Rule - When you graph the frequency of occurrence of a rare disease against the age of the individuals that develop the disease, there is usually one clear peak.
Brief Rationale - Rare diseases often result from a single mutation that enters the germline at the time of conception. The process by which the gene mutation leads to a clinical disease will require roughly the same length of time, in most affected individuals, producing a smooth, single peak, when disease occurrences are graphed against age of occurrence.
There are exceptions to the "one peak" rule. Some diseases have a bimodal distribution (i.e., two peaks). Distributions with more than two peaks are likely to occur, but the peaks in polymodal graphs run into one another and cannot, in general, be distinguished with certainty. Our ability to tease out polymodal data peaks may be improved, somewhat, as we become more adept at collecting information on large number of individuals, with verified, detailed quantitative feature data (i.e., age of occurrence of disease, gene mutations present in lesions, gene expression profiles)
Rule - Bimodality, when it occurs, is more often observed in the rare diseases, than the common diseases.
Brief Rationale - Because there are many occurrences of a common disease, second peaks (i.e. subpopulations with separate peak occurrence with age), are likely to be masked by the large number of occurrences of the larger peak. Because the total number of individuals with a rare disease is small, a relatively small subpopulation, with its own specific age of disease occurrence, is likely to produce a visible second peak, when the data is graphed.
For example, Hodgkin lymphoma, a rare tumor, has two peaks of disease occurrence
Graph showing incidence of Hodgkin Lymphoma, by age of occurrence of disease. There are two peaks in the graph. The first peak occurs in the early 20s. After the first peak, there is a trough, in the mid 40s, after which incidence increases steadily with age, toward a second peak. The graph was generated at the National Cancer Institute's Surveillance, Epidemiology and End Results "Fast Stats" query site.
What does it mean when a rare disease breaks the "one peak" rule and demonstrates a bimodal age distribution? Here are a few possibilities:
1. Two different diseases, presumably with overlapping phenotypes, occur in two peak age groups, and are mistakenly assigned the same name.
2. A population is exposed to two environmental disease-causing agents, one working slower than the other.
3. A subpopulation is exposed to a different concentration of disease-causing agent, or at a different age, either resulting in disease occurring at a different average age, for the subpopulation.
4. Two genetic causes for the same disease have different latencies (i.e., lengths of time for the disease to develop)
5. Two sub-populations have different disease modifiers (i.e., sets of genes that alter the pathogenesis of the disease).
6. Faulty or insufficient data. Bimodality may be a distortion due to poor data that does not adequately conform to the naturally occurring (unimodal) distribution.
7. False conclusions based on accurate data. The second peak may be caused by valid by "noisy" data. Scientists should not assume that statistical conclusions, based on a single set of data, are correct. All conclusions must be constantly re-examined in light of new findings.
8. Combinations of examples 1 through 7.
Occasionally, we can determine the biological mechanism that accounts for a bimodal age distribution. For example, Kaposi sarcoma, caused by human herpesvirus-8, has two peaks in occurrence. The first peak, in young people, occurs in individuals with AIDS-related Kaposi sarcoma. The second peak occurs in older men, was a recognized disease entity prior to the AIDS epidemic (i.e., prior to 1980s), and is often referred to as "classic" Kaposi sarcoma. Classic Kaposi sarcoma is slow-growing, arises on the skin, often on the leg, and does not metastasize. It tends to occur in individuals of Mediterranean descent.
Once you begin to think about diseases in terms of multimodality, there is a short leap to thinking that the common, complex diseases are composite entities, composed of small sets of separate diseases that share a clinical phenotype.
Rule - A disease that can be separated into biological subsets, based on a quantifiable trait, such as age, can be interpreted as an aggregate of separate diseases, each with a smaller occurrence rate than the original disease.
Brief Rationale - By definition, a disease is a pathological condition that is biologically distinct from other pathologic conditions.
In a provocative journal article entitled,"The many 'small COPDs', COPD should be an orphan disease," Stephen Rennard argued that many chronic diseases are actually heterogenous groups of diseases that we are just now learning to distinguish from one another (1). When we begin the process of separating diseases into related but distinguishable subsets of disease, we can begin to see why the common diseases may be aggregates of less common diseases. For example, mutation in the BRCA2 gene account for some cases of breast cancer, but the percentage is small. In fact, all of the known breast cancer risk genes, in aggregate, account for under 10% of the incidence of breast cancer. The remaining 90% would qualify today as sporadic tumors.
Interestingly, the same BRCA2 gene that accounts for a subset of cases of breast cancer, also accounts for a miniscule subset of a rare disease: Fanconi anemia. Most cases of Fanconi anemia are caused by mutations in genes coding for protein components of the Fanconi anemia protein complex which, along with BRCA2, helps coordinate DNA repair (2). A small percentage of Fanconi anemia patients are caused by homozygous mutations in the BRCA2 gene.
Rule - Single gene mutations may account for small subsets of common diseases, but they do not account for large subsets of common diseases.
Brief Rationale - All the single gene disease mutations are rare. If this were not so, we would expect to see Mendelian inheritance, typical for monogenic diseases, among the common diseases; but we do not.
Though a rare disease hidden within a common disease accounts for only a small proportion of the total number of disease cases, the genetic cause of the rare disease subset may be much easier to find than the genetic cause of the so-called sporadic cases (3). When one mutated gene fully accounts for a subset of cases of a disease, its statistical association with with the disease can be demonstrated with a relatively small number of cases (3).
Rule - Rare diseases that are subsets of common diseases often occur in a younger population than the cases occurring in the larger set of individuals with so-called sporadic disease.
Brief Rationale - Rare diseases are typically germline, monogenic diseases that occur in young individuals.
A rare subset of lung cancers is caused by a rearrangement in the NUT gene. As in so many other rare diseases that have a germline, monogenic cause, these cancers tend to occur in a much younger age group than cancers caused by an environmental factor (i.e., smoking, in this case) (4). The same observation holds for secretory breast carcinoma, formerly known as juvenile carcinoma of breast, which occurs in a younger age group than classic ductal breast carcinoma, and which is characterized by a specific fusion gene (5). Similarly, myelodysplastic syndrome, a preleukemic condition for which the preponderance of casses occur in elderly individuals, is known to occur in children who inherit a predisposition to losing chromosome 7 in somatic blood forming cells (6), (7).
Rule - In a bimodal disease wherein the disease occurs in two age groups: young and old, the strongest likelihood of finding an effective treatment resides in the younger age group.
Brief Rationale - The younger age group is more likely to have a monogenic or oligogenic cause of the disease, and this often translates into a targeted cure. The older age group is likely to develop disease after the accumulation of multiple epigenetic, genetic, and environmental alterations, making it difficult to find an effective treatment.
Every type of cancer that is curable at an advanced stage (i.e., having multiple and widespread metastases) is a cancer of childhood. All of the cancers that typically occur late in life are incurable when they progress to an advanced stage.
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.
- Jules Berman (copyrighted material)
key words: rare disease, orphan drugs, orphan diseases, zebra diseases, rare disease day, disease complexity, common diseases, monogenic disease, disease genetics, jules j berman
 Rennard SI, Vestbo J. The many "small COPDs", COPD should be an orphan disease. Chest 134:623-627, 2008.
 D'Andrea AD.Susceptibility pathways in Fanconi's anemia and breast cancer. N Engl J Med 362(20):1909-1919, 2010.
 Li B, Leal SM. Discovery of Rare Variants via Sequencing: Implications for the Design of Complex Trait Association Studies. PLoS Genet 5:e1000481, 2009.
 French CA, Kutok JL, Faquin WC, Toretsky JA, Antonescu CR, Griffin CA, et al. Midline Carcinoma of Children and Young Adults With NUT Rearrangement. J Clin Oncol 22:4135-4139, 2004.
 Tognon C, Knezevich SR, Huntsman D, Roskelley CD, Melnyk N, Mathers JA, et al. Expression of the ETV6-NTRK3 gene fusion as a primary event in human secretory breast carcinoma. Cancer Cell 2:367-376, 2002.
 Lizcova L, Zemanova Z, Malinova E, Jarosova M, Mejstrikova E, Smisek P, et al. A novel recurrent chromosomal aberration involving chromosome 7 in childhood myelodysplastic syndrome. Cancer Genet Cytogenet 201:52-56, 2010.
 Shannon KM, Turhan AG, Chang SS, Bowcock AM, Rogers PC, Carroll WL, et al. Familial bone marrow monosomy 7. Evidence that the predisposing locus is not on the long arm of chromosome 7. J Clin Invest 84:984-989, 1989.