Irisin as a Potential Biomarker Associated with Myocardial Injuries in Patients with Severe Hypothyroidism

Objective. Irisin, a novel myokine, has recently been considered to produce a cardioprotective effect. Potential biomarkers for myocardial injuries in patients with severe hypothyroidism have yet to be identified. We aimed to investigate whether serum irisin may serve as a promising biomarker for early detecting the myocardial injuries in patients with severe hypothyroidism. Methods. This cross-sectional study comprised 25 newly diagnosed drug-naive patients with severe primary hypothyroidism and 17 age- and sex-matched healthy controls. Circulating irisin levels and cardiac magnetic resonance (CMR) were evaluated in each participant. Left ventricular (LV) myocardial injuries were detected by CMR-based T1 mapping technique using a modified look-locker inversion recovery (MOLLI) sequence, which is quantified as native T1 values. Results. Compared with healthy controls, the severe hypothyroidism group had significantly lower levels of serum irisin, especially those with pericardial effusion ( P < 0.05 ). The severe hypothyroidism subjects exhibited lower peak filling rates (PFRs) and higher native myocardial T1 values than controls ( P < 0.05 ). Additionally, the ROC analysis displayed that the sensitivity and specificity of serum irisin for diagnosing pericardial effusion in patients with severe hypothyroidism were 73.3% and 100.0%, respectively. The AUC was 0.920 (0.861–1.000) ( P < 0.001 ). The cutoff value was 36.94 ng/mL. Moreover, the results in subgroup analysis revealed that the native T1 values of the low-irisin group were significantly higher than that of the high-irisin group ( P < 0.05 ). According to multivariate linear regression analysis, serum irisin concentrations were negatively and independently correlated with native myocardial T1 values after adjustment for age, sex, and other conventional confounding factors (β = −1.473, P < 0.05 ). Conclusions. Irisin may be a potential biomarker for predicting myocardial injuries in patients with severe hypothyroidism.

Genetics of Myocardial Interstitial Fibrosis in the Human Heart and Association with Disease

Myocardial interstitial fibrosis is a common thread in multiple cardiovascular diseases including heart failure, atrial fibrillation, conduction disease and sudden cardiac death. To investigate the biologic pathways that underlie interstitial fibrosis in the human heart, we developed a machine learning model to measure myocardial T1 time, a marker of myocardial interstitial fibrosis, in 42,654 UK Biobank participants. Greater T1 time was associated with impaired glucose metabolism, systemic inflammation, renal disease, aortic stenosis, cardiomyopathy, heart failure, atrial fibrillation and conduction disease. In genome-wide association analysis, we identified 12 independent loci associated with native myocardial T1 time with evidence of high genetic correlation between the interventricular septum and left ventricle free wall (r2g = 0.82). The identified loci implicated genes involved in glucose homeostasis (SLC2A12), iron homeostasis (HFE, TMPRSS6), tissue repair (ADAMTSL1, VEGFC), oxidative stress (SOD2), cardiac hypertrophy (MYH7B) and calcium signaling (CAMK2D). Transcriptome-wide association studies highlighted the role of expression of ADAMTSL1 and SLC2A12 in human cardiac tissue in modulating myocardial tissue characteristics and interstitial fibrosis. Harnessing machine learning to perform large-scale phenotyping of interstitial fibrosis in the human heart, our results yield novel insights into biologically relevant pathways for myocardial fibrosis and prioritize investigation of pathways for the development of anti-fibrotic therapies.

Left Ventricular Myocardial T1 Values and Extracellular Volume Fraction in Asymptomatic Subjects: Variations According to Left Ventricular Segments and Correlation with Cardiovascular Risk Factors

Purpose: To evaluate the normal range and variation in pre-contrast (preT1) and post-contrast (postT1) myocardial T1 values and extracellular volume fraction (ECV) according to left ventricular (LV) segments and to check for correlations between them and known cardiovascular risk factors.Methods: This study included 233 asymptomatic subjects (210 men and 23 women; aged 54.1±6.0 years) who underwent cardiac magnetic resonance imaging with preT1 and postT1 mapping on a 1.5-T scanner. T1 values and ECVs were compared among LV segments, age groups, and sex, and correlated with renal function. Based on the presence of hypertension (HTN) and diabetes mellitus (DM), the subjects were subdivided into the control (n=121), HTN (n=58), DM (n=25), and HTN and DM (HTN-DM) groups (n=29).Results: T1 values and ECV showed significant differences between the basal septal and lateral segments (p≤0.001) and between the mid-septal and mid-lateral segments (PreT1 p≤0.003, postT1 and ECV p<0.001). Among subgroups according to the HTN and DM status, the HTN-DM group showed a significantly higher ECV (0.260±0.023) than the control (0.240±0.021, p=0.011) and HTN (0.241±0.024, p=0.041) groups. Overall postT1 and ECV of the LV had significant correlation with the estimated glomerular filtration rate (r = 0.19, p=0.038 for postT1; r = -0.23, p=0.011 for ECV).Conclusion: Septal segments show higher preT1 and ECV but lower postT1 than lateral segments at the mid-ventricular and basal levels. ECV is significantly affected by cardiovascular risk factors such as HTN, DM, and decreased renal function, even in asymptomatic subjects.

Bioelastic properties of the aorta in children, adolescents and young adults after cardiac transplantation: a cardiovascular magnetic resonance study

Background Long-term complications after cardiac transplantation are common and typically include arterial hypertension and coronary allograft vasculopathy. Few studies also suggested that heart transplant recipients have an increased arterial stiffness. Purpose This prospective study aimed to assess the bioelastic properties of the aorta as well as LV function, morphology and structure in children and young adults after cardiac transplantation. Methods CMR studies from 34 patients (median age: 17.1 years, range: 8–24 years) who underwent cardiac transplantation in childhood were analysed. Aortic anatomy and distensibility were assessed at five locations of the thoracic aorta using steady-state free precession cine sequences. Pulse wave velocity (PWV) of the aortic arch and the descending thoracic aorta was measured from 2-dimensional phase contrast images. Size and function of the left atrium and the ventricles were assessed from a stack of short axis slices. Myocardial T1 times were determined using a standard MOLLI sequence. Results Cross-sectional areas of the ascending aorta and the aortic arch tended to be lower in patients compared to controls (ascending aorta 464.5±172.5 mm2 vs. 515.3±186.3 mm2, aortic arch 342.4±113.3 mm2 vs. 376.9±148.5 mm2) whereas cross-sectional areas of the descending aorta tended to be higher (aortic isthmus 283.7±102.1 mm2 vs. 257.9±89.5 mm2, aorta descendens diaphragmal 218.4±75.8 mm2 vs. 214.2±75.0 mm2) and showed a correlation with systolic blood pressure (r=0.33). PWV was higher in the aortic arch (4.8±2.4 m/s vs. 3.6±0.7 m/s). Aortic distensibility was slightly higher at all measuring points in the study population compared to the control group and showed an increase with rising distance from the heart (ascending aorta 10.5±5.8 10–3 mm Hg-1, aortic isthmus 13.1±7.5 10–3 mm Hg-1, descending aorta 16.6±6.8 10–3 mm Hg-1). Biventricular volumes were slightly reduced in the patient group compared to the control group but this was not statistically significant. Only left ventricular mass messured during the systolic phase was higher in the study population compared to the control group (males 55.1 g/m2 vs. 53.0 g/m2, females 46.2 g/m2 vs. 45.2 g/m2). T1 mapping demonstrated increased T1 times in the heart-transplanted group compared to published data in healthy adults. In particular, T1 times of the lateral and inferior myocardial segments were higher. Conclusion Patients who underwent cardiac transplantation in childhood seem to have a reduced bioelasticity of the thoracic aorta. Increased myocardial T1 times suggesting alterations in myocardial structure. FUNDunding Acknowledgement Type of funding sources: None.

Hepatic T2-times on cardiovascular magnetic resonance imaging reflect liver fibrosis and predict outcome in an all-comer cohort

Background Non-alcoholic fatty liver disease (NAFLD) is associated with dismal outcomes in patients with cardiac disorders but infrequently assessed by cardiologists. Cardiovascular magnetic resonance (CMR) is evolving as one-stop-shop imaging modality in cardiology, allowing for non-invasive myocardial tissue characterization by T1-mapping. On standard CMR exams, hepatic tissue is also assessable on T1-maps. However, it is unknown whether hepatic T1-times are associated with 1) myocardial T1-times, 2) established NAFLD scores, and 3) outcomes in patients referred for CMR. Methods In consecutive patients undergoing CMR we assessed hepatic and myocardial T1-times, and the NAFLD Fibrosis Score (NFS). Correlation analyses were used to test the association between hepatic and myocardial T1-times as well as the NFS. We used Kaplan-Meier estimates and Cox-regression models to investigate the association between hepatic T1-times and a composite endpoint of heart failure hospitalization and cardiovascular death. Results 513 patients were included (57±18 y/o, 49% female). Hepatic T1-times were 588±98ms on average and were correlated with myocardial T1-times (r=0.42, p&lt;0.001) and – weakly – with the NFS (r=0.11, p=0.04). Patients with severe liver fibrosis or cirrhosis (n=47) had significantly higher hepatic T1-times as compared to patients with no or mild fibrosis based on the NFS (635±197ms versus 588±80ms, p=0.02). During follow-up (100±40 months), a total of 137 (27%) events occurred. When stratified by quartiles, patients in the highest hepatic T1-time quartile (&gt;700ms) were at higher risk for events compared to all other quartiles (log-rank, p=0.01), which was consistent across different NAFLD risk groups based on the NFS (no/mild fibrosis, indeterminant score, severe fibrosis/cirrhosis). On Cox regression analyses, higher hepatic T1-times yielded significantly higher risk estimates for events (adj. HR 1.20 [95% CI: 1.04–1.38] per 1-SD increase, p=0.01) even when adjusted for age, sex, left and right ventricular ejection fractions, and myocardial T1-times. Conclusion Hepatic T1-times assessed on standard CMR reflect severity of NAFLD and predict outcome on top of established risk factors, including myocardial T1-times, in an all-comer CMR cohort. FUNDunding Acknowledgement Type of funding sources: Public hospital(s). Main funding source(s): Medical University of Vienna

Myocardial tissue phenotyping by radiomic features of native T1 maps and machine learning enhances disease detection and classification

Background Myocardial T1 mapping by cardiac magnetic resonance (CMR) is a useful technique to detect diffuse myocardial fibrosis, but a major limitation of T1 mapping is the significant overlap in native T1 values between health and disease. Purpose We explored whether radiomic features from T1 maps could enhance the diagnostic value of T1 mapping in distinguishing health from disease and classifying cardiac disease phenotypes. Methods In a total of 149 patients (n=30 with no evidence of heart disease, n=30 with LVH of various etiologies, n=61 with hypertrophic cardiomyopathy (HCM) and n=28 with cardiac amyloidosis) undergoing a CMR scan for various indications were included in this study. In addition to measuring native myocardial T1 values from T1 maps, we extracted a total of 843 radiomic features of myocardial texture and explored their value in disease classification. Results We first demonstrated that T1 mapping images are a rich source of extractable, quantifiable data. The first three principal components of the T1 radiomics were significantly and distinctively correlated with cardiac disease type. Unsupervised hierarchical clustering of the population by myocardial T1 radiomics was significantly associated with myocardial disease type (chi2=55.98, p&lt;0.0001). After machine learning for feature selection, training with internal validation and external testing, a model of T1 radiomics had good diagnostic performance (AUC 0.753) for multinomial classification of disease phenotype (normal vs. LVH vs. HCM vs. amyloid). A subset of seven radiomic features outperformed mean native T1 values for classification between myocardial health vs. disease and HCM phenocopies (for normal: T1 AUC 0.549 vs. radiomics AUC 0.888, for LVH: T1 AUC 0.645 vs. radiomics AUC 0.790, for HCM T1 AUC 0.541 vs. radiomics AUC 0.638 and for amyloid T1 AUC 0.769 vs. radiomics AUC 0.840). Conclusions We have shown that specific imaging patterns in myocardial native T1 maps are linked to features of cardiac disease and we have provided for the first-time evidence that radiomic phenotyping can be used to enhance the diagnostic yield of native T1 mapping for myocardial disease detection and classification. FUNDunding Acknowledgement Type of funding sources: None.