Human Diversity:  Impact on Genetic Testing and Screening

by Dana C. Crawford, Ph.D.
National Center on Birth Defects and Developmental Disabilities
Centers for Disease Control and Prevention

A well-publicized announcement on June 26, 2000, declared that a working draft of the human genome had been completed with efforts from the Department of Energy-funded Human Genome Project and Celera, a private for-profit company.  Since that announcement, a clearer picture of the human genome in general has developed.  We have learned that much of the DNA sequence is repetitive and a small proportion of the sequence actually codes for proteins.  In fact, the DNA sequence may code for as little as 30,000 genes, which is a fraction of the 100,000 genes predicted a few years ago.  Also, results suggest that the DNA sequence of any two humans will be >99.9%.  That is, the order and number of the chemical bases (A’s [adenines], T’s [thymines], G’s [guanines], and C’s [cytosines]) that make up our complete DNA sequence are almost uniform across human populations.

Despite this uniformity, every person is unique.  At least three factors are thought to play a role in shaping individuality and susceptibility to disease.  The first of these factors is the “environment.”  The term “environment” is broad and can represent anything nongenetic:  nutrition (what you eat), habits (smoking, alcohol use), and exposure to chemicals (medication, toxins).  Environment can also encompass broader measures of psychology (stress), sociology (peer groups), and geography (arid, tropical), all of which affect individuality and health at some level.  The list of what can be considered “environment” is long, making specific factors associated with individuality or disease challenging to identify.  Related to this challenge is how we measure environmental exposures.  These measurements must not only precisely estimate which person was exposed, but also when he or she was exposed (e.g., as a fetus or as an adult) and the magnitude of exposure (e.g., first-hand or second-hand smoke).

A second factor related to individuality and susceptibility to disease is our DNA sequence.  Although 0.1% doesn’t sound like much, given that the genome represents approximately 3 billion bases (As, Ts, Cs, and Gs), this fraction actually represents approximately 3 million bases that contribute to our complete DNA sequence.  Some of these single-base or multiple-base differences disrupt normal gene function, which can lead to serious medical disorders.  One example is sickle cell disease.  For the most common form of this disorder, an adenine (A) has been changed to a thymine (T) within a single position of the gene, disrupting the normal function of the beta-globin gene on chromosome 11.  The disruption causes the shape of the red blood cell to change from a round, flexible cell to a sickle-shaped cell.  The sickle cell is more likely than the round cell to clog small arteries and capillaries, resulting in local oxygen deficiency.  The mutations like the one that causes sickle cell are serious and, as a result, are usually rare in the general population.  Also, many of these diseases are caused by mutations in a single gene and are inherited from family members in specific patterns.

In contrast to the mutations that cause rare disorders, more common base changes known as polymorphisms can subtly affect gene function or might not affect it at all.  The more common variants that have a subtle impact on gene function are thought to be major factors in shaping individuality and susceptibility to disease. Unlike the rare mutations, the inheritance of these polymorphisms in relation to a disease within a family is difficult to characterize.  Also, these polymorphisms might work in combination in leading to disease, making it very difficult to identify and predict which combinations will lead to disease.  Researchers hope that understanding these complex gene-gene interactions will help prevent more common disorders in the general population such as hypertension, heart disease, and cancer.  Because of these potential medical benefits, the Human Genome Project is cataloguing these base-changes in several world populations and making these data available in a public database.  This effort to catalog human diversity by single base-changes is known as the Single Nucleotide Polymorphism (SNP) Consortium and promises to enhance our understanding of the impact genetic diversity on susceptibility to disease.

The third factor shaping diversity is gene-environment interaction.  A gene-environment interaction requires both a particular base change or changes and a particular environmental exposure to develop disease or a trait.  Like the complex gene-gene interactions, the gene-environment interactions are difficult to identify and comprehend in relation to the development of disease.  For example, a sedentary lifestyle and a diet high in saturated fats is related to the development of heart disease later in adult life.  However, heart disease also is common in some families, suggesting a strong genetic component.  The genes involved and their response to the environment and whether removal of the environmental risk factor lowers the chance of developing the disease are key elements to the promises of the Human Genome Project on the health of the general population.

Once the factors related to a particular disease are identified, testing or screening for these factors becomes possible.  Genetic testing and screening can take on many forms in both the types available and the populations to which they are offered.  The types of screening are carrier screening (identifying people who carry the mutation and can pass it to their children), predisposition screening (identifying people who are more susceptible than other people to a disease but who don’t yet have the disease), presymptomatic screening (identifying people who have a disease but don’t yet have the signs and symptoms of that disease), and affected screening (identifying people who have a disease and who have the signs and symptoms of that disease).  The tests can be offered to individuals, to entire populations, or to subsets of a specific population.  Many forms of testing can emerge from different combinations of the type of test and the population to which the test is offered.

One example of a specific form of screening is newborn screening. Newborn screening identifies infants affected with specific genetic disorders.  This screening strategy is performed at the population level because the treatments are effective only if these infants are identified soon after birth.  Population-based screening also ensures that infants who can benefit from these treatments are not missed.

Before laboratory tests can be used for any genetic testing or screening, they must meet several criteria to be considered suitable for use.  First, considerable knowledge must already exist about the disease including which genes contribute to it and how many and what kind of mutations are expected in these genes.  Also, the laboratory test itself must be accurate in identifying people with the mutations.  Each test should identify all or most of the people with the disease.  In addition, the test needs to be specific to one disease.  One type of laboratory test that meets these requirements is an approach that looks at gene products.  These tests can identify people with the disorder, including presymptomatic and affected persons.  These tests focus on the gene product rather than on the mutations in the gene and are usually biochemical tests.  Examples of these tests include the test for cystic fibrosis that examines the immunoreactive trysinogen, the test for sickle cell disease that examines the properties of hemoglobin, and the test for phenylketonuria or PKU that examines the levels of blood phenylalanine.  Although all of these disorders are caused by mutations in a single gene, the tests focus on the product of the gene rather than on the actual gene itself.

A second laboratory test approach identifies mutations in a gene.  Like the gene product approach, this approach can identify people with the disorder.  However, unlike some product approaches, these tests can also identify people who are themselves at-risk for the disorder or at risk of having a child with the disorder.  These tests focus on the sequence of the gene and are DNA-based.  An example of this approach is testing people to predict how they will react to certain drugs, testing people who are at-risk for breast cancer before they develop cancer, and testing people for carrier status for cystic fibrosis.

Although gene-based testing has great promise in predicting and preventing or treating disease, designing accurate tests in not easy.  Again, for DNA-based screening, one must know which gene is involved and which mutations cause disease.  Few disorders are caused by only one mutation in a single gene.  In fact, many single gene disorders are caused by one of thousands of single mutations within that gene.  Two disorders illustrate this difference: sickle cell disease and cystic fibrosis.  Both are single-gene disorders, yet most cases of sickle cell disease are caused by only one mutation in a single gene, while cystic fibrosis can result from one of a thousand mutations in a single gene.  Most conventional technology does not allow the entire gene to be searched for every possible mutation.  Therefore, for cystic fibrosis, the question is: “For which mutations should we search first?”.

To answer this question, researchers rely on the population genetics and history of the mutation, that is, some diseases and the corresponding mutations occur more often in one population than in another.  For sickle cell disease, the disorder-causing mutation originated in Africa; therefore, persons of African descent are at higher risk for this disease than are persons of non-African descent.  The mutations for cystic fibrosis originated in Europe; therefore, persons of European descent are at higher risk than are other populations.  Furthermore, some specific mutations that cause cystic fibrosis are clustered within certain European ethnic groups, such as the Ashkenazi Jewish population.  This phenomenon is known as a founder effect, where the common mutation(s) are thought to be direct descendants from the original or founding mutation within that specific population.  Researchers use this information to guide decisions about which mutations might be detected by screening.

This population genetics approach can provide clues, but it is not without challenges.  First, a person is difficult to define in the context of a larger population.  For the United States, the population is constantly mobile and in flux.  Most populations are a mixture of two or more populations.  These two factors make it more difficult to predict the particular mutations that might be found in an individual.  Given these factors, genetic testing and screening must be inclusive rather than exclusive to identify all mutations in all people.

A broader problem of genetic research is the lack of data in many populations.  Often, groups tend not to participate in research because of concern about genetic discrimination or because of a general distrust of science because of religious or cultural beliefs.  As research in genetics continues, different populations need to become involved, and representatives from these populations need to be included to address these concerns for genetic testing and screening.

As demonstrated above, the decision to test for specific mutations is difficult for single-gene disorders.  The decisions will be even more complicated for more common disorders that have gene-gene and gene-environment interactions.  Despite these current limitations, many researchers have declared that, “the future of medicine is now.”  Undoubtedly, research inspired by the Human Genome Project will lead to a better understanding of human diversity.  This understanding will translate into ways we can predict disease and ultimately promote health by preventing or treating disease. For this hope to become a reality, populations from around the world must participate in this research to ensure that no one group is excluded from the education and benefits these research findings have to offer.