Considerations include test quality, the potential usefulness of the information
the test provides, available preventive or treatment options, and social issues.
Test Quality
The analytical validity of a test can be determined by its
- Sensitivity - test detects the mutations it was designed to detect
- Specificity - test detects only those mutations it was designed to detect (i.e., it
does
not flag other DNA sequence variations, some of which may be normal variation)
Clinical Utility
What practical information can this test provide? What is the probability
that a person who has or will get a disease will test positively? Need to consider
test results in the context of mutation variability, gene penetrance,
and gene expressivity.
Mutation variability (heterogeneity): Many different mutations
can cause the same disease. Mutations can be in the same or different genes.
Mutation tests often test for only the most common mutations.
Example: Cystic fibrosis --over 700 mutations (most are rare) in CFTR gene. Current tests are for
about 70 common mutations.
It is important to consider the proportion of people with clinically significant disease that are
detected by the test (clinical sensitivity). Current CF tests pick up 90% of CF mutations in whites,
50% in African-Americans and Hispanics, and 30% in Asian Americans.
Gene Penetrance: Probability of getting the disease when mutation
is present. Incomplete penetrance - an individual with a mutation may never
get the disease.
Example: BRCA1 and 2 genes (associated with a rare form of breast
cancer) and ApoE gene (modifies risk of Alzheimer's Disease). Possible reasons
for incomplete penetrance: Some mutations work together with other (unknown)
mutations or with environmental factors.
Some mutations are completely penetrant - an individual with the mutation always gets the
disease. Examples are Huntington's disease and Familial Adenomatous Polyposis (FAP) --a rare,
inherited colon cancer that accounts for about 1% of all colorectal cancers.
Gene Expressivity: Range of disease severity for a mutation. Severity can vary
widely
for some diseases, and few specific mutations have been correlated with the severity of their
expression in an individual.
Example: Severity of cystic fibrosis ranges from mild bronchial symptoms
and male sterility to severe lung, pancreatic, and intestinal difficulties (usually
fatal by 30 years of age).
The most common mutation in Caucasians has been associated with pancreatic insufficiency, but
few other correlations have been made of disease gene mutations and their particular expression.
Available Treatment Options
Few treatments or preventive strategies exist for patients testing positive for most gene tests.
Unfortunately, knowledge of a gene mutation alone is insufficient information for researchers
trying to devise intervention strategies. Researchers must first understand the normal function of
the disease-associated gene(s) and determine how the mutation disrupts that function.
Some exceptions exist, such as that for FAP. Experts recommend that even children at high risk
be screened for mutations in the APC gene associated with FAP, because they can be monitored
more frequently for growths and effective preventive surgical options can be chosen. Left
untreated, FAP causes death at an average age of 42.
Social Issues
Genetic information is personal, powerful, potentially predictive, pedigree sensitive (affects
families as well as individuals), permanent, and prejudicial.
Education on implications of testing and results is critical,
yet only 2000 specially trained genetic counselors are currently available in
the U.S., and training programs are not increasing their rolls. Most people
will need to rely on primary-care physicians to explain results. This poses
a great challenge for physicians, many of whom are not trained in molecular
genetics. Many commercially available gene tests are still controversial in
the scientific community, where their interpretation is debated.
Psychological issues - fear of unknown, coping with uncertainty, guilt, shame,
survivor guilt, family dynamics.
Discrimination risk - by employers, insurers, commercial institutions, schools,
army,
others.
Ethical issues - privacy and confidentiality, fairness in use of information,
commercialization/patents, social concepts of health and disease, reproductive rights.
For more information, see:
August 1998. Denise Casey, Science Writer (caseydk@ornl.gov)
Human Genome Management Information System
Oak Ridge National Laboratory
1060 Commerce Park
Oak Ridge, TN 37830
865/574-0597, Fax: /574-9998
HGMIS Web Site
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