TY - JOUR
T1 - Use of Computation Ecosystems to Analyze the Kidney-Heart Crosstalk
AU - Wu, Z.J.
AU - Lohmoeller, J.
AU - Kuhl, C.
AU - Wehrle, K.
AU - Jankowski, J.
N1 - Funding Information:
This study was supported by the state government and by a grant from the German Research Foundation (Deutsche Forschungsgemeinschaft, SFB/TRR219 project C-04 to J. Jankowski, Project-ID: 322900939) and CRC1382 to J. Jankowski (Project-ID: 403224013) and by Rheinisch-Westfälische Technische Hochschule Aachen University under the Excellence Strategy of the German federal. J. Jankowski was supported by the European Union’s Horizon 2020 research and innovation program European Union International Network for Training on Risks of Vascular Intimal Calcification and roads to Regression of Cardiovascular Disease (722609), CArdioREnal SYndrome ANalysis (764474), and the European Union-Cost PerMedik (CA21165). J. Jankowski is supported by a grant from the Interdisciplinary Center for Clinical Research within the Faculty of Medicine at Rheinisch-Westfälische Technische Hochschule Aachen University. The authors thank Jan Pennekamp and Shruti Bhargava for their support in preparing the article.
Publisher Copyright:
© 2023 American Heart Association, Inc.
PY - 2023/4/14
Y1 - 2023/4/14
N2 - The identification of mediators for physiologic processes, correlation of molecular processes, or even pathophysiological processes within a single organ such as the kidney or heart has been extensively studied to answer specific research questions using organ-centered approaches in the past 50 years. However, it has become evident that these approaches do not adequately complement each other and display a distorted single-disease progression, lacking holistic multilevel/multidimensional correlations. Holistic approaches have become increasingly significant in understanding and uncovering high dimensional interactions and molecular overlaps between different organ systems in the pathophysiology of multimorbid and systemic diseases like cardiorenal syndrome because of pathological heart-kidney crosstalk. Holistic approaches to unraveling multimorbid diseases are based on the integration, merging, and correlation of extensive, heterogeneous, and multidimensional data from different data sources, both -omics and nonomics databases. These approaches aimed at generating viable and translatable disease models using mathematical, statistical, and computational tools, thereby creating first computational ecosystems. As part of these computational ecosystems, systems medicine solutions focus on the analysis of -omics data in single-organ diseases. However, the data-scientific requirements to address the complexity of multimodality and multimorbidity reach far beyond what is currently available and require multiphased and cross-sectional approaches. These approaches break down complexity into small and comprehensible challenges. Such holistic computational ecosystems encompass data, methods, processes, and interdisciplinary knowledge to manage the complexity of multiorgan crosstalk. Therefore, this review summarizes the current knowledge of kidney-heart crosstalk, along with methods and opportunities that arise from the novel application of computational ecosystems providing a holistic analysis on the example of kidney-heart crosstalk.
AB - The identification of mediators for physiologic processes, correlation of molecular processes, or even pathophysiological processes within a single organ such as the kidney or heart has been extensively studied to answer specific research questions using organ-centered approaches in the past 50 years. However, it has become evident that these approaches do not adequately complement each other and display a distorted single-disease progression, lacking holistic multilevel/multidimensional correlations. Holistic approaches have become increasingly significant in understanding and uncovering high dimensional interactions and molecular overlaps between different organ systems in the pathophysiology of multimorbid and systemic diseases like cardiorenal syndrome because of pathological heart-kidney crosstalk. Holistic approaches to unraveling multimorbid diseases are based on the integration, merging, and correlation of extensive, heterogeneous, and multidimensional data from different data sources, both -omics and nonomics databases. These approaches aimed at generating viable and translatable disease models using mathematical, statistical, and computational tools, thereby creating first computational ecosystems. As part of these computational ecosystems, systems medicine solutions focus on the analysis of -omics data in single-organ diseases. However, the data-scientific requirements to address the complexity of multimodality and multimorbidity reach far beyond what is currently available and require multiphased and cross-sectional approaches. These approaches break down complexity into small and comprehensible challenges. Such holistic computational ecosystems encompass data, methods, processes, and interdisciplinary knowledge to manage the complexity of multiorgan crosstalk. Therefore, this review summarizes the current knowledge of kidney-heart crosstalk, along with methods and opportunities that arise from the novel application of computational ecosystems providing a holistic analysis on the example of kidney-heart crosstalk.
KW - disease progression
KW - ecosystem
KW - heart
KW - kidney
KW - multimorbidity
KW - CARDIORENAL SYNDROME
KW - CARDIOVASCULAR OUTCOMES
KW - OMICS DATA
KW - DIAGNOSIS
KW - HEALTH
KW - MORTALITY
KW - DISEASE
KW - PATHOPHYSIOLOGY
KW - MULTIMORBIDITY
KW - DYSFUNCTION
U2 - 10.1161/CIRCRESAHA.123.321765
DO - 10.1161/CIRCRESAHA.123.321765
M3 - (Systematic) Review article
C2 - 37053282
SN - 0009-7330
VL - 132
SP - 1084
EP - 1100
JO - Circulation Research
JF - Circulation Research
IS - 8
ER -