Genetic variants in association studies--review of strengths and weaknesses in study design and current knowledge of impact on cancer risk

Acta Oncol. 2009;48(7):948-54. doi: 10.1080/02841860903124648.

Abstract

Sequencing of the human genome has recently been completed and mapping of the complete genomic variation is ongoing. During the last decade there has been a huge expansion of studies of genetic variants, both with respect to association studies of disease risk and for studies of genetic factors of prognosis and treatments response, i.e., pharmacogenomics. The use of genetics to predict a patient's risk of disease or treatment response is one step toward an improved personalised prevention and screening modality for the prevention of cancer and treatment selection. The technology and statistical methods for completing whole genome tagging of variants and genome wide association studies has developed rapidly over the last decade. After identifying the genetic loci with the strongest, statistical associations with disease risk, future studies will need to further characterise the genotype-phenotype relationship to provide a biological basis for prevention and treatment decisions according to genetic profile. This review discusses some of the general issues and problems of study design; we also discuss challenges in conducting valid association studies in rare cancers such as paediatric brain tumours, where there is support for genetic susceptibility but difficulties in assembling large sample sizes. The clinical interpretation and implementation of genetic association studies with respect to disease risk and treatment is not yet well defined and remains an important area of future research.

Publication types

  • Review

MeSH terms

  • Genetic Markers
  • Genetic Predisposition to Disease
  • Genetic Variation*
  • Genome, Human
  • Genome-Wide Association Study / methods*
  • Genotype
  • Humans
  • Neoplasms / epidemiology
  • Neoplasms / genetics*
  • Neoplasms / prevention & control
  • Pharmacogenetics
  • Phenotype
  • Polymorphism, Genetic
  • Predictive Value of Tests
  • Rare Diseases / genetics
  • Research Design*
  • Risk Assessment
  • Sample Size

Substances

  • Genetic Markers