Identifying different osteoarthritis phenotypes through epidemiology.

The Oxford English Dictionary (1) defines a phenotype as the “sum total of observable characteristics of an individual, regarded as the consequences of the interaction of the individual’s genotype and environment; a variety of an organism distinguished by observable characteristics rather than underlying genetic features.” Wikipedia (2) expands this definition to” any observable characteristic or trait of an organism such as its morphology, development, biochemical, or physiologic properties or behavior.” One key element of these definitions is that a phenotype is defined by a characteristic that is observable by the naked eye, by images or by blood tests. A genotype is often the source of phenotypic variation, but a genotype is only relevant to phenotypes when it creates an observable difference between two organisms with the same disease; thus a genotype expression can create phenotypic variation when the effect of the genotype is observable. Examples of phenotypes in medicine include treatment defining phenotypes such as when a woman with breast cancer has a tumor that is estrogen receptor positive and therefore is treated with tamoxifen. If her tumor were estrogen-receptor negative, she would not be so treated. Another example constitutes families who inherit the BRCA gene which alters the prevention approach to their breast cancer or ovarian cancer and a third is when a phenotype alters the conceptualization of disease biology such as when Marshall suggested that gastric ulcers might actually be caused by bacteria, a prophetic suggestion confirmed when the H. pylori bacterium was discovered and characterized in ulcers. The overall goal of this paper is to explore the existence of distinct phenotypes in osteoarthritis. To accomplish this goal, I will posit criteria to use to define phenotypes and then will suggest which phenotypes exist and which do not. Ultimately, there are hundreds of phenotypes that could be defined in osteoarthritis. To be meaningful for clinical practice and for epidemiologic studies, phenotype distinctions should be confined to those that affect treatment or prevention decisions and to those which clearly have a fundamental effect on the way we view disease biology and/or disease etiology. Since our knowledge of disease and our ability to observe or image aspects of disease are continually changing, it is likely that new insights will, in turn, support the existence of new or evolving phenotypes. Therefore, any elaboration of disease phenotypes is necessarily limited to current knowledge and technology. The most common factors defining phenotypes are risk or etiologic factors in addition to genetic variation. For example, hip osteoarthritis phenotypes are defined based on developmental hip abnormalities such as congenital dysplasia. Hips with developmental abnormalities often need early surgeries and are therefore different phenotypes than those without such early changes. Among the most common factors differentiating disease phenotypes is extent of disease. In cancer, TNM classifications which describe the extent and severity of a cancer often define different treatment choices. For example, breast cancer that is small and limited in scopewithin the breast might be treated with a lumpectomy, whereas metastatic disease would require chemotherapy. Since osteoarthritis is widely regarded as a final common pathway of joint destruction for multiple different pathophysiologic etiologies including trauma, developmental etiologies, primary cartilaginous disorders, and even crystal induced arthritis, differentiating these etiologies might provide different phenotypes of osteoarthritis. Identifying different phenotypes in osteoarthritis may be highly relevant to treatment and prevention development in this disease. Therefore, isolating phenotypes in osteoarthritis may be critical to development of effective treatment and disease prevention. If treatment works only in one sub-type, for example, a treatment targeted to bone marrow lesions, we will miss the therapeutic effect of that treatment if it is tested in everyone with osteoarthritis, because many do not have bone marrow lesions. If, on the other hand, treatment does not work in a subset of disease with a particular common feature, we may miss the effect of treatment on the less common subset that does not have this feature. An example of this might be if malalignment of the knee creates too much focal stress for a chondroprotective agent to work. The same considerations would be relevant for disease prevention as for disease treatment. Epidemiologists approach phenotypic distinctions by invoking sufficient cause models (see figure). Each of these pie charts constitutes a hypothetical cause of osteoarthritis. For example, on the left, we could hypothesize that 40% of knee osteoarthritis was due to a combination of risk factors including obesity, getting older, and being a women. Since not all overweight, older women develop knee osteoarthritis, an unknown set of causes is also invoked. What is relevant about this particular sufficient cause pie is that if any of the causes is removed (e.g., if obesity were eliminated), a sufficient cause of disease would no longer occur and knee osteoarthritis prevalence would decrease. Thus, if obesity were eliminated, up to 40% of knee osteoarthritis would no longer occur. In the middle figure is another pie of disease caused by knee injury along with age and combined with the usual unknown set of causes because not all people with injury who are older get osteoarthritis. On the right, we postulate that roughly 15% of knee OA is due to genetic causes and that genes could translate into a phenotype if the effects of the gene created an observable characteristic, a phenotype. The hypothetical pie charts depicted do not account for 100% of knee OA, because there must be other causal pathways that determine other phenotypes in disease. The remainder of this paper will address three specific issues. First, what is the evidence supporting the validity of widely used phenotypes in osteoarthritis? Second, what are other likely phenotypes, not currently widely hypothesized as being phenotypes in OA? And lastly, how will we determine and confirm phenotype distinctions that might be of importance in osteoarthritis?