Research Methods for Genetic Studies

  • Sadeep Shrestha
  • Donna K. Arnett


This chapter introduces the basic concepts of genes and genetic studies to clinicians. Some of the relevant methods and issues in genetic epidemiology studies are briefly discussed with an emphasis on single nucleotide polymorphism based association studies which are currently the main focus of clinical and translational genetics.

Genetics is the fundamental basis of any organism so understanding of genetics will provide a powerful means to discover hereditary elements in disease etiology. In recent years, genetic studies have shifted from disorders caused by a single gene (e.g. Huntington’s disease) to common multi-factorial disorders (e.g. hypertension) that result from the interactions between inherited gene variants and environmental factors, including chemical, physical, biological, social, infectious, behavioral or nutritional factors.

A new field of science, Genetic Epidemiology emerged in the 1960s as a hybrid of genetics, biostatistics, epidemiology and molecular biology, which has been the major tool in establishing whether a phenotype (any morphologic, biochemical, physiologic or behavioral characteristic of an organism) has a genetic component. A second goal of genetic epidemiology is to measure the relative size of that genetic effect in relation to environmental effects. Morton and Chung defined genetic epidemiology as “a science that deals with the etiology, distribution, and control of disease in groups of relatives, and with inherited causes of disease in populations”.1 In the era of a known human genome sequence, genetic epidemiology methods have been instrumental in identifying the contribution of genes, the environment and their interactions to better understanding disease processes.

Genomic scientists have predicted that comprehensive, genomic-based care will become the norm, with individualized preventive medicine, early detection of illnesses and tailoring of specific treatments to genetic profile. Practicing physicians and health professionals need to be knowledgeable in the principles, applications, and limitations of genetics to understand, prevent, and treat any biological disorders in their everyday practice. The primary objective of any genetic research is to translate information from individual laboratory specimen and build inferences about the human genome and its influence on the risk of disease. This chapter will focus on the fundamental concepts and principles of genetic epidemiology that are important to help clinicians understand genetic studies.


Genetic Effect Short Tandem Repeat Population Stratification Familial Aggregation Candidate Gene Approach 
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  1. 1.
    Morton NE. Genetic Epidemiology. New York: Academic; 1978.Google Scholar
  2. 2.
    Redon R, Ishikawa S, Fitch KR, et al. Global variation in copy number in the human genome. Nature. Nov 23 2006; 444(7118):444–454.PubMedCrossRefGoogle Scholar
  3. 3.
    Lewontin RC. The interaction of selection and linkage. I. General considerations; heterotic models. Genetics. 1964; 49:49–67.PubMedGoogle Scholar
  4. 4.
    Ardlie K, Kruglyak L, Seislstad. Patterns of linkage disequilibrium in the human genome. Nat Genet. 2002; 3:299–309.Google Scholar
  5. 5.
    Clark AG. Inference for haplotypes from PCR-amplified samples of diploid populations. Mol Biol Evol. 1990; 7:111–122.PubMedGoogle Scholar
  6. 6.
    Lin S, Cutler D, Zwick M, Chakravarti A. Haplotype inference in random population samples. Am J Hum Genet. 2002; 71:1129–1137.PubMedCrossRefGoogle Scholar
  7. 7.
    Excoffier L, Slatkin M. Maximum-likelihood estimation of molecular haplotype frequencies in a diploid population. Mol Biol Evol. 1995; 12:921–927.PubMedGoogle Scholar
  8. 8.
    Istrail S, Waterman M, Clark AG. Computational Methods for SNPs and Haplotype Inference. Berlin, Heidelberg: Springer; 2004.Google Scholar
  9. 9.
    Kerber RA, O’Brien E. A cohort study of cancer risk in relation to family histories of cancer in the Utah population database. Cancer. May 1 2005; 103(9):1906–1915.PubMedCrossRefGoogle Scholar

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© Springer Science + Business Media B.V 2008

Authors and Affiliations

  • Sadeep Shrestha
    • 1
  • Donna K. Arnett
    • 1
  1. 1.Department of Epidemiology, School of Public HealthUniversity of Alabama at BirminghamBirmingham

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