Understanding comorbidity: from epidemiological designs and model-fitting approaches to systems biology as a new tool

Excerpt

It is a common observation that persons with one particular psychiatric disorder often present with other disorders. This so-called co-occurrence, co-existence or comorbidity of disorders occurs at all ages, and cannot be explained away simply by sampling bias. Co-occurrence of disorders may lead to a higher rate of clinical referrals and use of services, and this could suggest inflated rates of co-occurrence. However, population-based studies confirm that many psychiatric disorders cluster in the same individual more than to be expected by chance [1‐3]. Traditional explanatory models for this co-occurrence specify the following possibilities: artificial factors, such as overlapping diagnostic criteria or population stratification (the risk factors that influence the two disorders maybe more common in a part of the population); one disorder being a risk factor for the other; one disorder being a cause of the other; risk factors that are being shared between the two disorders; and both disorders being alternative expressions or different phases of the same overarching disorder [4]. Comorbidity has found to be associated with greater severity of illness, increased use of services and health care costs, lower response to treatment and an overall worse prognosis. Therefore, it is important to study the causes of comorbidity. This can have then a major impact on future research examining the two disorders, including research on classification, treatment, and etiology. …