Analysis Of Systems Influencing Renal Hemodynamics And Sodium Excretion. I. Biochemical Systems Theory
Enviado por paochina • 23 de Junio de 2015 • 334 Palabras (2 Páginas) • 152 Visitas
SHARON L. REILLY, CHARLES F. SING, AND MICHAEL A. SAVAGEAU
University of Michigan Medical School, Ann Arbor
and
STEPHEN T. TURNER
Dept. of lnternal Medicine, Mayo Clinic
Abstract--In this article we present a new methodology--Biochemical Systems Theory
and Analysis---as an alternative to traditional parametric statistical procedures for investigating
differences between risk groups in a population. We review the systems theory and
how it can be used to represent a model of processes influencing renal hemodynamics and
sodium (Na § excretion. We also discuss the potential for new measures of the biology of
common diseases that can emerge from a synergism between systems theory and population-
based statistical approaches.
Key Words: Systems theory, Hypertension, Renal Hemodynamics, Genetics, Common
Diseases
Introduction
Common diseases, such as hypertension, coronary artery disease, and cancer, are the
clearest examples of biological complexity. One property of complex systems that all
common diseases share is a complex etiological hierarchy (Sing and Reilly, 1993). This
hierarchy consists of many genes (level I) determining the biochemical, physiological and
anatomical systems (level II) that are associated with the initiation, progression, and manifestation
of the disease (level III). Environmental factors, such as diet and lifestyle, also
play a key role in determining risk of disease since they influence each of these etiological
levels. As information at these etiological levels continues to accumulate there is an increasing
need to determine if this piecewise knowledge can be integrated to simultaneously
model the relationship within and between the three levels for a common disease.
Systems analysis is one class of quantitative methods that has been successful in modeling
many different types of physiological and biochemical processes (level II) and their
impact on traits associated with a particular disease (level III) (Guyton et
...