from SECTION 2 - MOLECULAR PATHOLOGY
Published online by Cambridge University Press: 04 June 2019
INTRODUCTION
Many disorders with a Mendelian pattern of inheritance have been well characterised and many of the genes controlling these disorders have been identified. There are, however, many common diseases with an inherited component that do not follow a specific pattern of inheritance. These diseases are conventionally known as complex multi factorial traits and include conditions such as asthma, diabetes and many of the cardio vascular disorders. The term multifactorial indicates that there are multiple causative agents – both genetic and environmental. These traits therefore have a complex molecular mechanism that involves many processes such as physiological mechanisms, development and homeostasis, to name but a few.
This chapter will review basic concepts of multifactorial inheritance and illustrate what a complex disease is, and how it differs from Mendelian disorders. Furthermore, the design and implementation of complex disease gene discovery, and the strengths and pitfalls of these approaches, will be discussed. Finally, the impact of the knowledge of complex disease genetics on clinical medicine and its relevance to future disease treatment will be discussed.
HOW DO COMPLEX DISEASES DIFFER FROM MENDELIAN DISORDERS?
Complex diseases differ in very distinct ways from Mendelian disorders, and the key differences are summarised in Table 1. The single most important difference is related to the impact of the genetic factors on the disease. For most Mendelian diseases, the inheritance of a pathogenic gene variant or mutation is associated with that disease because it has such a debilitating impact on the gene product that it almost always results in disease. This is not the case with complex diseases, where the presence of a specific genetic factor is not causal but may increase or decrease the risk of developing disease. Risk is defined as the probability of an adverse event and its value in clinical medicine is primarily to predict outcome. The goal of complex disease prediction is therefore to identify an individual or a population in which an intervention could prevent adverse outcome. Complex diseases are usually not influenced by only one gene but by many genes that contribute to disease outcome and may have an additive, multiplicative or interactive effect.
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