Perspectives in systems nephrology
Standard
Perspectives in systems nephrology. / Lindenmeyer, Maja T; Alakwaa, Fadhl; Rose, Michael; Kretzler, Matthias.
in: CELL TISSUE RES, Jahrgang 385, Nr. 2, 08.2021, S. 475-488.Publikationen: SCORING: Beitrag in Fachzeitschrift/Zeitung › SCORING: Review › Forschung
Harvard
APA
Vancouver
Bibtex
}
RIS
TY - JOUR
T1 - Perspectives in systems nephrology
AU - Lindenmeyer, Maja T
AU - Alakwaa, Fadhl
AU - Rose, Michael
AU - Kretzler, Matthias
PY - 2021/8
Y1 - 2021/8
N2 - Chronic kidney diseases (CKD) are a major health problem affecting approximately 10% of the world's population and posing increasing challenges to the healthcare system. While CKD encompasses a broad spectrum of pathological processes and diverse etiologies, the classification of kidney disease is currently based on clinical findings or histopathological categorizations. This descriptive classification is agnostic towards the underlying disease mechanisms and has limited progress towards the ability to predict disease prognosis and treatment responses. To gain better insight into the complex and heterogeneous disease pathophysiology of CKD, a systems biology approach can be transformative. Rather than examining one factor or pathway at a time, as in the reductionist approach, with this strategy a broad spectrum of information is integrated, including comprehensive multi-omics data, clinical phenotypic information, and clinicopathological parameters. In recent years, rapid advances in mathematical, statistical, computational, and artificial intelligence methods enable the mapping of diverse big data sets. This holistic approach aims to identify the molecular basis of CKD subtypes as well as individual determinants of disease manifestation in a given patient. The emerging mechanism-based patient stratification and disease classification will lead to improved prognostic and predictive diagnostics and the discovery of novel molecular disease-specific therapies.
AB - Chronic kidney diseases (CKD) are a major health problem affecting approximately 10% of the world's population and posing increasing challenges to the healthcare system. While CKD encompasses a broad spectrum of pathological processes and diverse etiologies, the classification of kidney disease is currently based on clinical findings or histopathological categorizations. This descriptive classification is agnostic towards the underlying disease mechanisms and has limited progress towards the ability to predict disease prognosis and treatment responses. To gain better insight into the complex and heterogeneous disease pathophysiology of CKD, a systems biology approach can be transformative. Rather than examining one factor or pathway at a time, as in the reductionist approach, with this strategy a broad spectrum of information is integrated, including comprehensive multi-omics data, clinical phenotypic information, and clinicopathological parameters. In recent years, rapid advances in mathematical, statistical, computational, and artificial intelligence methods enable the mapping of diverse big data sets. This holistic approach aims to identify the molecular basis of CKD subtypes as well as individual determinants of disease manifestation in a given patient. The emerging mechanism-based patient stratification and disease classification will lead to improved prognostic and predictive diagnostics and the discovery of novel molecular disease-specific therapies.
U2 - 10.1007/s00441-021-03470-3
DO - 10.1007/s00441-021-03470-3
M3 - SCORING: Review article
C2 - 34027630
VL - 385
SP - 475
EP - 488
JO - CELL TISSUE RES
JF - CELL TISSUE RES
SN - 0302-766X
IS - 2
ER -