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 (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

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, than waiting for the U.S. win its war against cancer.

Despite the many billions of dollars spent on research and treatment for cancer, we have made negligible progress toward reducing the number of people who die each year from cancer. The reason that cancer organizations can announce major gains against cancer and can promise to eliminate cancer deaths by 2015 is due entirely to the magic of data misinterpretation!

To see how the deception works in the cancer field, you need to start with the definition of "survival." To a layperson, the term "survival" indicates avoidance of death. For example, the survivors of a plane crash are the people who did not die in the crash. To an oncologist, survival is the time interval between diagnosis and death. Suppose that oncologists announce that a new treatment of pancreatic cancer produces a 1% increase in survival. Layman will interpret this to mean that a person with pancreatic cancer will have a 1 in 100 chance of being cured of his cancer above and beyond his chances for cure with the older treatment. To most people with cancer, that 1 in 100 improvement, though small, is worth any price. Unfortunately, this is not the case at all. To the oncologists who made the announcement, a 1% increase in survival indicates that if the life expectancy following diagnosis of pancreatic cancer is 100 days, then the life expectancy following diagnosis with the new treatment is 101 days. In either case, most patients with advanced pancreatic cancer will die. The patients receiving the new treatment may reasonably expect to survive a bit longer (in this hypothetical case, an average of one day longer).

You may be asking yourself about the validity of claims that we can now cure many childhood cancers that could not be cured in prior generations. Thankfully, these claims are true and accurate. Many children with cancer can now be cured. However, the overall incidence of childhood cancers has risen 36% since 1976 (10). This rise in childhood cancer incidence has erased about half of the overall benefits from the rising cure rates.

Real progress has been made towards curing rare cancers, such as gastrointestinal stromal tumors (GISTs), chronic myelocytic leukemia, and Hodgkin Disease. There is a biological reason why the rare cancers are easier to cure than the common cancers, and this fascinating topic is discussed in detail in my book, Rare Diseases and Orphan Drugs: Keys to Understanding and Treating the Common Diseases. In a nutshell, research into the genetics of tumors has shown us that some cancers are characterized by simple genetic errors. It turns out that the tumors with simple genetic errors coincide with the rare tumors of childhood and certain rare tumors of adults. The small number of gene alterations in these rare tumors permits us to effectively target chemotherapeutic agents against a single vulnerable metabolic pathway. Complex common cancers may share key metabolic pathways with simple rare cancers, but it will take a while before we can effectively use this knowledge to develop effective treatments for the common cancers.

Cancer projections provided by the NCI's SEER program (the National Cancer Institute's Surveillance, Epidemiology, and End Results), indicate that between the years 2000 and 2050, the number of new cancer cases per year will more than double, from 1.3 million new cases in 2000 to 2.8 million new cases in 2050 (11). The projected yearly increase in cancer cases, if unchecked, will put additional strain on the wobbly American healthcare system.

After hundreds of billions of dollars were spent on cancer research and cancer treatment, with little to show for the effort, why did any of us believe that the dying would end by 2015? Humans live in hope; we would rather believe a hopeful lie than a hopeless truth.

- Jules Berman (copyrighted material)

key words: cancer, rare diseases, orphan diseases, cancer cure, cancer treatments, progress in cancer research, cancer statistics, jules j berman

References:

[1] MedicineNet. Better and Longer Survival for Cancer Patients. Available from: http://www.medicinenet.com/script/main/art.asp?articlekey=157

[2] Kaiser J. NCI Goal Aims for Cancer Victory by 2015. Science 299:1297-1298, 2003.

[3] Eschenbach AC. NCI sets goal of eliminating suffering and death due to cancer by 2015. Journal of the National Medical Association 95:637-639, 2003.

[4] Berman JJ. Precancer: The Beginning and the End of Cancer. Jones and Bartlett, Sudbury, 2010.

[5] Bailar JC, Gornik HL. Cancer undefeated. N Engl J Med 336:1569-1574, 1997.

[6] Leaf C. Why We're Losing The War On Cancer: And How To Win It. Fortune Magazine, March 22, 2004.

[7] Hoyert DL, Heron MP, Murphy SL, Kung H-C. Final Data for 2003. National Vital Statistics Report. 54:(13), April 19, 2006.

[8] Health, United States, 2004. National Center for Health Statistics, Hyattsville, Maryland, 2004.

[9] Ferlay J, Soerjomataram I, Ervik M, Dikshit R, Eser S, Mathers C, et al. GLOBOCAN 2012 v1.0, Cancer Incidence and Mortality Worldwide: IARC CancerBase No. 11. Lyon, France: International Agency for Research on Cancer, 2013.

[10] Ries LAG, Smith MA, Gurney JG, Linet M, Tamra T, Young JL, et al. Cancer Incidence and Survival among Children and Adolescents: United States SEER Program 1975-1995, National Cancer Institute, SEER Program. NIH Pub. No. 99-4649. Bethesda, MD, 1999.

[11] Hayat MJ, Howlader N, Reichman ME, Edwards BK. Cancer Statistics, Trends, and Multiple Primary Cancer Analyses from the Surveillance, Epidemiology, and End Results (SEER) Program. The Oncologist 12:20-37, 2007.

Links to Rare Disease Posts

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.

For today, I've listed my posts from prior years, featuring the rare diseases.

Phenocopy Mimics of Rare Diseases: Lessons for the Common Diseases

Phenocopy Diseases: Their Relationship to Rare Diseases and Common Diseases

What Rare Diseases Teach Us About the Cellular Basis of Aging

Disease Complexity: Rare Diseases and Common Diseases

Case Reports of Rare Diseases Have General Value

When Rare Diseases and Common Diseases Converge to Same Clinical Picture

Rare Diseases and Common Diseases can Converge to the Same Clinical Conditions

Rare Disease Legislation in the U.S.

Definition of Rare Disease

Developing Diagnostic Tests for Common Diseases: Role of the Rare Diseases

Rare Diseases Account for Subsets of Common Diseases

Improving Clinical Trials by Focusing on Rare Diseases

Rare Diseases of Unknown Origin

Rare Diseases are Sentinels for the Common Diseases

Biological Differences between Rare Cancers and Common Cancers

Rare Diseases are Biologically Different from Common Diseases

Rare Cancers are Biologically Different from Common Cancers

Rare Cancers

Clinical Trials and Rare Diseases

Rules for the Rare Diseases

The Rationale for Funding Rare Disease Research

New Book Explains the Importance of Rare Disease Research

- Jules Berman

key words: rare diseases, zebra diseases, orphan drugs, common diseases, pathology, principles of disease, pathogenesis, orphan diseases, complex diseases, genetics of disease, molecular biology of disease, epidemiology, sentinel, rare disease research, rare disease organizations, importance of rare diseases, funding for rare diseases, Jules J. Berman, Ph.D., M.D.

Rules for Rare Diseases

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.

For today, please consider these three biological "Rules" that I use when I'm trying to convince my colleagues of the importance of rare disease research.

Rule - Rare diseases are not the exceptions to the general rules of disease biology; they are the exceptions upon which the general rules are based.
Brief Rationale - All biological systems must follow the same rules. If a rare disease is the basis for a general assertion about the biology of disease, then the rule must apply to the common diseases.

Every rare disease tells us something about the normal functions of organisms. When we study a rare hemoglobinopathy, we learn something about the consequences that befall when the normal hemoglobin is replaced with an abnormal hemoglobin. This information leads us to a deeper understanding of the normal role of hemoglobin. Likewise, rare urea cycle disorders, coagulation disorders, metabolic disorders, and endocrine disorders have taught us how these functional pathways operate under normal conditions (1).

Rule - Every common disease is a collection of different diseases that happen to have the same clinical phenotype.
Brief Rationale - Numerous causes and pathways may lead to the same biological outcome.

Consider the heart attack; its risk of occurrence is elevated by dozens, many hundreds of factors. Obesity, poor diet, smoking, stress, lack of exercise, hypertension, diabetes, disorders of blood lipid metabolism, infections, male gender; they all contribute to heart attacks. Regardless of the contributing factors, a common event precedes and causes the heart attack; the blockage of a coronary artery. Blockage is often caused by an atherosclerotic plaque. Consequently, rare inherited conditions that produce atherosclerotic plaques can produce the common heart attack (e.g., inherited disorders of lipid metabolism). We infer that for every common disease, there are rare, inherited disease that account for a small subset of cases.

Rule - Rare diseases inform us how to treat common diseases.
Brief Rationale - When we encounter a common disease, we look to see what pathways are dysfunctional, and we develop a rational approach to prevention, diagnosis, and treatment based on experiences drawn from the rare diseases that are driven by the same dysfunctional pathways.

Many heart attacks are caused by atherosclerotic plaque blocking a coronary artery. Many conditions produce atherosclerotic plaque, but a rare condition known as familial hypercholesterolemia is associated with some cases of coronary atherosclerosis that occur in young individuals. Studies on familial hypercholesterolemia led to the finding that statins inhibit the rate-limiting enzyme in cholesterol synthesis (hydroxymethylglutaryl coenzyme A), thus reducing the blood levels of cholesterol and blocking the formation of plaque. The treatment of a pathway operative in a rare form of hypercholesterolemia has become the most effective treatment for commonly occurring forms of hypercholesterolemia, and a mainstay in the prevention of the common heart attack (2).

[1] Wizemann T, Robinson S, Giffin R. Breakthrough Business Models: Drug Development for Rare and Neglected Diseases and Individualized Therapies Workshop Summary. National Academy of Sciences, 2009.

[2] Stossel TP. The discovery of statins. Cell 134:903-905, 2008.

- Jules Berman (copyrighted material)

key words: rare diseases, biological rules, disease funding, common diseases, complex diseases, precision medicine, jules j berman

Genes that Cause More Than One Disease

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 related to the rare diseases.

There are numerous examples wherein mutations in one gene may result in more than one different diseases, usually depending on the mutation involved. In some cases, each of the diseases caused by the altered gene are 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 one example, diverse diseases that include 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. As another example, Stickler syndrome type III (STL3), Fibrochondrogenesis-2 and a form of non-syndromic hearing loss are all caused by mutations in the COL11A2 gene.

What is the significance of these observations? It tells us that it may be impossible to create a gene-based classification of diseases. Think about it: How can you group diseases by causal gene when the diseases caused by the gene are otherwise unrelated? It also tells us that there is a great deal that we do not understand about how genes cause diseases.

In the following list, each disease-causing gene is followed by the different diseases caused by gene alterations.

ABCB6 gene
The Lan(-) blood group phenotype
Microphthalmia, isolated, with coloboma 7

ACTA2 gene
Moyamoya disease-5
Form of thoracic aortic aneurysm

ACYLTRANSFERASE GENE
Fish-eye disease
Norum disease

ALPHA-SPECTRIN GENE
Hereditary spherocytosis-3
Elliptocytosis-2

ALPHA-SYNUCLEIN GENE
Parkinson disease-1
Autosomal dominant Parkinson disease-4

ALX4 gene
Frontonasal dysplasia-2
Parietal foramina-2

ANO5 gene
Gnathodiaphyseal dysplasia; gdd, or osteogenesis imperfecta with unusual skeletal lesions
Limb-girdle muscular dystrophy-2L
Miyoshi muscular dystrophy-3

ARX gene
Proud syndrome
Form of nonspecific X-linked mental retardation

ATN1 gene
Dentatorubral-pallidoluysian atrophy
Haw River syndrome

ATR gene
Seckel syndrome-1
Form of ataxia telangiectasia

BAG3 gene
Autosomal dominant myofibrillar myopathy
Dilated cardiomyopathy-1HH

BAP1 gene
Susceptibility to uveal melanoma
Predisposition to malignant mesothelioma upon asbestos exposure

BCS1L gene
Bjornstad syndrome
GRACILE syndrome

BUB1B gene
Mosaic variegated aneuploidy syndrome-1 (See Glossary item, Aneuploidy)
Form of premature chromatid separation

C20ORF54 gene
Brown-Vialetto-Van Laere syndrome, a ponto-bulbar palsy with deafness
Fazio-Londe disease

CACNA1A gene
Familial hemiplegic migraine
Spinocerebellar ataxia 6

CACNA1F gene
X-linked cone-rod dystrophy-3
Aland Island eye disease

CARD15 gene
Early-onset sarcoidosis
Blau syndrome

CASK gene
FG syndrome-4 ("FG" are the initials of the first proband)
Mental retardation, x-linked, with or without nystagmus
Mental retardation and microcephaly with pontine and cerebellar hypoplasia

CAVEOLIN-3 GENE
Limb-girdle muscular dystrophy type 1C
Tateyama type of distal myopathy

CEP152 gene
Autosomal recessive primary microcephaly-4
Seckel syndrome-5

CEP290 gene
Bardet-Biedl syndrome 14
Joubert syndrome 5
Leber congenital amaurosis 10
Meckel syndrome 4
Senior-Loken syndrome 6

CHAT (Choline acetyltransferase) gene
Presynaptic congenital myasthenia syndrome with episodic ataxia
Familial infantile myasthenia gravis

CHX10 gene

Microphthalmia, isolated-2
Microphthalmia with coloboma-3
Isolated colobomatous microphthalmia-3

CLCN5 gene
X-linked recessive hypophosphatemic rickets
X-linked recessive nephrolithiasis with renal failure
Dent disease-1

CLN8 gene
Neuronal ceroid lipofuscinosis-8
Progressive epilepsy with mental retardation

CLRN1 gene
Usher syndrome type IIIA
Retinitis pigmentosa-61

COL11A2 gene
Stickler syndrome type III
Fibrochondrogenesis-2
Form of nonsyndromic hearing loss

COL2A1 gene
Stickler syndrome type I, sometimes called membranous vitreous type
Osteoarthritis with mild chondrodysplasia
Achondrogenesis type II
Czech dysplasia

COL7A1 gene
Classic dystrophic epidermolysis bullosa pruriginosa
Nonsyndromic congenital nail disorder-8

COL9A1 gene
Form of autosomal recessive form of Stickler syndrome
Multiple epiphyseal dysplasia-6

COL9A2 gene
Multiple epiphyseal dysplasia-2
Stickler syndrome type V

COLLAGEN GENE
Autosomal dominant epidermolysis bullosa dystrophica
Pretibial dystrophic epidermolysis bullosa
Stickler syndrome
Strudwick type of spondyloepimetaphyseal dysplasia
Spondyloperipheral dysplasia
Ehlers-Danlos syndrome type IV

CONNEXIN-26 GENE
Keratitis-ichthyosis-deafness syndrome
Deafness, autosomal dominant-3A

CRYAB gene
Posterior polar cataract-2
Fatal infantile hypertonic myofibrillar myopathy

CYLD gene
Familial cylindromatosis
Multiple familial trichoepithelioma-1
Brooke-Spiegler syndrome

DOCK8 gene
Hyper-IgE recurrent infection syndrome, also known as Job syndrome
Autosomal dominant mental retardation-2

DYM gene
Dyggve-Melchior-Clausen disease
Smith-McCort dysplasia

DYNC1H1 gene
Autosomal dominant axonal Charcot-Marie-Tooth disease type 2O
Autosomal dominant mental retardation-13

ENPP1 gene
Generalized arterial calcification of infancy-1
Autosomal recessive hypophosphatemic rickets-2

ESCO2 gene
SC phocomelia syndrome, also known as SC pseudothalidomide syndrome
Roberts syndrome

FBLN5 gene
Autosomal recessive cutis laxa type IA
Macular degeneration, age-related-3

FBN1 gene
Acromicric dysplasia
Stiff skin syndrome
Autosomal dominant form of isolated ectopia lentis
Weill-Marchesani syndrome-1
Weill-Marchesani syndrome-2
Geleophysic dysplasia-2

FGFR1 gene
Trigonocephaly-1
8p11 myeloproliferative disorder

FGFR2 gene
Beare-Stevenson cutis gyrata syndrome
Form of craniosynostosis
Classic Crouzon syndrome

FGFR3 gene
Muenke craniosynostosis syndrome
Hypochondroplasia
CATSHL syndrome
Crouzon syndrome with acanthosis nigricans

FIG4 gene
Charcot-Marie-Tooth type 4J
Form of autosomal dominant ALS
Amyotrophic lateral sclerosis 11

FLNA gene
Terminal osseous dysplasia
FG syndrome-2
X-linked cardiac valvular dysplasia

FLNC gene
Filamin C-related myofibrillar myopathy
Distal myopathy-4 (MPD4), also known as Williams distal myopathy

FMR1 gene
Fragile X tremor/ataxia syndrome
Fragile X mental retardation syndrome

FOXL2 gene
Blepharophimosis, ptosis, and epicanthus inversus syndrome, with premature ovarian failure (BPES type I)
Blepharophimosis, ptosis, and epicanthus inversus syndrome, without premature ovarian failure without premature ovarian failure (BPES type II)

FREM1 gene
Bifid nose with or without anorectal and renal anomalies
Trigonocephaly-2

GATA2 gene
Primary lymphedema with myelodysplasia
Dendritic cell, monocyte, B lymphocyte, and natural killer lymphocyte deficiency

GDAP1 gene
Autosomal recessive axonal CMT with vocal cord paresis
Autosomal recessive demyelinating CMT4A
Autosomal recessive axonal Charcot-Marie-Tooth disease type 2K

GDF3 gene
Klippel-Feil syndrome-3
Isolated microphthalmia with coloboma-6
Isolated microphthalmia-7

GDF6 gene
Klippel-Feil syndrome-1
Isolated microphthalmia-4

GJA1 gene
Syndactyly type III
Oculodentodigital dysplasia
Atrioventricular septal defect 3

GJB2 gene
Autosomal recessive deafness-1A
Hystrix-like ichthyosis-deafnesss syndrome

GJC2 gene (encodes gap junction protein, gamma 2)
Autosomal recessive spastic paraplegia-44
Hereditary lymphedema type IC
Form of Pelizaeus-Merzbacher disease

GLUCOKINASE GENE
Familial hyperinsulinemic hypoglycemia-3
Maturity onset diabetes of the young-2

GNAS gene
Progressive osseous heteroplasia
Pseudopseudohypoparathyroidism
Pseudohypoparathyroidism type Ia

GPR143 gene
Ocular albinism type I
X-linked congenital nystagmus-6
Nystagmus 6, congenital, X-linked

HCN4 gene
Brugada syndrome-8
Autosomal dominant form of sick sinus syndrome

HEDGEHOG GENE
Holoprosencephaly-3
Isolated microphthalmia with coloboma-5

HPRT gene
Lesch-Nyhan syndrome
Kelley-Seegmiller syndrome

HRG gene
Histidine-rich glycoprotein deficiency
Thrombocythemia-11

HSPB8 gene
HMN2A
Axonal Charcot-Marie-Tooth disease type 2L
HMN2A

IGHMBP2 gene
Distal hereditary motor neuronopathy type VI (dHMN6 or HMN6)
Spinal muscular atrophy, with respiratory distress-1

INF2 gene
FSGS5
Focal segmental glomerulosclerosis-5
Charcot-Marie-Tooth disease E with focal segmental glomerulonephritis

JAK2 gene
Thrombocythemia-3
Polycythemia vera, the most common form of primary polycythemia

KCNE2 gene
ATFB4
Form of atrial fibrillation
Long QT syndrome-6

KCNH2 gene
Long QT syndrome-2
Short QT syndrome-1

KCNJ11 gene
Hyperinsulinemic hypoglycemia-2 (HHF2)
TNDM3

KCNJ5 gene
Familial hyperaldosteronism type III
Long QT syndrome-13

KCNQ1 gene
Form of Jervell and Lange-Nielsen syndrome (JLNS1)
Form of autosomal dominant atrial fibrillation
ATFB3 (607554)
Short QT syndrome-2

KIF1A gene
Hereditary sensory neuropathy type IIC
Form of mental retardation

KLF1 gene
Congenital dyserythropoietic anemia type IV (See Glossary item, Dyserythropoiesis)
Form of hereditary persistence of fetal hemoglobin

KRT74 gene
Hypotrichosis simplex of the scalp-2
Autosomal dominant form of woolly hair
Hypotrichosis simplex of the scalp-2

LDB3 gene
Left ventricular noncompaction-3
Form of dilated cardiomyopathy with or without left ventricular noncompaction

LMNA gene
Form of autosomal recessive axonal CMT
Slovenian type heart-hand syndrome

LRP4 gene
Cenani-Lenz syndactyly syndrome
Sclerosteosis-2

LRP5 gene
Familial exudative vitreoretinopathy-4
Autosomal dominant osteopetrosis type I

MATRILIN-3 GENE
Form of multiple epiphyseal dysplasia
Form of autosomal recessive spondyloepimetaphyseal dysplasia

MECP2 gene
Form of neonatal severe encephalopathy
Classic Rett syndrome

MED12 gene
Lujan-Fryns syndrome
Opitz-Kaveggia syndrome, also known as FG syndrome-1

MFRP gene
Posterior microphthalmia, retinitis pigmentosa, foveoschisis, and optic disc drusen
MCOP5

MLL2 gene
Kabuki syndrome-1
Otitis media in infancy

MSX1 gene
Form of selective tooth agenesis
Orofacial cleft 5
Witkop syndrome

MYH6 gene
Familial hypertrophic cardiomyopathy-14
Form of dilated cardiomyopathy

MYH7 gene
Form of scapuloperoneal myopathy
Hypertrophic cardiomyopathy-1
Cardiomyopathy, dilated, 1S

MYH9 gene
Fechtner syndrome
May-Hegglin anomaly
Sebastian syndrome

NEMO gene
Anhidrotic ectodermal dysplasia with immunodeficiency, osteopetrosis, and lymphedema
Atypical mycobacteriosis, familial
Familial incontinentia pigmenti
Invasive pneumococcal disease, recurrent isolated, type 2

NF1 gene
Neurofibromatosis-1
Watson syndrome
Neurofibromatosis-Noonan syndrome variant of neurofibromatosis-1

NHS gene
Nance-Horan syndrome
X-linked congenital cataract

NKX2-5 gene
Atrial septal defect of the secundum type, with or without atrioventricular conduction defects
Congenital nongoitrous hypothyroidism-5
Hypoplastic left heart syndrome-2

NOTCH2 gene
Hajdu-Cheney syndrome
Alagille syndrome-2

NPHP1 gene
Senior-Loken syndrome-1
Form of Joubert syndrome plus nephronophthisis

NPHP3 gene
Meckel syndrome, type 7
Nephronophthisis-3

NPHP4 gene
Form of Senior-Loken syndrome that maps to 1p36
Type 4 nephronophthisis

NPHP6 gene
Form of Senior-Loken syndrome that maps to 12q21-32
Joubert syndrome-5

NR0B1 gene
X-linked congenital adrenal hypoplasia with hypogonadotropic hypogonadism
46,XY sex reversal-2

NR5A1 gene
Premature Ovarian Failure-7
Form of 46,XY sex reversal

NRAS gene
Form of Noonan syndrome (NS6)
Form of autoimmune lymphoproliferative syndrome, designated type IV (ALPS4)

NSD1 gene
Familial Sotos syndrome
Sotos syndrome
Weaver syndrome-1
Classic Sotos syndrome

OPTN gene
Amyotrophic lateral sclerosis-12
Form of adult-onset primary open angle glaucoma (POAG), designated GLC1E

P63 GENE
Ectrodactyly, ectodermal dysplasia, and cleft lip/palate syndrome-3
Split-hand/split-foot malformation

PAX3 gene
Craniofacial-deafness-hand syndrome
Waardenburg syndrome type-3
Waardenburg syndrome type-1

PDE6B gene
Autosomal dominant congenital stationary night blindness-2
Form of retinitis pigmentosa

PDE8B gene
Autosomal dominant striatal degeneration
Primary pigmented nodular adrenocortical disease-3

PDX1 gene
Congenital pancreatic agenesis
Maturity onset diabetes of the young-4

PIGA gene
Paroxysmal nocturnal hemoglobinuria
Multiple congenital anomalies-hypotonia-seizures syndrome-2

PLA2G6 gene
Neurodegeneration with brain iron accumulation-2A
Neurodegeneration with brain iron accumulation-2B
Adult-onset dystonia-parkinsonism, also known as Parkinson disease-14

PLEC1 gene
Epidermolysis bullosa simplex with pyloric atresiawhich
Epidermolysis bullosa simplex
Autosomal recessive limb-girdle muscular dystrophy type 2Q

POLG gene
Alpers syndrome
Neurogastrointestinal encephalopathy

POLYMERASE-GAMMA GENE
Autosomal recessive progressive external ophthalmoplegia (PEOB)
Sensory ataxic neuropathy, dysarthria, and ophthalmoparesis

POMGNT1 gene
Walker-Warburg syndrome (WWS) or muscle-eye-brain disease
Muscular dystrophy-dystroglycanopathy-B3
Muscular dystrophy-dystroglycanopathy-C3

PRKAR1A gene
Acrodysostosis with hormone resistance
Carney complex, type 1

PROM1 gene
Macular dystrophy, retinal, type 2
Stargardt disease-4

PROMININ-1 GENE
Stargardt disease-4
Retinal macular dystrophy-2
Cone-rod dystrophy-12

PRPS1 gene
Arts syndrome
X-linked deafness-1

PRRT2 gene
Familial infantile convulsions with paroxysmal choreoathetosis
Benign familial infantile seizures-2
Paroxysmal kinesigenic dyskinesia

PSEN1 gene
Dilated cardiomyopathy-1U
Familial acne inversa-3
Form of early onset Alzheimer's disease

PTPN11 gene
Noonan syndrome-1
Metachondromatosis

PYCR1 gene
Autosomal recessive cutis laxa type IIIB
Autosomal recessive cutis laxa type IIB

RAB27A gene
Melanosis with immunologic abnormalities with or without neurologic impairment
Griscelli syndrome type 2

RAF1 gene
Form of Noonan syndrome
LEOPARD syndrome-2

RDS gene
Retinitis pigmentosa-7
Adult-onset vitelliform macular dystrophy (AVMD)

RET gene
Susceptibility to Hirschsprung disease-1
Multiple endocrine neoplasia-2B
Familial medullary thyroid carcinoma MTC

ROR2 gene
Brachydactyly type B1
Autosomal recessive Robinow syndrome

RPE65 gene
Leber congenital amaurosis-2
Form of autosomal recessive retinitis pigmentosa

RPGR gene
Retinitis pigmentosa-3
X-linked cone-rod dystrophy
X-linked retinitis pigmentosa with recurrent respiratory infections

RPGRIP1 gene
Autosomal recessive cone-rod dystrophy-13
Leber congenital amaurosis-6

SAMHD1 gene
Aicardi-Goutieres syndrome-5
Chilblain lupus-2

SCN1A gene
Febrile seizures, familial, type 3A
Familial hemiplegic migraine-3

SCN1B gene
Generalized epilepsy with febrile seizures plus, type 1
Brugada syndrome-5

SCN2A gene
Benign familial neonatal-infantile seizures-3
Early infantile epileptic encephalopathy-11

SCN4A gene
Hypokalemic periodic paralysis type 2
Form of congenital myasthenic syndrome

SCN5A gene
Brugada syndrome-1
Long QT syndrome-3
Sick sinus syndrome (some cases)
Atrial fibrillation, (some cases)
Dilated cardiomyopathy (some cases)

SEMA4A gene
Form of RP
Cone-rod dystrophy-10

SH3TC2 gene
Charcot-Marie-Tooth disease type 4C
Mild mononeuropathy of the median nerve

SHH gene
Holoprosencephaly-3
Microphthalmia with coloboma 5

SLC16A1 gene
Erythrocyte lactate transporter defect
Form of hyperinsulinemic hypoglycemia

SLC25A19 gene
Amish lethal microcephaly
Thiamine metabolism dysfunction syndrome-3
Bilateral striatal degeneration and progressive polyneuropathy

SLC26A4 gene
Enlarged vestibular aqueduct
Pendred syndrome

SLC2A1 gene
Dystonia 18 (DYT18)
Autosomal recessive primary hypertrophic osteoarthropathy-2

SLC33A1 gene
Spastic paraplegia-42
Congenital cataracts, hearing loss, and neurodegeneration

SLC34A1 gene
Autosomal recessive form of Fanconi renotubular syndrome
Hypophosphatemic nephrolithiasis/osteoporosis-1
Fanconi renotubular syndrome-2

SLC4A1 gene
Band 3 Coimbra
Waldner blood group expression
Autosomal recessive distal renal tubular acidosis with hemolytic anemia

SLC4A11 gene
Corneal endothelial dystrophy-2
Fuchs endothelial corneal dystrophy-4

SMAD4 gene
Myhre syndrome
Juvenile polyposis syndrome

SOS1 gene
Gingival fibromatosis-1
Form of Noonan syndrome

SOST gene
Craniodiaphyseal dysplasia, autosomal dominant
SclerosteosiS
Van Buchem disease

STAT1 gene
Mycobacterial and viral infections, susceptibility to, autosomal recessive
Familial chronic mucocutaneous candidiasis-7

SYCP3 gene
Spermatogenic failure 4
Recurrent pregnancy loss 4

TGFBR2 gene
Loeys-Dietz syndrome type 2B
Hereditary nonpolyposis colorectal cancer-6

TITIN GENE
Autosomal dominant dilated cardiomyopathy-1G
Limb-girdle muscular dystrophy type 2J
Tardive tibial muscular dystrophy

TMEM216 gene
Meckel syndrome type 2
Joubert syndrome-2

TNFRSF13B gene
Immunoglobulin A (IgA) deficiency-2
Common variable immunodeficiency-2

TREX1 gene
Aicardi-Goutieres syndrome-1 (can also be caused by mutations in the SAMHD1, TREX1, or Ribonuclease H2 genes)
Chilblain lupus-1

TRPV4 gene
Brachyolmia type 3
Metatropic dysplasia
Parastremmatic dwarfism
Form of scapuloperoneal spinal muscular atrophy
Maroteaux type of spondyloepiphyseal dysplasia
Kozlowski type of spondylometaphyseal dysplasia
Congenital distal spinal muscular atrophy
Hereditary motor and sensory neuropathy type IIC

TTR gene
Form of hereditary amyloidosis
Euthyroidal hyperthyroxinemia

TULP1 gene
Retinitis pigmentosa-14
Leber congenital amaurosis-15

VHL gene
Von Hippel-Lindau syndrome
Familial erythrocytosis-2

VSX1 gene
Posterior polymorphous corneal dystrophy-1
Craniofacial anomalies and anterior segment dysgenesis syndrome

WAS gene
Wiskott-Aldrich syndrome
X-linked thrombocytopenia
X-linked neutropenia

WDR35 gene
Cranioectodermal dysplasia-2
Short rib-polydactyly syndrome type V

WNK1 gene
Hereditary sensory and autonomic neuropathy type IIA
Form of pseudohypoaldosteronism type II

- Jules Berman

key words: rare diseases, allelic heterogeneity, allelic to, polymorphism, gene variation, genetic heterogeneity, genetics, genetics of disease, jules j berman

Rare Diseases: High Priority in Precision Medicine

It is very difficult to steer medical scientists away from their belief that common diseases are more important than rare diseases. Too often, scientists are persuaded by the observation that a few dozen common diseases account for the vast majority of the morbidity and mortality suffered by humans. Hence, a breakthrough in treating any of the common diseases will benefit many more people than an advance in any of the rare diseases. The reasoning seems flawless, but research targeted at the common diseases has been disappointing. In the past 50 years, most of the major advances in medicine have involved the rare diseases. Advances in the common diseases have come about as a consequence of discoveries made on rare diseases.

As it happens, the rare diseases are much easier to understand and treat than the common diseases. If we waited for medical scientists to cure the common diseases, we would miss our currently available opportunity to cure diseases, either rare or common.

Rule - Rare diseases are easier to treat than common diseases.

Brief Rationale - Rare diseases have simple genetic defects, have little heterogeneity, and have few metabolic options with which they can evade targeted treatments.

Ryanodine receptor 2 mutations are responsible for several rare arrhythmia syndromes in humans (e.g., forms of catecholaminergic polymorphic ventricular tachycardia and arrhythmogenic right ventricular dysplasia) Individuals with these disorders can be treated with drugs that stabilize the receptor. Damage to ryanodine receptor 2 seems to occur as a component of common heart failure; leading to calcium leak and arrhythmia. Preliminary studies indicate that drugs that stabilize the receptor may ameliorate all types of heart failure and the lethal arrhythmias that ensue (2). Thus, our deep understanding of a rare disease had led us to a general understanding of a common disease.

Alexion is a pharmaceutical company that specializes in developing drugs intended to treat rare diseases. For example, Alexion discovered and developed Eculizumab (trade name Soliris), a first-in-class terminal complement inhibitor. Eculizumab was approved by the FDA in 2007 for the treatment of paroxysmal nocturnal hematuria; and in 2011 for the treatment of atypical hemolytic uremic syndrome. Subsequently, eculizumab was tested for its effectiveness for several common diseases. Eculizumab was a candidate treatment for so-called dry age-related macular degeneration, a common disease; though it was not shown to be effective (3). On the brighter side, eculizumab has been shown to prevent acute and chronic rejection in certain subsets of patients who received renal transplants (4). When you have a drug that is known to target a particular member of an active physiologic pathway, it is likely to have some benefit in one or more common diseases whose clinical phenotype is due, in part, to aberrations of the same pathway.

Rule - Dugs that are safe and effective against rare diseases will be used in the treatment of one or more common diseases.

Brief Rationale - The rare diseases, as an aggregate group, comprise every possible pathogenic pathway available to cells. Hence, pathogenic pathways that are active in the common diseases will be active in one or more rare diseases. Agents that target pathways in the rare diseases are candidate treatments for the common diseases with which they share active pathways.

Wrinkled skin is one of the most common physical conditions. Every man and woman who lives long enough will wrinkle a bit. For some individuals, wrinkling is problem that merits medical attention. Botox (botulism toxin) is the drug du jour for treating wrinkles. Botox is also one of the most powerful poisons known. How did it come about that Botox emerged as a popular wrinkle treatment? Botox was original developed, tested, and approved to treat several rare diseases characerized by uncontrolled blinking. After approval was awarded, botox was found to be extremely effective for rare spasmodic conditions, including spasmodic torticollis (i.e. wry neck). In the course of treating rare diseases, it was noticed that Botox injections could temporarily erase wrinkles. The rest is history. The Botox story exemplifies how an effective treatment developed for a rare diseases can gain popularity as a treatment for a common conditions.

Rule - It is much more useful to treat a disease pathway than it is to treat the individual gene mutation or its expressed protein.

Brief Rationale - Many different diseases may respond to a drug that targets a pathogenic pathway, while only one genetic variant of one rare disease is likely to respond to a drug that targets the disease-causing gene or its expressed protein.

There is a very important lesson to be learned: Treat the pathway, not the gene. This lesson is somewhat counter-intuitive and is received with some skepticism from experienced medical researchers. Nonetheless, it is a core principal that diseases are caused by perturbed pathways, and that the successful treatment of diseases have always involved compensating, in one way or another, for pathway disturbances. Let us review some examples that demonstrate the point.

Imatinib (trade name Gleevec) inhibits tyrosine kinase, an enzyme involved in a pathway that drives the growth of various rare tumors and proliferative diseases (e.g., chronic myelogenous leukemia, gastrointestinal stromal tumor, hypereosinophilic syndrome) (5), (6), (7), (8), (9). Pathways with increased tyrosine kinase activity, and pathways whose tyrosine kinase activity is particularly sensitive to the inhibiting action of imatinib would make the best drug targets. Because Imatinib is targeted to a key protein in a general pathway that contributes to a proliferative phenotype, it has potential benefit in diseases caused by mutations in genes other than tyrosine kinase.

Bevacizumab, trade name Avastin, is an angiogenesis (i.e., vessel-forming) inhibitor (See Glossary item, Angiogenesis). All cancers require vessel growth. In theory, bevacizumab is a universal tumor growth inhibitor because its target is the non-neoplastic mesenchymal cells that form the vessels that feed growing tumor cells. Bevacizumab is employed in the treatment of common cancers, including cancers of the colon, lung, breast, kidney, ovaries, and brain (i.e., glioblastoma). Bevacizumab produces tumor shrinkage in more than half of vestibular schwannomas occurring in Neurofibromatosis 2 (10). As you might expect, Bevacizumab has its greatest value in diseases for which neovascularization has a required role in pathogenesis. Two non-cancerous diseases of vascularization, treated with angiogenesis inhibitors, are hereditary hemorrhagic telangiectasia (11), and various forms of ocular neovascularization, including common age-related macular degeneration (12).

Because pathways are interconnected, a drug that is effective against a component of a pleiotrophic pathway may be effective against multiple diseases. For example, Janus Kinase genes (e.g., AK1, JAK2, JAK3, TYK2) influence the growth and immune responsiveness in various blood cells, through their activity on cytokines. Mutations of the JAK2 gene are involved in several myeloproliferative conditions, including myelofibrosis, polycythemia vera, and at least one form of hereditary thrombocythemia (13), (14), (15).

Inhibitors of JAK genes have been approved for the treatment of various diseases that involve heightened proliferation of lymphocytes, in immune reactions, or blood cells, in myeloproliferative disorders. Ruxolitinib has been approved, in the U.S. for use in psoriasis, myelofibrois and rheumatoid arthritis (16). A host of JAK pathway inhibitors are either approved or under clinical trials for the treatment of allergic diseases, rheumatoid arthritis, psoriasis, myelofibrosis, myeloproliferative disorders, acute myeloid leukemia, and relapsed lymphoma (17). Again, specialized knowledge of rare diseases had led to generalized methods of treating a variety of related diseases, some of which are quite common.

Rule - Common diseases and rare diseases that share a pathway are likely to respond to the same pathway-targeted drug.

Brief Rationale - Pathogenesis (i.e., the biological steps that lead to disease) and clinical phenotype (i.e., the biological features that characterize a disease) are determined by cellular pathways. If a pathway has a crucial role in the development of disease, then you would have reason to hope that drugs that disrupt the pathway will alter the progression and the expression of the disease, whether the disease is common or rare.

Individuals with a rare resistance to HIV infection have a specific deletion in the gene that codes for the CCR5 co-receptor. The gene plays a role in the entry of HIV into cells; no entry, no infection. As it happens, both HIV virus and smallpox virus enhance their infectivity by exploiting a receptor, CCR5, on the surface of white blood cells. This shared mode of infection may contribute to the cross-protection against HIV that seems to come from smallpox vaccine. It has been suggested that the emergence of HIV in the 1980s may have resulted, in part, from the cessation of smallpox vaccinations in the late 1970s (18). The same, rare CCR5 gene deletion that protects against HIV infection may very well protect against smallpox infection. We may never know with certainty whether this is true because smallpox has been eradicated, along with smallpox experiments. Nonetheless, knowledge of the role of CCR5 in HIV infection has inspired the development of a new class of HIV drugs targeted against entry receptors (19).

Individuals with genetic absence of Duffy antigen receptor for chemokines (i.e., DARC, formerly known as Duffy blood group antigen) are protected from malaria cased by Plasmodium vivax. It turns out that entry of the parasite requires participation by DARC (20), (21). A new vaccine candidate for P. vivax malaria, targeted against the Duffy binding protein was developed based on observations of naturally occurring resistance in individuals lacking DARC (22), (20).

Osteoporosis-pseudoglioma syndrome is a rare disease characterized clinically by multiple bone fractures and various eye and neurologic abnormalities. It is caused by loss-of-function mutations in the low-density lipoprotein receptor-related protein-5 (LRP5). LRP5, under normal conditions, reduces the production of serotonin in the gut. Based on rare disease research directed towards understanding the role of LRP5, agents that compensate for the reduction in LRP5 by reducing gut serotonin are candidate drugs for the treatment of both rare osteoporosis-pseudoglioma syndrome, and common osteoporosis (23) (24), (25).

Of course, advances in the common diseases may have value in treating rare diseases. Losartan is an effective drug against one of the most common diseases of humans: hypertension. Losartan blocks the angiotensin II type 1 receptor, and it also blocks TGF-alpha (Transforming Growth Factor-alpha). In Marfan syndrome, a rare disease of connective tissue, growth of the aortic root may lead to life-threatening aortic aneurysm. A reduction in TGF-alpha activity, following losartan treatment, reduces growth of the aortic root, and slows the progression of aortic root distension in Marfan syndrome (26).

Shared cures for the rare diseases and the common diseases do not occur as low-probability events in an unpredictable world. Knowledge of disease biology leads us to conclude that whenever a cure for a rare disease is found, there is a high likelihood that this same cure will have practical application in the treatment of a common disease. Pharmaceutical companies understand that rare disease research and common disease research is often the prelude to common disease research (27).

It is crucially important to appreciate the role of rare diseases in drug development. If funding agencies do not appreciate how cures for the rare diseases will lead to cures for the common diseases, the field of rare disease research will continue to be under-funded and generally ignored by the medical research community.

References

[1] Holland Frei Cancer Medicine. Kufe D, Pollock R, Weichselbaum R, Bast R, Gansler T, Holland J, Frei E, eds. BC Decker, Ontario, Canada, 2003.

[2] Yamamoto T, Yano M, Xu X, Uchinoumi H, Tateishi H, Mochizuki M, et al. Identification of target domains of the cardiac ryanodine receptor to correct channel disorder in failing hearts. Circulation 117:762-772, 2008.

[3] Leung E, Landa G. Update on current and future novel therapies for dry age-related macular degeneration. Expert Rev Clin Pharmacol Aug 24, 2013.

[4] Legendre C, Sberro-Soussan R, Zuber J, Rabant M, Loupy A, Timsit MO, et al. Eculizumab in renal transplantation. Transplant Rev (Orlando) 27:90-92, 2013.

[5] Berman J, O'Leary TJ. Gastrointestinal stromal tumor workshop. Hum Pathol. 2001 Jun;32(6):578-82.

[6] Heinrich MC, Joensuu H, Demetri GD, Corless CL, Apperley J, Fletcher JA, et al. Phase II, Open-Label study evaluating the activity of Imatinib in treating life-threatening malignancies known to be associated with Imatinib-Sensitive Tyrosine Kinases. Clin Cancer Res 14:2717-2725, 2008.

[7] Heinrich MC, Corless CL, Demetri GD, Blanke CD, von Mehren M, Joensuu H, et al. Kinase mutations and imatinib response in patients with metastatic gastrointestinal stromal tumor. J Clin Oncol 21:4342-4349, 2003.

[8] Selvi N, Kaymaz BT, Sahin HH, Pehlivan M, Aktan C, Dalmizrak A, et al. Two cases with hypereosinophilic syndrome shown with real-time PCR and responding well to imatinib treatment. Mol Biol Rep 40:1591-1597, 2013.

[9] Cools J, DeAngelo DJ, Gotlib J, Stover EH, Legare RD, Cortes J, et al. A tyrosine kinase created by fusion of the PDGFRA and FIP1L1 genes as a therapeutic target of imatinib in idiopathic hypereosinophilic syndrome. New Eng J Med 348:1201-1214, 2003.

[10] Plotkin SR, Merker VL, Halpin C, Jennings D, McKenna MJ, Harris GJ, et al. Bevacizumab for progressive vestibular schwannoma in neurofibromatosis type 2: a retrospective review of 31 patients. Otol Neurotol 33:1046-1052, 2012.

[11] Bose P, Holter JL, Selby GB. Bevacizumab in hereditary hemorrhagic telangiectasia. N Engl J Med 360:2143-2144, 2009.

[12] Eyetech Study Group. Anti-vascular endothelial growth factor therapy for subfoveal choroidal neovascularization secondary to age-related macular degeneration: phase II study results. Ophthalmology 110:979-86, 2003.

[13] Mead AJ, Rugless MJ, Jacobsen SEW, Schuh A, Germline JAK2 mutation in a family with hereditary thrombocytosis. New Eng J Med 366:967-969, 2012.

[14] Barosi G, Bergamaschi G, Marchetti M, Vannucchi AM, Guglielmelli P, Antonioli E, et al. JAK2 V617F mutational status predicts progression to large splenomegaly and leukemic transformation in primary myelofibrosis. Blood 110:4030-4036, 2007.

[15] Zhang L, Lin X. Some considerations of classification for high dimension low-sample size data. Stat Methods Med Res. 2011 Nov 23. Available from: http://smm.sagepub.com/content/early/2011/11/22/0962280211428387.long, viewed January 26, 2013.

[16] Mesa RA, Yasothan U, Kirkpatrick P. Ruxolitinib. Nat Rev Drug Discov 11:103-104, 2012.

[17] Pesu M, Laurence A, Kishore N, Zwillich SH, Chan G, O'Shea JJ. Therapeutic targeting of Janus kinases. Immunol Rev 223:132-42, 2008.

[18] Smallpox demise linked to spread of HIV infection. BBC News May 17, 2010.

[19] Huang Y, Paxton WA, Wolinsky SM, Neumann AU, Zhang L, He T, et al. The role of a mutant CCR5 allele in HIV-1 transmission and disease progression. Nat Med 2:1240-1243, 1996.

[20] Arevalo-Herrera M, Castellanos A, Yazdani SS, Shakri AR, Chitnis CE, Dominik R, et al. Immunogenicity and protective efficacy of recombinant vaccine based on the receptor-binding domain of the Plasmodium vivax Duffy binding protein in Aotus monkeys. Am J Trop Med Hyg 73:25-31, 2005.

[21] Miller LH, Mason SJ, Clyde DF, McGinniss MH. The resistance factor to Plasmodium vivax in blacks. The Duffy-blood-group genotype, FyFy. N Engl J Med 295:302-304, 1976.

[22] Hill AVS. Evolution, revolution and heresy in the genetics of infectious disease susceptibility. Philos Trans R Soc Lond B Biol Sci 367:840-849, 2012.

[23] Long F. When the gut talks to bone. Cell 135:795-796, 2008.

[24] Field MJ, Boat T. Rare Diseases and Orphan Products: Accelerating Research and Development. Institute of Medicine (US) Committee on Accelerating Rare Diseases Research and Orphan Product Development. 2010. The National Academics Press, Washington, D.C. Available from: http://www.ncbi.nlm.nih.gov/books/NBK56189/

[25] Zhang W, Drake MT. Potential role for therapies targeting DKK1, LRP5, and serotonin in the treatment of osteoporosis. Curr Osteoporos Rep 10:93-100, 2012.

[26] Chiu HH, Wu MH, Wang JK, Lu CW, Chiu SN, Chen CA, et al. Losartan added to beta-blockade therapy for aortic root dilation in Marfan syndrome: a randomized, open-label pilot study. Mayo Clin Proc 88:271-276, 2013.

[27] Ayme S, Hivert V (eds.), "Report on rare disease research, its determinants in Europe and the way forward", INSERM, May 2011. Available from: http://asso.orpha.net/RDPlatform/upload/file/RDPlatform_final_report.pdf, viewed February 26, 2013.

- Jules Berman (copyrighted material)

key words: rare diseases, orphan drugs, precision medicine, medical research, research funding, justification for medical research, jules j berman

Precision Medicine meets the Data Complexity Barrier

A funny thing happened on the way to "Precision Medicine". It seems that many of the fundamental studies in the field of pharmacogenomics and personalized medicine are yielding irreproducible results. We find that we can not depend on the data that we depend on. If you don't believe me, consider these shocking headlines:

1. "Unreliable research: Trouble at the lab." (1) The Economist, in 2013 ran an article examining flawed biomedical research. The magazine article referred to an NIH official who indicated that "researchers would find it hard to reproduce at least three-quarters of all published biomedical findings." The article also described a study conducted at the pharmaceutical company Amgen, wherein 53 landmark studies were repeated. The Amgen scientists were successful at reproducing the results of only 6 of the 53 studies. Another group, at Bayer HealthCare, repeated 63 studies. The Bayer group succeeded in reproducing the results of only one-fourth of the original studies.

2. "A decade of reversal: an analysis of 146 contradicted medical practices." (2) The authors reviewed 363 journal articles, reexamining established standards of medical care. Among these articles were 146 manuscripts (40.2%) claiming that an existing standard of care had no clinical value.

3."Cancer fight: unclear tests for new drug." (3). This New York Times article examined whether a common test performed on breast cancer tissue (Her2) was repeatable. It was shown that for patients who tested positive for Her2, a repeat test indicated that 20% of the original positive assays were actually negative (i.e., falsely positive on the initial test). (3).

4. "Why most published research findings are false." (4). Modern scientists often search for small effect sizes, using a wide range of available analytic techniques, and a flexible interpretation of outcome results. Under such conditions, the manuscript author found that research conclusions are more likely to be false than true (4).

5. "Reproducibility crisis: Blame it on the antibodies" (5). Biomarker developers are finding that they cannot rely on different batches of a reagent to react in a consistent manner, from test to test. Hence, laboratory analytic methods, developed using a controlled set of reagents, may not have any diagnostic value when applied by other laboratories, using different sets of the same analytes (5).

Anyone who tries to stay current in biomedical research understands that much of the published literature is irreproducible (6); and that almost anything published today might be retracted tomorrow. This appalling truth applies to some of the most respected laboratories in the world (7), (8), (9), (10), (11), (12), (13). Those of us who have been involved in assessing the rate of progress in disease research are painfully aware of the numerous reports indicating a general slowdown in medical progress (14), (15), (16), (17), (18), (19), (20), (21).

For the optimists, it is tempting to assume that any problems that we may be experiencing today are par for the course, and temporary. It is the nature of science to stall for a while and lurch forwards in fits. Errors and retractions will always be with us so long as humans are involved in the scientific process.

For the pessimists, such as myself, there seems to be something going on that is really new and different; a game changer. This game changer is the "complexity barrier", a term credited to Boris Beizer, who used it to describe the impossibility of managing increasingly complex software products (22). The "complexity barrier" applies equally well to biomedical research. Recent studies have shown that inherited behavior is not fully determined by the genetic sequence of DNA. There are many different elements that modify and control genetic expression, and these elements do not have simple functionality (23). When complex cells are perturbed from their normal, steady-state activities, the rules that define cellular behavior become complex, and impossible to predict (24).

Modern biomedical data is high-volume (e.g., gigabytes and larger), heterogeneous (i.e., derived from diverse sources), private (i.e., measured on human subjects), and multi-dimensional (e.g., containing thousands of different measurements for each data record). The complexities of handling such data are daunting. When we closely examine the kinds of systemic flaws that cropping up in the recent biomedical literature, complexity always seems to play a supporting role. Here are a few examples:

1. Errors in sample selection, labeling, and measurement (25), (26), (27)

3. Misinterpretation of the data (28), (4), (29), (19), (30), (31), (32)

4. Data hiding and data obfuscation (33), (34)

5. Unverified and unvalidated data (35), (36), (37), (38), (30), (39)

6. Outright fraud (34), (40)

As biomedical data becomes increasingly complex, the complexity barrier will become impenetrable. It is ironic that just as we are coming to accept the limits of analyzing complex data, we are given President Obama's gift of a new funding initiative in support of precision medicine (41). How can we use this money effectively when we know that human diseases reside on the far side of the complexity barrier?

As it happens, not all diseases are genetically complex. The rare genetic diseases of humans, with very few exceptions, involve a single mutation in a single gene. In the past decade, we have made remarkable advances in understanding the rare diseases. For example, FDA approved a total of 44 drugs in 2014 (42). Of those 44 drugs, 21 (47%) were approved for the treatment of rare diseases, including: non-24-hour sleep-wake disorder, Morquio A syndrome, neurogenic orthostatic hypotension, generalized lipodystrophy, psoriatic arthritis, hemophilia B, multicentric Castleman's disease, hemophilia A (two drugs), Non-Hodgkin lymphoma, hereditary angioedema, leukemia (two drugs), multiple sclerosis, Gaucher disease, idiopathic pulmonary fibrosis (two drugs), gastric cancer, melanoma (two drugs), and ovarian cancer. In fact, most of the medical advances in the past two decades have occurred in the rare diseases; not the common diseases (43).

The rare diseases, being genetically simple, can be successfully treated with drugs targeted to a specific pathway. As it happens all of the cancers that we can cure in an advanced stage of growth (i.e., with metastases) are rare cancers (43), (44): choriocarcinoma, acute lymphocytic leukemia of childhood, Burkitt lymphoma, Hodgkin lymphoma, acute promyelocytic leukemia, large follicular center cell (diffuse histiocytic)lymphoma, embryonal carcinoma of testis, hairy cell leukemia, and seminoma.

Too often, the rare diseases are casually dismissed as outliers, not representative of metabolic pathways that drive the common diseases. Bad decision. Historically, the most important advances in common diseases have come from studying the rare diseases (43). Pathways that are studied, understood, and treated in the rare cancers will likely apply to common (i.e., genetically complex) cancers that share some of the same pathogenic pathways. Hence, the rare diseases are not the exceptions to the general rules that apply to common diseases; the rare diseases are the exceptions upon which the general rules of common diseases are based (43).

In this new, highly-funded era of precision medicine research, funding should flow to the rare diseases. If the common diseases are the genetic puzzles that modern medical researchers are mandated to solve, then the rare diseases are the pieces of the puzzles (43).

- © 2015 Jules J. Berman

References

[1] Unreliable research: Trouble at the lab. The Economist October 19, 2013.

[2] Prasad V, Vandross A, Toomey C, Cheung M, Rho J, Quinn S, et al. A decade of reversal: an analysis of 146 contradicted medical practices. Mayo Clin Proc 88:790-8, 2013.

[3] Kolata G. Cancer fight: unclear tests for new drug. The New York Times April 19, 2010.

[4] Ioannidis JP. Why most published research findings are false. PLoS Med 2:e124, 2005.

[5] Baker M. Reproducibility crisis: Blame it on the antibodies. Nature 521:274-276, 2015.

[6] Naik G. Scientists' Elusive Goal: Reproducing Study Results. Wall Street Journal December 2, 2011.

[7] Zimmer C. A sharp rise in retractions prompts calls for reform. The New York Times April 16, 2012.

[8] Altman LK. Falsified data found in gene studies. The New York Times October 30, 1996.

[9] Weaver D, Albanese C, Costantini F, Baltimore D. Retraction: altered repertoire of endogenous immunoglobulin gene expression in transgenic mice containing a rearranged mu heavy chain gene. Cell 65:536 (inclusive), 1991.

[10] Chang K. Nobel winner in physiology retracts two papers. The New York Times September 23, 1010.

[11] Fourth paper retracted at Potti's request. The Chronicle March 3, 2011.

[12] Whoriskey P. Doubts about Johns Hopkins research have gone unanswered, scientist says. The Washington Post March 11, 2013.

[13] Lin YY, Kiihl S, Suhail Y, Liu SY, Chou YH, Kuang Z, et al. Retraction: Functional dissection of lysine deacetylases reveals that HDAC1 and p300 regulate AMPK. Nature 482:251-255, retracted November, 2013.

[14] Innovation or Stagnation: Challenge and Opportunity on the Critical Path to New Medical Products. U.S. Department of Health and Human Services, Food and Drug Administration, 2004.

[15] Hurley D. Why Are So Few Blockbuster Drugs Invented Today? The New York Times November 13, 2014.

[16] Angell M. The Truth About the Drug Companies. The New York Review of Books Vol 51, July 15, 2004.

[17] Crossing the Quality Chasm: A New Health System for the 21st Century. Quality of Health Care in America Committee, editors. Institute of Medicine, Washington, DC., 2001.

[18] Wurtman RJ, Bettiker RL. The slowing of treatment discovery, 1965-1995. Nat Med 2:5-6, 1996.

[19] Ioannidis JP. Microarrays and molecular research: noise discovery? The Lancet 365:454-455, 2005.

[20] Weigelt B, Reis-Filho JS. Molecular profiling currently offers no more than tumour morphology and basic immunohistochemistry. Breast Cancer Research 12:S5, 2010.

[21] Personalised medicines: hopes and realities. The Royal Society, London, 2005.Available from: https://royalsociety.org/~/media/Royal_Society_Content/policy/publications/2005/9631.pdf, viewed Jan 1, 2015.

[22] Beizer B. Software Testing Techniques. Van Nostrand Reinhold; Hoboken, NJ 2 edition, 1990.

[23] Ecker JR, Bickmore WA, Barroso I, Pritchard JK, Gilad Y, Segal E. Genomics: ENCODE explained. Nature 489:52-55, 2012.

[24] Rosen JM, Jordan CT. The increasing complexity of the cancer stem cell paradigm. Science 324:1670-1673, 2009.

[25] Bandelt H, Salas A. Contamination and sample mix-up can best explain some patterns of mtDNA instabilities in buccal cells and oral squamous cell carcinoma. BMC Cancer 9:113, 2009.

[26] Knight, J. Agony for researchers as mix-up forces retraction of ecstasy study. Nature 425:109, September 11, 2003.

[27] Gerlinger M, Rowan AJ, Horswell S, Larkin J, Endesfelder D, Gronroos E, et al. Intratumor heterogeneity and branched evolution revealed by multiregion sequencing. N Engl J Med 366:883-892, 2012.

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

[29] Ioannidis JP. Some main problems eroding the credibility and relevance of randomized trials. Bull NYU Hosp Jt Dis 66:135-139, 2008.

[30] Ioannidis JP, Panagiotou OA. Comparison of effect sizes associated with biomarkers reported in highly cited individual articles and in subsequent meta-analyses. JAMA 305:2200-2210, 2011.

[31] Ioannidis JPA, Panagiotou OA. "Comparison of effect sizes associated with biomarkers reported in highly cited individual articles and in subsequent meta-analyses. JAMA 305:2200-2210, 2011.

[32] Ioannidis JP: Excess significance bias in the literature on brain volume abnormalities. Arch Gen Psychiatry 68:773-780, 2011.

[33] Harris G. Diabetes drug maker hid test data, files indicate. The New York Times July 12, 2010.

[34] Berman JJ. Machiavelli's Laboratory. Amazon Digital Services, Inc., 2010.

[35] Misconduct in science: an array of errors. The Economist. September 10, 2011.

[36] Begley S. In cancer science, many 'discoveries' don't hold up. Reuters Mar 28, 2012,

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[39] How science goes wrong. The Economist Oct 19, 2013.

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[41] Pear R. Obama to Request Research Funding for Treatments Tailored to Patients’ DNA. The New York Times January 24, 2015.

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key words: precision medicine, personal medicine, pharmacogenomics, pharmacogenetics, personalized medicine, genomics, bioinformatics, funding, President Obama's initiative, common diseases, rare diseases, complexity barrier, complexity ceiling, scientific error

The Genome Complexity Barrier in Precision Medicine

Elsevier has just published an editorial of mine entitled, The Data Complexity Barrier and the Surprising Importance of Rare Diseases. The premise of the article is that the common diseases of humans are way too complex to understand. Money spent on President Obama's Precision Medicine initiative will be wasted if funds are primarily directed to the common diseases. As it happens, the rare diseases are genetically simple, compared with the common diseases. Money spent on rare disease research is money well spent. In most instances, breakthroughs in understanding the rare diseases have led to new treatments for the common diseases.

I urge you to read the full editorial. Unlike much of the newsfeed hype on the subject of Precision Medicine, my article is well-researched and includes 44 references to the supporting literature.

- Jules J. Berman, Ph.D., M.D.

key words: precision medicine, pharmacogenomics, pharmacogenetics, personalized medicine, genomics, bioinformatics, funding, President Obama's initiative, common diseases, rare diseases, complexity barrier

More on Luck and Cause

Earlier this week, I posted a blog criticizing the conclusions reached in a highly publicized paper written by a group of scientists at Johns Hopkins Medical Center. The authors conclude that "bad luck", rather than environmental or genetic causes, is responsible for the bulk of human cancers. My prior blog post explained why Hopkins is wrong.

After the blog was written, I received some very interesting feedback from a LinkedIn group (Science writers), much of which centered on the different ways that people use the words "luck" and "cause". Though mathematicians will despair, the word "good luck" is routinely applied to just about anything that has desirable outcome. So if a high school student gets a perfect score on the SAT exam, he or she was very very lucky. If you would interject to say that luck had nothing to do with it ("It was all due to student's high intelligence!"), you would be informed that the intelligence was a matter of luck, being as the student had done nothing to earn his or her intelligence. If you were to suggest that the "cause" of the high score was hard work, you would be told that "hard work" was just one of many conditions that led to the high score (e.g., "lucky" intelligence, a good night's sleep the night before, growing up in a stable living environment where current events, history and literature are discussed). There being many different "causes," it wouldn't make much sense to think in terms of any specific cause, and you might as well chalk it up to just plain good luck.

Getting back to biology and disease, consider these hypotheticals:

If you have 5 people living with an Ebola patient, and three of the five come down with the disease, would you say that these three came down with Ebola because they were "unlucky"? Or would you say that these three came down with Ebola because they were infected with the virus [and the other two were not]?

Would you say that the Ebola virus caused the infection in these three individuals? Or would you say that many factors, such as "luck", the environment, low innate viral resistance, poor nutrition, all set the stage for their infections, and that the Ebola virus was just one of many ingredients in the brew?

There's a real danger with using "luck" to describe events that we do not understand or cannot predict. Likewise, causation can be deceptive when dealing with a multi-step process that plays out over years or decades (like cancer).

When I think about "cause" I'm usually applying the "but-for" criteria ("but-for" this, that would not have happened). So, for me, Ebola virus causes Ebola hemorrhagic fever, and infections are not a matter of luck. Likewise, for me, there are "but-for" causes of cancer (e.g., chemicals, viruses, predisposing genes), and many important modifying factors that probably don't rise to the level of "but-for" causes (e.g., cell proliferation, DNA repair, genomic and epigenomic influences, regression-causing events, immune status); and cancer is not caused by bad luck.

Today, cancer has become the quintessential "bad luck" disease. In a prior blog, I described examples of "bad luck" cancers that transformed into "specific cause" cancers, when we studied the data. My personal opinion is that most cases of cancer are associated with known "but-for" causes. As we learn more and more about the different types of cancers, particularly the huge variety of rare cancers, we continue to find specific causes for specific cancers. I just assume, perhaps incorrectly, that every cancer has a cause.

I urge everyone reading this blog to also read my prior blog, which provides a full rebuttal to the Johns Hopkins "bad luck" cancer hypothesis.

- Jules Berman

tags: johns hopkins, press release, cancer news, bad luck, data repurposing, opinion, criticism, carcinogenesis, rare cancer, rare diseases, cancer incidence, comparative carcinogenesis, Jules J. Berman, Ph.D., M.D., cancer research, new findings, mutation rate, rebuttal, stem cell renewal, probabilistic models, data modeling, randomness, chance, misfortune, accident, unpredictable, causation, causative role, but-for, but for, sine qua non

Human diseases are not caused by bad luck

Earlier this week, I posted a blog criticizing the conclusions reached in a highly publicized paper written by a group of scientists at Johns Hopkins Medical Center. The authors conclude that "bad luck", rather than environmental or genetic causes, is responsible for the bulk of human cancers. My prior blog post explained why Hopkins is wrong.

After the blog was written, I got some very interesting feedback from a LinkedIn group (Science writers). Much of the discussion centered on the meaning of "luck", as it applies to biological processes.

Terms such as "luck", "accident", "misfortune", and "unpredictable" are often used, inappropriately, to describe complex events that we do not fully understand. For example, we speak in terms of "motor vehicle accidents" to describe vehicular crashes, even when we have discovered non-accidental causes (e.g., driving while intoxicated, driving on the wrong side of the road, failure to yield). We use the term "cerebrovascular accident" to describe strokes, even in individuals who have abundant risk factors (e.g., high blood pressure, e.g., occluded carotid artery). When we come down with a cold, we often say that it was our bad luck or our misfortune to get sick, even when we know that the cold was caused by a virus.

When we flip a coin, we like to think that the outcome occurs randomly, because there is a 50% chance of heads or of tails. But we all know, at some level, that the outcome of the toss is predetermined at the moment that the coin flips into the air. The laws of physics come into play, with a complexity that defies human prediction. Coin tosses, and roulette spins, are examples of processes that can be modeled, mathematically and intuitively, as probabilistic events. But we shouldn't confuse a probabilistic model with a physical reality.

Biology and medicine are replete with examples of phenomena that were attributed to "bad luck" until we finally determined their causes. For example, until the dawn of the twentieth century, the cause of malaria was unknown. There must have been something in the air (mala aria = bad air in medieval Italian). In 1880, Laveran identified the causative agent, a protozoan, in the blood of affected patients, for which he was awarded the Nobel prize in 1907. Through the centuries, people suffering from infectious diseases, vitamin deficiencies, and environmental toxins were considered "unfortunate", meaning "without luck."

Do not presume that modern-day scientists are too enlightened to be taken in by "chance" phenomenon. For many years, medical scientists sought a cause for sudden infant death syndrome (SIDS). Children were dying in their cribs, unpredictably, as though they had the bad luck to just stop breathing. In the past half century, we have learned that the majority of cases of SIDS are associated with sleeping conditions that limit the infants ability to breathe (e.g., sleeping on stomach, in hot room, with overabundance of soft bedding, etc.).

Today, cancer has become the quintessential "bad luck" disease. The literature gives us lots of examples of "bad luck" cancers that transformed into "specific cause" cancers, when we studied the data.

For example, In a landmark paper published in 1971 by Herbst and coworkers, the authors found an increase in the number of young women who developed an extremely rare cancer: clear cell adenocarcinoma of the cervix or of the vagina. The mothers of these young women had ingested a nonsteroidal synthetic estrogen (diethylsilbestrol, DES) during their pregnancies. In utero exposure to the drug caused a specific rare tumor to occur in the daughters. The offspring were classic "bad luck" cancer victims, having done nothing to put themselves at risk. Herbst had to go back a generation to find the real cause.

Women who developed mesotheliomas, a very rare cancer, in the 1970s and 1980s, were also the victims of "bad luck", until cancer epidemiologists found the common factor that linked these cases. These women had washed the asbestos-laden clothes of their fathers or husbands, who worked in the shipyards during World War II. Their brief exposure to asbestos resulted in mesotheliomas 20+ years later.

Much of what we observe in biology and medicine looks exactly like luck... until we understand the cause. The effect of "bad luck" hypotheses, as they apply to biology and medicine, is to halt scientific progress. Why would scientists waste their time looking for the causes of cancer, if cancers are caused by "bad luck"? The U.S. Environmental Protection Agency certainly can't protect us from bad luck!

I urge everyone reading this blog to also read my prior blog, which provides a rebuttal to the Johns Hopkins "bad luck" cancer hypothesis.

- Jules Berman

tags: johns hopkins, cancer news, bad luck, data repurposing, opinion, criticism, carcinogenesis, rare cancer, rare diseases, cancer incidence, comparative carcinogenesis, Jules J. Berman, Ph.D., M.D., cancer research, new findings, mutation rate, rebuttal, stem cell renewal, probabilistic models, data modeling, randomness, chance, misfortune, accident, unpredictable

Hopkins is wrong. Role of bad luck in cancer not shown!

Amidst much fanfare, Johns Hopkins issued a news release, dated Jan. 1, 2015, under the banner, “Bad Luck of Random Mutations Plays Predominant Role in Cancer, Study Shows" The subtitle to the banner is, "Statistical modeling links cancer risk with number of stem cell divisions.”

Whoever wrote the Hopkins news report doesn't seem to understand that the subtitle contradicts the title. The title implies that the authors have proven an assertion (i.e., that bad luck causes cancer). The subtitle indicates that they have only established an association (i.e., there is a statistical link between cancer incidence and random mutations occurring as stem cells divide). It seems like a quibble, but there is an immense conceptual gulf between a "link" and a "cause". It's easy to find a correlation, but it's hard to prove a causal role. In many cases, correlations simply disappear when the original data is reanalyzed with different analytic methods, or when some of the original assumptions are changed, or when new data is obtained, or when information from some other study provides better results that support an opposing hypothesis.

The Hopkins researchers reviewed the literature to find, "the cumulative total number of divisions of stem cells among 31 tissue types during an average individual’s lifetime." These numbers for the different tissues, correlated closely with the risk of cancer occurring in those tissues. Having arrived at the correlation, "using statistical theory, the pair calculated how much of the variation in cancer risk can be explained by the number of stem cell divisions, which is 0.804 squared, or, in percentage form, approximately 65 percent." Of the 31 tissues they studied, the tumor incidence in 9 of the tissues did not fit their "bad luck" correlation. Tumor incidence in these tissues, according to the news report, must come from some other source, such as environmental carcinogens. The 22 tissues that fit their model were deemed the "bad luck" tumors.

The bad luck hypothesis is not new. Cancer researchers have been trying to titrate the various suspected causes of cancer for decades. In the 1970s, when there was a large push to find chemicals in the environment that cause cancer, it was widely accepted that about 85% of cancers were caused by environment agents; 15% were caused by other things, such as genes, and this last 15% would also include "bad luck" mutations. These numbers were based on statistical inferences from data on the geographic variations in cancer incidence, looking at how the types of cancers occurring in populations changed in different locations on earth and in response to identified carcinogens.

Back in the early '70s, there was an awareness of the special place of "rare cancers" in the discussion. The common cancers (i.e., skin, lung, colon), were all presumed to be caused by environmental toxins (e.g., UV light, cigarettes, food and water contaminants, chronic infections, etc). More than 90% of the burden of cancer in the U.S. is accounted for by just a handful of cancer types (namely, basal cell carcinoma of skin, squamous cell carcinoma of skin, bronchogenic lung cancer, adenocarcinoma of colon, adenocarcinoma of breast, adenocarcinoma of prostate, adenocarcinoma of pancreas, ovarian carcinoma, esophageal cancer, and maybe one or two others). There are over 6,000 different kinds of cancer. All but a half dozen or so of these 6,000 varieties of cancer are rare, accounting in the aggregate for fewer than 10% of the tumors occurring in humans. Many of the rare cancers have well-studied patterns of inheritance. Because there are so many known inherited rare cancers, we tend to assume (perhaps incorrectly) that the bulk of rare cancers are caused by inherited genes (i.e., not caused by random mutations occurring in individuals with cancer).

OK, so lessons learned through the history of cancer research seems to be at odds with the conclusions drawn by the Hopkins team. Let's ignore history, for a moment. Here is a list of present-day concerns that should, at the very least, tone down the conclusions reached by the Hopkins study.

1. There are animals with much higher stem cell renewal than that seen in humans. Consider the whale. Whales have tons of intestines with trillions of dividing cells. If stem cell division and random mutation account for cancer, then you would expect every whale to be chock full of intestinal cancers. They are not. Please, spare me the argument that whales are different from humans and the two species cannot be compared. If you assert that random mutations in the DNA of stem cells is the cause of cancer, then your assertion should apply equally to any organisms that contains DNA and stem cells.

2. Carcinogenesis (i.e., the biological process that leads to cancer) is known to be a multi-step phenomenon. Mutation may be the first step, but many additional steps, leading to cancer, must occur, sometimes playing out over decades. In a multi-step process, you cannot expect any single event (e.g., a random bad luck mutation) to account, by itself, for the incidence of cancer.

3. There is a high cancer rate in mice and rats, both relatively short-lived animals. Wouldn't you expect a low accumulation of random bad mutations in animals that only live a year or two? The rapid evolution of cancers in short-lived animals (i.e., weeks or months) suggests that something in addition to random bad luck mutations must account for carcinogenesis in these animals.

4. Biological systems are complex, and causation is seldom a meaningful concept when many events contribute to a single observed phenomenon. For example, random mutation may occur more frequently in tissues with rapidly dividing stem cells, but rapid division of cells may occur in response to some toxic effect or chronic condition that causes a subpopulation of cells to die. Hence, rapid division of stem cells may be the result of some other "cause". Likewise, chronic toxicity and subsequent stem cell renewal in various tissues may result from higher rates of activation of carcinogens (i.e., metabolism) in those tissues. Hence, stem stem cell renewal may be tightly coupled with a variety of biological influences other than "bad luck".

In summary, the correlation observed by the Hopkins scientists is interesting, and it probably deserves further investigation. But the assertion that "bad luck" causes most human cancers is pretty much meaningless, at the moment.

- Jules J. Berman

p.s. The topic of today's blog is covered in depth in several of my published books, particularly Neoplasms: Principles of Development and Diversity, and expanded in my next blog post.

tags: johns hopkins, cancer news, bad luck, data repurposing, opinion, criticism, carcinogenesis, rare cancer, rare diseases, cancer incidence, comparative carcinogenesis, Jules J. Berman, Ph.D., M.D., cancer research, new findings, mutation rate, rebuttal, stem cell, stem cell renewal

Rare Diseases and Orphan Drugs: Recent Blogs

In June, 2014, my book, entitled Rare Diseases and Orphan Drugs: Keys to Understanding and Treating the Common Diseases was published by Elsevier. The book builds the argument that our best chance of curing the common diseases will come from studying and curing the rare diseases.

Over the past several weeks, I've been posting to several different blogs on the subject of rare diseases.

Here is the list of my rare disease posts, with links:

Developing Diagnostic Tests for Common Diseases: Role of the Rare Diseases

Rare Diseases Account for Subsets of Common Diseases

Phenocopy Mimics of Rare Diseases: Lessons for the Common Diseases

Phenocopy Diseases: Their Relationship to Rare Diseases and Common Diseases

What Rare Diseases Teach Us About the Cellular Basis of Aging

What is the Fundamental Biological Process that Causes Aging?

Wrinkling and Sagging are Chronic Toxic Processes Not Directly Caused by Aging

Disease Complexity: Rare Diseases and Common Diseases

Case Reports of Rare Diseases Have General Value

When Rare Diseases and Common Diseases Converge to Same Clinical Picture

Rare Diseases and Common Diseases can Converge to the Same Clinical Conditions

Rare Disease Legislation in the U.S.

Definition of Rare Disease

Developing Diagnostic Tests for Common Diseases: Role of the Rare Diseases

Rare Diseases Account for Subsets of Common Diseases

Improving Clinical Trials by Focusing on Rare Diseases

Rare Diseases of Unknown Origin

Rare Diseases are Sentinels for the Common Diseases

Biological Differences between Rare Cancers and Common Cancers

Rare Diseases are Biologically Different from Common Diseases

Rare Cancers are Biologically Different from Common Cancers

Rare Cancers

Clinical Trials and Rare Diseases

Rules for the Rare Diseases

The Rationale for Funding Rare Disease Research

New Book Explains the Importance of Rare Disease Research

I urge you to read more about this book. There's a good preview of the book at the Google Books site. If you think that you and your colleagues may benefit from reading this book, please request your librarian to purchase a copy of this book for your library or reading room.

- Jules J. Berman, Ph.D., M.D.

tags: rare diseases, orphan diseases, orphan drugs, funding opportunities, rare cancers, common diseases, complex diseases, clinical trials, rare disease organizations, disease advocates