Clinical phenomapping and outcomes after heart transplantation

Maral Bakir, Nicholas J. Jackson, Simon X. Han, Alex Bui, Eleanor Chang, David A. Liem, Abbas Ardehali, Reza Ardehali, Arnold S. Baas, Marcella Calfon Press, Daniel Cruz, Mario C. Deng, Eugene C. DePasquale, Gregg C. Fonarow, Tam Khuu, Murray H. Kwon, Bernard M. Kubak, Ali Nsair, Jennifer L. Phung, Elaine F. ReedJoanna M. Schaenman, Richard J. Shemin, Qiuheng J. Zhang, Chi Hong Tseng, Martin Cadeiras

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

Background: Survival after heart transplantation (HTx) is limited by complications related to alloreactivity, immune suppression, and adverse effects of pharmacologic therapies. We hypothesize that time-dependent phenomapping of clinical and molecular data sets is a valuable approach to clinical assessments and guiding medical management to improve outcomes. Methods: We analyzed clinical, therapeutic, biomarker, and outcome data from 94 adult HTx patients and 1,557 clinical encounters performed between January 2010 and April 2013. Multivariate analyses were used to evaluate the association between immunosuppression therapy, biomarkers, and the combined clinical end point of death, allograft loss, retransplantation, and rejection. Data were analyzed by K-means clustering (K = 2) to identify patterns of similar combined immunosuppression management, and percentile slopes were computed to examine the changes in dosages over time. Findings were correlated with clinical parameters, human leucocyte antigen antibody titers, and peripheral blood mononuclear cell gene expression of the AlloMap (CareDx, Inc., Brisbane, CA) test genes. An intragraft, heart tissue gene coexpression network analysis was performed. Results: Unsupervised cluster analysis of immunosuppressive therapies identified 2 groups, 1 characterized by a steeper immunosuppression minimization, associated with a higher likelihood for the combined end point, and the other by a less pronounced change. A time-dependent phenomap suggested that patients in the group with higher event rates had increased human leukocyte antigen class I and II antibody titers, higher expression of the FLT3 AlloMap gene, and lower expression of the MARCH8 and WDR40A AlloMap genes. Intramyocardial biomarker-related coexpression network analysis of the FLT3 gene showed an immune system–related network underlying this biomarker. Conclusions: Time-dependent precision phenotyping is a mechanistically insightful, data-driven approach to characterize patterns of clinical care and identify ways to improve clinical management and outcomes.

Original languageEnglish (US)
Pages (from-to)956-966
Number of pages11
JournalJournal of Heart and Lung Transplantation
Volume37
Issue number8
DOIs
StatePublished - Aug 2018
Externally publishedYes

Fingerprint

Heart Transplantation
Biomarkers
Immunosuppression
HLA Antigens
Cluster Analysis
Genes
Gene Expression
Antibodies
Gene Regulatory Networks
Therapeutics
Immunosuppressive Agents
Allografts
Blood Cells
Multivariate Analysis
Survival

Keywords

  • allograft
  • biomarkers
  • heart transplantation
  • immunosuppression
  • phenomapping
  • rejection

ASJC Scopus subject areas

  • Surgery
  • Pulmonary and Respiratory Medicine
  • Cardiology and Cardiovascular Medicine
  • Transplantation

Cite this

Clinical phenomapping and outcomes after heart transplantation. / Bakir, Maral; Jackson, Nicholas J.; Han, Simon X.; Bui, Alex; Chang, Eleanor; Liem, David A.; Ardehali, Abbas; Ardehali, Reza; Baas, Arnold S.; Press, Marcella Calfon; Cruz, Daniel; Deng, Mario C.; DePasquale, Eugene C.; Fonarow, Gregg C.; Khuu, Tam; Kwon, Murray H.; Kubak, Bernard M.; Nsair, Ali; Phung, Jennifer L.; Reed, Elaine F.; Schaenman, Joanna M.; Shemin, Richard J.; Zhang, Qiuheng J.; Tseng, Chi Hong; Cadeiras, Martin.

In: Journal of Heart and Lung Transplantation, Vol. 37, No. 8, 08.2018, p. 956-966.

Research output: Contribution to journalArticle

Bakir, M, Jackson, NJ, Han, SX, Bui, A, Chang, E, Liem, DA, Ardehali, A, Ardehali, R, Baas, AS, Press, MC, Cruz, D, Deng, MC, DePasquale, EC, Fonarow, GC, Khuu, T, Kwon, MH, Kubak, BM, Nsair, A, Phung, JL, Reed, EF, Schaenman, JM, Shemin, RJ, Zhang, QJ, Tseng, CH & Cadeiras, M 2018, 'Clinical phenomapping and outcomes after heart transplantation', Journal of Heart and Lung Transplantation, vol. 37, no. 8, pp. 956-966. https://doi.org/10.1016/j.healun.2018.03.006
Bakir, Maral ; Jackson, Nicholas J. ; Han, Simon X. ; Bui, Alex ; Chang, Eleanor ; Liem, David A. ; Ardehali, Abbas ; Ardehali, Reza ; Baas, Arnold S. ; Press, Marcella Calfon ; Cruz, Daniel ; Deng, Mario C. ; DePasquale, Eugene C. ; Fonarow, Gregg C. ; Khuu, Tam ; Kwon, Murray H. ; Kubak, Bernard M. ; Nsair, Ali ; Phung, Jennifer L. ; Reed, Elaine F. ; Schaenman, Joanna M. ; Shemin, Richard J. ; Zhang, Qiuheng J. ; Tseng, Chi Hong ; Cadeiras, Martin. / Clinical phenomapping and outcomes after heart transplantation. In: Journal of Heart and Lung Transplantation. 2018 ; Vol. 37, No. 8. pp. 956-966.
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T1 - Clinical phenomapping and outcomes after heart transplantation

AU - Bakir, Maral

AU - Jackson, Nicholas J.

AU - Han, Simon X.

AU - Bui, Alex

AU - Chang, Eleanor

AU - Liem, David A.

AU - Ardehali, Abbas

AU - Ardehali, Reza

AU - Baas, Arnold S.

AU - Press, Marcella Calfon

AU - Cruz, Daniel

AU - Deng, Mario C.

AU - DePasquale, Eugene C.

AU - Fonarow, Gregg C.

AU - Khuu, Tam

AU - Kwon, Murray H.

AU - Kubak, Bernard M.

AU - Nsair, Ali

AU - Phung, Jennifer L.

AU - Reed, Elaine F.

AU - Schaenman, Joanna M.

AU - Shemin, Richard J.

AU - Zhang, Qiuheng J.

AU - Tseng, Chi Hong

AU - Cadeiras, Martin

PY - 2018/8

Y1 - 2018/8

N2 - Background: Survival after heart transplantation (HTx) is limited by complications related to alloreactivity, immune suppression, and adverse effects of pharmacologic therapies. We hypothesize that time-dependent phenomapping of clinical and molecular data sets is a valuable approach to clinical assessments and guiding medical management to improve outcomes. Methods: We analyzed clinical, therapeutic, biomarker, and outcome data from 94 adult HTx patients and 1,557 clinical encounters performed between January 2010 and April 2013. Multivariate analyses were used to evaluate the association between immunosuppression therapy, biomarkers, and the combined clinical end point of death, allograft loss, retransplantation, and rejection. Data were analyzed by K-means clustering (K = 2) to identify patterns of similar combined immunosuppression management, and percentile slopes were computed to examine the changes in dosages over time. Findings were correlated with clinical parameters, human leucocyte antigen antibody titers, and peripheral blood mononuclear cell gene expression of the AlloMap (CareDx, Inc., Brisbane, CA) test genes. An intragraft, heart tissue gene coexpression network analysis was performed. Results: Unsupervised cluster analysis of immunosuppressive therapies identified 2 groups, 1 characterized by a steeper immunosuppression minimization, associated with a higher likelihood for the combined end point, and the other by a less pronounced change. A time-dependent phenomap suggested that patients in the group with higher event rates had increased human leukocyte antigen class I and II antibody titers, higher expression of the FLT3 AlloMap gene, and lower expression of the MARCH8 and WDR40A AlloMap genes. Intramyocardial biomarker-related coexpression network analysis of the FLT3 gene showed an immune system–related network underlying this biomarker. Conclusions: Time-dependent precision phenotyping is a mechanistically insightful, data-driven approach to characterize patterns of clinical care and identify ways to improve clinical management and outcomes.

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