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Cancer Genetics Overview (PDQ®): Genetics - Health Professional Information [NCI] - Methods of Genetic Analysis and Gene Discovery

Linkage Analyses

The recognition that cancer clusters within families has led many investigators to collect data on multiple-case families with the goal of localizing cancer susceptibility genes through linkage studies.

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Linkage studies are typically performed on high-risk kindreds, in whom multiple cases of a particular disease have occurred, in an effort to identify disease susceptibility genes. Linkage analysis statistically compares the genotypes between affected and unaffected individuals and looks for evidence that known genetic markers are inherited along with the disease trait. If such evidence is found (linkage), it provides statistical data that the chromosomal region near the marker also harbors a disease susceptibility gene. Once a genomic region of interest has been identified through linkage analysis, additional studies are required to prove that there truly is a susceptibility gene at that position. Linkage analysis is affected by the following:

  • Family size and having a sufficient number of family members who volunteer to contribute DNA.
  • The number of disease cases in each family.
  • Factors related to age at disease onset (e.g., utilization of screening).
  • Gender differences in disease risk (not relevant in gender-specific cancers).
  • Heterogeneity of disease in cases (e.g., aggressive vs. nonaggressive phenotype).
  • The accuracy of family history information.
  • Prevalence of phenocopies.

An additional issue in linkage studies is the background rate of sporadic cancer in the context of family studies. For example, because a man's lifetime risk of prostate cancer is one in six,[1] it is possible that families under study have both inherited and sporadic prostate cancer cases. Thus, men who do not inherit the prostate cancer susceptibility gene that is segregating in their family may still develop prostate cancer.

One way to address inconsistencies between linkage studies is to require inclusion criteria that defines clinically significant disease.[2,3,4] This approach attempts to define a homogeneous set of cases/families to increase the likelihood of identifying a linkage signal. It also prevents the inclusion of cases that may be considered clinically insignificant that were identified by screening in families.

Investigators have also incorporated clinical parameters into linkage analyses with the goal of identifying genes that may influence disease severity.[5,6] This type of approach, however, has not yet led to the identification of consistent linkage signals across datasets.[7,8]

Genome-wide Association Studies (GWAS)

GWAS are showing great promise in identifying common, low-penetrance susceptibility alleles for many complex diseases,[9] including cancer. This approach can be contrasted with linkage analysis, which searches for genetic-risk variants cosegregating within families that have a high prevalence of disease. While linkage analyses are designed to uncover rare, highly penetrant variants that segregate in predictable heritance patterns (e.g., autosomal dominant, autosomal recessive, X-linked, and mitochondrial), GWAS are best suited to identify multiple, common, low-penetrance genetic polymorphisms. GWAS are conducted under the assumption that the genetic underpinnings of complex phenotypes, such as prostate cancer, are governed by many alleles, each conferring modest risk. Most genetic polymorphisms genotyped in GWAS are common, with minor allele frequencies greater than 1% to 5% within a given population (e.g., men of European ancestry). GWAS capture a large portion of common variation across the genome.[10,11] The strong correlation between many alleles located close to one another on a given chromosome (called linkage disequilibrium) allows one to "scan" the genome without having to test all 10 million known single nucleotide polymorphisms (SNPs). With GWAS, researchers can test 500,000 to 1 million SNPs per study and ascertain almost all common inherited variants in the genome.

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WebMD Public Information from the National Cancer Institute

Last Updated: February 25, 2014
This information is not intended to replace the advice of a doctor. Healthwise disclaims any liability for the decisions you make based on this information.
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