The class I currently teach in generative medicine uses a content system called Blackboard. Blackboard allows me to upload material and pose questions to a forum-like discussion area. One of my students, upon reading the assignment in the textbook made the following comments:

You talk about the division between classical science and naturopathic science, which you equate, respectively, with reductionism and emergence (p. 30). Do they necessarily have to oppose one another and can they not coexist. And does not naturopathic medicine incorporate some degree of reductionism and classical science some degree of emergence?

I guess this goes back to the old question of: can’t we all just get along but, further, isn’t it sort of imperative that we not categorize conventional versus naturopathic medicine in such black and white terms? Or maybe it is a more useful distinction than I’m discerning?

If, indeed, scientific reductionism is dead (p. 20) and the biomedical community is unaware, how do you best suggest we, as NDs (or future NDs), start to make inroads into that community to convince them that the idea of emergence/holism/a generative approach is worth substantively incorporating into the larger paradigm of “modern” medicine?

I would argue that there is a global groundswell of desire among consumers of healthcare for this generative approach, but it might be up to us as practitioners of naturopathic medicine to bring it mainstream. But the path to that end is not clear. At the end of the day, not only do we have to all get along, but we need to understand what the other is saying.

If we define ‘dead’ as having lived a life with purpose, and perhaps even being so lucky as to exhaust that purpose, then reductionism is quite dead in the sense of being ‘not alive’. [Which leads to the question: if an idea has no purpose, hence no life, does it even get to die?]

The web of life is indeed a network.

There will always be a reason to think in reductionist terms when the facts do indeed fit the scenario. IMHO there will always be opportunities for non-complex thinking (and indeed one should seize them whenever one can).

My position is that, as a profession, we are perhaps running the risk of being overly seduced by the simplicity of fitting our oeuvre to the existing allopathic framework. In essence we will be moving into a neighborhood in which the prior occupants have already sucked out the life and are themselves moving on to new areas.

Moreover in doing so we may well be creating a nascent culture of new dogmatists, apparatchiks who insist on only dealing with issues on these terms. If that was not bad enough, this then runs the risk of creating its own response element, its own duality, such that a second subculture results that does the exact opposite, accepting facts a priori.

So, what about this generative medicine idea? As you so astutely point out, the goal is to blend both the complex-systems approach with the mechanistic-reductionist approach, point being that we, as naturopaths, should have a pretty good feel for where the work needs to be done and how to go about doing it. Perhaps this duality is itself a power law: we may be using an 80% reductionist formula to discern 20% of our total causalities. Certainly systems-complexity-network (SCN) medicine comprises only a small fraction of current biomedical information analysis. Generative Medicine, as I see it, should resolve that duality.

No matter what, the informational chasm does indeed lay which complexity, as well as any future potential for understanding and treating the life process itself.

Like they say, if you really want to learn something, teach it.

Tags: complexity | power-law

Carbohydrates comprise only about 1 percent of the human body; proteins comprise 15 percent, fatty substances 15 percent and inorganic substances 5 percent (the rest being water). Nevertheless, carbohydrates are important constituents of the human diet, accounting for a high percentage of the calories consumed. Thus some 40 percent of the calorie intake of Americans (and some 50 percent of that of Britons and Israelis) is in the form of carbohydrates: glucose, fructose, lactose (milk sugar, a disaccharide of glucose and galactose), sucrose, and starch.

Carbohydrates are the fuel of life, being the main source of energy for living organisms and the central pathway of energy storage and supply for most cells. They are the major products through which the energy of the sun is harnessed and converted into a form that can be utilized by living organisms. According to rough estimates, more than 100 billion tons of carbohydrates are formed each year on the earth from carbon dioxide and water by the process of photosynthesis. Polymers of glucose, such as the starches and the glycogens, are the mediums for the storage of energy in plants and animals respectively. Coal, peat, and petroleum were probably formed from carbohydrates by microbiological and chemical processes.

Carbohydrates are the fuel of life, being the main source of energy for living organisms and the central pathway of energy storage and supply for most cells.

Carbohydrates are the most abundant group of biological compounds on the earth, and the most abundant carbohydrate is cellulose, a polymer of glucose; it is the major structural material of plants. Another abundant carbohydrate is chitin, a polymer of N-acetylglucosamine; it is the major organic component of the exoskeleton of arthropods, such as insects, crabs, and lobsters, which make up the largest class of organisms, comprising some 900,000 species (more than are found in all other families and classes together). It has been estimated that millions of tons of chitin are formed yearly by a single species of crab. (1)

The name carbohydrate was originally assigned to compounds thought to be hydrates of carbon, that is, to consist of carbon, hydrogen, and oxygen. They are typical hexose monosaccharides, meaning that they have six carbon atoms. However, carbohydrates now include polyhydroxy aldehydes, ketones, alcohols, acids and amines, their simple derivatives and the products formed by the condensation of these different compounds through glycosidic linkages (essentially oxygen bridges) into oligomers (oligosaccharides) and polymers (polysaccharides).

The biological roles of carbohydrates are particularly important in the assembly of complex multicellular organs and organisms, which requires interactions between cells and the surrounding matrix. All cells and numerous macromolecules in nature carry an array of covalently attached sugars (monosaccharides) or sugar chains (oligosaccharides and polysaccharides), the latter that are generically referred to as “glycans.” (2)

Localization of glycoconjugates in the intracellular and extracellular compartments.

Because many carbohydrates are on the outer surface of cellular and secreted macromolecules, and are often freestanding entities, they are in a position to modulate or mediate a wide variety of events in cell–cell, cell–matrix, and cell–molecule interactions critical to the development and function of a complex multicellular organism. Much of the current interest in carbohydrates is focused on such substances as glycoproteins and glycolipids, complex carbohydrates in which sugars are linked respectively to proteins and lipids. They are termed glycoconjugates. They can also act as mediators in the interactions between different organisms (for example, between host and a parasite). In addition, simple, rapidly turning over, protein-bound glycans are abundant within the nucleus and cytoplasm, where they can serve as regulatory switches. A more complete paradigm of molecular biology must therefore include glycans, often in covalent combination with other macromolecules, (glycoconjugates) such as glycoproteins and glycolipids. (3) The term glycan may also be used to refer to the carbohydrate portion of a glycoconjugate, such as a glycoprotein, glycolipid, or a proteoglycan.

During the initial phase of the molecular biology revolution of the 1960s and 1970s, studies of glycans lagged far behind those of other major classes of molecules. This was in large part due to their inherent structural complexity and the great difficulty in determining their sequences. Also inhibiting interest was the fact that their biosynthesis could not be directly predicted from a DNA template. In addition, unlike genome products, glycans are highly dynamic and have extraordinarily complex biosynthetic pathways. The development of many new technologies for exploring the structures and functions of glycans has since opened a new frontier of molecular biology. The coming together of the traditional disciplines of carbohydrate chemistry and biochemistry with a modern understanding of the cell and molecular biology of glycans, and in particular, their conjugates with proteins and lipids, is called “glycobiology.” (4)

Analogous to genomics and proteomics, glycomics represents the systematic methodological elucidation of the “glycome” (the totality of glycan structures) of a given cell type or organism. The glycome, a subset of glycobiology, is immense and far more complex than the genome or proteome. In the past decade, over 30 genetic diseases have been identified that alter glycan synthesis and structure, and ultimately the function of nearly all organ systems. Many of the causal mutations affect key biosynthetic enzymes, but more recent discoveries point to defects in chaperones and Golgi-trafficking complexes that impair several glycosylation pathways. As more glycosylation disorders and patients with these disorders are identified, the functions of the glycome are starting to be revealed. (5,6)

1. Sharon N. Carbohydrates Sci. Am. 245: (5) 90-116. 1980
2. Varki A and Sharon N. Historical Background and Overview: Varki A, Cummings R, Esko J, Freeze H, Stanley P, Bertozzi C, Hart G, and Etzler M. Essentials of Glycobiology, 2nd edition, Cold Spring Harbor (NY): Cold Spring Harbor Laboratory Press; 2009.
3. Ibid.
4. Rademacher TW, Parekh RB, Dwek RA. Glycobiology. Annu Rev Biochem. 1988;57:785-838
5. Freeze HH. Genetic defects in the human glycome. Nat Rev Genet. 2006 Jul; 7(7):537-51.
6. Taylor ME and Drickamer. Introduction to Glycobiology. Oxford University Press 2nd Edition 2006

A

n insignificant percentage of the total amount of DNA is devoted actual gene function. The most common protein recipe in the human genome is not even for a human protein, but rather an enzyme commonly used by viruses to copy them called reverse transcriptase, an essential part of the toolbox used by the AIDS virus. Reverse transcriptase genes account for about 1-2% of the entire junk DNA in the human genome, which may not sound like much, but then again remember that the actual genes that account for you only amount to about 3% of the genome. Humans have about 23,000 genes, which is certainly more than most fungus (around 6,000) and many worms (around 19,000) but less than some fish (around 40,000) and most plants (around 60,000).

As with most techniques, it’s not what you have, but rather what you do with it.

You’d think that the job was simple enough, string some nucleotides into a few codons, and away you go. But no, it has to be difficult! I remember when I first had Cable TV installed in my house, it was advertised as being commercial-free, and for a while it was. However, gradually more and more commercials have been added to the Cable Program Roster, to the point where it is hard to tell the difference between Pay or Cable TV and Commercial TV —other than the fact that you pay for one and not the other. Genes are fond of running commercials during their broadcasts.

In geneticalese we call these commercials introns and the programs exons.

Messenger RNA (mRNA) is usually primped before it is shot out of the nucleus, the primping usually involves taking out all the introns, and reconnecting the exons, just as if you had paused the VCR during commercials as you were recording the Super Bowl.

I can still taste the chocolate.

When completed, the haploid human genome found far fewer genes than had been expected before it was sequenced. However the case has been advanced that a process by which exons of the precursor RNA produced by transcription of a gene are reconnected in multiple ways during the RNA splicing that produces mRNA. The resulting different mRNAs may be translated into any of several different forms of the same protein (protein isoforms) or a variety of glycoproteins with different attached glycans (polysaccharides). Thus a single gene may code for multiple proteins. Alternative splicing greatly increases the diversity of proteins that can be encoded by the genome, and in humans it is estimated that over 80% of genes are alternatively spliced.

Just exactly how much DNA makes up a gene? One common definition, advanced by Richard Dawkins, is that a gene “is any portion of chromosomal material small enough to last for a large number of generations.” However, this definition has utility only with regard to evolution. Many geneticists use the concept of a cistron interchangeably with the term “gene.” The most common definition of a cistron is “a section of DNA that contains the genetic code for a single polypeptide and functions as a hereditary unit.” Sound like a gene, doesn’t it? However using the terms interchangeably, although common, is not correct. Why? Because as a result of some recent research, it appears that some cistrons can encode for more than one protein.

To understand how this is possible, it is necessary to understand the deeper working of the cistron, which it turns out, is rather complex. Like genes, cistrons contain “meaningful” information –the sequence of bases that code for amino acids. As we’ve learned, these are called exons. However, dispersed in the cistron are chunks of additional base sequences that don’t appear to do anything at all, called introns. Now imagine a recipe for chocolate chip cookies is made up of mixing two cups of flour, one tablespoon of chopped peanuts, one cup of butter, one cup of chocolate chips, one cup of sugar and two eggs. The way information is contained in DNA is exactly like the way that information needed for making your cookie dough is contained here: (1)

Mix two cups of flour, one cross related two cups tablespoon of chopped bag element peanuts, one cup of case honest butter, one cup of penguin green chocolate flint chips, one walking spoon cup of nail bank sugar and two canvas eggs.

A process known as alternative splicing has been identified by which the spliceosomes in different cells can do different things with the same pre-RNA, thereby generating two or more different proteins (called isoforms) from the same code of pre-RNA. In other words, the same block of information can produce two different outcomes, two different protein products. In humans, over 80% of genes are alternatively spliced, which may help explain why the total number of genes in our genome is rather on the low side. For example, our chocolate chip cookie recipe, hidden inside the gibberish of cookie introns, also has inside of it a recipe for peanut butter cookies as well:

Mix two cups of flour, two cups peanut butter, one cup of sugar and two eggs

The vast majority of reverse transcriptase coding in junk DNA probably has little to do with retroviruses such HIV, or Feline Leukemia Virus. Rather, the reverse transcriptase is probably there as a leftover of certain types of “jumping genes” called reverse transposons (retrotransposons).

Much of our junk DNA is repetitive; certain patterns of Cs, Ts, Gs and As just repeat themselves. These chunks are usually about 50-100 bases long and the number of these spread across the chromosome vary considerably from person to person.

Genes differ widely from each other. The gene for insulin, a relatively smallish gene, is 1700 base pairs long which, in a railroad analogy, would produce a stretch of insulin railroad track 1700 sleepers long. Figuring each sleeper as being about two feet apart, a stretch of railroad track gene sufficient to code for insulin would be a little longer than half of a mile. At the other end of the spectrum is the gene that codes for a common type of muscular dystrophy. It is two million base pairs long. If it were a railroad line, this length of gene track would stretch from New York City to Chicago.

1. Moore D. The Dependent Gene. Owl Books. Henry Holt and Company New York NY USA (2001)

Portions excerpted from Fundamentals of Generative Medicine copyright 2010, Drum Hill Publishing, USA.

Tags: Generative Medicine

It was known early in the century that ABO blood group substances occur in human tissues and secretions in two forms, water-soluble and alcohol-soluble, and that persons with these substances in saliva (secretors) have more water-soluble substances in their tissues than those lacking the substance in their saliva (non-secretors). One of the primary differences in physiology between secretors and non-secretors has to do with qualitative and quantitative differences in blood type antigen components of their saliva, mucus, and other body secretions. Two alleles, Se, and se control ABH secretion. Se is dominant and se is recessive (or amorphic). Approximately 80% of people are secretors (SeSe or Sese).

The term ABH secretor, as used in blood banking, refers to secretion of ABO blood group antigens in fluids such as saliva, sweat, tears, semen, and serum. If people are ABH secretors, they will secrete antigens according to their blood groups. For example, group O people will secrete H antigen, group A people will secrete A and H antigens, etc. Soluble (secreted) antigens are called substances. To test for secretor status, an inhibition or neutralization test is done using saliva. The principle of the test is that if ABH antigens are present in a soluble form in a fluid (e.g., saliva) they will neutralize their corresponding antibodies and the antibodies will no longer be able to agglutinate red cells possessing the same antigens.

It's often not what you are eating, but what is eating you.

In the most rudimentary sense, the secretor gene (FUT2 at 19q13.3) codes for the activity of the glycosyltransferases needed to assemble aspects of both the ABO and Lewis blood groups. This it does in concert with the gene for group O, or H (FUT1). These enzymes are then active in places like goblet and mucous gland cells, resulting in the presence of the corresponding antigens in body fluids. (1)

Secretor status and Candida albicans

ABH non-secretors are much more likely to be carriers of Candida species and to have problems with persistent Candida infections. Blood group O non-secretors are the most affected of the non-secretor blood types. One of the innate defenses against superficial infections by Candida species appears to be the ability of an individual to secrete the water-soluble form of his ABO blood group antigens into body fluids. The protective effect afforded by the secretor gene might be due to the ability of glycocompounds in the body fluids of secretors to inhibit adhesins (attachment lectins) on the surface of the yeast. In attachment studies, preincubation of certain bacterial spores with boiled secretor saliva significantly reduced their ability to bind to epithelial cells. ABH non-secretor saliva did not reduce the binding and often enhanced the numbers of attached yeasts. (2,3) In one study, among individuals with Type II diabetes, 44% of ABH non-secretors were oral carriers of this yeast. (4)

Although non-secretors make up only about 26% of the population, they are significantly over represented among individuals with either oral or vaginal Candida infections, making up almost 50% of affected individuals. (5) The inability to secrete blood group antigens in saliva also appears to be a risk factor in the development or persistence of chronic hyperplastic candidosis. In one study, the proportion of non-secretors of blood group antigens among patients with chronic hyperplastic candidosis was 68%. (6)

Women with recurrent idiopathic vulvovaginal candidosis are much more likely to be ABH non-secretors. Combining both ABH non-secretor phenotype and absence of the Lewis gene, Lewis (a- b-), the relative risk of chronic recurring vulvovaginal candidosis is between 2.41-4.39, depending on the analysis technique and control group. (7)

Oral carriage of Candida is also significantly associated with blood group O (p < 0.001) and independently, with non-secretion of blood group antigens (p < 0.001), with the trend towards carriage being greatest in group O non-secretors. (8)

Blood Groups and Microbiome

This is especially interesting in light of the fact that many of the fucosyltransferase enzymes convey blood group and/or secretor status. (9) Human feces contain enzymes produced by enteric bacteria that degrade the A, B, and H blood group antigens of gut mucin glycoproteins. The autosomal dominant ABH secretor gene together with the ABO blood group gene controls the presence and specificity of A, B, and H blood group antigens in human gut mucin glycoproteins. There is evidence that the host’s ABO blood group and secretor status affects the specificity of blood group-degrading enzymes produced by his fecal bacteria in vitro. (10) Comparatively small populations of fecal bacteria produce blood group-degrading enzymes but their presence is highly correlated with the ABO /secretor phenotype of the host: Fecal populations of B-degrading bacteria were stable over time, and their population density averaged 50,000-fold greater in blood group B secretors than in other subjects. In fact, the large populations of fecal anaerobes may be an additional source of blood group antigen substrate for blood group antigen degrading bacteria: antigens cross-reacting with blood group antigens were detected on cell walls of anaerobic bacteria from three of 10 cultures inoculated. (11)

1. Henderson J, Seagroatt V, Goldacre M. Ovarian cancer and ABO blood groups. J Epidemiol Community Health. 1993 Aug; 47(4):287-9.
2. Toft AD, Blackwell CC, Saadi AT, et al. Secretor status and infection in patients with Graves” disease. Autoimmunity 1990; 7(4):279-89.
3. Blackwell CC, Aly FZ, James VS, et al. Blood group, secretor status and oral carriage of yeasts among patients with diabetes mellitus. Diabetes Res 1989 Nov; 12(3):101-4.
4. Thom SM, Blackwell CC, MacCallum CJ, et al. Non-secretion of blood group antigens and susceptibility to infection by Candida species. FEMS Microbiol Immunol 1989 Jun; 1(6-7):401-5.
5. Thom SM, Blackwell CC, MacCallum CJ, et al. Non-secretion of blood group antigens and susceptibility to infection by Candida species. FEMS Microbiol Immunol 1989 Jun; 1(6-7):401-5.
6. Lamey PJ, Darwazeh AM, Muirhead J, et al. Chronic hyperplastic candidosis and secretor status. J Oral Pathol Med 1991 Feb; 20(2):64-7.
7. Chaim W, Foxman B, Sobel JD. Association of recurrent vaginal candidiasis and secretory ABO and Lewis phenotype. J Infect Dis 1997 Sep; 176(3):828-30.
8. Burford-Mason AP, Weber JC, Willoughby JM. Oral carriage of Candida albicans, ABO blood group and secretor status in healthy subjects. J Med Vet Mycol 1988 Feb; 26(1):49-56.
9. D’Adamo PJ, Kelly GS. Metabolic and immunologic consequences of ABH secretor and Lewis subtype status. Altern Med Rev. Aug;6(4):390-405; 2001
10. Hoskins LC, Boulding ET. Degradation of blood group antigens in human colon ecosystems. I. In vitro production of ABH blood group-degrading enzymes by enteric bacteria. J Clin Invest Jan;57(1):63-73;1976
11. Hoskins LC, Boulding ET. Degradation of blood group antigens in human colon ecosystems. II. A gene interaction in man that affects the fecal population density of certain enteric bacteria. J Clin Invest Jan;57(1):74-82; 1976

The last century has seen science and technology used to justify any and all supremacist theories, culminating in the development of a pseudoscience called “Eugenics”, which advocated the improvement of society through what might me called selective breeding. Now, not all of the eugenic goals were crackpot and indeed many prominent scientists (including one of the greatest scientists of all, R.A. Fisher) allied themselves with the movement, at least in its early stages. Indeed one can still see some aspects of eugenic thinking in society’s use of prenatal testing and screening, genetic counseling and birth control.

However, eugenics had a far seedier side. For example, in July 1933 Germany passed a law allowing for the involuntary sterilization of “hereditary and incurable drunkards, sexual criminals, lunatics, and those from an incurable disease which would be passed on to their offspring.” Sweden, the USA, Canada, and virtually every non-Catholic country had Eugenic Societies. In the USA, immigration policies were motivated by the goals of eugenics, in particular a desire to exclude “inferior” races from the national gene pool.

As the human legacy of Nazism became known to the postwar scientific community, and it shuddered at its consequences, and many scientists began to look upon genetics and anthropology as the very opposite of race-definers; they saw it instead as a way of showing just how bankrupt the notion of racial stereotyping was.

William Boyd and Isaac Asimov put the first modern scientific approach to race forward in a simple, readable, and completely forgotten book called Races and People. Written in 1955, it is an unabashed championing of the essential value of any human being. Asimov, well known to three generations of Science Fiction readers, had grown up Jewish in an era when significant portions of the world found anti-Semitism innocuous or even virtuous. Boyd, blood type anthropologist, science fiction writer and the discoverer of of the blood type specificity of certain lectins (talk about a life!), used research with blood groups to demonstrate that the superficial characteristics which so many of us use to define race and determine our value vis-à-vis other human beings are utterly without scientific basis. (1)

Publishing their book in a time when racial segregation and colonialism were still the norm and in the wake of terrible genocide, Boyd and Asimov set the pattern for all future anthropologic and genetic analysis of race. However, with the onset of those classic liberal values we so identify with the 1960’s and 1970’s and their effects in popular culture and academia, the pendulum began to swing the other way round. In scientific circles, race became a non-entity, possessing no significance whatsoever.

'Around a flowering tree, one finds many insects.' - Proverb from Guinea

Boyd defined later race as “not an individual, not a single genotype, but a group of individuals more or less from the same geographical area (a population), usually with a number of identical genes, but in which many different types may occur.” For Boyd, as with Livingstone, you got your racial characteristics from where you live more than from your genes, and this explained why the variability made the notions of race untenable. (2)

Rather than being racists themselves, I think we should consider the early blood group researchers rare beacons of tolerance in a world still coming to grips with the notion of equality for all.

However, just because you say something doesn’t exist doesn’t necessarily make it go away, and it is childish to think that we can contribute to the elimination of racism by putting our heads in the sand with the belief that there are no clearly defined races. One of the primary blood type/ anthropology sources I’ve cited, Frank Livingstone, (3) even rejected the concept of race altogether. Livingstone suggested that the variability in the frequency of any gene does not utilize the concept of race. He pointed out that although it is true that there is biological variability between the populations of organisms which comprise a species, this variability does not conform to the discrete packages we call ‘races’. In other words, there are no races, the are only clines (a ‘cline’ is a gradient of physiological change in a group of related organisms usually along a line of environmental transition). This is still the guiding principle in contemporary anthropology; at least in name, if not in practice. Instead of racial distributions, we now have “clines”: distribution lines very much like those you would see on a weather map. Not surprisingly, most of these clines do a very nice job of delineating population differences that any person could have arrived at by simply traveling to that area and having a look around.

Alice Brues, a well-known physical anthropologist, addressed the folly of avoiding race as a physical characteristic:

“A popular political statement now is, “There is no such thing as race.” I wonder what people think when they hear this. They would have to suppose that the speaker, if he were dropped by parachute into downtown Nairobi, would be unable to tell, by looking around him, whether he was in Nairobi or Stockholm. This could only damage his credibility. The visible differences between different populations of the world tell everyone that there is something there.”

An important paper written against the use of race as a method of classification argued that since the probability of mis-classifying an individual based on variation in a single gene is approximately 30%, race is an invalid taxonomic construct: In short because humans share 50% of their DNA with a rose bush, we must be 50% the same. This was countered by an argument (“Lewontin’s Fallacy“) that argued if one took into account more genetic markers, the possibility of a racial mis-classification rapidly dropped to almost 0%. The counterargument to this counterargument is that if we looked at enough genes we could presumably distinguish Swedes and Norwegians as two distinct races.

Let’s take a moment to remember while that Boyd and Asimov did not deny the existence of race, they demolished the notion of using race to determine an individual’s value. For our purposes, we’ll use race and ethnicity simply to get additional information that may be valuable in helping to design a more intelligent lifestyle for you, the reader. Let’s just assume that you can and do belong to certain human groupings whose members have more in common with each other than they do with other groupings.

What we call a “race” is really just another fact. Moreover, when we try to subsume it into non-existence, we do injustice to both sides of the distinction. When you share a fact with someone, it makes no one the better or worse, just better informed.

‘History is bunk,” wrote the industrialist Henry Ford. It is a quote with the ring of truth in it. We are destined to interpret past events through the eyes of who left the record (usually the winner) and our own modern day thoughts and rationales. Losers rarely write history, and it is just about impossible for the average person to put himself or herself in the mindset of a person living in a world without light, heat, supermarkets, and the Internet.

Science is fact-based, but scientists can sometimes be charmingly naïve. One of the most common ways they display this naiveté is the coining of politically correct euphemisms. Thus, instead of the negatively charged term “race” you sometimes see the phrase “mutually inbred ancestral groups” which, at least to me, sounds even worse.

Despite the gloss, we at least now have a framework to allow us to collect and categorize those genes and polymorphisms that show different frequencies between races.

Called Ancestry-Informative Markers (AIM) this category of genes includes blood groups, markers of pigmentation and other SNP’s that distinguish between races but don’t always result in some visually detectable difference. A collection of AIM’s that distinguish African and European populations contains over 3000 highly differentiated SNP’s.

An example of an AIM gene is called “Duffy,” which codes for the Duffy blood group, The Duffy blood group has a variant that codes for a Duffy blood type (Duffy Null allele) that is found 100% of Sub-Saharan Africans, but occurs very infrequently in other races. Interestingly, like some of the hemoglobins, this variant has been known to provide some resistance to malaria infection.

Another interesting variant of the APOA1 gene (the TT genotype) is seen in high concentration in African Americans. This variant may help to explain their higher rates of heart disease as a genetic factor leading to difficulty in adapting to new nutritional environments. (1)

Once, after a public lecture, I was approached by an attendee who asked if I was aware that there were criticisms of my work as ‘racist’ on the internet, and that I had derived my conclusions from long-discredited research done by the Nazis in concentration camps. It turned out that the accuser was a zealous follower of veganism , who thought this might be an effective way to quell further interest in my conclusions.

In all of my trolling through the scientific literature on blood groups since 1910 I’ve not recovered a single reference on ABO blood group that supported any of the racial notions then in vogue in Nazi Germany. My suspicion is that if any research was done the results were not supportive of their racist prejudices — i.e. the subjects were more alike on a blood group basis than they would have liked to admit.

1. Boyd WC and Asimov I. Races and People. Abelard-Schuman 1955
2. Boyd WC. 1952 The Contribution of Genetics to Anbthyropology. in Anthropology Today, ed. by A.L. Kroeber,
3. Livingstone FB. 1962 On the non-existence of human race. Current Anthropology 3 (3):279-281.
4. Lutucuta S, Ballantyne CM, Elghannam H, Gotto AM Jr, Marian AJ. Novel polymorphisms in promoter region of ATP-binding cassette transporter gene and plasma lipids, severity, progression, and regression of coronary atherosclerosis and response to therapy. Circ Res. May 11; 88(9):969-73. (2001)

After a self-declared coding holiday, I was back at things this weekend working on the Pathscrubber module of the Datapunk platform. A recently developed vexing problem that needed to be addressed was actually two problems intertwined. If you used Pathscrubber and clicked on any gene/protein node, PS would query Entrez-gene for the descriptive text and pull a bunch of theory and clinical stuff together and send it all out as a pop-up window. For some reason the response time (on their end) was unbearably slow. The second problem was a change to the interface between NCBI and the OMIM database. OMIM is run by Johns Hopkins and suddenly one day the NCBI query tool that PS uses to get the OMIM entry on any gene stopped working. It was certainly their problem since the NCBI’s own links do not work. However I discovered that OMIM was now available for download (something like 200 megabytes total).

Gotta love having an email address that ends in ‘.edu’!

Datapunk Logo.

However there were problems with the data files, beyond the fact that they were incredibly huge. They are not in a typically common data file format, where each record is delineated by a carriage return (‘enter’) and each field in the record is delineated by a tab, comma or pipe (|) character. The OMIM gene records as weird blend of individual lines that contain data and other lines that name fields, all of which are variable in length and appearance. I’ve dealt with files like these before (some KEGG files have this format) and you have to really work hard to code a way for Perl (the computer language I typically use) to tease out what you need. Fortunately, Perl has a vibrant community of programmers that produce different ‘modules’ that expand Perl’s capabilities. Thus you do not have to reinvent the wheel if someone has already done it.

One module I use a lot is called BIO::PERL. This has lots of cool interfaces and tools, including one that parses (reads) OMIM gene files. Normally that would be end of the story. However that BIO::PERL module, while doing a good job, was too slow, so I developed a work-around that involved using the module to tease out specific data, which was then re-organized and written to new data files indexed by the OMIM gene ID number. By the time I was done, I have four different data files which the program could quickly query and execute rapidly.

One problem I encountered doing this was the exceedingly complex nature of the data returned from the BIO::PERL parser. Much of it was nested inside a series of ‘hash arrays.’ In the computer world an array is a place to store data, much like an egg carton stores eggs: once the eggs are in the carton, you can specify which egg you want by naming the column and row number of the egg you want. Easy enough, but in computer world, in addition to an egg (or an empty space), the location of any place in our egg carton can also contain the location of another egg carton!

This is how data often gains meaning from organization.