Catch-up growth (CUG), referring to individuals with low birth weight reaching or exceeding normal body weight later in life, is negatively correlated to adult health and lifespan. From the energetic viewpoint, CUG and diet restriction (DR) are two sides of the same coin; the former speeds up growth, the latter suppresses growth, and both alter animalsí energy allocation strategy, and therefore affect health maintenance. Chen has developed a theoretical model (Hou et al. 2011, J. Gerontol. A Biol. Sci.) for quantitatively elucidating the tradeoff between CUG and health maintenance in mammals growing in different sets of prenatal and postnatal environments. We try to extend the model, and develop a theoretical framework for designing growth therapies for human individuals with low birth weight.

Much efforts and resources have been devoted to growth therapies for children with low birth weight. However, growth therapies, which lead to catch-up growth, may be dangerous in terms of adult diseases and lifespan, if they ignore the energy tradeoff between growth and health maintenance. To take this tradeoff into account, two theoretical efforts must be made.

First, many descriptive and statistical models have been proposed for studying human growth. However, there is no theoretical framework based on first principles that specifies the energetic mechanisms underlying human growth. The existing energetic growth models, e.g., West et al (2001, Nature), successfully predict the energy allocations and growth trajectories in a variety of animals. But, none of these models predicts human growth from the energetic viewpoint. Compared to other animals in the same taxon, human growth is considerably slow in the early years, and then accelerates later. Some researchers have hypothesized that slow growth in humans in the early years is due to the development of brain, which is assumed to be energetically expensive. However, no quantitative study has been done to estimate the energetic cost of synthesizing brain tissue.

Recently, Chen and one of his students, who is majored in physics, develop a series of differential equations based on the first principles of energy and mass conservation for understanding the energetics of brain development. Using empirical data and our equations, we estimated that it costs about 50 kilojoules to synthesize one gram of human brain tissue. This value is 10-fold higher than that of other tissues, and therefore confirms that brain development may distract a large amount of energy from synthesizing other tissues in early development.

Currently, we are trying to couple the differential equations for the growth of the brain and the rest of the body, and take into account of the energetic cost of maintaining brain function in the model. The solutions of the coupled differential equation will predict the unique growth trajectory of the brain as well as the whole human body from the energetic viewpoint.

Second, our preliminary results (
(Hou, 2014 American Naturalist)) indicate that the energetic cost of synthesizing one unit of biomass is not a constant during development. With the model developed in the first step and empirical data, we try to estimate the dynamic change in the energy cost of human growth as a function of age. The model and the estimate of the dynamic energy cost of growth will offer a theoretical foundation for designing growth therapies that optimize (not maximize) growth, and balance growth and maintenance. Such therapies will accelerate growth during the age periods, identified by the model, when biosynthesis is relatively cheap, but avoid fast growth when it is expensive.