Editor’s Note: The U.S. Transhumanist Party has published this research paper and proposal for a practical gene therapy by member Kyrtin Atreides in order to solicit input from other researchers in the field of gene therapy as well as to provide some ideas for further directions in research and practical applications of genetic engineering. The U.S. Transhumanist Party does not itself conduct research or recommend particular medical procedures, so the publication of this paper should be seen as promoting the exploration of research paths that could one day (hopefully sooner rather than later) materialize into viable treatments for curing diseases and lengthening lifespans.
~ Gennady Stolyarov II, Chairman, United States Transhumanist Party, April 1, 2018
A wise medical director once told me that 50% of those who go into the field of Psychology need psychological help themselves. I suspect that one day I’ll be able to say the same of genetic engineering.
Epigenetics control our neurochemistry, which dictates base level reactions to stimuli, and everything from a bad meal, job, relationship, or traumatic childhood event, to warzone PTSD, can trigger epigenetic changes.  De Bellis, M. D., & A.B., A. Z. (2014),  Gudsnuk, K., & Champagne, F. A. (2012),  Hardy, T. M., & Tollefsbol, T. O. (2011)
Over time these changes build up, and since human society is often highly unstable due to rapid and lopsided progression, the net result is cumulative damage, similar to aging, because epigenetics attempt to attune you to an environment that doesn’t change in compatible ways.  Bowers, E. C., & McCullough, S. D. (2017)
What this means is that in order to roll back the clock the epigenetic equation needs to be recalculated in a local space, a process which occurs with a viral knockout, or insertion of new genetic data, within a region surrounding any given gene. The basic idea is that if you alter the dimensions of the space that the epigenetic equation covers via methylation, you cause it to recalculate the ideal distribution and genetic activation for that region based on current data, rather than the trauma which previously altered it.
By causing this update to take place, the gene expression is recalculated to values which are more closely aligned with current needs and environmental factors. Previously in human history, lives were shorter and epigenetic influences served a healthy role in promoting survival, but the problem with amassing a large pile of trauma-induced epigenetic changes becomes acutely apparent as age increases.  Teschendorff, A. E., West, J., & Beck, S. (2013)
Each change is based on data fixed to the point of trauma, and any alteration to that expression is glacially slow, if it occurs at all. Often times such changes break an element of neurochemistry in the sense that the change can’t naturally reverse itself once it has been made, but it can be easily reversed with minor engineering.
Different genes act like functions in code, separate blocks which can function together, but which also contain sites where new code can be placed without causing harm to the current code. In the same way the human genome also contains 8% integrated viral DNA, which makes for an ideal target for gene knock-out.  (International Human Genome Sequencing Consortium, 2001; Smit, 1999)
Proposal Part 1:
What I propose is two-fold. The first step is the creation of a gene therapy which is practically viable, costing no more than $5 per person in production. The second step is testing the top gene sites active in controlling neurochemistry with both knock-out of viral DNA, and knock-in of dormant placeholder DNA, to cause recalculation to take place.
The first is easily accomplished by understanding the nature of why anything evolves in the first place, for survival. If you create a gene therapy whose survival is guaranteed it loses reason to adapt maliciously, because there is no advantage to be gained. A classic case that demonstrates a virus becoming less lethal over time is HIV, where initially it was a death sentence, but over time not only were treatments developed, the virus became less lethal, because that lethality was acting as a detriment to the purpose of survival, and it evolved in order to live longer.  Payne, R., Muenchhoff, M., Mann, J., Roberts, H. E., Matthews, P., Adland, E., … Goulder, P. J. R. (2014)
The myriad of bacteria, archaea, viruses, and eukaryotic microbes in our bodies that outnumber our own cells have come to a balanced state, where our bodies are the ecosystem, and as that 8% viral DNA demonstrates a virus is no different, it favors survival and a stable environment.  Eloe-Fadrosh, E. A., & Rasko, D. A. (2013)
I mention this because of a key factor which makes gene therapy completely impractical today, 293T cells. Having to use specialty cells for cloning a virus that isn’t replication-competent, and is often very fragile to begin with, is one monumental waste, which is built on the unfounded fear that a replication-competent virus is in and of itself a threat. As machine learning is applied to the human genome, as well as non-human genomes, the error in that line of reasoning will become increasingly apparent.
What we need is a new gene therapy, engineered for high conversion rates, such as Adeno-Associated-Virus-7 or Lentivirus, and hybridized with a more durable, low-symptom (“clinically silent”), low-transmission-potential virus, such as Epstein-Barr Virus. By making such a virus replication-competent, but also self-inactivating (EBV) and able to integrate itself as a genetic landing site capable of being periodically updated, not only is the problem of practicality and cost solved, but the speed with which new research can be tested is greatly accelerated, and the virus is rendered stable. EBV in particular is already present in roughly 95% of adults, as it has integrated with their genomes. When combined with revised best practices any risk of bad-actor genetic engineering remains a practical impossibility.
By keeping the intermediate stages of the gene therapy in a controlled environment and only releasing the end result beyond that point, the Bio-Safety risk remains functionally unchanged, as the hypothetical “bad actor” would still require the same advanced tools, knowledge, and materials to generate a harmful virus as they already do today. The key difference in Bio-Safety terms is that by allowing the field to advance, the benefits and possible means of defense against that hypothetical would move forward, while undermining the root cause of said hypotheticals. This would be roughly equivalent to creating bulletproof sleepwear before the invention of the firearm.
The end result of utilizing such a gene therapy would be a symbiotic relationship with a genetic update mechanism, where increases to lifespan and survival rates favor both parties, resulting in potential rare mutations that better serve that purpose, like a bird evolving a better beak for catching fish.
Selection of EBV to hybridize with Lentivirus would also allow for the therapy to enter dormant cycles, avoiding immune-system rejection, and reactivating when introduced to engineered updates from additional gene therapy treatments.  Houldcroft, C. J., & Kellam, P. (2015)
The replication-competent gene therapy can be created with either AAV-7 or Lentivirus by means of recombination during the manufacturing process. An AAV-2 or AAV-7 variant may be preferable, if not required, for the treatment of HIV-positive humans due to the risk of interaction between any Lentivirus gene therapy and the HIV virus. It is however probable that a Lentivirus/EBV chimeric gene therapy would overwrite wild HIV virus variants rather than being overwritten by them, but rigorous testing is required, which development of this therapy would also make possible. This is partly due to the far greater size, complexity, and long-term stability of EBV compared to Lentivirus.  Haifeng Chen. (2015)
On a side note the genetics study that led me to realize this epigenetic mechanic was in play is shown here:
 Welle, S., Cardillo, A., Zanche, M., & Tawil, R. (2009)
It was by examining the difference between an adult with gene knock-out applied after maturation versus one born with the modification that the mechanic of Methylation Dimensions / Dimensions of DNA was illuminated. Since this process occurs naturally as a part of viral integration, a mechanic had to evolve that could handle the recalculation. The above study also highlights that gene therapies shouldn’t be administered to individuals prior to adulthood, due to the differences in how they impact an individual prior to biological maturation, unless the need is dire, or unless the difference can be corrected upon maturation.
Another failing point of gene therapies as they exist today is that, due to the lack of replication-competence, viral titers act as a choke-point, where the virus is injected in-mass rather than gradually converting cells, massively increasing the risk of cellular toxicity and immunotoxicity. If a gene therapy was replication-competent, even an extremely low dose could achieve a high level of cellular conversion over a period of time, potentially closing in on Bayes Error, regardless of host mass. In effect, the same dose that yields positive results in a mouse could also work for a human.  White, M., Whittaker, R., Gándara, C., & Stoll, E. A. (2017)
Proposal Part 2:
Once the new gene therapy is complete, the ability to repair damage at the epigenetic level becomes practical, speeding up the testing process by an order of magnitude, as well as greatly reducing cost. For the purpose of initial testing and separation of documented effects, knock-out of viral DNA and placeholder-gene knock-in will be targeted to recalculate small regions surrounding key neurochemistry controlling genes, a few of which I’ve listed below:
HTR6 – Chromosome 1 – (5-Hydroxytryptamine Receptor 6) is a Protein Coding gene. Diseases associated with HTR6 include Acute Stress Disorder and Amnestic Disorder.
NR4A2 – Chromosome 2 – (Nuclear Receptor Subfamily 4 Group A Member 2) is a Protein Coding gene. Diseases associated with NR4A2 include Arthritis and Late-Onset Parkinson Disease. Among its related pathways are Dopaminergic Neurogenesis and Corticotropin-releasing hormone signaling pathway. GO annotations related to this gene include transcription factor activity, sequence-specific DNA binding, and protein heterodimerization activity. An important paralog of this gene is NR4A3.
HES1 – Chromosome 3 – (Hes Family BHLH Transcription Factor 1) is a Protein Coding gene. Among its related pathways are Signaling by NOTCH1 and NOTCH2 Activation and Transmission of Signal to the Nucleus. GO annotations related to this gene include transcription factor activity, sequence-specific DNA binding, and sequence-specific DNA binding. An important paralog of this gene is HES4.  Epigen Global Research Consortium(2015)
DRD5 – Chromosome 4 – (Dopamine Receptor D5) is a Protein Coding gene. This receptor is expressed in neurons in the limbic regions of the brain. It has a 10-fold higher affinity for dopamine than the D1 subtype.
SLC6A3 – Chromosome 5 – (Solute Carrier Family 6 Member 3) is a Protein Coding gene. Diseases associated with SLC6A3 include Parkinsonism-Dystonia, Infantile and Nicotine Dependence, Protection Against.
DRD1 – Chromosome 5 – (Dopamine Receptor D1) is a Protein Coding gene. Diseases associated with DRD1 include Cerebral Meningioma and Drug Addiction.
TAAR1 – Chromosome 6 – (Trace Amine Associated Receptor 1) is a Protein Coding gene. Although some trace amines have clearly defined roles as neurotransmitters in invertebrates, the extent to which they function as true neurotransmitters in vertebrates has remained speculative. Trace amines are likely to be involved in a variety of physiological functions that have yet to be fully understood.
DDC – Chromosome 7 – (Dopa Decarboxylase) is a Protein Coding gene. Among its related pathways are Dopamine metabolism and Metabolism.
CRH – Chromosome 8 – CRH (Corticotropin Releasing Hormone, aka CRF) is a Protein Coding gene. Diseases associated with CRH include Crh-Related Related Nocturnal Frontal Lobe Epilepsy, Autosomal Dominant and Autosomal Dominant Nocturnal Frontal Lobe Epilepsy. Among its related pathways are G alpha (s) signalling events and Signaling by GPCR. GO annotations related to this gene include receptor binding and neuropeptide hormone activity.  Sandman CA, Curran MM, Davis EP, Glynn LM, Head K, Baram TZ.(2018)
HTR7 – Chromosome 10 – (5-Hydroxytryptamine Receptor 7) is a Protein Coding gene. Diseases associated with HTR7 include Autistic Disorder and Byssinosis.
ETS1 – Chromosome 11 – (ETS Proto-Oncogene 1, Transcription Factor) is a Protein Coding gene. Among its related pathways are Photodynamic therapy-induced NF-kB survival signaling and MAPK-Erk Pathway. GO annotations related to this gene include transcription factor activity, sequence-specific DNA binding and transcription factor binding. An important paralog of this gene is ETS2.
HTR2A – Chromosome 13 – (5-Hydroxytryptamine Receptor 2A) is a Protein Coding gene. Diseases associated with HTR2A include Schizophrenia and Major Depressive Disorder and Accelerated Response to Antidepressant Drug Treatment.
SLC6A4 – Chromosome 17 – (Solute Carrier Family 6 Member 4) is a Protein Coding gene. Diseases associated with SLC6A4 include Obsessive-Compulsive Disorder and Slc6a4-Related Altered Drug Metabolism.
TCF4 – Chromosome 18 – (Transcription Factor 4) is a Protein Coding gene. Among its related pathways are Mesodermal Commitment Pathway and Regulation of Wnt-mediated beta catenin signaling and target gene transcription. GO annotations related to this gene include transcription factor activity, sequence-specific DNA binding and protein heterodimerization activity. An important paralog of this gene is TCF12.
OXT – Chromosome 20 – (Oxytocin/Neurophysin I Prepropeptide) is a Protein Coding gene. This gene encodes a precursor protein that is processed to produce oxytocin and neurophysin I. Oxytocin is a posterior pituitary hormone which is synthesized as an inactive precursor in the hypothalamus along with its carrier protein neurophysin I. Together with neurophysin, it is packaged into neurosecretory vesicles and transported axonally to the nerve endings in the neurohypophysis, where it is either stored or secreted into the bloodstream. The precursor seems to be activated while it is being transported along the axon to the posterior pituitary. This hormone contracts smooth muscle during parturition and lactation. It is also involved in cognition, tolerance, adaptation, and complex sexual and maternal behavior, as well as in the regulation of water excretion and cardiovascular functions.
AVP – Chromosome 20 – (Arginine Vasopressin) is a Protein Coding gene. Diseases associated with AVP include Diabetes Insipidus, Neurohypophyseal and Hereditary Central Diabetes Insipidus. Among its related pathways are G alpha (s) signalling events and HIV Life Cycle. GO annotations related to this gene include protein kinase activity and signal transducer activity. An important paralog of this gene is OXT.
These genes represent only a fraction of the neurochemistry control sites, but they are disproportionately represented in terms of impact due to being frequently targeted by a wide variety of damaging sources focused on addiction, conditioning, reward-behaviors, and various forms of trauma. By changing the dimensions of a region that methylation, phosphorylation, acetylation, and histone modification have to cover the recalculation is triggered and optimized to the current environment.  Tuesta, L. M., & Zhang, Y. (2014),  Samonte FGR.(2017)
It is also worth noting that in the case of more extreme imbalances two or more gene targets would either need to be iteratively, or simultaneously, recalculated in order to reach a balanced state. By using one gene therapy, then a second on the parallel site, such as the case with OXT vs. AVP balance, you could iteratively progress towards a balanced state with less extreme gene expression levels, like turning the sides of a Rubik’s Cube. Using multiple versions of the same gene therapy, attaching to different target sites, this process could be activated simultaneously, causing the recalculation to factor in all discovered and targeted regions at once, effectively “training” the epigenetic weights of highly connected regions, instead of working iteratively where half of them are frozen at any given time. Initially this simultaneous trigger could be via standard injection, but it could also be automated a variety of ways, including using links to circadian rhythm conditions and seasonal changes, causing routine recalculation of mental and emotional health critical gene expression.  Neumann, ID, Landgraf R.(2012)
Since none of the genes are directly impacted, only recalculating their level of activation, risk is kept to a bare minimum, and the same approach can be repeated to yield different results by varying the conditions present as the gene therapy takes effect. Ideal circumstances for any given outcome can be established by varying environmental factors until the result is optimized, potentially even personalized, and though this approach would be ideally suited for a laboratory environment, it could also help to establish best-practices for administering the gene therapies once they reached human trials.
Results of epigenetic recalculation could be further utilized for mathematically modeling the potential space of gene activation when coupled with environmental data from the trial facility, increasing prediction accuracy for post-therapy gene expression, as well as the subsequent benefits.
The before-versus-after comparison between fully mapped genomes could also be used in Deep Neural Network terms to generate accurate predictions for post-therapy gene activation levels and the approximate benefits of those changes. A DNN could even be modeled to map causal relationships between epigenetic activation changes in a way that has likely never been done before, allowing for many genes with currently unknown functions to be defined, opening the door to more advanced models that could map the causal and probable space of genetic engineering with far greater accuracy.
How long we remain mired in the Medieval times of genetic engineering is purely up to us, as a collective we can form a safety committee which agrees to create a practical gene therapy that shifts the paradigm away from monopolistic control to one where science can advance, and people can benefit from advances without waiting 20 years for approval.
The best way to win the hearts and minds of people around the world is to give them something to be grateful for, benefiting either themselves or those they love in meaningful ways. I can think of no better start down this path than curing the epigenetic effects of trauma, as virtually everyone has suffered some form of trauma in their lives, and many are needlessly crippled by it today.
Without the scars left on humanity at the epigenetic level the negative-influence house of cards collapses, along with all of the industries who prey upon it, breaking the downward spiral and moving the dial forward, from pointing towards a deeper Dystopia to a brighter future.
Transhumanism is likewise about the freedom to choose who you are, and who you become, which in the field of genetic engineering means that a practical method for genetic updates is as much a prerequisite as the computer was a prerequisite for the Internet. It would by no means remove the threat of archaic legal constructs, but it would greatly reduce their potency, taking us one step closer to being truly Transhuman.
Taking this a step further, the ability to reset the epigenetic level influence of trauma, addiction, and conditioned behaviors is also prerequisite to any major social change, as backlash comes into play when friction of the old meets new paradigms. The act of curing the effects of trauma would in this way also serve to make people more open to new ideas, since the baseline of their neurochemistry shifting would trigger subsequent recalculation going up the chain, all the way to higher order cognitive functions. This could potentially be used to shift neurochemistry into unexplored probability space, allowing for configurations that couldn’t arise naturally.
Without the practical potential there is no room for innovation, and progress stagnates behind monumental pay-gates, but the solution can be engineered today, giving innovators access to build a better tomorrow.
Humanity is but one life form among billions of ever-evolving forms of life that we know of today, and even if only 1 in 10,000 of those lifeforms were evolving in ways compatible with our genetic structure we’d be wasting 99.9999% of the potential evolutionary improvements being made by other species. Life in the known universe is in a perpetual race to evolve, and to compete in that race in any meaningful way, increasing the survival of the species, it is necessary to take advantage of the advances that other forms of life make, the other 99.9999%+ compute power dedicated to the task of evolving into ever more advanced and resilient beings. While humanity may not be ready to take this step any time soon, perhaps once the world is cured of trauma this will enter the realm of consideration.
If humanity is to survive, let alone thrive, in the hazards of space, genetic engineering that grants us the resilience of life forms able to survive considerable exposure to radiation, extreme temperatures, increased gravity, and even the vacuum of space, are required for us to move forward. Even survival on Earth is a moving target, and as humanity stands today, vulnerability to any number of cataclysms remains much higher than it could be. Fans of longevity research should favor the generation of a practical gene therapy most of all, because it would only take a few direct gene edits using such a therapy to significantly increase life span, granting talented scientists more years with which they could work towards overcoming challenge after challenge.
Limiting gene therapy treatment to the rarest of diseases is like limiting internet access to the most remote parts of the world, an astronomical waste, and it is time for that to change. From the more directly Transhumanist perspective, this is a step towards being free to choose who you are right down to the genetic level, accessible to everyone, a basic human right that has yet to be written, but before reaching that point humanity needs an epigenetic tabula rasa, a slate clean of trauma, conditioning, and addiction.
Kyrtin Atreides is a researcher and member of the U.S. Transhumanist Party. In his spare time over the past two years, he has conducted research into Psychoacoustics, Quantum Physics, Genetics, Language (Advancement of), Deep Learning / Artificial General Intelligence (AGI), and a variety of other branching domains, and continues to push the limits of what can be created or discovered.
For additional reading on the subject matter mentioned herein, please refer to:
Adeno-Associated Virus: https://www.wjgnet.com/2220-3184/full/v5/i3/28.htm
1. De Bellis, M. D., & A.B., A. Z. (2014). “The Biological Effects of Childhood Trauma.” Child and Adolescent Psychiatric Clinics of North America, 23(2), 185–222. http://doi.org/10.1016/j.chc.2014.01.002
2. Gudsnuk, K., & Champagne, F. A. (2012). Epigenetic Influence of Stress and the Social Environment. ILAR Journal, 53(3-4), 279–288. http://doi.org/10.1093/ilar.53.3-4.279
3. Hardy, T. M., & Tollefsbol, T. O. (2011). Epigenetic diet: impact on the epigenome and cancer. Epigenomics, 3(4), 503–518. http://doi.org/10.2217/epi.11.71
4. Bowers, E. C., & McCullough, S. D. (2017). Linking the Epigenome with Exposure Effects and Susceptibility: The Epigenetic Seed and Soil Model. Toxicological Sciences, 155(2), 302–314. http://doi.org/10.1093/toxsci/kfw215
5. Teschendorff, A. E., West, J., & Beck, S. (2013). Age-associated epigenetic drift: implications, and a case of epigenetic thrift? Human Molecular Genetics, 22(R1), R7–R15. http://doi.org/10.1093/hmg/ddt375
6. Pakorn Aiewsakun, Aris Katzourakis(2015) Endogenous viruses: Connecting recent and ancient viral evolution. Virology. 2015 May;479-480:26-37. doi: 10.1016/j.virol.2015.02.011. Epub 2015 Mar 12.
7. Payne, R., Muenchhoff, M., Mann, J., Roberts, H. E., Matthews, P., Adland, E., … Goulder, P. J. R. (2014). Impact of HLA-driven HIV adaptation on virulence in populations of high HIV seroprevalence. Proceedings of the National Academy of Sciences of the United States of America, 111(50), E5393–E5400. http://doi.org/10.1073/pnas.1413339111
8. Eloe-Fadrosh, E. A., & Rasko, D. A. (2013). The Human Microbiome: From Symbiosis to Pathogenesis. Annual Review of Medicine, 64, 145–163. http://doi.org/10.1146/annurev-med-010312-133513
9. Houldcroft, C. J., & Kellam, P. (2015). Host genetics of Epstein–Barr virus infection, latency and disease. Reviews in Medical Virology, 25(2), 71–84. http://doi.org/10.1002/rmv.1816
10. Haifeng Chen. (2015) Adeno-associated virus vectors for human gene therapy. Published by Baishideng Publishing Group Inc. doi: 10.5496/wjmg.v5.i3.28
11. Welle, S., Cardillo, A., Zanche, M., & Tawil, R. (2009). Skeletal muscle gene expression after myostatin knockout in mature mice Address for reprint requests and other correspondence: S. Welle, Univ. of Rochester Medical Center, 601 Elmwood Ave., Box 693, Rochester, NY 14642 (e-mail: firstname.lastname@example.org). Physiological Genomics, 38(3), 342–350. http://doi.org/10.1152/physiolgenomics.00054.2009
12. White, M., Whittaker, R., Gándara, C., & Stoll, E. A. (2017). A Guide to Approaching Regulatory Considerations for Lentiviral-Mediated Gene Therapies. Human Gene Therapy Methods, 28(4), 163–176. http://doi.org/10.1089/hgtb.2017.096
13. Lillycrop KA1, Costello PM2, Teh AL3, Murray RJ2, Clarke-Harris R2, Barton SJ4, Garratt ES2, Ngo S5, Sheppard AM5, Wong J3, Dogra S3, Burdge GC2, Cooper C6, Inskip HM4, Gale CR7, Gluckman PD8, Harvey NC4, Chong YS9, Yap F10, Meaney MJ11, Rifkin-Graboi A3, Holbrook JD3; Epigen Global Research Consortium, Godfrey KM12. Int J Epidemiol. 2015 Aug;44(4):1263-76. doi: 10.1093/ije/dyv052.
14. Sandman CA, Curran MM, Davis EP, Glynn LM, Head K, Baram TZ.(2018) Am J Psychiatry. 2018 Mar 2:appiajp201716121433. doi: 10.1176/appi.ajp.2017.16121433.
15. Tuesta, L. M., & Zhang, Y. (2014). Mechanisms of epigenetic memory and addiction. The EMBO Journal, 33(10), 1091–1103. http://doi.org/10.1002/embj.201488106
16. Samonte FGR.(2017) The Epigenetic of Dopamine Reward in Obesity and Drug Addiction: A Philippine Perspective. J Clin Epigenet. 2017, 3:2. doi: 10.21767/2472-1158.100051
17. Neumann, ID, Landgraf R.(2012) Balance of brain oxytocin and vasopressin: implications for anxiety, depression, and social behaviors. Trends Neurosci. 2012 Nov;35(11):649-59. doi: 10.1016/j.tins.2012.08.004. Epub 2012 Sep 11.