Defining the Pathogenicity of DNA Sequence Variation

Abstract

Understanding the relationship between genotype and phenotype remains one of the most challenging hurdles in human genetics, especially as efforts are made to translate genetic data into clinical prediction of disease or therapeutic outcomes.1 For many cardiac or vascular conditions in which the initial presentation may be fatal, a strong genotype–phenotype correlation is of fundamental importance if genetic diagnosis or prognostication is ever to be useful. Even in classic monogenic disorders, in which large effect sizes are observed, genetic prediction is often confounded by reduced penetrance, wide variation in the final phenotypes (pleiotropy), or sporadic phenocopies.2 Although such trait “complexity” has been viewed largely in terms of environmental or genetic modifiers, such factors have proven difficult to identify. It is also possible that strong selection pressures against many cardiovascular traits may result in purely stochastic events playing a larger role in shaping phenotype.3 Rigorous genetic studies have identified many cardiovascular disease genes, leading to broader investigation in smaller families and individual probands. Although identifying variants in these same genes in unrelated individuals provides important confirmation and strengthens the initial data, the clinical significance of the numerous additional variants uncovered in subsequent resequencing efforts may be ambiguous.4 The level of support for these variants as disease causing is often much less robust than for the original discovery. As a result, rare (or not so rare) benign polymorphisms populate many mutation databases, often indistinguishable from pathogenic mutations. Article see p 182 The interpretation of sequence data in the absence of relevant genetic or functional data to support pathogenicity is fraught with problems. The pertinent issues are well illustrated in research and commercial proband-based “gene screening” efforts in several cardiac syndromes in which detected rates of de novo DNA sequence variants are high, reliable data to predict their clinical …