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The concept of predictive medicine based on the detection of genetic markers for disease susceptibility stemmed from the finding that many diseases are associated with specific HLA alleles. This model suggested that similar associations probably existed with other genes located all along the human genome. The Human Specimen Study Center (HSSC) was created to assist in investigating this possibility and has contributed significantly to the knowledge contained in current genetic and physical human genome maps. Predictive medicine is intended not for patients but for healthy individuals, its goal being to determine whether their susceptibility to a specific disease is increased or not. Fetuses with evidence of disease are excluded from the province of predictive medicine, which can, however, determine whether a healthy fetus is at high risk for developing a disease in adolescence or adulthood. Predictive medicine is based on probabilities: it evaluates diseases susceptibility but cannot predict with 100% certainty that a specific disease will occur. Whereas many preventive interventions are directed at groups (e.g., immunization programs), predictive medicine is conducted on an individualized basis. For instance, glaucoma is a monogenic disease whose early detection can allow to prevent permanent loss of vision. The fruits of predictive medicine are expected to be greatest, however, in the polygenic multifactorial diseases that are prevalent in industrialized countries, such as diabetes mellitus, hypertension, myocardial infarction, hyperlipidemia, and arteriosclerosis. An ability to detect subjects who are susceptible to breast cancer would be extraordinarily useful, and may be a goal within reach since two breast cancer susceptibility genes have already been identified. Genes associated with increased susceptibility to colon cancer have also been reported. Predictive medicine raises a number of sensitive ethical issues. Individuals should be free to accept or decline disease susceptibility testing after having been fully informed. Confidentiality is vital. The results of susceptibility tests should not be made available to employers or insurance agencies. Susceptibility testing should be offered only if the disease requires a specific treatment or lifestyle modification. Unnecessary anxiety may be one of the main adverse effects of susceptibility testing. A large number of disease susceptibility or resistance genes will probably be identified in the near future, and this will inevitably have an impact on the way physicians approach their patients. Physicians in the XXIst century will spend an increasingly large proportion of their time counselling their patients on how to stay healthy. This trend can be expected to translate into a marked increase in life expectancy. Rather than seeking to add years to life, physicians will strive to add life to years.
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PMID:[Predictive medicine and its ethics]. 929 63

As new genes and common mutations are identified, DNA testing can be offered. Like clinical testing used in glaucoma, such as IOP, tonography, disc measurements, nerve fiber layer analysis, and the various methods of visual field analysis, well-designed studies are needed to be able to interpret clearly the meaning of abnormal results. To use DNA testing to identify individuals at high risk for glaucoma, it is necessary to have solid evidence with sensitivity and specificity parameters, genotype-phenotype correlations, and information on prevalence and penetrance. These data will have to be replicated in several studies using large, population-matched control groups. Mass screening of glaucoma patients for Myocilin mutations may be worthwhile if 3% to 5% of glaucoma patients will be positive. For comparison, screening all cases of colon cancer for gene mutations involved in hereditary nonpolyposis colorectal cancer is considered feasible and desirable with a yield of only 3%. Recent research has shown the value of early treatment of glaucoma. The cost effectiveness of genetics screening will need to be weighed against the cost of conventional screening and the benefits of early treatment considered. Within glaucoma pedigrees with known mutations, DNA mutation-positive individuals will need more frequent clinical screening, whereas DNA mutation-negative individuals will need less frequent follow-up. It is likely that, for every positive-mutation glaucoma case identified, there will be on average two siblings and two children to test. In addition to the laboratory costs, the costs of counseling, and, in particular, the availability of suitably trained individuals who can correctly interpret these test results, must be considered. The risk and benefits of these measures must be calculated and then balanced with the long-term visual outcome of such a strategy. How could genetic testing alter management in glaucoma? If a family member in a Myocilin pedigree with a severe mutation is negative for the mutation, that individual's risk changes from 50% to that of the general population (ie, -2%), and the frequency of clinical screening can be reduced. There are ethical issues involved in testing, particularly in children, but testing would seem justified in congenital, developmental, and juvenile glaucoma. Issues related to insurance may affect the decision making of some patients. A further consideration, which may regrettably become important in the future, is that of intellectual property and patent issues pertaining to glaucoma gene discovery. In addition to clinical evidence of the value of predictive DNA testing, it is incumbent on those working in the field to evaluate the acceptability of testing to patients and their family members. The authors' experience to date is that predictive DNA testing in glaucoma is well supported in suitable families. As with predictive DNA screening in other ophthalmic conditions, issues relating to insurance, ethics, and confidentiality need to be taken into consideration. Although many of the more recently described genetic associations of POAG require more thorough evaluation, Myocilin gene testing can and should be offered for young-onset severe glaucoma cases with a positive family history.
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PMID:Predictive DNA testing for glaucoma: reality in 2003. 1474 Oct 4

Clinically relevant family history information is frequently missing or not readily available in electronic health records. Improving the availability of family history information is important for optimum care of many patients. Family history information on five conditions was collected in a survey from 163 primary care patients. Overall, 53% of patients had no family history information in the electronic health record (EHR) either on the patient's problem list or within a templated family history note. New information provided by patients resulted in an increase in the patient's risk level for 32% of patients with a positive family history of breast cancer, 40% for coronary artery disease, 50% for colon cancer, 74% for diabetes, and 95% each for osteoporosis and glaucoma. Informing physicians of new family history information outside of a clinic visit through an electronic clinical message and note in the EHR was not sufficient to achieve recommended follow-up care. Better tools need to be developed to facilitate the collection of family history information and to support clinical decision-making and action.
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PMID:Do physicians take action on high risk family history information provided by patients outside of a clinic visit? 1791 69

Associations of cytochrome P450 (CYP) polymorphisms with risk of disease development have been reported widely. For lung cancer, a large number of studies on CYP1A1, CYP2D6, and CYP2A6 polymorphisms have been performed. However, recent studies, including meta-analyses and genome-wide association studies, suggest that only the CYP2A6 association, where genotypes associated with low activity decrease susceptibility possibly due to slower nicotine metabolism, appears significant. Associations with lung cancer susceptibility have also been reported for CYP1A2, CYP1B1, and CYP2E1 polymorphisms but these, though biologically plausible, have not been well replicated. For cancers where exposure to xenobiotics other than tobacco smoke affects risk, CYP polymorphisms may also be relevant. Examples include CYP3A for hepatocellular carcinoma due to aflatoxin exposure, CYP1A2 for colon cancer associated with heterocyclic arylamine exposure and CYP2E1 for nitrosamine-related nasopharyngeal cancer. For other diseases, a well-established example relates to CYP1B1 where homozygosity for rare mutations occurs in primary congenital glaucoma. Rare CYP1B1 mutations and possibly polymorphisms may also contribute to risk for more common forms of glaucoma. CYP2C isoforms and CYP2J2 contribute to extrahepatic metabolism of arachidonic acid to epoxyeicosanoic acids which have effects in the cardiovascular system. Genotype for these isoforms may be relevant to risk of cardiovascular disease but evidence is still lacking. CYP2C19 poor metabolizers may be at increased risk of endometriosis, and CYP2E1 genotype may modulate risk of development of alcoholic liver disease. In conclusion, CYP polymorphisms are relevant to risk for some diseases but this may have been overstated in earlier studies.
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PMID:Polymorphic Variants of Cytochrome P450: Relevance to Cancer and Other Diseases. 2623 4

A fundamental goal of epidemiologic research is to investigate the relationship between exposures and disease risk. Cases of the disease are often considered a single outcome and assumed to share a common etiology. However, evidence indicates that many human diseases arise and evolve through a range of heterogeneous molecular pathologic processes, influenced by diverse exposures. Pathogenic heterogeneity has been considered in various neoplasms such as colorectal, lung, prostate, and breast cancers, leukemia and lymphoma, and non-neoplastic diseases, including obesity, type II diabetes, glaucoma, stroke, cardiovascular disease, autism, and autoimmune disease. In this article, we discuss analytic options for studying disease subtype heterogeneity, emphasizing methods for evaluating whether the association of a potential risk factor with disease varies by disease subtype. Methods are described for scenarios where disease subtypes are categorical and ordinal and for cohort studies, matched and unmatched case-control studies, and case-case study designs. For illustration, we apply the methods to a molecular pathological epidemiology study of alcohol intake and colon cancer risk by tumor LINE-1 methylation subtypes. User-friendly software to implement the methods is publicly available.
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PMID:Statistical methods for studying disease subtype heterogeneity. 2661 6