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Specified Life

Devoted to the topic of data specification (including data organization, data description, data retrieval and data sharing) in the life sciences and in medicine.

Updated: 2018-03-17T05:38:06.327-07:00


Inscrutable Genes


"In most cases, the molecular consequences of disease, or trait-associated variants for human physiology, are not understood." from: Manolio TA, Collins FS, Cox NJ, Goldstein DB, Hindorff LA, Hunter DJ, et al. Finding the missing heritability of complex diseases. Nature 2009;461:747–53. The 1960s was a wonderful decade for the field of molecular genetics. Hundreds of inherited metabolic diseases were being studied. Most of these diseases could be characterized by a simple inherited mutation in a disease-causing gene. Back then, we thought we understood genetic diseases. Here’s how it all might have worked, if life were simple: one mutation! one gene ! one protein ! one disease. This lovely genetic parable, from a bygone generation, seldom applies in the era of Precision Medicine. The purpose of this section is to explain some of the complexities of modern genetics and to lay out the job of the Precision Medicine scientist who must dissect the pathways that lead from gene to disease. In Precision Medicine and the Reinvention of Human Disease, two of the most confuding aspects of modern disease genetics are discussed: that a single disease may result from one of many distinct molecular defects; and that a single gene may produce many different diseases. These two countervailing phenomena tell us something very important about disease development. The first is that different pathways may converge to the same disease, and that any single gene may perturb a biological system (i.e., a living organism) in different ways. Some of that discussion is excerpted here. There are numerous examples wherein mutations in one gene may result in more than one disease [2]. In some cases, each of the diseases caused by the altered gene is fundamentally similar (e.g., spherocytosis and elliptocytosis, caused by mutations in the alpha-spectrin gene; Usher syndrome type IIIA and retinitis pigmentosa-61 caused by mutations in the CLRN1 gene). In other case, diseases caused by the same gene may have no obvious relation to one another. For example, the APOE gene encodes apolipoprotein E, which is involved in the synthesis of lipoproteins. One common allele of the APOE locus, e4, increases the risk of Alzheimer disease and of heart disease, two disorders of no obvious clinical similarities [3,4]. Let’s look at a few other examples where mutations in a single gene play causal roles in the development of diverse diseases. For example, different mutations of the same gene, desmoplakin, cause the following diseases [2]: Arrhythmogenic right ventricular dysplasia 8 Dilated cardiomyopathy with woolly hair and keratoderma Lethal acantholytic epidermolysis bullosa Keratosis palmoplantaris striata II Skin fragility-woolly hair syndrome How is it possible that errors in the gene coding for desmoplakin, a constituent protein found in intercellular junctions, could account for such apparently unrelated diseases as arrhythmogenic right ventricular dysplasia and lethal acantholytic epidermolysis bullosa? It happens that we know that specialized desmosomes in cardiac cells (i.e., intercalated discs) tightly couple myocytes so that they can function as a coordinated group. Desmosomes are also required to adhese skin epidermal cells to one another and to the underlying basement membrane. In the case of desmoplakin mutations, it is relatively easy to see the pathogenetic relationship among these diseases. In other sets of diseases that result from an error in one specific gene, the pathogenetic relationship may not be so easily discerned. Some cases of Charcot-Marie-Tooth axonal neuropathy, lipodystrophy, Emery-Dreyfus muscular dystrophy, and premature aging syndromes are all caused by mutation in the LMNA (Lamin A/C) gene. Stickler syndrome type III, Fibrochondrogenesis-2, and a form of nonsyndromic hearing loss are all caused by mutations in the COL11A2 gene. In these cases, how can variations in a single gene cause many different diseases? Let’s look at just a few of the possibilities: One gene can control the synthesis of more t[...]

Infections Develop Via a Sequence of Biological Steps


A prior post listed 7 assertions regarding the role of infectious organisms on the human genome. In the next few blogs we'll look at each assertion, in excerpts from Precision Medicine and the Reinvention of Human Disease. Here's the seventh: By dissecting the biological steps involved in the pathogenesis of infectious disease, it is possible to develop new treatments, other than antibiotics, that will be effective against a range of related organisms. Nature, by interfering with the different steps in the development of infectious diseases, has a variety of protective mechanisms against organisms. For example, to defend against malaria, nature has preserved various mutations that render red cells unsuitable hosts for malarial guests. For example, individuals with hemoglobin variants HbS (sickle cell trait), HbC, and HbE increase the likelihood that an infected red cell will lyse. Likewise, but for obscure reasons, regulatory defects in hemoglobin synthesis, as seen in thalassemia, may also confer some protection against malaria. Also, variations in a structural protein of erythrocytes, SLC4A1, causing ovalocytosis; and polymorphisms of the glucose-6-phosphate dehydrogenase gene [57] both seem to protect against malaria. We see individuals resistant to malaria due to absence of the Duffy protein required for Plasmodium vivax to bind and enter erythrocytes [58]. Knowing this, the Duffy-binding protein in the malaria parasite is now being studied as a potential drug or vaccine target as a new strategy against malaria [58]. More generally, drugs known as entry inhibitors are being developed based on knowledge that the attachment and entry of organisms may depend upon specific cooperative pathways, in host and invader cells, that can be targeted by drugs. We know that there are many steps in the infection process that could be blocked by small changes in proteins that are unrelated to the immune process. For example, for an infectious agent to invade and flourish in an organism, it must gain entry into the tissues of the body, evading physical and chemical defenses along its way. It must find a place in which it can receive nourishment appropriate to its species and avoid any toxins that may be produced by its host. It must be able to grow as a collection of organisms, and this typically means that the host must permit some degree of invasion through its own tissues. These are just a few of the nonimmunological hurdles that invasive organisms must jump over, if they are to infect an organism. Every step in the pathogenesis of infectious disease provides another therapeutic opportunity. As we learn more about the pathways of development of infectious diseases that have become increasingly resistant to antibiotics, we will come to rely on Precision Medicine to prevent, diagnose, and treat infections. - Jules Berman key words: precision medicine, infections disease, biological steps, pathogenesis, jules j berman Ph.D., M.D. [...]

Non-immunologic Causes of Increased Susceptibility to Disease


A prior post listed 7 assertions regarding the role of infectious organisms on the human genome. In the next few blogs we'll look at each assertion, in excerpts from Precision Medicine and the Reinvention of Human Disease. Here's the sixth:

Cellular defects that have no direct connection to immunity may increase susceptibility to infectious organisms.

If we want to understand why certain individuals are susceptible to infections and other individuals are not, we must understand that immune deficiencies cannot account for all infections. Infectious diseases, just like any other disease, develop in steps, and it stands to reason that there must be many different pathways through which those steps can be enhanced or blocked. Theory aside, what is the actual evidence that susceptibility to infectious diseases arise through deficiencies unrelated to the immune system?

  • Time and again, we encounter serious infections from organisms thought to be nonpathogenic, occurring in immunocompetent individuals [48–51].

  • Not everyone with an immune deficit will succumb to an infectious disease, implying that these individuals are protected by resistance mechanisms other than immunity.

  • We know of various genetic conditions that increase our susceptibility to infectious diseases, and some of these genetic flaws have nothing to do with the adaptive (i.e., antibody-forming) immune systems. For example, children with sickle cell disease or congenital asplenia will have a heightened susceptibility to invasive pneumococcal diseases [52]. Otherwise-normal children with IRAK4 or NEMO gene mutations will also have a high risk of invasive pneumococcal disease [52]. IRAK4 or NEMO genes code for proteins involved in the phagocytosis of bacteria by splenic macrophages. Likewise, in mice, natural resistance to infection is influenced by the Bcg gene, which affects the early phagocytosis and destruction of intracellular organisms by macrophages [53]. As a final example, both humans and zebrafish that have mutations that reduce the synthesis of a proinflammatory leukotriene have heightened susceptibility to Mycobacterium tuberculosis [54]. It is easy to find examples of nonimmunologic mechanisms for susceptibility to infections [55,56].

- Jules Berman

key words: precision medicine, immune system, susceptibility to disease, non-immunologic, jules j berman Ph.D., M.D.

Infection without Disease (from Precision Medicine and the Reinvention of Human Disease)


A prior post listed 7 assertions regarding the role of infectious organisms on the human genome. In the next few blogs we'll look at each assertion, in excerpts from Precision Medicine and the Reinvention of Human Disease. Here's the fifth: Normal defenses can block every infectious disease. Hence, every infectious disease results from a failure of our normal defenses, immunologic and otherwise. For any given infectious agent, no matter how virulent they may seem, there are always individuals who can resist infection. Moreover, as a generalization, the majority of individuals who are infected with a pathogenic microorganism will never develop any clinically significant disease [42]. As one example, Naegleria fowleri is often found in warm freshwater. Swimmers in contaminated waters may develop an infection that spreads from the nasal sinuses to the central nervous system, to produce an encephalitis that is fatal in 97% of cases [43]. Despite the hazard posed by Naegleria, health authorities do not generally test freshwater sources to determine the presence of the organism. Do not expect to find warning signs posted at swimming holes announcing that the water is contaminated by an organism that produces a disease that has a nearly 100% fatality rate. It is simply assumed that anyone who spends any time around freshwater will eventually be exposed to Naegleria. As it happens, although many thousands of individuals are exposed each year to Naegleria in the United States, only a few cases of Naegleria encephalitis occur in this country. In fact, since Naegleria was recognized as a cause of encephalitis, in 1965, fewer than 150 cases have been reported [44]. Most of the reported cases have occurred in children and adolescents and are associated with recreational water activities [45,46]. The children who develop Naeglerian encephalitis, though exhibiting no signs of immune deficiency, are nonetheless susceptible to Naegleria. What makes these children different from all the other children and adults who were exposed to the same organisms? Neisseria meningitidis, a cause of bacterial meningitis, can be cultured from nasal swabs sampled from the general population. If N. meningitidis were a primary pathogen, then why doesn’t it cause disease in the vast majority of infected individuals. If N. meningitidis were an opportunistic infection, then why does it typically cause disease in healthy college-age individuals (not immunocompromised individuals)? If this organism is neither a primary pathogen nor an opportunistic pathogen, then what kind of pathogen is it? More importantly, why is N. meningitidis a potentially fatal pathogen in some individuals and a harmless commensal in others [47]? Organisms that were formerly thought to be purely pathogenic are now known to frequently live quietly within infected humans, without causing symptoms of disease. For example, parasites such as the agents that cause Chagas disease, leishmaniases, and toxoplasmosis are commonly found living in apparently normal individuals. Viruses, including the agents that cause herpes simplex infections and infections by hepatitis viruses B and C, can be found in healthy individuals. Mycobacterium tuberculosis can infect an individual, produce a limited pathologic reaction in the lung, and remain in the body in a quiescent state for the life of the individual. In fact, it has been estimated that about one out of three individuals, worldwide, is infected with Mycobacterium tuberculosis, and will never suffer any consequences. Luckily, asymptomatic carriers of tuberculosis, in whom the there is no active pulmonary disease, are noninfective. Staphylococcus aureus, a bacterial pathogen that is known to produce abscesses, invade through tissues, and release toxins, is also known to circulate in the blood, without causing symptoms, in a sizeable portion of the human population [40]. We now know that potentially virulent organisms are normally tamed within our bodies. He[...]

Cellwise, We Are Mostly Inhuman


A prior post listed 7 assertions regarding the role of infectious organisms on the human genome. In the next few blogs we'll look at each assertion, in excerpts from Precision Medicine and the Reinvention of Human Disease. Here's the fourth:

Most of the cells residing in human bodies are nonhuman

There are about 10 times as many nonhuman cells living in our bodies as there are human cells [40]. The human intestines alone contain 40,000 different species of bacteria [9]. These 40,000 species contain about 9 million different genes. Compare that with the paltry 23,000 genes in the human genome, and we quickly see that we homo sapiens contribute very little to the genetic diversity of the human body’s ecosystem.

- Jules Berman

key words: precision medicine, commensals, symbiotes, symbiotic, host organisms, jules j berman Ph.D. M.D.

Genome-Specific Responses to Infection


A prior post listed 7 assertions regarding the role of infectious organisms on the human genome. In the next few blogs we'll look at each assertion, in excerpts from Precision Medicine and the Reinvention of Human Disease. Here's the third:

A good portion of the genes in humans (perhaps 10%) are involved in responses to infectious organisms.

It has been estimated that over 1000 human genes are involved in inflammation pathways [37]. Several studies have shown that following an inflammatory challenge or challenged by the introduction of a pathogen, more than a hundred genes are activated [38–40]. The activated genes include some of the same genes that have been associated with autoimmune diseases, suggesting that these disease-associated genes are conserved because they have a beneficial role, protecting us from invading pathogens [39]. The genetic profile of genes activated by inflammation is very similar from human to human, but quite dissimilar from the profile of genes activated by inflammation in the mouse [41]. This would suggest that species develop their own genome-wide responses to agents that cause inflammation (e.g., invading organisms).

- Jules Berman

key words: precision medicine, evolution, virus, viral, jules j berman Ph.D. M.D.

Vertebrate Evolution Driven by DNA from Infectious Organisms


A prior post listed 7 assertions regarding the role of infectious organisms on the human genome. In the next few blogs we'll look at each assertion, in excerpts from Precision Medicine and the Reinvention of Human Disease. Here's the second: Some of the key steps in the development of vertebrate animals, and mammals in particular, have come from DNA acquired from infectious organisms. The human genome has preserved its viral ballast, at some cost. At every cell division, energy is expended to replicate the genome, and the larger the genome, the more energy must be expended. Why do we spend a large portion of the energy required to replicate our genome, on inactive sequences, of viral origin? Why doesn’t our genome simply eject the extra DNA, a biological process that is commonplace in the evolution of obligate intracellular parasitic organisms? Maybe it's because we use viral genes to our own advantage. Two evolutionary leaps, benefiting the ancestral classes of humans, and owed to the acquisition of viral genes, include the attainment of adaptive immunity and the development of the mammalian placenta. Let’s take a moment to see how these innovations came about. Adaptive immunity evolved at about the same time that jawed vertebrates first appeared on earth. The crucial gene responsible for the great leap to adaptive immunity, the recombination activating gene (RAG), was stolen from a retrovirus. To understand the pivotal evolutionary role of RAG, we need to review a bit of high school biology. The adaptive immune system responds to the specific chemical properties of foreign antigens, such as those that appear on viruses and other infectious agents. Adaptive immunity is a system wherein somatic T cells and B cells are produced, each with a unique and characteristic immunoglobulin (in the case of B cells) or T-cell receptor (in the case of T cells). Through a complex presentation and selection system, a foreign antigen elicits the replication of a B cell whose unique immunoglobulin molecule (i.e., so-called antibodies) matches the antigen. Secretion of matching antibodies leads to the production of antigen-antibody complexes that may deactivate and clear circulating antibodies, or may lead to the destruction of the organism that carries the antigen (e.g., virus or bacteria). To produce the many unique B and T cells, each with a uniquely rearranged segment of DNA that encodes specific immunoglobulins or T-cell receptors, recombination and hypermutation must take place within a specific gene region. This process yields on the order of a billion unique somatic genes, and requires the participation of recombination activating genes (RAGs). The acquisition of a recombination activating gene is presumed to be the key evolutionary event that led to the development of the adaptive immune system present in all jawed vertebrates (gnathostomes). Before the appearance of the jawed vertebrates, this sort of recombination was genetically unavailable to animals. Our genes simply were not equal to the task. Retroviruses, however, are specialists at cutting, moving, and mutating DNA. Is it any wonder that the startling evolutionary leap to adaptive immunity was acquired from retrotransposons? Thus,we owe our most important defense against infections to genetic material retrieved from the vast trove of retrovirally derived DNA carried in our genome [33]. As one might expect, inherited mutations in RAG genes are the root causes of several immune deficiency syndromes [34,35]. Many millions of years later, vertebrates acquired another gene that did much to enable the evolution of all mammals. Members of Class Mammalia are distinguished by the development of the placenta, an organ that grows within the uterine cavity (i.e., the endometrium). After birth, the placenta must detach from the uterus. You can imagine the delicate balancing act between attaching firmly to t[...]



Yesterday's post listed 7 assertions regarding the role of infectious organisms on the human genome. In the next few blogs we'll look at each assertion, in excerpts from Precision Medicine and the Reinvention of Human Disease. Here's the first:

The majority of the human genome consists of relic DNA derived from ancient invasive organisms.

Nearly half of the human genome is filled with sequences such as LINE and Alu, and DNA transposons, all derived from ancient retroviruses [21]. About 8% of our genome is derived from longer sequences with similarity to known infectious retroviruses, and these longer sequences can usually be recognized by their contained subsequences (e.g., gag, pol, and env genes) and long terminal repeats. The viral sequences in our genomes are the remnants of ancient retroviral infections, and the occasional nonretroviral infection, that were branded into DNA, and subsequently amplified [21–23]. Because much of the endogenous retroviral load in the human genome is due to amplification, and subsequent mutation, it is hard to determine the number of retroviral species that established their niche in the human gene pool, but studies of these viral remains would suggest that we contain species from several dozen families of retroviruses, with an undetermined number of contributions from individual family members [24]. Based on comparisons of the viruses present in different species of primates, it would appear that the most recent acquisition of an endogenous retrovirus occurred in humans between 100,000 and 1 million years ago [25]. Most of the retroviral sequences in our genomes are inactivated due to an accumulation of degenerative mutations collected over the eons, indicating that there has been little or no selective pressure to conserve retroviruses in their pristine sequences.

- Jules Berman

key words: precision medicine, human genome, evolution, infectious diseases, jules j berman, Ph.D., M.D.

Infections have made their mark on the Human Genome


In the context of Precision Medicine, infections draw our attention because they have played an important role in the evolution of the eukaryotic genome. Over the next few blog posts, we will explore the following:

  • The majority of the human genome consists of relic DNA derived from ancient invasive organisms.
  • Some of the key steps in the development of vertebrate animals, and mammals in particular, have come from DNA acquired from infectious organisms.
  • A good portion of the genes in humans (perhaps 10%) are involved in responses to infectious organisms.
  • Most of the cells in the human (at least 90%) consist of infectious organisms and commensals that have adapted to life within human hosts. [Glossary Commensal]
  • Normal defenses can block every infectious disease. Hence, every infectious disease results from a failure of our normal defenses, immunologic and otherwise.
  • Cellular defects that have no direct connection to immunity may increase susceptibility to infectious organisms.
  • By dissecting the biological steps involved in the pathogenesis of infectious disease, it is possible to develop new treatments, other than antibiotics, that will be effective against a range of related organisms.
Over the next few blogs, we'll do our best to justify each of these (as yet) unproven assertions.

- Jules Berman

key words: precision medicine, infections, evolution, resistance to infection, jules j berman Ph.D., M.D.

Precision Medicine and Public Health (from Precision Medicine and the Reinvention of Human Disease)


Excerpted from Precision Medicine and the Reinvention of Human DiseaseDespite having the most advanced healthcare technology on the planet, life expectancy in the United States is not particularly high. Citizens from most of the European countries and the highly industrialized Asian countries enjoy longer life expectancies than the United States. According to the World Health Organization, the United States ranks 31st among nations, trailing behind Greece, Chile, and Costa Rica, and barely edging out Cuba [42]. Similar rankings are reported by the US Central Intelligence Agency [43]. These findings lead us to infer that access to advanced technologies, such as those offered by Precision Medicine, will not extend lifespan significantly. Every healthcare professional knows that most of the deaths occurring in this country can be attributed to personal lifestyle choices: smoking, drinking, drug abuse, and over-eating. Lifestyle diseases account for the majority of deaths in the United States and in otherwestern countries, these being:heartdisease,diabetes, obesity, andcancer.Population-basedtrials that seek to improve theways inwhichindividuals live, by introducing adaily exercise routine, healthydiet, and cigarette abstinence, have yielded huge benefits, in terms of extending average lifespans [44]. At the front end of the human life cycle, it has been demonstrated that infant mortalities can be markedly reduced with simple measures, focusing on improved maternal education [45]. It has been credibly argued that cleanwater, clean air, clean housing, clean food, and clean living yieldgreater societal benefits than clean operating rooms [46,47]. If this be the case, should we be investing heavily in Precision Medicine, when simple, low-tech public health measures are likely to provide a greater return on investment, in terms of overallmorbidity andmortality? In a certain sense, public health is the opposite of personalized medicine. Whereas personalized medicine involves finding the best possible treatment for individuals, based on their uniqueness, public health involves finding ways of treating whole populations based on their collective sameness. Let’s not dwell on these somewhat contrived philosophic points. Precision Medicine, as viewed in this book, is a new way of understanding human diseases. As such, Precision Medicine provides opportunities to advance both personalized medicine and public health. Precision Medicine tells us that we should think of diseases as developmental process, with each step in the process representing an opportunity for intervention. Perhaps the most important function of Precision Medicine will be to give society the opportunity to institute public health measures aimed at blocking the pathogenesis of human diseases. Here are just a few examples: – Population screening for early stages of common diseases.The successful reduction in deaths from cervical cancer demonstrates the effectiveness of screening for early stages of disease. Cervical cancer is a type of squamous cell carcinoma that develops at the junction between the ectocervix (the squamous lined epithelium) and the endocervix (the glandular lined epithelium) in the os of the uterine cervix of women. Before the introduction of cervical precancer treatment, cervical carcinoma was one of the leading causes of cancer deaths in women worldwide. Today, in many countries that have not deployed precancer treatment, cervical cancer remains the leading cause of cancer deaths in women [48– 50]. In the United States, a 70% drop in cervical cancer deaths followed the adoption of routine Papsmear screening[51–53].Noeffort aimedat treatinginvasive cancers has providedanequivalent reduction in the number of cancer deaths. [Glossary Age-adjusted incidence, Pap smear] Today, we know that cervical carci[...]

Treat the Pathway, not the Gene (from Precision Medicine and the Reinvention of Human Disease)


Treat the key pathway, not the genetic mutation (from Precision Medicine and the Reinvention of Human Disease)Some of the earliest and most successful Precision Medication drugs have targeted specific mutations occurring in specific subsets of diseases. One such example is ivacaftor, which targets the G551D mutation present in about 4% of individuals with cystic fibrosis [135]. It is seldom wise to argue with success, but it must be mentioned that the cost of developing a new drug is about $5 billion [136]. To provide some perspective, $5 billion exceeds the total gross national product of many countries, including Sierra Leone, Swaziland, Suriname, Guyana, Liberia, and the Central African Republic. Many factors contribute to the development costs, but the most significant is the incredibly high failure rate of candidate drugs. About 95% of the experimental medicines that are studied in humans fail to be both effective and safe. The costs of drug development are reflected in the rising costs of drugs. When a new drug is marketed to a very small population of affected individuals, the cost of treating an individual may be astronomical. Americans should not pin their hopes on the belief that one day, the FDA or CMS (which administrates Medicare) will step in and put a stop to the price rises. The Food and Drug Administration can approve or reject drugs, but it does not regulate prices. Likewise, Medicare is not permitted to consider cost when it decides whether a treatment can be covered. Knowing this, some notable pharmaceutical companies have raised the prices of medications far beyond their manufacturing costs [137–139]. In effect, the cost of curing curable diseases may exceed our ability to pay for those cures [139]. It is strongly in the interests of society to develop drugs that have the widest possible user market [140]. Drugs that target a mutation that is specific for a few individuals with a rare disease, or a tiny subpopulation of individuals who have a common disease, are highly problematic. Our experiences with disease convergence teach us that clinical phenotypes are influenced by the activities of pathways and are seldom restricted to a specific mutation in a specific gene. We know this because rare diseases that exhibit locus heterogeneity affect different genes, but often target the same pathway. Likewise, acquired phenotypes of genetic diseases often involve inhibitors of the same key pathways that drive their genetic counterparts, without involving the protein product of the genetic form of the disease. We also know that the acquired version of most genetic diseases account for the bulk of disease occurrences. Therefore, if we want to develop treatments that benefit the greatest number of individuals affected by a disease, it would be far more practical to find treatments that target the disease-driving pathways than to design drugs that target a specific gene mutation involved in a small subset of affected patients. Before closing, here are a few points worth considering (to be discussed in later blogs): As a generalization, any drug that can block a pathway, without producing serious side effects, may serve as a candidate treatment for all of the diseases that are driven by the pathway. Individuals in the early stages of common diseases, before multiple disease pathways converge to produce an intractable clinical phenotype, may be particularly amenable to treatments that interfere with the pathways that promote the ensuing steps in pathogenesis. The topic of clinical trials designed to test drugs targeting convergent disease pathways is discussed in Precision Medicine and the Reinvention of Human Disease, Section 9.6, “Fast, Cheap, Precise Clinical Trials.” - Jules Bermankey words: precision medicine, precision treatment, clin[...]

National Patient Identifiers (from Precision Medicine and the Reinvention of Human Disease)


Readers from outside the United States are probably wondering why the United States agonizes over the problem of patient identification. In many other countries, individuals are given a unique national identifier, and all medical data associated with the individual is kept in a central data repository under the aegis of the government’s health service. A single, permanent identifier is used by a patient throughout life, in every encounter with a hospital, clinic, or private physician. As a resource for researchers, the national patient identifier ensures the completeness of data sets and eliminates many of the problems associated with poorly implemented local identifier systems. In the United States, there has been fierce resistance to the idea of national patient identifiers. The call for a national patient identification system is raised from time to time. The benefits to patients and to society are many. Regardless, US citizens are reluctant to have an identifying number that is associated with a federally controlled electronic record of their private medical information. In part, this distrust results from the lack of any national insurance system in the United States. Most health insurance in the United States is private, and private insurers have wide discretion over the fees and services provided to enrollees. There is a fear that if there were a national patient identifier with centralized electronic medical records, insurers would withhold reimbursements or raise premiums or otherwise endanger the health of patients. Because the cost of US medical care is the highest in the world, medical bills for uninsured patients can quickly mount, impoverishing individuals and families. Realistically, though, no data is safe. Medical records can be stolen, and governments can demand access to medical records, when necessary [See Lewin T. Texas orders health clinics to turn over patient data. The New York Times; October 23, 2015]. Life has its compromises. Everyone wants their privacy and we all get angry when we hear that our confidential information has been stolen. Data breaches today may involve hundreds of millions of confidential records. The majority of Americans have had social security numbers, credit card information, and private identifiers (e.g., birth dates, city of birth, names of relatives) misappropriated or stolen. It’s natural to object to anything that might jeopardize our privacy. Nonetheless, we must ask ourselves the following: “Is it rational to forfeit the very real opportunity of developing new safe and effective treatments for serious diseases, for the very small likelihood that someone will crack your deidentified research record and somehow leverage this information to your disadvantage?” Suppose everyone in the United States were given a choice: you can be included in a national patient identifier system, or you can opt out. Most likely, there would be many millions of citizens who would opt out of the offer, seeing no particular advantage in having a national patient identifier, and sensing some potential harm. Now, suppose you were told that if you chose to opt out, you would not be permitted to use any of the therapeutic or preventive benefits that come from studies performed with data collected from the national patient identifier system. These lost benefits would include safe and effective drugs, warnings of emerging epidemics, information on side effects associated with your medications, biomarker tests for preventable illnesses, and so on. Those who made no effort to help the system would be barred from any of the benefits that the system provided. Would you reconsider your refusal to cooperate, if you knew the consequences? Of course, this is a fanciful scenario, but it makes a poin[...]

Paradoxes of Classification (and terrible Class definitions)


The formal systems that assign data objects to classes, and that relate classes to other classes, are known as ontologies. When the data within a Big Data resource is classified within an ontology, data analysts can determine whether observations on a single object will apply to other objects in the same class. Similarly, data analysts can begin to ask whether observations that hold true for a class of objects will relate to other classes of objects. Basically, ontologies help scientists fulfill one of their most important tasks; determining how things relate to other things. A classification is a very simple form of ontology, in which each class is allowed to have only one parent class. To build a classification, the ontologist must do the following: 1) define classes (i.e., find the properties that define a class and extend to the subclasses of the class); 2) assign instances to classes; 3) position classes within the hierarchy; and 4) test and validate all the above. The constructed classification becomes a hierarchy of data objects conforming to a set of principles: The classes (groups with members) of the hierarchy have a set of properties or rules that extend to every member of the class and to all of the subclasses of the class, to the exclusion of unrelated classes . A subclass is itself a type of class wherein the members have the defining class properties of the parent class plus some additional property(ies) specific for the subclass. In a hierarchical classification, each subclass may have no more than one parent class. The root (top) class has no parent class. The biological classification of living organisms is a hierarchical classification. At the bottom of the hierarchy is the class instance. For example, your copy of this book is an instance of the class of objects known as "books". Every instance belongs to exactly one class. Instances and classes do not change their positions in the classification. As examples, a horse never transforms into a sheep, and a book never transforms into a harpsichord. The members of classes may be highly similar to one another, but their similarities result from their membership in the same class (i.e., conforming to class properties), and not the other way around (i.e., similarity alone cannot define class inclusion). Classifications are always simple; the parental classes of any instance of the classification can be traced as a simple, non-branched list, ascending through the class hierarchy. As an example, here is the lineage for the domestic horse (Equus caballus), from the classification of living organisms: Equus caballusEquus subg. EquusEquusEquidaePerissodactylaLaurasiatheriaEutheriaTheriaMammaliaAmniotaTetrapodaSarcopterygiiEuteleostomiTeleostomiGnathostomataVertebrataCraniataChordataDeuterostomiaCoelomataBilateriaEumetazoaMetazoaFungi/Metazoa groupEukaryotacellular organismsTaxonomists who view this lineage instantly grasp the place of domestic horses in the classification of all living organisms. The rules for constructing classifications seem obvious and simplistic. Surprisingly, the task of building a logical, and self-consistent classification is extremely difficult. Most classifications are rife with logical inconsistencies and paradoxes. Let's look at a few examples. In 1975, while touring the Bethesda, Maryland campus of the National Institutes of Health, I was informed that their Building 10, was the largest all-brick building in the world, providing a home to over 7 million bricks . Soon thereafter, an ambitious construction project was undertaken to greatly expand the size of Building 10. When the work was finished, building 10 was no longer the largest all-brick building in the world. What happened? The builders used[...]

Precision Medicine and the Reinvention of Human Disease (not just about genes)


If everything you know about Precision Medicine comes from the lay press, you may have an unrealistic notion of what's happening in this field. The news seems to stress the one gene -> one disease paradigm that is easy to understand, but largely irrelevant to all the common diseases that occur in humans.

The one gene -> one disease paradigm is this: the clinical expression of each disease is caused by a genetic mutation in a particular gene responsible for that particular disease, or a particular subtype of a disease, in a particular individual. By finding and targeting the gene responsible for an individual's disease, Precision Medicine will cure the patient.

This paradigm is short and sweet, and it is more or less true for a number of rare diseases; but it is wrong for just about every disease that occurs commonly in humans, and it serves to distract our attention from the medical revolution that Precision Medicine will bring.

The purpose of my new book, Precision Medicine and the Reinvention of Human Disease, discussed in previous blogs, is to explain how Precision Medicine is changing our fundamental understanding of the pathogenesis of disease (i.e., the biological steps that lead to the development of diseases), and how this new information is changing the way that we prevent, diagnose, and treat human diseases.

Precision Medicine is not about finding the right gene for the right patient. Precision Medicine is about finding the common events and metabolic pathways that account for the development and the expression of diseases; and using these insights to reduce the morbidity and mortality of disease in the population.

Google Books has a very good "look inside" for my book, and I hope that readers of this blog will take a few moments to see if they might be interested in the subject.

- Jules Berman


key words: precision medicine, jules j berman, Ph.D., M.D., disease biology, pathogenetic, monogenic, rare diseases, complex diseases, common diseases

Precision Medicine and the Reinvention of Human Disease (a better definition)


We can define Precision Medicine as an approach to the prevention, diagnosis, and treatment of disease that is based on a deep understanding of the sequence of biological events that lead to disease. With this approach we are learning:

(1) that we can develop new drugs that target specific steps in the development of disease;

(2) that drugs developed to interfere with a cellular event or pathway may serve as effective treatments for those individuals whose disease is driven by the pathway; and

(3) that a treatment effective for a subtype of one disease may also be effective against other diseases that happen to be driven by the same pathway.

This approach, based on learning the steps that precede the development of disease, shifts the emphasis of Precision Medicine from finding unique treatments for unique individuals to finding general treatments that are effective against precisely identified biological processes, in whichever diseases those processes may occur. In the era of Precision Medicine, every disease has a biological history, and every event in the history of the disease is a possible target for prevention, diagnosis, or treatment. At this point, we can begin to see the thread of a story that will unfold throughout my book, Precision Medicine and the Reinvention of Human Disease.

-Jules Berman

key words: precision medicine, definition, pathogenesis, steps in disease development, jules j berman

Precision Medicine and the Reinvention of Human Disease (not just the genome)


If you believe the lay press, Precision Medicine involves sequencing a patient's genome and determining the proper treatment based on the individual's unique genetic attributes. The NIH (National Institutes of Health) seems to be encouraging this interpretation of the field. From the US National Institutes of Health comes the following description: "Precision Medicine is an emerging approach for disease prevention and treatment that takes into account people's individual variations in genes, environment, and lifestyle. The Precision Medicine Initiative will generate the scientific evidence needed to move the concept of Precision Medicine into clinical practice". An Advisory Committee to the NIH Director would include, under the mantle of Precision Medicine, "providing individual side-effect profiles of drugs, and preventative health care check-ups that include specific recommendations developed from interpreting an individual's genetic risk profile". Between the millions of inter-individual variations in our genomes, the highly personalized lifestyle choices, and the differences in our environments, there seems to be plenty of uniqueness to spread around. It is easy to forget that our uniqueness as individuals often has much less to do with our diseases than does our sameness as members of the same species. Our sameness goes a long way toward explaining why humans seem to suffer from the same list of textbook diseases, regardless of their individualized genes and geography. Someone had to put the brakes on this epidemic of uniqueness. Much to their credit, the National Research Council of the US National Academies tacked on the following caveat to the definition of Precision Medicine: "It does not literally mean the creation of drugs or medical devices that are unique to a patient, but rather the ability to classify individuals into subpopulations that differ in their susceptibility to a particular disease, in the biology and/or prognosis of those diseases they may develop, or in their response to a specific treatment". The Research Council wisely distinguished Personalized Medicine from Precision Medicine, by adding, "Although the term 'Personalized Medicine' is also used to convey this meaning, that term is sometimes misinterpreted as implying that unique treatments can be designed for each individual. For this reason, the Committee thinks that the term 'Precision Medicine' is preferable to 'Personalized Medicine'" The National Research Council pointed out what should have been obvious from the start. We cannot provide individualized treatments, because treatments must be tested for safety and efficacy on groups of people. The best we can ever do is to assign patients to a group that has been fitted to a preapproved treatment. So where does this leave us? More to follow in tomorrow's blog. - Jules Bermankey words: precision medicine, genomics, individualized treatments, definition, jules j berman, Jules Berman Ph.D., M.D.[...]

Precision Medicine and the Reinvention of Human Disease (from Preface)


Something has happened in the past two decades that has changed the way that modern biomedical scientist thinks about diseases. Because the changes in our perceptions have happened slowly, few of us have really taken notice of what it all means. The purpose of my latest book, Precision Medicine and the Reinvention of Human Disease, published January, 2018, is to show how advances in the field of Precision Medicine will forever change the way we understand and treat disease. Specifically, these advances are:

  • Diseases develop in steps. Modern methodology has enabled us to dissect the biological events and metabolic pathways that ultimately lead to the expression of disease. We can no longer think in terms of the "cause" of a disease, because most diseases have multiple contributory causes, that act over time. [Glossary Pathway]

  • Because disease development requires the successful completion of multiple, sequential steps, and because we can now observe some of these steps, Precision Medicine has given us multiple targets that we can attack, with the expectation of preventing diseases from developing, delaying the development of disease, or treating diseases that are driven by identifiable pathways.

  • Because different paths of development may lead to the same set of clinical findings, diseases can be subtyped into classes according to the specific pathways that drive their biology. Hence, treatment can be precisely targeted to subtypes of diseases that were formerly indistinguishable from one another.

  • Because diseases that appear to be unrelated might share biological pathways that can be successfully targeted by new classes of drugs, we can now prevent or treat a variety of diseases, using a drug that was specifically developed for one rare subtype of disease.

Precision Medicine and the Reinvention of Human Disease explains how we have come to believe that these four advances in Precision Medicine are true, and how these advances are impacting the practice of medicine.

- Jules Berman

key words: precision medicine, rare diseases, jules j berman, jules berman, pathogenesis

Precision Medicine and the Reinvention of Human Disease (The Myth)


If you believe the hype, we are entering a new era of medicine in which each individual will receive unique treatment, determined by the sequence of his or her genome. This widely promulgated notion is simply ridiculous. There is no practical way to develop a unique treatment, test the treatment for safety and effectiveness, and titrate the correct dose, all for one person.

The terms "Precision Medicine" and "Personalized Medicine" have given us the false impression that medical science is moving away from off-the-rack remedies and is seeking treatments tailored to the individual. In actuality, science has always been about seeking generalization. When Isaac Newton watched an apple drop, he was not working on a new Law of Falling Apples. He was trying to understand the general laws of gravity and motion that applied to every object in the universe. When Charles Darwin spent 8 years studying barnacles, he was not trying to build a display collection of handsome barnacles for the national museum. He was developing a general theory of evolution that would apply to every living organism on earth. Likewise, when we study a specific pathway that is operative in a small percentage of cases of a rare tumor, accounting for perhaps a dozen patients worldwide, we expect that our findings will have general application to a wide variety of conditions.

Precision Medicine has very little to do with developing unique treatments. Like all medical research, Precision Medicine seeks to find general treatments that will be effective for the largest number of patients. The "Precision" in Precision Medicine refers to our ability to precisely diagnose rare diseases, and subsets of common diseases, that share a particular sensitivity to particular forms of treatment.

- Jules Berman

Precision Medicine and the Reinvention of Human Disease (Book Index)


In January, 2018, Academic Press published my book Precision Medicine and the Reinvention of Human Disease. This book has an excellent "look inside" at its Google book site, which includes the Table of Contents. In addition, I thought it might be helpful to see the topics listed in the Book's index. Note that page numbers followed by f indicate figures, t indicate tables, and ge indicate glossary terms. AAbandonware, 270, 310geAb initio, 34, 48ge, 108geABL (abelson leukemia) gene, 28, 58ge, 95–97Absidia corymbifera, 218Acanthameoba, 213Acanthosis nigricans, 144geAchondroplasia, 74, 143ge, 354geAcne, 54ge, 198, 220geAcquired autoantibody disease, 133Acquired Parkinsonism, 105ge, 128, 281Acrodermatisis verruciformis, 26–27Acrokeratosis verruciformis of Hopf, 23–24Actinic keratoses, 33Actinobacillus actinomycetemcomitans, 217Actinomyces pyogenes, 217Activated oncogene, 28, 34–35, 57ge, 222geAcute anterior uveitis, 208Acute flaccid myelitis, 204–205Acutely transforming retroviruses, 46–47Acute myelogenous/myeloid leukemia, 33–34, 97, 139,156–157Adaptive immunity evolved, 192Adenosine deaminase, 46, 72, 80Adrenocortical carcinoma, 73, 103geAdult T-cell leukemia, 339Adverse effect, 275, 352–353Aflatoxin, 30, 182 and hepatocellular carcinoma, 30, 182Age adjusted incidence, 338, 354geAge related macular degeneration, 105ge, 138, 199Aggregate disease, 80, 98geAging, 35–36, 70–71, 125–126, 234, 354Agouti, 86–87AIRE gene, 198Albinism, 77–78, 81–82, 84Alcohol, 128, 156, 159, 287 abuse, 128, 158 related neurodevelopmental disorders, 159Allele, 70, 98ge, 158–159, 332–333, 347–348Allelic heterogeneity, 71, 98geAlpha1 antitrypsin deficiency, 82Alpha particles, 166–167Alpha-spectrin gene, 70Alpha thalassemia, 83, 92Alstrom syndrome, 122–123Alternative RNA, 85, 98geAlzheimer disease, 6–7, 70, 139, 233–234, 246, 327–328, 353Amateur scientists, 329–330Aminoglycoside, 128 induced hearing loss, 77Amoebic encephalitides, 213Amphotericin B, 128, 213Amyloidosis, 83, 98ge, 200Amyloid plaques, 126Amyotrophic lateral sclerosis, 77, 282Anaerobic conditions, 108geAnal squamous carcinoma, 45Anaphylactic shock, 133Anaphylaxis, 133Anaplasma phagocytophilum, 217Anatomic abnormalities, 6–7, 166–167Ancestral class, 184, 231Aneuploid, 89, 89fAneuploid cells, 49geAneuploidy, 47, 89fAngelman syndrome, 75, 86Angiofollicular lymph node hyperplasia, 50geAngiogenesis, 120, 138Angioimmunoblastic lymphadenopathy, 55geAngiopoietin, 139Angiotensin converting enzyme inhibitors, 4Animal model, 31, 33, 88, 170, 279, 351–354Ankylosing spondylitis, 208Anlagen, 243Annotation, 264, 271, 308, 341Anonymizing private and confidential medical data, 310Anoxia, 91–92Anterior segment mesenchymal dysgenesis, 53geAnthers, 90Antibasement membrane antigen, 132Antibiotics, 190, 195–196, 210, 213Antibody/antibodies, 21–22, 73, 126, 130–134, 139, 192,197, 209, 299, 348–350Anticipation, 86Anucleate ovum, 254geAnucleate red blood cell, 91Aortic dissection, 142geApicomplexans, 184, 186Aplastic anemia, 24–25, 95–96, 166Apolipoprotein E (APOE) gene, 70Apoptosis, 48–61, 73, 133–134, 197–200Archaeans, 191Archaeplastida, 186, 191–192Aromatase inhibitors, 136–137Arrhythmias, 135Arrhythmogenic right ventricular cardiomyopathy, 331Arrhythmogenic right ventricular dysplasia, 70Artemis gene, 72Arteriosclerosis, 171Arthritis, 131–132, 134, 139, 197–198, 201, 208, 346,349–350Arthropod vectors, 202Arylsulfatase, 121–122 deficiency, 121–122Asbestos, 26–27, 29, 167–169, 279–280Ash leaf spots, 102geAspergillus flavus, 182Asp[...]

Announcement: Precision Medicine and the Reinvention of Human Disease


In January, 2018, Academic Press is publishing my latest book, Precision Medicine and the Reinvention of Human DiseaseHere is the book description, from the back cover:Despite what you may have read in the popular press and in social media, Precision Medicine is not devoted to finding unique treatments for individuals, based on analyzing their DNA. To the contrary, the goal of Precision Medicine is to find general treatments that are highly effective for large numbers of individuals who fall into precisely diagnosed groups. We now know that every disease develops over time, through a sequence of defined biological steps, and that these steps may differ among individuals, based on genetic and environmental conditions. We are currently developing rational therapies and preventive measures, based on our precise understanding of the steps leading to the clinical expression of diseases. Precision Medicine and the Reinvention of Human Disease explains the scientific breakthroughs that have changed the way that we understand diseases, and reveals how medical scientists are using this new knowledge to launch a medical revolution. Key FeaturesClarifies the foundational concepts of Precision Medicine, distinguishing this field from its predecessors such as genomics, pharmacogenetics, and personalized medicine. Gathers the chief conceptual advances in the fields of genetics, pathology, and bioinformatics, and synthesizes a coherent narrative for the field of Precision Medicine. Delivers its message in plain language, and in a relaxed, conversational writing style, making it easy to understand the complex subject matter. Guides the reader through a coherent and logical narrative, gradually providing expertise and skills along the way. Covers the importance of data sharing in Precision Medicine, and the many data-related challenges that confront this fragile new field. Table of ContentsPreface. Chapter 1. Introduction: Seriously, What is Precision Medicine? Glossary ReferencesChapter 2. Redefining Disease Causality Section 2.1 Causality and Its Paradoxes Section 2.2 Why We Are Confident that Diseases Develop in Steps Section 2.3 Cause of Death Section 2.4 What Is a Disease Pathway? Section 2.5 Does Single Event Pathogenesis Ever Happen? Glossary ReferencesChapter 3. Genetics: Clues, Not Answers, to the Mysteries of Precision Medicine Section 3.1 Inscrutable Genes Section 3.2 Inscrutable Diseases Section 3.3 Recursive Epigenomic/Genomic Diseases Section 3.4 Why a Gene-based Disease Classification Is a Bad Idea Glossary ReferencesChapter 4. Disease Convergence Section 4.1 Mechanisms of Convergence Section 4.2 Phenocopy Diseases: Convergence Without Mutation Section 4.3 The Autoantibody Phenocopies Section 4.4 Pathway-Directed Treatments for Convergent Diseases Glossary ReferencesChapter 5. The Precision of the Rare Diseases Section 5.1 The Biological Differences Between Rare Diseases and Common Diseases Section 5.2 Precision Medici[...]

CLASS BLENDING: Simpson's Paradox


For the past two days, we've been posting on Class Blending. Simpson's paradox is a special case that demonstrates what may happen when classes of information are blended.

Simpson's paradox is a well-known problem for statisticians. The paradox is based on the observation that findings that apply to each of two data sets may be reversed when the two data sets are combined.

One of the most famous examples of Simpson's paradox was demonstrated in the 1973 Berkeley gender bias study (1). A preliminary review of admissions data indicated that women had a lower admissions rate than men:

Men Number of applicants.. 8,442 Percent applicants admitted.. 44%
Women Number of applicants.. 4,321 Percent applicants admitted.. 35%
A nearly 10% difference is highly significant, but what does it mean? Was the admissions office guilty of gender bias?

A closer look at admissions department-by-department showed a very different story. Women were being admitted at higher rates than men, in almost every department. The department-by-department data seemed incompatible with the combined data.

The explanation was simple. Women tended to apply to the most popular and oversubscribed departments, such as English and History, that had a high rate of admission denials. Men tended to apply to departments that the women of 1973 avoided, such as mathematics, engineering and physics. Men tended not to apply to the high occupancy departments that women preferred. Though women had an equal footing with men in departmental admissions, the high rate of women rejections in the large, high-rejection departments, accounted for an overall lower acceptance rate for women at Berkeley.

Simpson's paradox demonstrates that data is not additive. It also shows us that data is not transitive; you cannot make inferences based on subset comparisons. For example in randomized drug trials, you cannot assume that if drug A tests better than drug B, and drug B tests better than drug C, then drug A will test better than drug C (2). When drugs are tested, even in well-designed trials, the test populations are drawn from a general population specific for the trial. When you compare results from different trials, you can never be sure whether the different sets of subjects are comparable. Each set may contain individuals whose responses to a third drug are unpredictable. Transitive inferences (i.e., if A is better than B, and B is better than C, then A is better than C), are unreliable.

- Jules Berman (copyrighted material)

key words: data science, irreproducible results, complexity, classification, ontology, ontologies, classifications, data simplification, jules j berman


1. Bickel PJ, Hammel EA, O'Connell JW. Sex Bias in Graduate Admissions: Data from Berkeley. Science 187:398-404, 1975.

2. Baker SG, Kramer BS. The transitive fallacy for randomized trials: If A bests B and B bests C in separate trials, is A better than C? BMC Medical Research Methodology 2:13, 2002

Open for Comment


For the past several years, I've kept this blog closed to comments. Prior to that, most of the comments were thinly disguised advertisements for pharmaceuticals, and I got tired of rejecting them. For the past month or so, I've re-opened the blog for readers' comments, without announcing the change; just to check whether I'd be inundated with computer-generated promotions.

It seems that neither software agents or readers have noticed the change. So, please, if you are a human and would like to send a comment, feel free to use the comments link at the bottom of every post. Your comments will be moderated, but I intend to approve all blogs that are created by humans, and that do not promote products or services or other web sites. You are also welcome to comment on prior posts that appeared in the past month.

- Jules Berman

key words: blog, postings, comments, announcement, jules j berman

Expunging a Blended Class: The Fall of Kingdom Protozoa


In yesterday's blog, we introduced and defined the term "Class blending". Today's blog extends this discussion by describing the most significant and most enduring class blending error to impact the natural sciences: the artifactual blending of all single cell organisms into the blended class, Protozoa.For well over a century, biologists had a very simple way of organizing the eukaryotes (i.e., the organisms that were not bacteria, whose cells contained a nucleus) (1). Basically, the one-celled organisms were all lumped into one biological class, the protozoans (also called protists). With the exception of animals and plants, and some of the fungi (e.g., mushrooms), life on earth is unicellular. The idea of lumping every type of unicellular organism into one class, having shared properties, shared ancestry, and shared descendants, made no sense. What's more, the leading taxonomists of the nineteenth century, such as Ernst Haeckel (1834 - 1919), understood the class Protozoa was at best, a temporary grab-bag holding unrelated organisms that would eventually be split into their own classes. Well, a century passed, and complacent taxonomists preserved the Protozoan class. In the 1950s, Robert Whittaker elevated Class Protozoa as a kingdom in his broad new "Five Kingdom" classification of living organisms (2). This classification (more accurately, misclassification) persisted through the last five decades of the twentieth century. Modern classifications, based on genetics, metabolic pathways, shared morphologic features, and evolutionary lineage, have dispensed with Class Protozoa, assigning each individual class of eukaryotes to its own hierarchical position. A simple schema demonstrates the modern classification of eukaryotes (3). Many modern taxonomists are busy improving this fluid list (vida infra), but, most significantly, Class Protozoa is nowhere to be found. Eukaryota (organisms that have nucleated cells) Bikonta (2-flagella) Excavata Metamonada Discoba Euglenozoa Percolozoa Archaeplastida, from which Kingdom Plantae derives Chromalveolata Alveolata Apicomplexa Ciliophora Heterokontophyta Unikonta Amoebozoa Opisthokonta Choanozoa Animalia Fungi Why is it important to expunge Class Protozoa from modern classifications of living organisms? Every class of living organism contains members that are pathogenic to other classes of organisms. To the point, most classes of organisms contain members that are pathogenic to humans, or to the organisms that humans depend on for their existence (e.g., other animals, food plants, beneficial organisms). There are way too many species of pathogens for us to develop specific drugs and techniques to control the growth of each disease-causing organism. Our only hope is to develop general treatments for classes of organisms, that share the same properties; hence the same weaknesses. For example, in theory, it's much easier to develop drugs that work on Apicomplexans that it is to develop separate drugs that work on each pathogenic species of Apicomplexan (3). By lumping every single-celled organisms into one blended class, we have missed the opportunity to develop true class-based remedies for the most elusive disease-causing organisms on our planet. The past two decades have seen enormous progress in reclassifying the former protozoans. Unfortunately, the errors of the past are repeated in textbooks a[...]

Intro to Class Blending


I thought I'd devote the next few blogs to a concept that has gotten much less attention than it deserves: blended classes. Class blending lurks behind much of the irreproducibility in "Big Science" research, including clinical trials. It also is responsible for impeding progress in various disciplines of science, particularly the natural sciences, where classification is of utmost importance. We'll see that the scientific literature is rife with research of dubious quality, based on poorly designed classifications and blended classes.

For today, let's start with a definition and one example. We'll discuss many more specific examples in future blogs.

Blended class - Also known as class noise, subsumes the more familiar, but less precise term, "Labeling error." Blended class refers to inaccuracies (e.g., misleading results) introduced in the analysis of data due to errors in class assignments (i.e., assigning a data object to class A when the object should have been assigned to class B). If you are testing the effectiveness of an antibiotic on a class of people with bacterial pneumonia, the accuracy of your results will be forfeit when your study population includes subjects with viral pneumonia, or smoking-related lung damage. Errors induced by blending classes are often overlooked by data analysts who incorrectly assume that the experiment was designed to ensure that each data group is composed of a uniform and representative population. A common source of class blending occurs when the classification upon which the experiment is designed is itself blended. For example, imagine that you are a cancer researcher and you want to perform a study of patients with malignant fibrous histiocytomas (MFH), comparing the clinical course of these patients with the clinical course of patients who have other types of tumors. Let's imagine that the class of tumors known as MFH does not actually exist; that it is a grab-bag term erroneously assigned to a variety of other tumors that happened to look similar to one another. This being the case, it would be impossible to produce any valid results based on a study of patients diagnosed as MFH. The results would be a biased and irreproducible cacaphony of data collected across different, and undetermined, species of tumors. This specific example, of the blended MFH class of tumors, is selected from the real-life annals of tumor biology (1), (2).


[1] Al-Agha OM, Igbokwe AA. Malignant fibrous histiocytoma: between the past and the present. Arch Pathol Lab Med 132:1030-1035, 2008.

[2] Nakayama R, Nemoto T, Takahashi H, Ohta T, Kawai A, Seki K, et al. Gene expression analysis of soft tissue sarcomas: characterization and reclassification of malignant fibrous histiocytoma. Modern Pathology 20:749-759, 2007.

- Jules Berman (copyrighted material)

key words: data science, irreproducible results, complexity, classification, ontology, ontologies, jules j berman

Progress against cancer? Let's think about it.


It is difficult to pick up a newspaper these days without reading an article proclaiming progress in the field of cancer research. Here is an example, taken from an article posted on the MedicineNet site (1). The lead-off text is: "Statistics (released in 1997) show that cancer patients are living longer and even "beating" the disease. Information released at an AMA sponsored conference for science writers, showed that the death rate from the dreaded disease has decreased by three percent in the last few years. In the 1940s only one patient in four survived on the average. By the 1960s, that figure was up to one in three, and now has reached 50% survival."Optimism is not confined to the lay press. In 2003, then NCI Director Andrew von Eschenbach, announced that the NCI intended to "eliminate death and suffering" from cancer by 2015 (2), (3). Update: it's 2016 and still no cancer cure.Bullish assessments for progress against cancer are a bit misleading. There is ample historical data showing that the death rate from cancer has been rising throughout the twentieth century, and that the burden of new cancer cases will rise throughout the first half of the twenty-first century (4). If you confine your attention to the advanced common cancers (the cancers that cause the greatest number of deaths in humans), we find that the same common cancers that were responsible for the greatest numbers of deaths in 1950 are the same cancers killing us today, and at about the same rates (5), (6). Furthermore, the age-adjusted cancer death rate, the only valid measurement of progress against cancer, is about the same today as it was in 1950 (7). According the the U.S. National Center for Health Statistics, the age-adjusted cancer death rate in 1950 was 194 deaths per 100,000 population (8). In 2004, the death rate was the same, 194 per 100,000 population (8). Hardly an occasion for celebration. In 1971, President Richard M. Nixon signed the National Cancer Act into law, marking the year that the United States launched its War on Cancer. For the next two decades, the U. S. cancer death rate rose steadily. Then in 1991, the U. S. cancer death rate began to decline, incrementally. It is tempting to conclude that 1991 marked the beginning of victory in our war against cancer, and that the steady, incremental declines in U. S. cancer death rates will continue in future decades, until cancer is fully eradicated. The decline in the cancer rate since 1991 is counter-balanced by the rise in the rate of cancer deaths between 1975 and 1991. What accounts for the rise in cancer deaths after 1975 and the restoration of the 1975 rates following 1991? There's no mystery here. The rise was due to smoking; the fall was due to smoking cessation (4). The post-1991 drop in the U.S. cancer death rate has only served to bring us full circle to our 1950 cancer death rate.You may be thinking that cancer is a difficult problem, but at least the U.S. is working on the leading edge of cancer care. If cancer is a problem for us, it must be must worse for all the underdeveloped countries in the world. Nope. The U.S. has a high cancer death rate when compared to other countries (9). Kuwait, Panama, Ecuador, Mexico and Thailand have a much lower cancer death rate than the United States. American citizens intent on lowering their cancer death rate would be better off immigrating across the border, to Mexico[...]