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Abstract Number: 1929

Echocardiographic Phenomics for Novel Classification of Cardiac Involvement in Systemic Sclerosis

Monique Hinchcliff1, Vistasp Daruwalla2, Lauren Beussink-Nelson3, Sofia Podlusky4, Mary A. Carns4, John Varga5 and Sanjiv J. Shah6, 1Division of Rheumatology, Northwestern University Feinberg School of Medicine, Chicago, IL, 2Department of Internal Medicine, Division of Cardiology, Northwestern University Feinberg School of Medicine, Chicago, IL, 3Department of Cardiology, Northwestern University Feinberg School of Medicine, Chicago, IL, 4Department of Medicine, Division of Rheumatology, Northwestern University Feinberg School of Medicine, Chicago, IL, 5Rheumatology, Northwestern University Feinberg School of Medicine, Chicago, IL, 6Cardiology, Northwestern University Feinberg School of Medicine, Chicago, IL

Meeting: 2014 ACR/ARHP Annual Meeting

Keywords: Bioinformatics, Cardiovascular disease and systemic sclerosis

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Session Information

Title: Systemic Sclerosis, Fibrosing Syndromes and Raynaud's - Clinical Aspects and Therapeutics II: Approaches to Cardiac and Vascular Manifestations in Systemic Sclerosis

Session Type: Abstract Submissions (ACR)

Background/Purpose: Traditional studies of systemic sclerosis (SSc) cardiac involvement have examined one or a few echocardiographic (echo) variables; however, cardiac involvement in SSc can be multi-faceted and heterogeneous. We hypothesized that evaluation of dense quantitative echo phenotypic data using repurposed genetic analytic software would allow for novel classification of SSc cardiac involvement. 

Methods: We studied 377 patients with SSc enrolled in the Northwestern Scleroderma Program. All patients underwent comprehensive echo with Doppler and tissue Doppler imaging using a standardized protocol for image acquisition and interpretation. A total of 57 unique, quantitative echo phenotypes were standardized to mean=0 and SD=±1. The quantitative phenotypic data was entered into gene expression analysis software (Cluster), and a phenotype heatmap (“pheno-map”) was generated (TreeView). Cluster groups (“pheno-groups”) were defined based on the resultant heriarchical dendogram. We used linear, logistic, and Cox regression analyses to determine differences in clinical, laboratory, pulmonary function testing, and survival characteristics among pheno-groups.

Results: The mean±SD age was 51±13 years, 82% were female, 51% had limited cutaneous SSc, 32% had diffuse cutaneous SSc, and 17% had other forms of SSc (e.g., overlap syndromes). Prevalence of SSc complications were as follows: PAH in 9%, ILD in 17.5%, and LV systolic dysfunction (EF<50%) in 4%. After the phenomapping analysis, 4 distinct, mutually exclusive pheno-groups were identified. The 4 groups differed significantly on clinical characteristics and outcomes. The pheno-groups did not differ by SSc subtype (limited vs. diffuse cutaneous SSc), but autoantibodies did differ by pheno-group (e.g., anti-centromere antibody was most prevalent in pheno-group #4 [38%]). PAH prevalence differed across groups (highest [18.5%] in pheno-group #1, P=0.002). Clinical ILD did not differ among groups (P=0.24), but FVC and DLCO were lowest in pheno-group #1 (P<0.001). LV, RV, and left atrial mechanics were also worse in pheno-group #1 (P<0.02 for all comparisons). Pheno-group #1 had the highest risk for death (HR 6.0, 95% CI 1.3-28.5; P=0.024 after adjustment for age, sex, SSc subtype, disease duration, ILD, and PAH). 

Conclusion: Heirarchical cluster analysis of high-density, quantitative echo phenotypes results in novel, clinically relevant classification of cardiac structure/function in SSc. Further research into the identified echo pheno-groups of SSc may enhance pathophysiologic insight into SSc cardiac involvement.

Figure. Echocardiographic Phenotype Heatmap “Pheno-Map” (top panel) and Cumulative Hazard for Death by Pheno-Group (bottom panel)


Disclosure:

M. Hinchcliff,

Gilead Science,

9;

V. Daruwalla,
None;

L. Beussink-Nelson,
None;

S. Podlusky,
None;

M. A. Carns,
None;

J. Varga,
None;

S. J. Shah,
None.

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