GBIPM is a medical model that employs individuals’ genetic information in determining measures to prevent or treat certain illnesses. It emerged as a result of the Genome Project that was meant to evaluate the genetic sequence by identifying genes that cause various illnesses. People usually have different genetic makeup. For this reason, GBIPM is rapidly developing to improve personal health care. This model accomplishes its purpose of influencing decision making concerning individualized health care. This is attributed to the fact that it employs genetic information of individuals. As mentioned earlier, individuals have different genetic profiles. Therefore, individuals experience different health problems. Despite other contributing factors such as environment, genetics play a major role in individuals’ health issues. In this respect, prevention and treatment measures should be precisely tailored for individuals. This has been achieved through several dimensions that, if emphasized, will continue to shape the direction of public health (Willard and Ginsburg, 2009).
In the first place, there is the identification and development of predictive and preventive medicine. Predictive medicine deals with prediction about the likelihood of a disease. On the other hand, preventive medicine is concerned with preventing the disease. Genomic profiles can be prepared in advance by individuals undergoing specialized tests to provide their genetic information. For instance, if the genomic profile of an individual predicts the likelihood of a certain disease happening like the heart disease, the medical practitioner can initiate preventive measures to prevent or reduce the severity of the disease respectively (Willard and Ginsburg, 2009).
Another significant dimension that GBIPM has been using can be seen in the selection of treatment and medication for individuals. This has been successful in determining of treatments and medications for various diseases especially cancer. Furthermore, in prevention, prediction is necessary during the treatment of a disease. It can help to determine the disease cause and thus assist in selecting the appropriate treatment and medication for the disease. For example, when one has cancer, genetic information can be of vital importance in determining of medication. Cancer medication responds differently based on genetic variation. In addition, genetic variation can also be used to predict whether diseases such as cancer will spread to other organs of the body. This information can have a direct influence on how to treat the disease, as well as improve the patient outcomes (Willard and Ginsburg, 2009).
As earlier mentioned earlier, apart from genetic factors, there are other factors that contribute to causing health issues among individuals. However, these factors such as environment interact with the genetic factors in one way or another. Gene to gene and gene to environment interactions have taken a dominant position in epidemiology studies regarding disease causes and outcomes. Research has proved that the occurrence of any disease is attributed to genetic factors and other factors at the same time. Molecular and Genetic epidemiology seeks to evaluate ways in which genetic factors interact with various factors to contribute to human carcinogens that trigger heath issues within individuals. In the first way, it establishes the correlation between genes and the disease or disorder. Secondly, it establishes the magnitude of genetic impact with respect to other risk factors to the disorder. Finally, it identifies the genes that make up the genetic component. Molecular epidemiology measures exposures that relate to certain substances. It also evaluates characteristics of the genotypes using precise markers to identify disease categories. On the other hand, genetic epidemiology is similar to molecular epidemiology. However, it concentrates on the causes attributed to inheritance. It incorporates molecular biology into genetic research, and this has enabled medical practitioners to understand the nature and risk factors of inherited diseases. In turn, this has ensured the development of effective medical prevention and treatment methods (Friis, 2010).
Measurement of these carcinogens or bio-markers, which include proteins, chemicals, DNA, and hormones, provide relevant measures to human exposure. Exposure to certain environmental factors causes mutation of genes. The presence of carcinogens contributes to gene mutation in a great way. Epidemiology knowledge would thus help to identify the targeted genes and predict ways in which other factors cause diseases. In instances where carcinogens trigger gene mutation, detection of the mutation pattern can be instrumental in identifying the risk factors. Additionally, this would help to initiate early prevention and diagnostic measures of the disease (Friis, 2010).
Besides the advances of epidemiology in genetics, its absence would lead to certain implications. Without the use of molecular and genetic epidemiology, focus of GBIPM would mostly concentrate on the prevention of diseases rather than their treatment and outcomes. This will result to considerable challenges in the treatment of diseases. In this case, GBIPM relies on the gene to gene interactions to determine preventive and treatment measures of diseases. Next, epidemiology helps to identify the role that other factors play where genetic factors have minimal or no influence in a certain disease. The interaction of these factors is crucial in understanding, as well as interpreting genes’ contribution to diseases. Failure to incorporate the role of other risk factors would mean decreased sensitivity in determining the relation of the gene to the disease (Friis, 2010). Therefore, this would lead to inconsistent results pertaining to genes’ association with diseases hence poor prevention and treatment measures.
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