Human knowledge, especially medical knowledge now doubles every 5 years (or less). Since this results in an exponential increase in our knowledge while our aging rate is linear (up until about the last 10% of our lifespan) a point in time will come when we understand how and why we age faster than we are aging.
The Human Genome Project was originally planned to be complete by 2006. This date was subsequently revised to 2003. Perhaps in part due to competition from Celera Pharmaceutical who planned to have a complete sequence by 2001, the goverment funded participants sped up the pace of the work and a joint goverment-industry announcement that the genome map was substantially complete was made June 26, 2000. This was ~5 years ahead of the original schedule. A publication of the preliminary interpretation of the data is expected around October, 2000. Much of the human genome is believed to be junk DNA which may be leftover from the messy process of evolution where nature copys old DNA and creates new functions for the copies. Only for organisms like birds where weight is a concern does nature seem to make an effort to reduce the amount of junk DNA.
In the mid-1990s, Human Genome Sciences in collaboration with The Institute for Genomic Research and Incyte Pharmaceuticals, claimed to have isolated and partially sequenced the majority of the 65,000 genes which make up the Human Genome. (Isolating the genes allows one to study what a gene/protein does but does not tell you how it is regulated, that will require further genome analysis.) Those estimates may have been premature, since in September of 1999 Incyte believed there might be 140,000 genes in the human genome. If that number turns out to be accurate and genes are on average 2000 bases (letters) in size, then more than 93% of the genome would be junk DNA. This is significant because it problem of creating synthetic genomes for designer cells, to provide replacement tissues in aged individuals may be a significantly smaller problem than it appears to be at first glance.
Some might argue that the complexity of genomes is so great that we will require decades to understand how our genetic program causes aging. This assumption rests on three assumptions:
This is an improper way to look at the problem. Estimates of the number of genes involved in aging processes by gerontologists range from dozens to hundreds. In all likelyhood, there are a few dozen regulartory factors that control the activity and interaction between hundreds of genes that perform the actual functions that regulate aging processes. Once the general genetic pathways involved in such basic functions as growth, maintenance and repair, and replacement are worked out, methods to manipulate them will be developed. Most of the information in a genome is involved in constructing and managing a functional organism, not in regulating the rate of aging.
This is clearly untrue. Scientists can clone, put into artificial vectors, turn on or off, use pieces of, etc. genes that they have only minimal information about. The p53 gene which is involved in ~50% of all cancers has been studied for decades by hundreds of scientists and is still not completely understood. That does not prevent it from being used in a large number of gene therapy trials designed to introduce an operating copy of the gene back into tumors to retard their growth or even kill the cancerous cells. You do not have to know the intimate details of how internal combustion engines work to actually drive a car!
As the discussion of the genome projects above shows, the development of new methods (high througput DNA sequences and robotics) can significantly accelerate laboratory work. Current estimates are that the sequencing capacity now available can sequence a mammalian size genome every 6-8 months! Protein structure specialists are aware that the slow pace of determining the structure and function of genes needs to be acclerated and are working on the development of assembly lines for this task. IBM has announced that it will produce the "Blue Gene" computer to enable rapid and accurate computer modeling of the protein folding problem. Robotics and combinatorial chemistry have speeded up the drug candidate screening process so that hundreds of thousands of molecules may be tested in a single day. Continued increases in the pace of research will provide the information necessary for the mechanisms of aging to be understood and interventions developed.
An understanding of what causes aging (the declining force of natural selection due to accidental deaths in wild environments and antagonistic plieotropy) would suggest that preventing and reversing aging will die a death of a thousand cuts. We will uncover one problem in aging (for example, telomere loss in dividing cells), and a company (e.g. Geron) will be formed to address that. Then we will uncover another problem in aging (for example, free radical damage to the mitochondria), and ideas will be developed to combat that. This process will continue, until one by one, the processes that in aggregate produce aging, are understood and treated.
Genomes can be compared with languages. A genome's primary function is to produce proteins. Some of those proteins perform perform specific actions, such as catalyzing specific chemical reactions, these may be considered verbs. Some proteins, such as collagen, are structural in nature, they might be considered nouns. Other proteins, called transcription factors, exist to regulate or modify the production of the other enzymes and structural proteins, these could be considered adjectives or adverbs. Approximately several thousand words are used in everyday language. This level of complexity corresponds to that of a bacterial genome. A more sophisticated level of language for technical discussions (20,000-40,000) words, that is appoximately the size of vocbularies understood by speech recognition programs, would equate to the level of complexity of simple organisms from nematodes to fruit flies. The most complex genomes such as the Human Genome, would be around the language complexity found in a medium sized dictionary. The largest dictionaries for complex languages such as English or Russian contain 400,000+ words and would probably have a complexity greater than that of the most complex genome.
Genomes are less complex than machines which humans currently build. The DEC Alpha 21164 microprocessor contained 9.3 million transistors of which ~5 million were cache. The Alpha 21264 microprocessor chip contains more than 15.9 million transistors. The next-generation Alpha 21364 is expected to contain over 100 million transistors. DRAM chips now come in sizes of 256 megabits of memory (basically 256 million capacitor/transistor "blocks"). The Space Shuttle Main Engine has over 27,000 pieces in ~5000 parts. A Boeing 747 contains more than 6 million parts, though half of them are fasteners. The Boeing 777-200 contains more than 132,000 engineered parts and 3 million+ simple parts. This indicates that teams of hundreds or thousands of engineers can design and integrate complex systems and have them function reliably.
To understand the complexity of a program you want to understand how many functions(actions) the program does and how many conditions regulate those functions. A back of the envelope calculation for the Human Genome would be that each of the 140,000 genes on average equate to one object-action. Object genes usually have a single purpose. Action genes may serve more than one function or it may take several action genes to perform a single function. If we assume an average 10 conditions (regulatory elements) controlling each object-action, the control complexity of the Human Genome would be around 1.4 million. By comparison, the initial release of Microsoft's Windows NT operating system (version 3.0) contained over 3 million lines of code and the Windows 2000 version contains from 35 to 60 million lines. Because computer programs are structured differently from genome programs (usually with fewer conditions controlling more object-actions) a direct comparison is difficult. It seems reasonable to assume that the Human Genome is equivalent to or even less complex than modern computer operating systems that are the product of a few hundred to a few thousand person-years of engineering.
While it is unlikely that a single individual will ever be able to comprehend the entire genome without significant enhancement of his mental facilities, a reasonable number of people (certainly many less than worked to put a man on the moon) should be able to comprehend how the human program works and make the adjustments required to eliminate aging.
Information about the recent United Nations International Conference on Population and Development is here.
Issues involving overpopulation often involve the issues of hunger. To solve overpopulation, solving hunger is an important requirement. An excellent source for information on Hunger is:
As people will have much longer lifespans and more time to learn a variety of skills, their value and contributions to society should increase. As people save more to reach financial independence there should be increased capital accumulation in society resulting in lower capital costs for investments which increase productivity. These conditions will result in accelerated economic growth. As people's lifespans are extended there will be an increased emphasis on prevention of diseases and cancer through vaccinations and especially an emphasis on accident prevention which should decrease overall health care costs. Further changes may include the engineering of products to "last a lifetime" which might make them more expensive initially would result in lower costs over the lifetime of the product resulting in a decreased cost of living.
Depending on the investment by society, sometime within the next 50
years
nanotechnology should develop and
fundamentally shift the requirements for comfortable living within our
society. Nanotechnology will do for everyday materials and products what
semiconductor fabrication technology has done for the power and price of
computer chips. It has been estimated that an automobile built with
nanotechnology would cost less than $4.00.
It is useful to note that in the 6 years since the original version of this document was written, my time estimates have not altered significantly. The Human Genome was largely complete significantly ahead of schedule (Y2000 vs. the original 2006 plan). The prospects for transplants from enginneered animals and/or laboratory grown organs has also accelerated. Reproducible cloning and the isolation human stem cells was the talk of the news in 1998. The only time estimate which was too short from the original document was the estimate for completing the Drosophila genome. It was completed ~1 year later than the original estimate!