The Code of Life, Aging, and Disease
The “Dynamic Code”
by Dieter Hesch*
Multiple researchers have covered the process of aging as they seek to understand the phenomenon and the biologic processes involved. The motivation behind this research was based on the perception that the perspective employed by scientists in understanding the aging process is inaccurate. The aim of the study is to develop the “Dynamic Code” theory and identify its importance to the aging process and disease.
The aging process is perceived to be a partially reversible but mainly irreversible destruction of biological matter. Several considerations need to be taken into account to understand the concept under investigation. One such consideration is the physicochemical matter that leads to the production of life. Another consideration is the evolution process of the biological matter and life.
A study conducted by Springsteen et al. (2018) pointed out that the evolution of the metabolic cycle occurred under prebiotic conditions. The evolution further progressed to sophisticated metabolic pathways that are significantly controlled by the polymeric catalysts. The research also contributed to an understanding of the current view of the possible existence of extraterrestrial life.
The current knowledge on the life-generating catalytic cycles reflects the importance of a structural organization and compartmentalization throughout the various boundaries. The structural organization of the prebiotic components primordial soup is identified to be essential to support the generation of life (Schroedinger, 1944). The thermodynamic laws are used to explain the exchange of the catalytic reactions across the borders. Erwin Schroedinger, in 1943, provided the initial description of the basic theory of biological thermodynamic of matter (Schroedinger, 1944).
Maturana and Varela coined the term “autopoiesis” and subsequently developed the theory of autopoiesis (Hall, 2011). The theory covers the self-organization, self-preservation, and the reproduction of the thermodynamic networks (Hall, 2011).
Gladyshev (2017) investigated hierarchical thermodynamic laws, where he outlined that they are the physical foundation of Darwinism. However, I disagree with the findings he made regarding evolution and the aging process. The disagreement with his view does not in any manner contradict the thermodynamic approach he adopted when analyzing the origin of life.
The structural and thermodynamic evolution of single-cell organisms can be understood by assessing their borders. The single-cell organisms comprise two systems of “borders”: the outer cell membrane and the inner compartment. The outer cell membrane separates the organism from the outer environment and, as a result, safeguards the thermodynamic transfer. The inner compartment, however, comprises membranes that act as boundaries to promote the storage of the genome in the nucleus, which, in turn, supports gene expression and enhances the epigenetic modifications for reproduction purposes, for the mitochondria and the metabolome. The inner compartment is essential as it helps prevent chemical reactions as well as limiting the reactions with the outer environment.
The thermodynamics across borders refers to the structural atomic and molecular exchange of energy between the mediators that transport information. Energy as information is packed into conformation which represents packing of energy of possible spatial arrangements of atoms in a molecule that results from rotation of its constituents held by single bonds. When a messenger gives its conformational information to the next partner to perform an informational or metabolic event, the messenger loses part of the primary conformations. The transfer of the conformational information can be done with the goal of supporting the performance of the metabolic and informational event. Specific enzymes can afterward tag the massager for degradation. The “wear and tear” theory can be applied to support the understanding of the creation of “abnormal” products and bioactive mediators during the exchange of energy or the transportation of information along life.
The study can be applied to conclude that living organisms are thermodynamics “machines,” whereby their structure and functioning have been established and sustained by complex systems (“Was ist Leben?”, 2018).Therefore, the living systems can be characterized by several traits: (1) the metabolism also identified as the compartments; (2) the catalysis also identified as the enzymes; and (3) the regulation (“Was ist Leben?”, 2018). The regulation comprises various open systems that support thermodynamic metabolic exchange with the inner homeostasis and negative entropy (“Was ist Leben?”, 2018).
My understanding of the term metabolism is based on the German word “Stoffwechsel.” The term is made up of two words: “Stoff” and “Wechsel.” The first term, “Stoff,” refers to the matter of ions and molecules (a). The second term, “Wechsel,” refers to the change in the atomic and molecular structure and conformational content. The definition is based on the understanding that the thermodynamic energy of an ion and a molecule is packed in their structural conformation. The conformation comprises physiochemical information of any atom and molecule. Therefore, the metabolism is identified to be the “change” in the energy information from one ion or molecule (a) to a reactive partner (b).
Applying the term “Stoffwechsel” to the definition of metabolism, it is a process by which the matter of ions and molecules, (a) “Stoff,” transfers the conformational energy to the reactive partner (b). In this process, (a) changes “Wechsel,” the conformation, which is in turn transferred to the state of thermodynamically lower energy. The primary energy from matter is transferred to the reactive partner (b), for example, through a process of liberation of heat. The heat is then applied to boost the physiochemical reactions to support the development of complex structures that possess higher conformational energy alongside the evolutionary maturation of cells, organs, and organisms. Having been subjected to a state that poses less conformation and lowers energy content, the ion and molecules matter (a) may be perceived to be used. The secondary conformation is applied to support the thermodynamic energy transfer or in a manner that the “used” matter will be subjected to the disintegrating enzymes. During the change in the atomic and molecular structures and conformational content, specific enzymes will produce metabolic waste. In other cases, however, heat can result in the destruction of the reactive partners to produce the damaged conformational structures that, in turn, act as geno/cell toxic mediators.
Understanding the way biological matter is chemically self-organized with evolution from the first stellar molecular requires an assessment of the matter and the primordial soup (Zhao et al. 2018). Zhao et al. (2018) indicate that the heat and thermodynamics are the critical conditions that are needed initially for self-organization of matter. The provision is due to the understanding that these conditions are the “fundamental reaction mechanism which is essential to establish an understanding of the origin and the evolution of the molecular universe and, in particular, of Carbon in our Galaxy” (Zhao et al. 2018). The research further argues that these molecules are essential for the origin of life.
The author, as a young researcher at Gottingen University, was presented with the opportunity to discuss the fundamental research of Nobel Prize winner Manfred Eigen, who, for the first time, discussed “Selforganisation of Matter” (Eigen, 1971).
NASA has also supported the research on the issue as conducted by Patel (2015). The National Academy of Science of the United States of America gives the most recent research that supports the theory of self-organized matter (Forsythe et al., 2017).
First of Life
This section provides a general review of the evolution history of life as presented in Wikipedia and other sources. The core of this discussion is how the first matter obtained life from the prebiotic soup. The prebiotic soup is the sum of hypothetical condition on earth billions of years ago. These conditions led to chemical reactions within the atmosphere, thus giving matter life. Nonetheless, one Japanese publication argues that life began in a nuclear geyser that was powered by a uranium deposit (Lovett, 2018). I may not completely support or refute both theories, but rather combine the two ideas to analyze how life originated, evolved, and explain concepts of reproduction, aging, and end of life. Research shows that all species of organisms evolved from a common ancestor. The researchers have been able successfully to create life-like cells; eight ingredients that include two proteins, three buffering agents, two types of fat molecules, and some chemical energy. These ingredients were successful in the creation of a flotilla of bouncing, pulsating blobs-rudimentary cell-like structures, with the use of machinery which is essential to divide individually.
The art of life creation with the application of limited ingredient is available in the primordial soup. The art contributes to our understanding of the way that an effective energy machinery leads to the creation of “first life” and the way that a “Code” emerges from the self-organization (Power, 2018)
Wear and Tear
The wear and tear process occurs among all thermodynamic machines, both mechanical and biological. The wear and tear process can be attributed to the thermodynamic metabolic processes that lead to physiological segregation of carbon dioxide (CO2), urine, skins, stool, and other aberrant or toxic metabolites and mediators with the organism, plasma cells, or subcellular compartments.
In living organisms, the toxic wastes are cleared by enzymes to ensure they do not cause harm. However, some little amounts are never recognized by the enzymes due to their specific structure and hence escape and produce senescence in mature cells. Senescence is the deterioration of cells, causing loss of division capability and stem cell damage. Moreover, clearing the toxic wastes or avoiding them helps to delay or prevent diseases that result from senescence or wear and tear.
The “Code” (1)
The wear and tear process can be damaging to the organism, specifically in instances where senescence targets specific central organs where the complex dynamic networks of all these living processes have been encoded. The restoration process can help in saving lives and prevent diseases. The process of transfer of information and energy through the cellular and subcellular borders can, in conjunction with the change in the energetic status of the molecules and the transformation on the dynamic cascades, be crucial to the living organism. That, therefore, makes up the basic primary “Code” of life, which I call the “Dynamic Code” (Prank et al., 1991). However, my understanding is that there is no distinct single “Code,” neither is it encoded in the molecular architecture of genes, even though the “Code” is encoded in the distinct complex dynamic systems. The “Dynamic Code” regulates such crucial aspects as the expression of genes, the epigenome, RNA, miRNA, and the process of protein synthesis. The process is the universal code during the evolution of biogenetic self-organization and the subsequent destruction. The human organism cannot be differentiated from the construction plan, which is already present within the single-cell organisms, but it is rather more complicated.
Understanding the evolution of life requires an assessment of the manner through which the negative entropy concentrated against the environment by the thermodynamics organized in the compartments. Negative entropy is the transportation of molecules against gradient across borders of biological cells to extract, store, and produce energy in the compartments. Therefore, evolution and negative entropy depend on ambient environmental temperature and reactive ontogenetic thermodynamics for inner metabolome. The “Dynamic Code” is hidden in the thermodynamic systems with the super organization of compartmentalization for individual surviving, reporting, selection in the environment, and interaction with the reactive partners. The “Code” itself seems, however, not a primary inborn attribute just because of its presence in the earliest life of any biological organism, but because it is a result of dramatic evolution of any organism from the base of its initial stem cells. It is species- and time-dependent for the maturation of gene expression in single cells, organs, and organisms.
Mingers et al. (1991, p. 38) assert that life is a self-organizing dynamic system-based program known as “Autopoiesis.” The life span among all organisms is temporarily limited under the process. There is a time dependent process in decades, years, months, days, and subunits down to seconds. The process is a dynamic evolution from the embryo to the senescent and is governed by the encrypted program of aging and its stipulated “Code,” thus prompting scientists to conduct more research.
Joon Yun, the president of Palo Alto Investors, LLC, seems to believe that the aging code of life exists and can be hacked according to his Wikipedia page (https://en.wikipedia.org/wiki/Joon_Yun). Similarly, the Human Genome project was started to determine where the “Code” was hidden in the genetic code. However, after realizing it was not the case, “epigenome” also came into play only to realize that there was no code but DNA modifications like Horvath’s clock, according to the Wikipedia page of Epigenetic clock (https://en.wikipedia.org/wiki/Epigenetic_clock).
Cold and Hot Life
Assessing the evolution of life requires an evaluation of two extreme living organisms. One such organ is the Greenland Shark, which is the oldest living animal that lives in cold water for up to 400 years, whereas the other organ is the bowhead whale that lives for up to 200 years in cold water, as provided in the Wikipedia page of Bowhead Whale (https://en.wikipedia.org/wiki/Bowhead_whale).
The lives of mayflies depend on ambient temperatures. While some can live for 5 hours, others die just after minutes.
Recent research shows that longevity of human life greatly depends on lifestyle, education, biography, and environment. Data from previous research that showed that the human genome responsible for longevity is between 15 and 30%, but the most recent evidence shows that it should be 15% or even 10%, as shown by Ruby et al. (2018). This means that almost 85% of the human lifespan is dictated by factors such as education, lifestyle, biography, and environment. Therefore, there is a need for research on genome of animals that live long, like the bowhead whale (Keane, 2015, p. 119).
In essence, genes leading to the longevity of life result from secondary evolutionary adaptation and not just species specific inborn. These secondary adaptations can be achieved through lifestyle, diet, and environment, hence making organisms of the same species have different lifespans. For instance, using human beings as examples, lifestyle, eating habits, and environment greatly contribute to an individual’s lifespan. This is because lifestyle, education, and environment help avoid toxic substances that damage stem cells or cause disease and consequently death in living organisms. Particularly, the longevity of people in Ovodda, Okinawa, Limone, and Loma Linda differ largely due to different lifestyle and environment. Nonetheless, it should be noted that their polymorphism does not cause longevity, but rather as a consequence.
Ruby et al. (2018), however, illustrate a unique relationship between longevity of life and environmental conditions. The argument that harsh conditions in sub-Saharan regions or subterranean tunnels protect naked moles from predators is reasonable but also questionable. Harsh living conditions limit the longevity of life of every individual. However, those predated upon may adapt to the environment, thus contradicting the relationship between lifestyle and environment conditions to longevity, and is only applicable in a few cases. Moreover, it is worth noting that although animals keep away from predators, the harsh environmental condition is inevitable. As such, their lifespan may be shorter under less severe conditions, further underlying the notion that predators are not a catalyst to decreased lifespan.
In summary, induction of longevity into the human genome by lifestyle or environmental conditions is a questionable concept in gene engineering. The question is, will the individual resist or adapt to the environmental condition? Adaptation means the individual will persevere and adapt to the ambient conditions, while resistance may lead to a reduction in longevity. Since adults are already used to certain conditions, adaptation may not be possible if the conditions are harsh. However, stem cells or embryos may have chance of survival, hence working against senescence along aging. As noted earlier, ambient environmental temperature is important for evolution, aging, and death, as well as the thermodynamics of life.
Age and Diseases
An analysis of research provides data that can be used to draw the conclusion that thermodynamics of life and the aging process is shaped by the presence or absence of single molecules and mediators in the body organs, the cells, and the DNA in the biological fluids, such as the plasma and the cerebrospinal fluids. According to Kaiser (2017), if young plasma from a young human or animal cell is applied to an old subject, an aged “Code” and metabolome may be redirected toward youth. Tony Wyss-Coray found in his research that aged plasma produces alterations in the hippocampus if injected into young mice (Kaiser, 2017). The VCAMI, a genotoxic soluble mediator, produces aging in the hippocampus. Zhang (2015, p. 54) illustrate, that aged plasma prevents hippocampal neurogenesis and activates microglia. Activating microglia counteracts the harmful effects of aged plasma on young brain’s hippocampus (Hanadie, 2018).
In my personal interpretation of the research of Wyss-Coray, I find there is a good reason to believe that aging has to do with increased production of cell or genotoxic mediators over the cell or genoprotective mediators in plasma and cerebrospinal fluids, as described by Wyss-Coray (2016, p. 6). I believe that they occur by the “wear and tear” process along the thermodynamic metabolic process of an individual life. We can also state that, in agreement with Wyss-Coray, there exists a beneficial “rejuvenating” genoprotective mediator in young plasma.
The Beginning of Aging and Disease
The beginning of aging is at the point where more genotoxic than genoprotective emediators are produced. In human beings, organic aging normally starts at around 40 years. Once this crossroad is reached, genotoxic mediators are likely to override the concentration of genoprotective mediators. At this time, aging becomes a disease. De Grey (2017) proposes that aging can be undone using cellular and molecular repair. De Grey (2017) claims that aging has three stages. In the first stage, the metabolic processes produce certain toxins. In the second stage, the toxins damage the body but the endogenous repair is not sufficient to remove all the toxins. And, in the last stage, they accumulate to dangerous levels over time, hence leading to age-related pathology.
Unlike Wyss-Coray, who proposes preventive measures, Aubrey de Grey proposes repair. Similar to “wear and tear,” more cells are destroyed senescence, but the remedy may be preventive rather than repair. The repair will be quite difficult because there will be too much peripheral damage to manage. However, preventive methods may not be easy as the research on reverting aging has not been quite successful yet. In short, time-dependent waste materials are produced by all organisms due to thermodynamic biological cellular, intracellular, and organic processes, which are essential for life to continue. Consequently, accumulation of the materials makes them exhibit genotoxic mediators.
The “Code” (2)
My interest is to determine the central conductor, the “Code” that governs life and is interrupted by aging so that all the lower hierarchical processes become susceptible for cell/genotoxic mediators. The “Code” directs the thermodynamic transfer of energy and exchange systems between the surrounding of an organism and acts on cellular and subcellular compartments, such as the epigenome, DNA, and RNA. Conformational degradation during this interaction the metabolic mediators may either destruct or rejuvenate the code. I refer to this code as the “Dynamic Code,” which is the highest hierarchy whereby the hypothalamus is the central conductor that controls the “Inner Clockwork” of life. Research conducted by Cai at the Albert Einstein Institute, New York, in 2013 claimed that the hypothalamus has significant involvement in aging (Zhang, 2017, p. 56). Moreover, Cai described the hypothalamus as the central station that controls dynamic life. In 2017, Cai explained that young healthy stem cells could be implanted into the hypothalamus to retard aging in animals. Implanting healthy hypothalamic progenitor or stem cells into mid-aged mice enabled the mice to withstand hypothalamic inflammatory microenvironment that is related to aging. Hypothalamic stem cells control aging partially releasing exosomal miRNAs, which decline the process. As such, through the “Dynamic Code,” the hypothalamus is the main controller of the aging process by the pulse amplitude and frequency modulated secretion of signaling peptides like releasing hormones and genome, epigenome and RNA interacting mediators in the cerebrospinal fluid, and peripheral plasma. In doing so, the hypothalamus seems the master regulator controlling aging processes (Zhang, 2017, p. 57).
“The Dynamic Code”
My focus on the paper has been to address the gaps in the literature by providing a definition of the term “Dynamic Code” and help create meaning in the human physiology field. The term parallels the genetic code across the organic and cellular levels in that it regulates the expression of genes, the epigenome, and the metabolome (Prank, 1991).
I agree with the thermodynamic theory, or the wear and tear theory, as it does not oppose the Mitteldorf concept of evolution according to Mitteldorf and Dorion (2016).
The theory refers the cellular senescence. Bio-thermodynamic processes reduce the ability of cells to function over time. The functionality of these cells is lost because they secret toxic factors that damage the cells around them. According to Lebrasseur et al. (2015), the mechanism of aging and diseases that are related to aging are proof of cellular senescence. Problems with information coding cause cellular senescence. Due to wear and tear, aging cells secrete substances that make them lose the ability to divide, and at the same time destroy the cells around them.
The concept of the “Dynamic Code” can be clearly understood once one understands that biological systems are self-organized. Self-organization is the process where the interaction of various moving parts of a system leads to inner order. Therefore, the dynamic organization may encrypt the transfer of information between cells within organs or organisms.
The question of how I could detect the “Dynamic Code” kept rocking my mind. The concept emerged many years ago when I first met Ilya Prigogine, who introduced me to the self-organization of biological systems. He described self-organization as a process where inner order arises from local interactions between parts of an evolving system. This evolution does not need external control. Amplifying feedback stabilizes such systems. Initially, the organization is very robust in its survival and exhibits even self-repair, but may later in its evolution be “disturbed” by external influences. The mathematical law for its organization obeys the chaos theory of complex nonlinear dynamic systems, He convinced me that biological networks must be self-organized in a similar manner. Subsequently, I supposed that dynamic organization could encrypt intercellular information transfer in organs and organisms along life (Nicholis & Prigogine, 1977; Prigogine et al., 1984).
The first step of investigating is understanding self-organization of cells through human physiological systems where a “Code” can be hidden, such as bone metabolism regulation. Bone is particularly useful because its structured fractal construction reflects the common final path of its physiological regulatory principle, i.e., in a classical way “structure follows function.” The structural bone construction can be visualized histomorphometrically or using high-resolution CT.
Osteoporosis is an age-related bone disease. Investigating how a young structural system of bone builds up and ripens into a mature one, along with its morphological and cellular environment, and how it deteriorates during the aging process is an exceptional model to study. The clockwork along an aging bone presents the best way to understand how the “Dynamic Code” can be detected. The coding parathyroid hormone evolves along life and disease.
In young healthy subjects, there is a “high dynamic state” of nonlinear dynamic secretion of PTH and the analysis allowed even to make predictions of its evolution over a time period of 30 minutes. I called the principle underlying “Acting by Learning from the Future.” However, osteoporotic subjects and postmenopausal women show a low dynamic state. Substituting estrogen in the postmenopausal women helps to restore the parathyroid toward the younger program. Consequently, this process enabled the disturbed nonlinear complex function coding that can be directly related with the disease, aging, and final consequences on the structure in human physiology (Prank et al., 1995, p. 9).
“Dynamic Code” and Structure
Reznikov et al. (2018) highlight that bone microstructure has fractal characteristics. The self-affine fractal-like organization of the bone shows that the microarchitecture of the bone is directly acted upon through cellular metabolism of its composition by the nonlinear coding of parathyroid hormone. Therefore, nonlinear dynamic coding of information generally seems important in producing fractal structures in biology.
Determining the structure of the dynamic code as well requires looking into cellular levels. There is no information on whether nuclear and intracellular mediators in the bone cells follow the same organization of bones. However, this suggestion is an assumption from the study of yeast cells (“Kurzweilaccelerating Intelligence,” 2017).
There is a dynamic switching of chromatin silencing that occurs periodically between a closed state and open state (silencing loss). In analogy, during programming, bone cells longevity here is a high secretion of PTH in hyperparathyroidism (open state) and low coding of PTH in the closed state leading to osteoporosis and cell atrophy. The mathematical organization of the periodic switching may not be known, but it is evident that there is a program.
Central information coding by the “Dynamic Code” is translated to gene regulation, RNAs, cell metabolism, and epigenetic regulation from organizations of life, death, aging and disease – the general organisatory principle in biology. Veldhuis et al. (2008) give a review of coding in hormonal systems. The analysis concentrates on the pancreas and hypothalamo-pituitary hormone systems. Veldhuis et al. (2008) observe that endocrine glands transfer information to remote targets through the continuous and intermittent exchange of signals. Moreover, in chapter five, they describe the methods of deconvolution. Nevertheless, they give a pure description with mathematical concepts, yet no biological principle is inherent to the code of life.
My coworker Klaus Prank, working as a postgraduate fellow in the laboratory of Terence Sejnowski (Prank et al., 1991) and using classical nonlinear deconvolution analytical methods, demonstrated that PTH secretion patterns have characteristics of deterministic chaos. This can be demonstrated in the frequency and pulse amplitude modulation and PTH. Our publication showed for the first time in human physiology that this information coding obeys nonlinear deterministic complex dynamic function related directly to the final consequences on bone structure and its aging. The same procedure can also be applied to analyze secretory coding of growth hormone (Prank et al., 1991).
Life and the “Dynamic Code”
What is life? NASA and Joyce state that life is a self-sustaining chemical system capable of undergoing Darwinian evolution and self-replication or reproduction in a self-sustained manner. Molecular information in such a system is essential. Such system evolves to adapt information to environmental change. It has to be able to invent new functions; life emerges because chemistry records a history (Mullen, 2013).
What are the building blocks to create biological information and metabolism, the history, as I define it above: The conformation of carbon, hydrogen, nitrogen, oxygen, phosphorous, and sulphur are the six basic building blocks of all known life forms on Earth. Phosphorus is part of the chemical backbone of DNA and RNA that carries genetic instructions, and is considered an essential element for all living cells.
The building blocks to create a history of Darwinian evolution on all levels of life, though, must be driven indispensably by a dynamic system to make chemistry transform into life. The driving force for information, metabolism, and replication in a self-sustained manner is the “Dynamic Code.” In summary, the “Dynamic Code” proposes an evolutionary meaningful mathematical principle to analyze the biology of a code of life, aging, and disease. This is the new concept of a “Code of Life, Aging and Disease,”
De Grey, A. D. N. J. (2017). Undoing Aging with Molecular and Cellular Damage Repair. MIT Technology Review, Retrieved from www.technologyreview.com/s/609576/undoing-aging-with-molecular-and-cellular-damage-repair/
Eigen, M (1971). selforganisation of matter and the evolution of biological macromolecules.” Naturwissenschaften. 58(10), 465-523.
Forsythe, J. G., et al. (2017) Surveying the sequence diversity of model prebiotic peptides by mass spectrometry. Proceedings of the National Academy of Sciences, 114(37), E7652-E7659.
Gladyshev, G. P. (2014). Thermodynamics of the origin of life, evolution and aging. International Journal of Natural Science and Reviews 27(2), 2-7.
Hall, W. (2011). Physical basis for the emergence of autopoiesis, cognition and knowledge. Retrieved from https://www.researchgate.net/publication/216563937_Physical_basis_for_the_emergence_of_autopoiesis_cognition_and_knowledge.
Hanadie, Y (2018). The aged systemic milieu inhibits hippocampal neurogenesis and cognition through VCAM1. Retrieved from grantome.com/grant/NIH/F32-AG051330-02.
Kaiser, J. (2017). Protein isolated from human cord blood has antiaging effects on memory in mice. Science. Retrieved from www.sciencemag.org/news/2017/04/protein-isolated-human-cord-blood-has-antiaging-effects-memory-mice-0.
Keane, M. (2015). Insights into the Evolution of Longevity from the Bowhead Whale Genome. Cell Reports, 10(1), 112-22. doi.org/10.1016/j.celrep.2014.12.008.
KurzweilacceleratingIntelligence. (2017). Retrieved from www.kurzweilai.net/scientists-decipher-mechanisms-in-cells-for-extending-human-longevity.
Lebrasseur et al. (2015). Cellular Senescence and the Biology of Aging, Disease, and Frailty. NestleNutrInst Workshop Ser. 83, 11-18. Retrieved from www.ncbi.nlm.nih.gov/pmc/articles/PMC4780350/.
Lovett, R. A. (2018) “Nuclear geyser” may be origin of life. Cosmos Magazine. Retrieved from cosmosmagazine.com/biology/nuclear-geyser-may-be-origin-of-life.
Mingers, J., et al. (1991). The Cognitive Theories of Maturana and Varela. Systems Practice, 4(4), 319-38. Retrieved from cepa.info/fulltexts/2253.pdf.
Mitteldorf, J., & Sagan, D. (2016). Cracking the Aging Code: The New Science of Growing Old-and What It Means for Staying Young. New York: Flatiron Books
Mullen, L. (2013). Forming A Definition For Life”: Interview With Gerald Joyce – Astrobiology Magazine.” Astrobiology Magazine. Retrieved from https://www.astrobio.net/origin-and-evolution-of-life/forming-a-definition-for-life-interview-with-gerald-joyce/.
Neilson, J. (2016) Eye lens radiocarbon reveals centuries of longevity in the Greenland shark (Somniosusmicrocephalus). Science Retrieved from science.sciencemag.org/content/353/6300/702.
Nicolis, G., & Prigogine, I. (1977). Self-organization in Nonequilibrium Systems: From Dissipative Structures to Order Through Fluctuations. New York: John Wiley.
Park, H.-K., & Ahima, R. S. (2015). Physiology of leptin: energy homeostasis, neuroendocrine function and metabolism. Metabolism, 64(1), 24-34.
Patel, B. H., et al., (2015). Common origins of RNA, protein and lipid precursors in a cyanosulfidic protometabolism. Nature chemistry, 7(4), 301.
Powell, K. (2018). How Biologists Are Creating Life-Like Cells From Scratch. Nature.com. Retrieved from https://www.nature.com/articles/d41586-018-07289-x.
Prank, K., et al. (1991). The Dynamic Code: Information Transfer in Hormonal Systems. In Mosekilde E. & L. Mosekilde (eds), Complexity, Chaos, and Biological Evolution. NATO ASI Series (Series B: Physics), vol/ 270. Berlin: Springe. Retrieved from link.springer.com/chapter/10.1007%2F978-1-4684-7847-1_7#citeas.
Prank, K. et al. (1995). Time series prediction of plasma concentration: evidence for differences in predictability of parathyroid hormone secretion between osteoporotic patients and normal controls. J. Clin. Invest, 95(6), 2910-2919.
Prigogine, I., Stengers, I., & Toffler, A. Order Out of Chaos: Man’s New Dialogue with Nature. New York: Bantam Books.
Reznikov, N., et al. (2018). Fractal-like hierarchical organization of bone begins at the nanoscale. Science, 360(6388). doi: 10.1126/science.aao2189.
Ruby, J. G., et al. (2018). Naked mole-rat mortality rates defy Gompertzian laws by not increasing with age. eLife, 7(24). doi.org/10.7554/eLife.31157.001. Retrieved from https://elifesciences.org/articles/31157.
Schrödinger, E. (1944). What is Life? Cambridge, UK: Cambridge University Press.
Springsteen, G., et al. (2018). Linked cycles of oxidative decarboxylation of glyoxylate as protometabolic analogs of the citric acid cycle. Nature Communications, 9(91). Retrieved from www.nature.com/articles/s41467-017-02591-0.
Was ist Leben? (2018). Retrieved from https://www.synthetische-biologie.mpg.de/17480/was-ist-leben
Wyss-Coray, T. (2016). Aging, neurodegeneration and brain rejuvenation. Nature, 539(7628), 180-186. doi:10.1038/nature20411.
Veldhuis, J. D.. et al. (2008). Motivations and Methods for Analyzing Pulsatile Hormone Secretion, Endocrine Reviews, 29(7), 823-864. doi:10.1210/er.2008-0005.
Zhang, Y., et al. (2017). Hypothalamic stem cells control aging speed partly through exosomal miRNAs. Nature, 548, 52-57.
Zhao, L., et al. (2018). Pyrene synthesis in circumstellar envelopes and its role in the formation of 2D nanostructures. Nature Astronomy, 2(5), 413.
*Dieter Hesch, MD.
Professor of Medicine and Biology (h. c.)
Medical High School Hannover and University of Konstanz
CH 8597 Landschlacht
The DNAge Test
This diagnostic procedure was described by Steve Horvath
“What he calls the “epigenetic clock” is a bit like rust on a car. The DNA molecules experience chemical changes that could be interpreted as rust. So, as we age, things change on the molecule, and these changes are methylation, so by measuring the amount of “rust”, you can measure the age.
Another metaphor is that different locations on DNA are very much like hourglasses. Think of it like 353 different hourglasses in different locations, and I measure the height of sand in each to find an age estimate.”
A few days ago I asked to estimate my biological age:
Here it is:
“Your are 4 years younger than 83 % of people of your age”
What can be done that other people will achieve at least that?
Well the clock itself does not tell that. As I described only 16 % of the genome of a person has to do with longevity, around 85 % are due to biography.
It would be interesting to know what biographic lifestyle those people that are even younger than 100 % of people of their age.
I have asked Steve Horvath to explore this question from the data of people studied by his Zymo Company or from data of his other studies. Cant wait to get a result.
Further thoughts for aging:
Genome and environment in aging
There is recent evidence, that only 16% of the genome in human being are responsible for longevity in contrast to former data assuming about 30 %. This means that around 85 % have to do with environment, life style, education and biography.
That questions to me the research in the genome of long living animals like the whale bowl:
I mention particularly a sentence of the summary of this article:
“We also found potentially relevant changes in genes related to additional processes, including thermoregulation, sensory perception, dietary adaptations, and immune response.”
In essence, this means that genes involved in longevity are not a primary species specific inborn fact but the secondary evolutionary adaptation of these animals to their surrounding environment. Thermoregulation in this context is particularly relevant.
If so, the research in the naked mole by Calico may also be a wrong road to elaborate genes for longevity because in these animals longevity polymorphisms are not causative but they are secondary to their extremely harsh conditions in subterranean tunnels. They are protected from predators and the arid climate of the sub-Saharan region where they live.
The longevity of some human beings is also due to ambient environmental and life style conditions
although they differ largely:
Okinawa, Ovodda, Limone, Loma Linda.
Nevertheless their polymorphisms of longevity are the consequence and not the cause of it.
In summary it may be questioned if by gene engineering in the human genome or epigenome
longevity may be induced if lifestyle and environment continues , i.e. will they resist to unchanged
ambient conditions. It may well be possible that in the adult this will not work but if done on
embryos and stem cells there may be a chance to keep them working against senescence along
Currently I am preparing an article about aging and the “Dynamic Code” which will be ready to be published here within 2 weeks.
Meanwhile I wait for the result of the DNAge™ Epigenetic Aging Clock test by Steve Horvath.
Will I be older or younger than my biological age?
Write your guess to email@example.com.