Genetics of Common Disorders

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Chapter 77 Genetics of Common Disorders

Genetic studies are useful in diagnosing and treating rare pediatric conditions, often alleviating suffering, extending life, and, in the case of neonatal metabolic and presymptomatic screening, preventing injury before symptoms develop. Genetic studies can also contribute to the understanding of more common diseases such as asthma and diabetes. An understanding of the complex and potentially multiple pathways leading to disease is crucial for the development of new therapies and prevention strategies and screening of high-risk children.

Common pediatric diseases are often multifactorial, and the combination of many genes and environmental factors triggers a complex sequence of events leading to disease. Each individual has variations in his or her set of genes; the interactions of the individual’s gene variants with each other and with the environment influence susceptibility to disease, response to various medications, and susceptibility to specific drug toxicities. The complexity of the combination of contributing factors increases the challenge of finding genetic variants that cause disease. Genetic tools include the completed human genome sequence, public databases of genetic variants, and the human haplotype map. In addition to public genetic databases, dramatic reduction in the cost of genotyping and DNA sequencing has allowed very large numbers of genetic variants to be efficiently tested in large numbers of patients. New technologies for DNA sequencing will soon allow nearly complete genomic sequencing in many individuals at very low cost. The incorporation of these tools into large, well-designed population studies is the field of genetic epidemiology. Many new methods for analyzing genetic data have been developed, stimulating a renaissance in applied population genetics. So far, these methods of investigation have been used less extensively in pediatric diseases than in adult-onset conditions. This has been due to the relative lack of large-scale DNA sample sets for many common diseases of children.

We can now project that in the near future it will become routine to carry out “genomic profiling” by one technique or another for individual children. These methods will find clinical utility in decision algorithms for disease screening and initiation of treatment, drug selection, and targeted preventive strategies. The results will be of an unprecedented complexity, so that physicians and parents will increasingly rely on the coupling of genetic data to clinical decision support tools linked to the electronic health record.

77.1 Major Genetic Approaches to the Study of Common Pediatric Disorders

John W. Belmont and Brendan Lee

A model for the genetic contribution to health is shown in Figure 77-1. Genetic variation that can have an impact on disease susceptibility is present in every person. Sometimes single gene mutations cause a condition such as cystic fibrosis or sickle cell anemia. But other genetic variations can contribute much less strongly to the emergence of specific medical conditions, and the effect can depend upon exposure to certain environmental factors. One goal in medical genetics is to identify genes that contribute to disease in the hope of preventing the occurrence of disease, either by avoiding inciting environmental factors or by instituting interventions that reduce risk. For persons who cross the threshold of disease, the goal is to better understand the pathogenesis in the hope that this will suggest better approaches to treatment. Common genetic variation can also influence response to medications and the risk of toxicities of various medications and environmental toxins.

Complex traits may be inherently difficult to study if there are problems with the precision of clinical diagnosis. This is particularly true of neurobehavioral traits. A starting point in the genetic analysis of a complex trait is to obtain evidence in support of a genetic contribution and to estimate the relative strength of genetic and environmental factors. Complex traits typically exhibit familial clustering but are not transmitted in a regular pattern like autosomal dominant or recessive inheritance. Complex traits often show variation among different ethnic or racial groups, possibly reflecting the differences in gene variants among these groups.

Assessing the potential genetic contribution begins by determining whether the trait is seen among related individuals more often than in the general population. A common measure of familiality is the first-degree relative risk (usually designated by the symbol λs), which is equal to the ratio of the prevalence rate in siblings and/or parents to the prevalence rate in the general population. For example, the λs for type 1 diabetes is about 15. Collection of family data also allows the analysis of possible inheritance models using a method called segregation analysis. The relative strength of genetic and nongenetic risk factors can be estimated by variance components analysis, and the heritability of a trait is the estimate of the fraction of the total variance contributed by genetic factors (Fig. 77-2).

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