusion reserve; Stress MBF Endo, endocardial stress myocardial blood flow; Stress MBF Epi, epicardial stress myocardial blood flow; Stress MBF Ratio, stress myocardial blood flow ratio; Rest MBF Endo, endocardial rest myocardial blood flow; Rest MBF epi, epicardial rest myocardial blood flow; Rest MBF ratio, rest myocardial blood flow ratio; Endo MPR, endocardial myocardial perfusion reserve; Epi MPR, epicardial myocardial perfusion reserve.
Figure 2: Eigencor plot showing the correlation between principal components (1-10) on the x axis and cardiac MRI parameters from patients’ follow up study visit on the y axis. Colours indicate the strength and direction of the correlation, with red representing positive correlations and blue representing negative correlations. The scaled bar on the right represents correlation coefficients, and significance levels are denoted by asterisks (*p < 0.05, **p < 0.01, ***p < 0.001). PC, principal component; LVEDVi, indexed left ventricular end diastolic volume; LV Mass EDV, left ventricular mass to end diastolic volume ratio; LVESVi, left ventricular end systolic volume indexed; LVEF, left ventricular ejection fraction; GLS, global longitudinal strain; Atrial EF, atrial ejection fraction; MBF Stress, stress myocardial blood flow; MBF Rest, rest myocardial blood flow; MPR rest global, global myocardial perfusion reserve; Stress MBF Endo, endocardial stress myocardial blood flow; Stress MBF Epi, epicardial stress myocardial blood flow; Stress MBF Ratio, stress myocardial blood flow ratio; Rest MBF Endo, endocardial rest myocardial blood flow; Rest MBF epi, epicardial rest myocardial blood flow; Rest MBF ratio, rest myocardial blood flow ratio; Endo MPR, endocardial myocardial perfusion reserve; Epi MPR, epicardial myocardial perfusion reserve.