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(Hypertension. 1997;29:145.)
© 1997 American Heart Association, Inc.
Workshop on Molecular Genetic Analysis of Hypertension and Cardiovascular Disease |
Genetically Complex Cardiovascular Traits
Origins, Problems, and Potential Solutions
From the Department of Epidemiology and Biostatistics and the Department of Genetics, Case Western Reserve University, Cleveland, Ohio; the Department of Biostatistics and the Program for Population Genetics, Harvard University School of Public Health, Boston, Mass; and The Jackson Laboratory, Bar Harbor, Me.
Correspondence to Nicholas J. Schork, PhD, Department of Epidemiology and Biostatistics, Case Western Reserve University, R215 Rammelkamp Building, MetroHealth Medical Center, 2500 Metro-Health Drive, Cleveland, OH 44109-1998. E-mail njs2{at}po.cwru.edu
Modern molecular genetic analysis tools are making it possible for researchers to investigate, and in many cases actually disclose, mutations and other genetic factors that contribute to disease susceptibility. However, the ease with which these factors can be identified is dictated by not only the number of factors underlying or influencing the trait, but also by the manner in which these factors interact. Traits that are influenced by multiple genetic and nongenetic factors are termed "complex" genetic traits and are receiving a great deal of attention in the current medical literature. Hypertension and blood pressure regulation are considered paradigmatic complex traits. In this paper, the origin, nature, and dilemmas associated with the analysis of complex traits are considered. Basic biochemical and physiological determinants of blood pressure are described in an effort to show how genetic complexity could arise within an individual, and fundamental concepts in population genetics and evolutionary theory are discussed to expose the reasons certain forms of genetic complexity can emerge and be sustained in the population at large. Methods for approaching the genetic dissection of complex traits and diseases are also enumerated, with simple descriptions of the scientific motivation offered for each. Problems plaguing these approaches are also discussed. Finally, areas for future research are outlined with the hope of sparking further debate on the subject.
Key Words: linkage analysis • statistical models • gene mapping • complex traits • genetic epidemiology • Sewall Wright • evolution
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