title: A general theory of evolution based on energy efficiency: its implications for diseases.
abstract: We propose a general theory of evolution based on energy efficiency. Life represents an emergent property of energy. The earth receives energy from cosmic sources such as the sun. Biologic life can be characterized by the conversion of available energy into complex systems. Direct energy converters such as photosynthetic microorganisms and plants transform light energy into high-energy phosphate bonds that fuel biochemical work. Indirect converters such as herbivores and carnivores predominantly feed off the food chain supplied by these direct converters. Improving energy efficiency confers competitive advantage in the contest among organisms for energy. We introduce a term, return on energy (ROE), as a measure of energy efficiency. We define ROE as a ratio of the amount of energy acquired by a system to the amount of energy consumed to generate that gain. Life-death cycling represents a tactic to sample the environment for innovations that allow increases in ROE to develop over generations rather than an individual lifespan. However, the variation-selection strategem of Darwinian evolution may define a particular tactic rather than an overarching biological paradigm. A theory of evolution based on competition for energy and driven by improvements in ROE both encompasses prior notions of evolution and portends post-Darwinian mechanisms. Such processes may involve the exchange of non-genetic traits that improve ROE, as exemplified by cognitive adaptations or memes. Under these circumstances, indefinite persistence may become favored over life-death cycling, as increases in ROE may then occur more efficiently within a single lifespan rather than over multiple generations. The key to this transition may involve novel methods to address the promotion of health and cognitive plasticity. We describe the implications of this theory for human diseases.
authors.affiliation: Department of Radiology, Stanford University, 470 University Avenue, Palo Alto, CA 94301, USA. ayun@stanford.edu
authors.forename: Anthony J
authors.initials: AJ
authors.lastname: Yun
authors.forename: Patrick Y
authors.initials: PY
authors.lastname: Lee
authors.forename: John D
authors.initials: JD
authors.lastname: Doux
authors.forename: Buford R
authors.initials: BR
authors.lastname: Conley
mesh_terms: D000818:Animals; D005075:Biological Evolution; D002384:Catalysis; D004734:Energy Metabolism; D006801:Humans; D008954:Models, Biological; D008962:Models, Theoretical; D015398:Signal Transduction