Friday, February 12, 2016

Why the Common Diseases are Complex

"One does not discover new lands without consenting to lose sight of the shore for a very long time." - Andre Gide

In the last decades of the twentieth century, scientists hoped that the common diseases, like the rare diseases, were each caused by a single, disease-specific genetic mutation. Once the mutation was found, it could be targeted with a drug. Well, things didn't work out that way. Most scientists today will admit that the common diseases of humans are much more complex than they had ever imagined.

Rule - We may have reached the limit by which we can understand the common diseases through direct genetic studies.
Brief Rationale - The common diseases of humans are complex, and biological complexity cannot be calculated, predicted or solved, even with supercomputers.

An objective review of the genetics of common diseases yields only bad news. With no exceptions, the common diseases are genetically complex. Attempts at predicting the behavior of common diseases, based on detailed, yet incomplete, knowledge of their complex genetic attributes, have led to failure after failure (1), (2), (3).

Not to be discouraged, data analysts believe that with the right algorithm, and the right supercomputer, the complexities of common diseases can be predicted. This belief is based, in no small part, on the assumption that organisms and cells behave much like non-biological devices composed of many parts, each performing some well-defined function, according to well-defined laws of physics, and interacting to produce a predictable and repeatable effect. Physicians have bought into this fantasy. When a sampling of physicians was asked to rank the areas in which they needed additional genetics training, their number one choice was the "genetics of common disease" (4), (5).

Rule - Biological systems are much more complex than naturally occurring non-biological systems (i.e., galaxies, mountains, volcanoes) and man-made physical systems (e.g., jet airplanes, computers).
Brief Rationale - The components of biological systems, unlike the components of non-biological systems, have multiple functions, dependencies, and regulatory systems. We cannot predict how any single component of a biological system will react under changing physiologic conditions.

The grim truth is that biological systems are nothing like man-made physical systems. When an engineer builds a radio, she knows that she can assign names to components, and these components can be relied upon to behave in a manner that is characteristic of its type. A capacitor will behave like a capacitor, and a resistor will behave like a resistor. The engineer need not worry that the capacitor will behave like a semiconductor or an integrated circuit. What is true for the radio engineer does not hold true for the biologist (6).

In biological systems, components change their functions depending on circumstances. For example, cancer researchers discovered a protein that plays an important role in the development of cancer. This protein, p53, was once considered to be the primary cellular driver for human malignancy. When p53 mutated, cellular regulation was disrupted, and cells proceeded down a slippery path leading to cancer. In the past few decades, as more information was obtained, cancer researchers have learned that p53 is just one of many proteins that play a role in carcinogenesis, but the role changes depending on the species, tissue type, cellular micro-environment, genetic background of the cell, and many other factors. Under one set of circumstances, p53 may play a role in DNA repair; under another set of circumstances, p53 may cause cells to arrest the growth cycle (6), (7). It is difficult to predict a biological outcome when pathways change their primary functionality based on cellular context. Various mutations in the TP53 gene have been linked to 11 clinically distinguishable cancer-related disorders, and there is little reason to assume that the same biological role is played in all of these 11 disorders (8).

Likewise, the Pelger-Huet anomaly and Hydrops-ectopic calcification-'moth-eaten' (HEM) are both caused by mutations of a gene, coding for the lamin B receptor. Pelger-Huet anomaly is a morphologic aberration of neutrophils wherein the normally multi-lobed nuclei become coffee bean-shaped, or bilobed, with abnormally clumped chromatin. The condition is called an anomaly, rather than a disease, because despite the physical abnormalities, the affected white cells seem to function adequately. HEM is a congenital chondrodystrophy that is characterized by hydrops fetalis (i.e., accumulations of fluid in the fetus), and skeletal abnormalities. It would be difficult to imagine any two diseases as unrelated as Pelger-Huet anomaly and HEM. How could these disparate diseases be caused by a mutation involving the same gene? As it happens, the lamin B receptor has two separate functions: preserving the structure of chromatin, and serving as a sterol reductase in cholesterol synthesis (9). These two different and biologically unrelated functions, in one gene product, account for two different and biologically unrelated diseases.

A gene's role may be influenced by other genes, a phenomenon called epistasis. Likewise, the role of a gene is influenced by the temporal expression of the gene (e.g., at precise moments of organismal development), and by its sequential activation (e.g., preceding or succeeding sequential steps in multiple pathways). The activity of a protein encoded by a gene can be influenced by subtle variations in amino acid sequence, by three-dimensional structure, by chemical modifications of the protein, by quantity of the protein, by location of the protein molecules in cells, and by the type of cell in which the protein is expressed. Attempts to predict the functional effect of single or multiple gene variations are typically futile (10), (11).

The most complex man-made physical systems are laughably simplistic compared to human genetics. The fastest supercomputers cannot cope with networks of systems whose individual objects behave in unpredictable and indescribable ways.

- Jules Berman (copyrighted material)

key words: rare disease, orphan drugs, orphan diseases, zebra diseases, rare disease day, disease complexity jules j berman

Rare Disease Day is coming up February 29 (a rare day for rare diseases). In honor of the upcoming event, I'll be posting blogs all month, related to the rare diseases and to rare disease funding.


[1] Cecile A, Janssens JW, vanDuijn, CM. Genome-based prediction of common diseases: advances and prospects. Human Molecular Genetics 17:166-173, 2008.

[2] Ioannidis JP. Is molecular profiling ready for use in clinical decision making? The Oncologist 12:301-311, 2007.

[3] Venet D, Dumont JE, Detours V. Most random gene expression signatures are significantly associated with breast cancer outcome. PLoS Comput Biol 7:e1002240, 2011.

[4] Calefato JM, Nippert I, Harris HJ, Kristoffersson U, Schmidtke J, Ten Kate LP, et al. Assessing educational priorities in genetics for general practitioners and specialists in five countries: factor structure of the Genetic-Educational Priorities (Gen-EP) scale. Genet Med 10:99-106, 2008.

[5] Julian-Reynier C, Nippert I, Calefato JM, Harris H, Kristoffersson U, Schmidtke J, et al. Genetics in clinical practice: general practitioners' educational priorities in European countries. Genet Med 10:107-113, 2008.

[6] Madar S, Goldstein I, Rotter V. Did experimental biology die? Lessons from 30 years of p53 research. Cancer Res 2009;69:6378-6380, 2009.

[7] Zilfou JT, Lowe SW. Tumor Suppressive Functions of p53. Cold Spring Harb Perspect Biol 00:a001883, 2009.

[8] Vogelstein B, Lane D, Levine AJ. Surfing the p53 network. Nature 408:307-310, 2000.

[9] Waterham HR, Koster J, Mooyer P, van Noort G, Kelley RI, Wilcox WR, et al. Autosomal recessive HEM/Greenberg skeletal dysplasia is caused by 3-beta-hydroxysterol delta(14)-reductase deficiency due to mutations in the lamin B receptor gene. Am J Hum Genet 72:1013-1017, 2003.

[10] Chi YI. Homeodomain revisited: a lesson from disease-causing mutations. Hum Genet 116:433-444, 2005.

[11] Gerke J, Lorenz K, Ramnarine S, Cohen B. Gene environment interactions at nucleotide resolution. PLoS Genet 6(9): e1001144, 2010