Dec 26 2015

Opus 23








I’ve been gone for a while. Sorry. It’s been a busy time for me. I’ve spent most of the year coding a genomic analysis program called Opus 23 Pro.

Opus 23 Pro is a suite of apps that provide a development environment for precision medicine. It allows the clinician to import raw genomic data (such as provided by 23andMe and other services) and perform a series of extraordinarily sophisticated analytics upon it, culminating in a fully annotated and curated client report.

You can visit the developer blog I’ve put up by clicking here.

Opus 23 Pro is a suite of apps that provide a development environment for precision medicine. It allows the clinician to import raw genomic data (such as provided by 23andMe and other services) and perform a series of extraordinarily sophisticated analytics upon it. The process culminates in a complete chart report and a fully annotated client report, which can be easily modified to display only the data the client needs to know. Opus 23 Pro features:

  • Complex multi-SNP algorithms: Very few single SNPs have actionable consequences. The Opus 23 Pro app LUMEN runs over 300 algorithms on multi-SNP clusters, identifying significant haplotypes and epistatic relationships
  • Smart Interactive Network Maps: We’ve all studied pathway maps. However the Opus 23 Pro app MAPPER can populate network maps with the actual genotype data from your client. It can even try to approximate gene function based on SNP outcomes and overall network efficiency
  • Mega-Data Mashups: Opus 23 Pro synthesizes its results from a wide variety of data, including GWAS (genome wide association study) data, dbSNP, Interactome, Etiome, PubMed, HapMap, and many others. SUPERMOGADON takes GWAS data and displays it as interactive Manhattan plots.
  • GWASFED depicts Genome-Wide Association study (GWAS) data as applied to the client genotype, and links to the relevant PubMed references
  • Causes and Effects: Opus 23 Pro uses advanced data analysis tools to surf various networks and identify high value targets. ACCELERANT identifies complicating etiologic factors for the client by combining searches of the Diseasome and Etiome
  • Intelligent Prescriptives: Opus 23 Pro features a unique curated database of natural products known to regulate gene expression. The PSYCHIC app surfs the Interactome and identifies upstream and downstream targets, then identifies high value agents to consider
  • Complex Syndrome Modeling: Most complex syndromes are the result of genes acting in ‘subgraphs’ –specific neighborhoods in the network. MOBOCASTER supplies you with this data.
  • Fully Interactive Learning Tool: It’s inevitable that you’ll encounter genes or SNPs you’ve never heard of. Pop-ups give you details: Click on a gene or SNP and up pops an information screen with curated gene or SNP data, where available. Click on an agent and up comes the PubMed citation
  • Pharmacogenomics simplified: Adverse drug reactions are a potential threat to patient health. The DRUGGIE app will report over 350 potential adverse reactions based on your client’s genotype
  • Two smart search facilities: WANDERER searches the output of Opus 23 apps and algorithms for genes, SNPs and keywords; ARGONAUT searches the client’s raw data for genes, SNPs and curated SNP data text, as well as specific genotypes
  • Safe and Secure: Opus 23 Pro uses SSL (https) to protect sensitive data during transmission. In addition all data on the Opus 23 server is protected with AEM (Authenticated Encryption Methodologies) encryption that actually exceeds HIPAA standards
  • And Much More: The Opus 23 Pro app RARIFY checks for rare alleles. The FANTASMATRON app allows you to make dietary suggestions based on client genotype

Comments Off on Opus 23

Mar 13 2015

Fats, Blood Groups and the Intestines


o single diet theory can address all aspects of our individuality, and only a fool would claim that soy, red meat, grains, coconut oil or anything else is universally good or universally bad for everyone.

For example, people who are blood group O appear to derive significant benefit from a diet including lean animal proteins, including hormone and antibiotic free meats and poultry. There is a very basic physiologic reason for this: those with type O blood have almost three times the levels of an enzyme in their intestines known as intestinal alkaline phosphatase (IAP) [link]. This enzyme performs two very important functions in the body. First, IAP splits dietary cholesterol into smaller fragments, allowing for their proper breakdown. Second, IAP enhances the absorption of calcium from the diet.

When it comes to fats, one man's food may well be another man's poision.

The researchers looked at IAP and a second factor: apolipoprotein B-48 (APOB-48). Apolipoprotein B (APOB) is the primary apolipoprotein of low-density lipoproteins (LDL or “bad cholesterol”), which is responsible for carrying cholesterol to tissues. Both IAP and APOB-48 are exclusive to intestine, although only APOB-48 is found in chylomicrons, large lipoprotein particles that consist of triglycerides (85-92%), phospholipids (6-12%) and small amounts of cholesterol and proteins that transport dietary lipids from the intestines to other locations in the body. After most of the lipids in the chylomicron have been digested, APOB-48 returns to the liver as part of the chylomicron remnant, where it is endocytosed and degraded.

Levels in serum samples from 40 healthy subjects obtained after overnight fast and 3 hours after a high-fat meal. Both APOB-48 and IAP were greater in subjects without blood antigen A (blood groups B and O) than in those with this antigen (blood groups A and AB). The non-A group had 2.4 greater levels of IAP before the meal and a 4.7-fold greater level of for IAP after the meal. The non-A group had 1.5- and 2.0-fold level of apoB-48 over the A-group before and after the meal, respectively.

Moreover, IAP and apoB-48 levels were strongly correlated in the subjects with the secretor phenotype (r > 0.81). These results indicate that IAP is strongly involved in chylomicron formation and fatty acid metabolism might change among ABO blood type.

ABO blood type classification in apoB-48 measurement would improve the diagnostic value in the evaluation of metabolic syndrome.

Now you’d think this was cutting-edge, late-breaking news since it is obviously of tremendous interest in these nutrigenomic times. However, the first observations were made over four decades ago.[link]

In addition to these two critical functions IAP is an important influence on the ability of the digestive tract to heal. Thus in most of our type O patients (44% of the population) we see a marked improvement in their IBS, colitis and Crohn’s disease when they increase their protein and cut back on their carbohydrates. [link]

Blood group B makes considerable amounts of IAP as well, but blood group A and AB make very little. This probably explains why most studies that have looked at heart disease and blood type show a significantly higher rate of problems with blood group A individuals. These folks really should follow a Mediterranean-type diet.

Later studies showed that blood group A not only secreted almost no alkaline phosphatase in their intestines, but whatever little they did secrete was in and of itself inactivated by the presence of their own blood group A antigen. [link]

The significant variations in APO-B48 and IAP as seen between the ABO blood groups are some of the strongest indications for the long term benefit of a low-fat diet in blood group A, both with regard to the susceptibility to cardiovascular disease, and (although not mentioned here) their additional susceptibility to cancer. An emphasis on a healthy fats, low animal protein and the avoidance of foods high in phenylalanine, is the best method to maximize digestive efficiency in individuals who are blood type A, lower their level of intestinal dysfunction, and to influence their susceptibility to cardiovascular disease.

There are 3 comments on this article so far

Mar 02 2015

Blood groups, secretor status and the microbiome

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

There are 8 comments on this article so far

Jul 28 2014

Tracking the Blood Type Diet

Readers of this blog know my feelings concerning the recent PLOS study on the blood type diet. You can read them here and here. As these previous articles demonstrate, the problem was not so much the study’s methodology, but rather with its criteria, i.e. the assignment of blood type diet values to foods that had no actual value in the blood type diet, such as ‘hamburger,’ ‘beans, all kinds,’ and ‘Mac and Cheese.’

However, the PLOS study did point to a simple way that the theory could be tested: assigning a value to the consumption of beneficial and avoid foods and tracking the subject’s activity over time to see if changes in basic biomarkers (such as lab tests) correlate with adherence.

With this in mind, I began to consult with some colleagues about the possibility of developing a specific research tracking program that would allow us to collect data on dietary adherence that truly reflected whether or not the subject was following the BTD –or even some variant of it- or in fact if they did none of it at all. As I’ve already written a slew of programs of a sort similar to this, I began to go to work.

We wanted the program (now called Traktion) to fill a variety of needs. We aim to use anonymized data from Tracktion to see what kind of difference a high or low compliance level makes to people following the BTD. It also takes into account secretor status (if known), a major factor which the PLOS study overlooked.

These included:

A simple registration process and easy start-up: After an email verification (to screen out bots) users are initially required to provide only some very basic information, such as age, gender and ABO blood group. Traktion is freeware; there is no charge for its use.

A simplified way for users to input data: After testing a variety of human/computer interfaces it was clear that the best way to input diet diary information was what is known as a tagged-auto-complete form. Users simply type in the first few letters of the food they wish to add to the diary and select from the pull-down choices. The choices are from the official list of BTD value foods. This specificity requires a bit more work, since there are no foods such as ‘pizza’: instead, the user would input ‘wheat, whole wheat’, ‘tomato’, ‘mozzarella cheese,’ etc. However, it allows much more flexibility, since, for example, in our house we make pizza with spelt pizza dough.

Traktion’s diet diary entry screen. Click the image to see a larger version in a new window. Feedback, Stickiness and ‘Easter Eggs’: It would be nice to depend on the altruism of the user to consistently put in data day after day, but we know that the more ‘sticky’ the application, the more repeat usage it receives. So I developed an entire ‘dashboard’ that presents the user with infographic-type feedback: charts and graphs that show them just how they are doing. Users can customize their dashboard to show different info-graphics, such as diet compliance, exercise activity, etc. Also, there is a neat ‘Easter Egg’ feature called ‘How Do You Feel Today?’ that records day-to-day ‘soft dimensions’, such as ‘energy’, ‘concentration,’ etc. When the user adds this information, they receive simple suggestions of beneficial foods for their type they may wish to increase their daily usage of.

Traktion’s Dashboard screen. Click the image to see a larger version in a new window. Expandability: Although the basic requirements for getting started in Traktion are minimal, users can also supply additional information, such as SNP data from 23 And Me; additional blood type related data, such as their secretor status; information on supplements, OTC medications and drugs they are taking, lab values, and specific exercises and length of time exercising. This will give us the opportunity to do additional data-mining.

Traktion’s Exercise screen. Click the image to see a larger version in a new window.

Traktion’s Health Data screen. Click the image to see a larger version in a new window.

Traktion’s Supplements and Medications screen. Click the image to see a larger version in a new window.

Traktion’s Profile Development screen. Click the image to see a larger version in a new window. Support: Users can avail themselves of several support functions. A ‘Live Chat’ window is available for technical support and they can avail themselves of support forums, etc.

Anonymity and Security: Traktion uses SSL (secure sockets layer). All data is further encrypted on the server. On registration everyone must agree to a basic end user license agreement (EULA) that also clearly explains what the data that is being collected is to be used for. Other than the initial email, users are only identified by their chosen username.

At this point in time the basic user interface and data-gathering scripts are largely complete. I need to complete a few more dashboard plugins and finalize the data structures, and then Traktion can go into beta testing. I suspect we can have a real-world working version by September. The admin back-end can be developed over time.

What do users get out of it?

A way to track their BTD compliance level alongside other factors such as exercise, and correlate this with their wellbeing. Users may be able to work out factors that affect their personal state of health, such as specific foods or exercise levels that might make them feel better or worse.

What do I get out of it?

A way to see aggregated anonymized data from large numbers of people and their compliance levels to the BTD on a custom-designed tracking system which takes the latest BTD food values into account. I hope to combine this data with other influences to get an overall picture of how well the BTD works for specific groups of people using Tracktion. For those who enter GenoTypes, lab values, medication or SNPs this may lead to new discoveries and open up possibilities for future areas of research. In the long run it will be of great benefit to the whole nutrition community.

As Traktion gets closer to completion, I’ll update this blog with further details, so stay tuned.

Comments Off on Tracking the Blood Type Diet

Jan 24 2014

Kicking Bubbles

A look at the core data used in the PLOS Study [1] debunking the Blood Type Diet (BTD) finds support for the researcher’s conclusions that if your experimental  subjects eat potato chips, sandwiches, pizza, ‘beans,’ mac-and-cheese, French Fries and processed meat products while doing 13.7% of the Blood Type Diet, their final cardiometabolic markers will probably not vary much by blood type.

In other words, whilst the PLOS Study may have debunked something, it wasn’t the Blood Type Diet.

Laying aside my initial concerns about the study expressed in the previous blog, many of which were responded to personally by Dr. El-Sohemy, there remains the one over-arching issue: How accurately did the PLOS study model the Blood Type Diet? Despite Dr. El-Sohemy’s extensive response, this was the one point for which he chose to not answer. Since no clarification was forthcoming, I decided to seek out the answer for myself.

Soap bubbles

This turns out to have been quite easy, since the food values used in the PLOS study were included as a table in an appendix. [3] From there I simply prepared a spreadsheet with the corresponding values from my book Eat Right For Your Type (ERFYT)[2] and the PLOS Appendix, when a value in the appendix was available, which as you can see by clicking on the link below, was not very often. I then wrote a short program in Perl to run some simple analytical and counting functions.

Click Here to Read the Full Article

I started by simply comparing the incidence of values that  appear in ERFYT and the corresponding values that appear in the PLOS Study.

These appear as Table 1.

The results were even worse than I expected. An enormous number of foods containing values in ERFYT are missing values in the PLOS Appendix. Out of a total of 540 food values available in ERFYT (excluding ‘Herbs,’ ‘Beverages,’ and ‘Teas,’) only 74 (13.7%) show equivalent values in the PLOS Appendix. It’s easy to see the number of foods missing foods from the PLOS appendix in Table 1. They are the large chunks of grey-colored boxes in the table with the label ‘n/v’.

There are also a considerable number (822) of instances of foods containing specific values (being rated as either ‘beneficial’ or ‘avoid’) in ERFYT but having no equivalent values in the PLOS Appendix. In these occurrences, subjects consuming any of these foods would not have had their effects represented in the PLOS study.

In addition, there are no equivalent values in the PLOS Appendix for a large number of the foods (281) for which ERFYT supplies at least two blood type specific values.

Finally, there are a sizable number (77) of foods for which there are values in ERFYT that differ by blood type (i.e being a ‘beneficial’ for one blood type and  ‘avoid’ for another) that were not included in the PLOS Appendix. This number is especially pertinent, because a considerable number of foods where variation by blood type might have been expected were not included in the PLOS study. When the non-ERFYT equivalent foods are excluded (see Table 2) the number of foods missing from the PLOS Appendix containing values that vary by blood type is actually greater than the total number of  foods included in the PLOS Appendix  (74).

Then I looked at the food values used in the PLOS-BTD Study that have no equivalent value in ERFYT.

This appears as Table 2.

These results went from bad to ludicrous.

A total of 37 foods are classed in the PLOS Appendix as possessing BTD values despite having no direct representation in ERFYT. This appears to have resulted from study force-fitting foods from the Toronto-modified Willet 196-item semi-quantitative food frequency questionnaire (TMW) into the food framework of the BTD. However, many of these foods are complex combinations of various single ingredients (‘sandwiches’), or entire categories of foods (‘beans’). These ‘lumped categories’ often possess unknown BTD values, or contain  individual foods with specific BTD values that contradict the values assigned to the total category  by the PLOS authors.

There are several assumptions about the nature of these complex foods which lead to error. For example, ‘mac and cheese’ is listed as ‘neutral’ for blood types A, B, and AB in the PLOS Appendix, despite the fact that the dish is almost universally prepared with processed American cheese, which is clearly indicated in ERFYT as an ‘avoid.’ Pizza is listed as a ‘neutral’ for blood type A, when in fact pizza is almost always prepared with tomato sauce.  Tomatoes are clearly indicated as an ‘avoid’ for this blood type. ‘Hamburger’ is listed in the PLOS Study as ‘beneficial’ for type O, despite the fact that hamburgers are universally served on a wheat bun. Wheat is clearly listed as an ‘avoid’ for blood type O in ERFYT.

Many of the PLOS Appendix foods listed in Table 2 are these sorts of lumped categories, including ‘tropical fruits,’ ‘cooked breakfast cereal,’ ‘sandwiches,’ ‘mixed vegetables,’  ‘grains, other,’  ‘beans,’  etc. These generalizations have the effect of negating many of the BTD-specific food values, in particular the blood type specific lectin reactions. For example, the generalized category ‘beans’ are listed as ‘beneficial’ for blood type A in the PLOS Appendix, when in fact lima beans, in particular, contain a known hemagglutinating lectin specific for that blood type. [4]

In these circumstances, it appears that the PLOS authors chose to stick with the TMW food descriptions and shoe-horn the BTD values into the TMW. This yields a variety of questionable assertions, such as whether a category simplified into ‘beans’ can be given any sort of BTD value at all. In virtually all the instances of the ‘food-lumping’ seen in Table 2, when the TMW ‘food’ is actually split into BTD values the process yields erroneous conclusions. The PLOS Study does not provide any insight into the process used to determine the BTD rating for foods such as ‘mixed vegetables,’ ‘grains, other,’ etc. but the grading system appears quite arbitrary.

It is well-worth wondering how a study with such basic flaws in its design could have survived peer-review. I assume that the reviewers spent adequate time surveying the basic statistical functions used in the study, but I seriously wonder if any of the reviewers took the time to look  at just how closely the PLOS study modeled the BTD. It seems improbable that any of them spent time with a copy of  Eat Right For Your Type on their laps, cross-referencing its values with the PLOS Appendix. Yet this is perhaps the most basic question to ask of this study: Did it comprehensively model the BTD before reaching its conclusions? A look at the cross-comparision tabular data clearly indicates that it did not. Because of this very basic design flaw, all subsequent analysis and conclusions are moot; they derive from an improper, inaccurate, experimental model.

That the BTD theory is currently unproven by rigorous scientific study is not argued. In time this can be rectified by studies which accurately and comprehensively prove or disprove the hypothesis. Despite the rejoicing in certain circles [5] the Blood Type Diet/PLOS study by El-Sohemy, et al. is not that study. I call upon the editors of PLOS ONE to consider retracting this study unless they can justify the scientific basis of these concerns.

Click Here to Read the Full Article

  1. Jingzhou Wang,Bibiana García-Bailo,Daiva E. Nielsen, Ahmed El-Sohemy. ABO Genotype, ‘Blood-Type’ Diet and Cardiometabolic Risk Factors. PLOS ONE DOI: 10.1371/journal.pone.0084749
  2. Peter D’Adamo, Catheine Whitney. Eat Right For Your Type. Penguin-Putnam Publishers 1996
  3. Appendix S1 of the PLOS Study
  4. Sikder SK, Kabat EA, Roberts DD, Goldstein IJ. Immunochemical studies on the combining site of the blood group A-specific lima bean lectin.Carbohydr Res. 1986 Aug 15;151:247-60.
  5. NeuroLogica Blog: Blood Type Diet Disproved

There are 13 comments on this article so far

Jan 17 2014

Unbelievable Facts


A study purporting to ‘debunk’ the blood type diet theory has recently been published. [1,2] However, a closer look at the study’s experimental design raises serious questions about its conclusions, including whether in fact the participants were actually following the blood type diet at all, and given its other parameters, would it have even been possible for the study to have any other outcome.

In response, I’ve written about some of my concerns with the design of the study and consequently the strength of what conclusions can be drawn from it. I’ve also asked a few colleagues who are versed in research evaluation to read the article, look at the data, and weigh-in on the conclusions. Let’s take a look at some of the more serious flaws in the study:

1. None of the subjects actually followed the Blood Type Diet.

The study was done on 1,455 participants of the Toronto Nutrigenomics and Health study. The study’s subjects simply kept diet diaries and a ‘diet score’ was calculated to determine their adherence to the respective diet for their blood type. This is how the researchers calculated the subject’s adherence to the blood type diet:

“Based on the food items listed in the ‘Blood-Type’ diets, subjects received one positive point for consuming one serving of each recommended food item and one negative point for consuming one serving of an item on the list of foods to avoid. Foods that are listed as ‘Neutral’ were not included in the equation and do not contribute to the final score.”

From the start it should be obvious that this method is a gross simplification. For example, a type A subject eating 12 ounces of high-fat hamburger three times per week would have a ‘0’ rating if they garnished the hamburger with onions. Simply giving +1 and -1 values for following or not following the food choices will most likely result in the subject’s results simply marching backwards and forwards and often just canceling out.

Dr. Ryan Partovi: “My problem with this methodology is that two people —one who eats mostly neutrals and a few beneficials could end up with the same score as someone who eats heaps of avoids and then just covers them up with a slightly greater number of beneficials. That’s not the way I’ve found the BTD to work. You can’t offset avoids with beneficials.”

Dr. Natalie Colicci: “I’m fairly certain you do not recommend white bread and potato chips to any patients”.

Dr. Ryan Partovi: “I think one of the biggest issues that I see is one of food quality. The difference between a grass-fed, grass-finished beef steak and a corn-fed beef steak is as large as the difference between a corn-fed beef steak and a piece of salmon. The average reader/researcher is clueless to those distinctions as well as their impact on what they seem most interested in measuring (lipids, weight, and blood sugar regulation).

The researchers themselves point to the limitations of this model, admitting that “Since the scoring system in the present study only assessed relative adherence to each of the four ‘Blood-Type’ diets, we could not determine the absolute number of people who strictly followed any of the diets.” [1]

Dr. Joseph Veltman: “Whenever I see a researcher using a food frequency questionnaire to evaluate someone’s nutrition, the results and conclusions are meaningless. The American Dietetic Association has said as much too. Research subjects who use this instrument bias their intake on what they think the researchers want them to eat.”

The study misclassifies numerous foods or lumps them into impossible-to-categorize groups. For example, ‘Mac and Cheese’ is listed as neutral for types A, B and AB. However, ‘mac and cheese’ is almost universally made with processed American cheese, which is listed as an avoid for those types. ‘Other grains’ (whatever they are) is listed as neutral for types A, B and AB, which effectively removes the majority of lectin specificities.

Dr. Ryan Partovi: “Many of the food values they used are also flat out wrong. Generic hotdogs (almost always pork) beneficial for O’s? Fried potato chips neutral for B’s and AB’s? Fried corn chips neutral for A’s? Sandwiches beneficial for O’s?! Did they look at the typical ingredients of any of these foods?! Fish clumped up into fish cakes, Dark meat fish, Other fish, and assigned random values? You can’t conclude anything from this nonsense.”

If this wasn’t bad enough, the very design of the study resulted in almost the entire study population being high compliance with the AB diet. So in essence, this study is trying to find a relation between blood type and the blood type diet in a study population that is largely on the AB diet.

2. The study used healthy young adults.

The study was performed on young adults aged 20 to 29. Using a population comprised sole of heathy young adults is virtually guaranteed to produce very negligible differences between the blood types, especially since each of the blood type diets is fundamentally healthy whole-foods diet. A much more useful study would have looked at a more health-compromised population, for example individuals with digestive disorders. Most chronic illness is accompanied by changes in cell glycosylation and host micro-biome, and it is these changes that sharply define the differences in how each blood type might benefit from a specific diet.

Dr. Natalie Colicci: “These people are healthy and it would seem unlikely that you’d see much variation due to genetic differences in as short a time as one month.”

Dr. Todd LePine: “Is the Blood Type Diet the cure of all ailments? No, but food affects the immune system directly and indirectly via the interaction with lectins on the gut mucosa and how the food shifts bacterial populations which in turn affects host metabolism.”

3. The study was conducted over a very short period of time.

The study analyzed what the subject reported eating over a one-month period. Even under the best of conditions, this is a very short period of time to observe any difference as subtle as variation between individuals. Our observations have consistently shown that a minimum three-month period is required for even the earliest demonstrable differences to be discerned.

Dr. Natalie Colicci: “I don’t think 30 days is enough to cause a sustained improvement. I’ve always said that superficially the blood type diet is a whole foods diet. That can’t be argued with. So of course taking any one blood type and mismatching it to one of the diets would show improvement in 30 days to some extent just because you are ‘cleaning’ up someone’s diet, especially if their current diet was contributing to elevated cardio risk factors.”

Dr. Todd LePine: “Measuring a few ‘biomarkers’ in a month’s span that are associated with cardiovascular disease and which take years to develop is like observing just one mole on the skin not change in a month’s time and saying you can predict the probability of melanoma.”

4. The diets actually benefited many of the subjects.

Given even its very short length the study’s authors themselves admit that the diets produced positive effects: “However, the observed results showed that even relatively high adherence to Type-A, Type-AB and Type-O diets were associated with favorable levels of cardio-metabolic disease risk factors, albeit in an ABO-independent manner.” [1]

Dr. Ryan Partovi: “I did find it interesting that the Type O diet lowered triglycerides (much more of a problem for Type O’s anyway) much better than the Type A diet, which was better at lowering cholesterol (much more of a Type A problem anyway).”

5. The study’s scope was overly simplistic.

As previously discussed, nobody in the study actually followed the blood type diet. In addition, if the researchers were truly interested in whether there were differences between individuals of different blood types (in such a short time frame) were truly significant, they should have also included the subject’s secretor status in their workup, as I have repeatedly stressed in my subsequent writings. [3] Since ABO type was determined genomically, adding this additional data (and adjusting food values to include variations based on secretor status) would have minimally added to the cost and complexity of the study but might have produced observable differences in the short (30 day) time frame.

Dr. Todd LePine: What is the Blood Type Diet? As I’ve always understood it, it was based on both ABO status and secretor status. I don’t see that they measured secretor status in the paper.

Dr. Mitchell Stargrove: “On first pass it seems to have a narrow set of evaluation factors, and a shallow comprehension of what actually constitutes adherence; let alone missing out on deeper approaches such as secretor status.”

6. When you go looking for something (or not), you very often find it.

Dr. Todd LePine: “In the study the ‘drug’ was the food, for which they did not fully control.”

Dr. Ryan Partovi: “This is a retrospective study. When you know the data set ahead of time, it’s fairly easy to structure a study that ends up with the result that you’d like to find. Because there is no control group, and this is only a retrospective study based on general trends in a person’s eating, there’s no way to really say for certain that the people who were following a diet of avoids for their blood type weren’t doing much worse than the average. Put another way, this study looked at the wrong thing. I’d say that the fact that they didn’t involve you, the author of the blood type diet books, in the study design is evidence enough that they weren’t serious about figuring out what the diets can do for cardiovascular disease.”

7. Possible conflicts of interest.

According to the disclosed ‘competing interests’ section of the article, one of the study’s principle investigators, Ahmed El-Sohemy, holds shares in Nutrigenomix Inc., a genetic testing company for personalized nutrition. Nutrigenomix  markets a variety of nutrigenomic  test kits, genotyping and customized reports to  dietitians. [4] Although the article states that Dr. El-Sohemy holds shares in Nutrigenomix, in reality he is actually the founder of the company.  It should not be too difficult to imagine the possible benefits to invalidating the blood type diets under these circumstances.

8. Conclusions.

This study had the opportunity to shed new light on a complex topic in nutrigenomics.  However, its definition of what actually constitutes following the Blood Type Diet was  simplistic to the point of uselessness. In addition, the length of the study was too short  and the significance of its negative results over-extrapolated. Far from proving the ineffectiveness of the blood type diet, it simply demonstrates the previously known fact that,  in the short term, there  are a multitude of approaches to eating healthy –if you are an already healthy young person.

In addition, pejorative elements in the article’s syntax, such as the continued  use of the phase “Blood Type Diets” in quotation throughout the article;  the simultaneous  publication of a press release hailing the ‘debunking’ of the blood type diet, and the direct links between the principal investigator and other nutrigenomic business interests call into question, at least in my mind, if the study’s outcome was an already pre-ordained forgone conclusion.

Dr. Todd LePine: “From this study you can’t conclude anything, except that the Blood Type Diet was beneficial and not harmful in all cases. But in this limited time-frame, relatively unscientific study we don’t have the power or time-frame to conclude much of anything. The thousands of real patients, who have followed the diet for a myriad of aliments, especially those with inflammatory and autoimmune issues, benefit in the real world of do I feel better, think better and move more easily.”


  1. ABO Genotype, ‘Blood-Type’ Diet and Cardiometabolic Risk Factors
  2. ‘Popular blood type diet debunked’
  3. Metabolic and immunologic consequences of ABH secretor and Lewis subtype status.
  4. Nutrigenomix Scientific Advisory Board



There are 63 comments on this article so far

Sep 08 2013

Thoughts on the Immortality of the Crab

The deepest problem:
of the immortality of the crab,
is that a soul it has,
a little soul in fact …

That if the crab dies
entirely in its totality
with it we all die
for all of eternity

Miguel de Unamuno, ‘The Immortality of the Crab’


Pensar en la inmortalidad del cangrejo (‘Thinking about the immortality of the crab’) is a Spanish phrase used to excuse one’s daydreaming;  a humorous reference that one was not merely vegetating, but rather actively engaged in contemplation. A recent post on my Forum had me thinking about the immortality of a different crab. A visitor posted the following:

Why does Dr. D recommend chemo for cancer? Seems like a primitive approach, and not in line with the Hippocratic Oath.


First of all, the Hippocratic notion of ‘first do no harm’ (primum non nocere) is not an accurate interpretation. It is more accurately, ‘if at all possible, do no harm.’ i.e it is a heuristic, not an algorithm. If it were a law then draining a abscess or giving a B12 injection would be a violation.

I suspect this question came up because of a case I had written about in my book The GenoType Diet. It involved a man who was blood group A, FUT2 positive (secretor) and homozygous for blood group M (MM) that had a cancer known to have ‘A-like qualities’. Under these circumstances I have discovered that these individuals have a much more difficult time with things. There are a variety of reasons for this. This constellation of blood group genetics has a higher rate of multiple drug resistance (MDR). (1) There is evidence that the levels of p-glycoprotein (the carrier molecule that is part of the system) molecule that up to seven times more abundant in tissues of individuals who are blood group A, which may go along way towards explaining why it appears that type A’s with cancer who receive chemotherapy often do not have as beneficial an effect as the other blood types. Finally, blood group A appears to have lower circulating levels of anti-Tn (Thomsen-Freidenreich) antibodies. The Thomsen-Freidenreich (Tn) antigen (also known as is usually present on cell surfaces in a cryptic form covered by N-acetyl neuraminic acid moieties and released into circulation in many different cancers. (2) Thus it provides a means of cancer surveillance, and it is this function that is compromised in blood group A, probably because the Tn antigen shares some structural similarity with the group A antigen. The Tn antigen is currently under intense study as a possible site for a cancer vaccine. (3)

In this case, which is not all that uncommon, the patient had ‘shopped around’ until they found an oncologist who had recommended a very mild protocol. Upon consulting with me they were surprised that I had instead recommended that they seek the more aggressive alternative protocol.

Ocypode quadrata. Some crabs just look immeasurably perky.

Why did I recommend chemotherapy in this situation and why would I recommend chemotherapy at all? Because in many instances, without it, people die unnecessarily. Is that a ringing endorsement of modern oncology? No, there is much evidence that in many instances chemotherapy is not all that effective and merely degrades the patient’s quality of life. But what should we propose instead to tell a kid with a pediatric leukemia that is highly treatable: To juice raw liver and take coffee enemas instead?

I’m currently monitoring two brain cancer cases who are bucking the odds for long-term survival. In both cases they received convention treatment plus a tailored regimen from me. I doubt if they had received only one or the other that they would be alive today, though I am certain that some natural medicine gurus would have told them that this was all a big mistake. Trouble is, where are these guys when the patient comes back with the recurrence? I can tell you that they are no where in sight. That’s when they send in the assistant to tell you that ‘maybe it is time to do the chemotherapy.’

Here are some case histories from the front line of the naturopathic/conventional oncology interface:

Case History #1

Years ago I had a patient who had an early-stage testicular cancer. This cancer is 100% curable with chemotherapy. His wife, a massage therapist, was pushing that he go ‘completely natural.’   I politely explained that there were many, many options he could use to help control and optimize his results, but it would not be wise to forgo a treatment such as this, which was so reliably successful. They opted instead to do juice fasts and go elsewhere. Six months later they were back in my office, he riddled with metastasis, now taking that very same chemo to simply ‘debulk’ the cancer and help him survive a bit longer pain-free.

Case History #2

I treated a patient for a number of years who suffered from a rather uncommon combination of non-Hodgkin Lymphoma and Hodgkin Disease. It was though to be the result of Agent Orange exposure that occurred from the patient’s multiple tours of Vietnam while in the military. He received aggressive allopathic treatment from Sloan-Kettering, but was advised that the best one could hope for would be a rather short-lived reprise. We commenced some nutritional and botanical co-treatment, which none of the Sloan-Kettering physicians objected to. After two years disease-free it was clear that the patient had experienced an exceptional result. Frankly, although many people believe that conventional medicine has no interest in naturopathic type therapies, he was asked back to the hospital, and in his own words, ‘put in a large room filled with guys in white coats who wanted to know exactly what, how much and how long had I been taking these naturopathic things.’

Several years after that the patient, a life-long smoker, was diagnosed with bladder cancer. He was treated, with chemotherapy and with variable degrees of success by physicians at Johns Hopkins. The doctors here advised him that they would not treat him unless he stopped all naturopathic treatment, which he did. Eventually his bladder was removed and some metastatic spread was noted soon after that was thought to be from the non-Hodgkin Lymphoma He was placed on a series of Rituxan (Rituximab) injections and seemed to do well for a while. However, these eventually stopped working, the disease spread and at his final consult before being set up for hospice, when asked if there was anything left they could explore, was told that ‘maybe they should contact their naturopath and see if there was anything he could do.’

My take on things

A primitive approach, IMHO, is to base your decision on broad sweeping conclusions drawn from consumer reading material that limits your ability to decide what is the right thing to do then and there. Hopes, aesthetics and dreams are nice, but we must also deal with realities.

The goal of any good physician is simple: To get their patients from one side of the river over to the other. If it can be done exclusively with naturopathic modalities, so much the better. If in order to do that I need to combine modalities, well, that is part of the equation. If the only way that I would agree to ferry them across would be to require them to do only that which is acceptable to me I would not be much a ferryman, now would I?

A liability we physicians labor under is the delusion that our patients cannot get better without us and our methods. As soon as we let go of that we can participate in their improvement joyfully no matter from which direction it comes from.

  1. Weinstein RS, Kuszak JR, Jakate SM, Lebovitz MD, Kluskens LF, Coon JS.ABO blood type predicts the cytolocalization of anti-P-glycoprotein monoclonal antibody reactivity in human colon and ureter.Hum Pathol. 1990 Sep;21(9):949-58.

  2. Uhlenbruck G. The Thomsen-Friedenreich (TF) receptor: an old history with new mystery. Immunol Commun. 1981;10(3):251-64.
  3. Heimburg-Molinaro J, Lum M, Vijay G, Jain M, Almogren A, Rittenhouse-Olson K.Cancer vaccines and carbohydrate epitopes.Vaccine. 2011 Oct 1.

There are 2 comments on this article so far

Jun 03 2013

Gnomic Advice

I object, your honor! This trial is a travesty. It’s a travesty of a mockery of a sham of a mockery of a travesty of two mockeries of a sham.

— Fielding Melish

Blood Type Diets Don’t Work,” “No Science Behind Blood Type Diets,” scream headlines on mass media sites like Reuters and NewsMax, who report the results of a study published in the latest edition of the American Journal of Clinical Nutrition (AJCN).

Now, you might think that a scientific article that could generate that type of headline actually went ahead and did what is normally done to subject a theory to scientific scrutiny: Test the theory clinically, preferably by some sort of randomized, controlled trial on a significant number of test subjects. In fact the AJCN researchers did nothing of the sort. They simply went into PubMed (the medical online database) and searched for any prior studies that have been published on the blood type diets.

Not surprisingly, they didn’t find any. Had they contacted me prior to the study I could have saved them a lot of extra work. I’ve looked high and low and also never found one. That’s how original this theory is.

Since I became interested in the ABO blood groups three decades ago I’ve collected, archived and categorized virtually every scientific article on blood types (excluding the large number of articles that dealt solely with transfusion) going way back to the early twentieth century. I also own many articles in languages other than English, some of which I have paid to have translated. Finally, my collection includes a large number of articles written in the years 1940-1966, long before the time when medical articles became electronically indexed. And I fully concur with the researchers, that there is indeed not one article of value in all that time that ever linked anything regarding a person’s blood type with nutrition. It is no great news to hear that there is a lack of published studies on following a diet based on one’s blood type: I’ve proselytized for just these types of studies for over two decades. All the authors did was conclude, as did I many years ago, that there is a lack of direct research on the subject.

But here is where the dishonesty begins.

There is a big difference between an absence of evidence and evidence of absence. There is good science behind the blood type diets, just like there was good science behind Einstein’s mathmatical calculations that led to the Theory of Relativity. However Einstein’s theory required very specific and particular conditions to occur (solar eclipses at a certain time in a certain part of the world) before it could be subjected to testing and confirmation.

Just like Einstein’s math, the theoretical and empirical evidence behind the blood type diets is pretty good. Spend some time reading my books or this blog and you will understand. ABO blood type is a significant influence on the digestive tract, from stomach acid levels to intestinal enzymes to the particular strains of bacteria that grow inside of us. Much of the immunologic reactivity of many foods varies by blood type.

The connection between blood types and food lectins was universally maligned, except by some very accomplished lectin scientists, who obviously knew better. Especially vicious were the ‘paleolithic diet experts,’ who then conveniently rediscovered the lectin connection when it became evident that it could be used to justify their grain-phobic worldview. Virtually every skeptic I’ve ever discussed the theory with was completely ignorant of these facts, despite the notion that virtually all of the original studies (minus the pre-1966 stuff) can be perused on PubMed.

The biggest garden gnome in the world, in Nowa Sól, Poland  (Wikipedia)

The biggest garden gnome in the world, in Nowa Sól, Poland (Wikipedia)

The delightful fantasy that everything in modern medicine has a strong evidence basis is just that–a delightful fantasy. For example, many medical agents are often employed ‘off-label’ for uses other than those originally intended as a result of their original study –even if they lack the high degree of scientific scrutiny are routinely reserved for pharmaceuticals. [1] Most herbal medicines, many used successfully since antiquity and the basis for many modern drugs, also have a weak evidence basis in modern science. About 30% of drugs prescribed to children have never actually been tested on children. We continually live and work in a world of knowledge insecurity, typically for the very same reasons you don’t see any studies on blood types and nutrition: Little institutional interest and even less available money.

Long-term diet studies are renowned for their difficulties. Subjects would have to follow a prescribed diet for a significant period of time, perhaps as long as one year, as many of these differences would be rather slight in the short term. Other subjects would have to follow a control or ‘sham’ diet. Both groups would have to include a reasonable number of subjects, and since we are talking about comparing outcomes between the four basic blood groups, we’d have to take this total number of subjects and then quadruple it. Subjects would have to be paid, constantly monitored, and their food prepared and supplied to them. Since we are studying a complete food plan, versus a single food or even a single drug, the cost of doing an ongoing study of this sort would be enormous.

So what is empirically self-evident when employed on a day-in, day-out basis, (“Hey Doc, three weeks on the diet and my psoriasis is clearing up!”) becomes an uncontrollable, insupportable, unsustainable mess when subjected to what is normally the scientific gold standard; a paradigm much better suited for a clean, get-in, get-out, trial of a single agent or intervention, like a drug or a specific medical procedure.

We’ve done some very simple polling (for which I make no special claims to be scientific) that show that, in a rather large number of internet responders, the level of satisfaction following one of the four blood type specific diets runs consistently at about 85% across all four blood types. What made this observation interesting is not the degree of satisfaction, since that is subject to bias, but rather the constancy of that number across the four different blood type groups, especially since they are all following diametrically differing diets to a certain degree.

So, are the headlines truthful? Do the diets not work? Is there no science behind them?


A sure sign that things are turning jaundiced occurs when the registered dietician gets wheeled out for the requisite Parthian Shot. As is expected, the preferred slur here is ‘fad diet’ which is a truely ludicrous accusation since the main book about the blood type diets, Eat Right for Your Type has been in mass publication for almost two decades. A two-decade old fad. One can only wonder just how long something has to be around before it is no longer a fad. Now, with all due respect, your average dietician is simply in no position to comment on the technical basis of how blood groups influence digestive physiology. Sorry, but it’s advanced, high level glycomics/glycobiology stuff and they just don’t do that in these types of programs.

On the up-side, each of the specific diets recommended for each of the blood types is, in itself, a pretty healthy diet. Indeed, somewhere in the nutrition literature, someone is claiming that the scientific evidence supports the use of such a one-size-fits-all diet in everyone. Perhaps the only reasonable claim is that the blood type diets can help predict which healthy diet, among the many out there, is particularly healthy for you.

Should this type of study be performed? Absolutely. But unfortunately, every once in a while there comes along a theory that must remain, at least for the foreseeable future, as a simple thought experiment; a heuristic; a useful rule-of-thumb for those willing to try it. Sort of like chicken soup for a head cold.

Does this lack of ‘evidence’ bother me? Not really. In fact, I’ve moved on from my obsession with the ABO blood groups years ago, although I still keep an eye on new developments.

“Science.” so the quote goes. “If you’re not pissing people off, you’re doing it wrong.”

So I guess the Blood Type Diet is scientific after all.

gnomic, gnomical
1. (Literary & Literary Critical Terms) consisting of, containing, or relating to gnomes or aphorisms
2. (Literary & Literary Critical Terms) of or relating to a writer of such sayings

  1. Walton SM, Schumock GT, Lee KV et al., “Prioritizing future research on off-label prescribing: results of a quantitative evaluation,” Pharmacotherapy 2008; 28(12):1443-52.

There are 9 comments on this article so far

May 07 2013

The Watussi and the History Erasure Button

The Watussi (or Watusi) was a popular dance craze in the early 1960’s, in addition being the historical name for the Tutsi ethnic group in East Africa. ‘Watussi’ was also the lead track on the seminal offering (Musik von Harmonia) by those legends of Krautrock Michael Rother, Hans-Joachim Roedelius and Dieter Möbius (Harmonia). As I often name the software program that I am currently developing after the music that I’m listening to at the time, my latest creation in Datapunk now carries this esteemed moniker.

Since most of Datapunk is involved in displaying gene-protein signaling data as a molecular graph network, while linking and then displaying data about natural products known to influence action and expression, it was about time that I turn the telescope around and allow investigators to poll the networks instead by choice of natural product.

 1. The Watussi main screen, showing scrollable window and History Erasure Button.

[1] The Watussi main screen, showing scrollable window and History Erasure Button.

From the main menu you simply tick off the natural products that you are interested in. [Figure 1]

[2. Results screen showing nodes associated with the 'Apigenin,'  a natural product belonging to the flavone class that is the aglycone of several naturally occurring glycosides

[2] Results screen showing nodes associated with the ‘Apigenin,’ a natural product belonging to the flavone class that is the aglycone of several naturally occurring glycosides

And Watussi will display the Quodlibet molecular maps that contain nodes that reference the agent. [Figure 2]

 3. Quodlibet map 'Polyamine synthesis and recycling' showing highlighted node 'ODC' (orinthine decarboxylase) associated with natural product 'Apigenin'.

[3] Quodlibet map ‘Polyamine synthesis and recycling’ showing highlighted node ‘ODC’ (orinthine decarboxylase) associated with natural product ‘Apigenin’.

Click on the network link and the specific node will be highlighted [Figure 3]. From there you can click on the actual node to retrieve the specific citations.


Unfortunately, Watussi is a bandwidth hog (going even two or three levels out in a network of a few hundred nodes is a combinatoric nightmare) and my hosting service has already once had to shut the server down because of resource usage. However it runs just fine with small numbers of users, so if you are interested in using Watussi for research purposes, leave a comment here with a contact email and I’ll see about setting you up.

The History Erasure Button

People who don’t take risks generally make about two big mistakes a year. People who do take risks generally make about two big mistakes a year.

–Peter Drucker

The Watussi interface features a large red button in the upper right area labeled with the words ‘Don’t Press This Button.’ I was interested in the percentage of visitors who would actually press the button.

History Erasure Button.

Turns out about one in two people actually press the button, which simply darkens the screen and plays this video:

According to Wikipedia:

When doing the Watusi, the dancer is almost stationary with knees slightly bent, although may move forward and back by one or two small rhythmic paces. The arms, with palms flat in line, are held almost straight, alternately flail up and down in the vertical. The head is kept in line with the upper torso but may bob slightly to accentuate the arm flailing. The dance, which became popular in the American surf/beach sub-culture of 1960s, may be enhanced if one imagines that one’s feet are on sand.

I vaguely remember the dance, along with the ‘Monkey’ and the ‘Frug’ although none of the ND students on any of my teaching shifts had ever heard of it. To me it seemed that most people seemed to do a combination of all three.

There is 1 comment on this article so far

Mar 28 2013

Remembering the Memorable

One of the features of any network is the appearance of motifs, patterns that recur within a network much more often than expected via any sort of random occurence. The first four notes of Beethoven’s Fifth Symphony are an example of a motif: This opening phrase is one of the most widely recognized in music. It has mystified musicians, historians and philosophers for 200 years. Music critic Matthew Guerrieri says it’s “short enough to remember and portentous enough to be memorable.”

These small circuits can be considered as simple building blocks from which the network is composed. This analogy is quite useful, since many of these motifs would appear to have their corollaries in electronic circuitry. Motifs appear to play an important role in transcription factor regulation, providing the simple computational elements that function as integrated wholes to produce complex algorithmic outcomes.

Like the digital circuitry in your computer, clusters of network motifs are capable of computational processes. Think about this: Humans share about 98% of their genome (at least the sequences) with apes. This of course begs the question ‘why are we not more similar?’ The answer is that while we share much of the base sequences, there are tremendous differences in the computational knowledge that acts upon these sequences, in particular the networks involved in transcription factor regulation: operons, regulons and modulons. It is the combinatoric wisdom that seems to differentiate between the classes of life forms. This is especially true with regard to gene regulatory elements, which lie within the 98% of the DNA that does not contain gene coding. Gene regulatory elements instruct genes as to when, where and at what levels to turn on or off. [1]

One of the most common and interesting motifs found in biological systems is known as a feed-forward loop. This motif is commonly found in many gene systems and organisms. The motif consists of three genes and three regulatory interactions. The target gene Z is regulated by 2 transcription factors X and Y and in addition TF Y is also regulated by transcription factor X. The target gene is usually operated on in a logical AND manner, in that it requires both inputs to be logically true (both X and Y are required for Z activation) in order to activate. Since each of the regulatory interactions may either be stimulatory or inhibitive there are possibly eight types of FFL motifs.

Feed-forward loops are classified as coherent or incoherent. A coherent feed-forward loop is distinguished by the fact that the final actions of transcription factors X and Y are symmetrical; i.e. they result in the same type of stimulus (stimulation-stimulation or inhibition-inhibition) at their termination, Z. Incoherent feed-forward loops result in differing signals (stimulus-inhibition) at their termination.


The coherent type 1 feed-forward loop (C1-FFL) with an AND gate was shown to have a function of a ‘sign-sensitive delay’ element and a persistence detector both theoretically and experimentally with the arabinose system of E. coli. [2] This means that this motif can provide pulse filtration in which short pulses of signal will not generate a response but persistent signals will generate a response after short delay. The shut off of the output when a persistent pulse is ended will be fast.

The incoherent type 1 feed-forward loop (I1-FFL) is a pulse generator and response accelerator. The two signal pathways of the I1-FFL act in opposite directions where one pathway activates Z and the other represses it. When the repression is complete this leads to a pulse-like dynamics. I1-FFL is a pulse generator and response accelerator. [3] In some cases the same regulators X and Y regulate several Z genes of the same system. This is known as a multi-output feed-forward loop. By adjusting the strength of the interactions this motif was shown to determine the temporal order of gene activation. [4]

Other common motifs include auto-regulation, single input modules and dense overlapping regulons (DOR). Negative auto-regulation (NAR) occurs when a transcription factor represses its own transcription. This motif was shown to perform two important functions. The first function is response acceleration. NAR was shown to speed-up the response to signals both theoretically and experimentally. The second function is increased stability of the auto-regulated gene product concentration against stochastic noise, thus reducing variations in protein levels between different cells. [5] Positive auto-regulation (PAR) occurs when a transcription factor enhances its own rate of production. Opposite to the NAR motif this motif slows the response time compared to simple regulation. In the case of a strong PAR the motif may lead to a bimodal distribution of protein levels in cell populations. [6] The single input module (SIM) motif occurs when a single regulator regulates a set of genes with no additional regulation. This is useful when the genes are cooperatively carrying out a specific function and therefore always need to be activated in a synchronized manner. In the dense overlapping regulon motif, many inputs regulate many outputs. This motif occurs in the case that several regulators combinatorially control a set of genes with diverse regulatory combinations. This motif was found in E. coli in various systems such as carbon utilization, anaerobic growth, stress response and others. [4]

Coding for motif detection in Datapunk QUODLIBET was quit challenging. Although there are many helpful modules in the CPAN archives, there exists no simple module for FFL motif detection in network graphs. However, with experimentation I was able to work out a simple algorithm. Any metabolic map can display FFLs (if there are any in them) by clicking the FFL icon in the floating tool bar (indicated by red arrow).


Here we see a Type 2 Coherent FFL motif in the Datapunk Adipocytokine map. Suppressor of cytokine signaling (SOCS) proteins are key regulators of immune responses and exert their effects in a classic negative-feedback loop. SOCS3 is transiently expressed by multiple cell lineages within the immune system and functions predominantly as a negative regulator of the leptin receptor and downstream cytokines that activate Janus Kinase 2.

To me, looking for basic circuitry motifs in metabolic maps (and understanding their function and significance) is equivalent to a composer who hears an entire symphonic arrangement in his head while reading a musical score, while the rest of us mere mortals just see black dots on white paper.


1. Davidson E. The Regulatory Genome. Academic Press. (2006)
2. Mangan S, Zaslaver A, Alon U. The coherent feedforward loop serves as a sign-sensitive delay element in transcription networks.J Mol Biol. 2003 Nov 21;334(2):197-204
3. Mangan S, Itzkovitz S, Zaslaver A, Alon U.The incoherent feed-forward loop accelerates the response-time of the gal system of Escherichia coli. J Mol Biol. 2006 Mar 10;356(5):1073-81. Epub 2005 Dec 19.
4. Alon U. An Introduction to Systems Biology: Design Principles of Biological Circuits. Chapman and Hall/ CRC. New York, NY (2007)
5. Rosenfeld N, Elowitz MB, Alon U. Negative autoregulation speeds the response times of transcription networks. J. Mol. Biol. 323 (5): 785–93. (November 2002)
6. Maeda YT, Sano M. Regulatory dynamics of synthetic gene networks with positive feedback. J. Mol. Biol. 359 (4): 1107–24. (June 2006)

No comments on this article yet

Older Entries »