Research Article: Genome Paths: A Way to Personalized and Predictive Medicine

Date Published: October , 2009

Publisher: A.I. Gordeyev

Author(s): V. S. Baranov.

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Abstract

The review is devoted to the impact of human genome research on progress in modern medicine. Basic achievements in genome research have resulted in the deciphering of the human genome and creation of a molecular landmarks map of the human haploid genome (HapMap Project), which has made a tremendous contribution to our understanding of common genetic and multifactorial (complex) disorders. Current genome studies mainly focus on genetic testing and gene association studies of multifactorial (complex) diseases, with the purpose of their efficient diagnostics and prevention . Identification of candidate (“predisposition”) genes participating in the functional genetic modules underlying each common disorder and the use of this genetic background to elaborate sophisticated measures to efficiently prevent them constitutes a major goal in personalized molecular medicine. The concept of a genetic pass as an individual DNA databank reflecting inherited human predisposition to different complex and monogenic disorders, with special emphasis on its present state, and the numerous difficulties related to the practical implementation of personalized medicine are outlined. The problems related to the uncertainness of the results of genetic testing could be overcome at least partly by means of new technological achievements in genome research methods, such as genome-wide association studies (GWAS), massive parallel DNA sequencing, and genetic and epigenetic profiling. The basic tasks of genomic today could be determined as the need to properly estimate the clinical value of genetic testing and its applicability in clinical practice. Feasible ways towards the gradual implementation of personal genetic data, in line with routine laboratory tests, for the benefit of clinical practice are discussed.

Partial Text

The revolutionary achievements in human genetics such as full genome seguencing, the successful completion of the HapMap program (haploid genome), the rapid development of bioinformatics and nanotechnology, advances in the delelopment of efficient methods for genome analysis are signs of a new era: the era of genomics. The 21st century could well be remembered as the century of genetics [1, 2]. Impressive progress in comparative and functional genomics has assured the widespread introduction of this branch in medicine. Thus, it has led to the emergence and rapid development of medical genomics in which such problems of classical medicine as diagnosis, prevention, and treatment are solved at the level of nucleic acids and the products of their expression: RNA and proteins [3, 4, 5]. The preventive direction in molecular medicine gave rise to predictive medicine (PM). Its main features appear to be its individual (the genome of every human individual) and preventive character (analyses of the genome are possible at any stage of ontogeny, long before the onset of a particular disease). The main principles of predictive medicine and genetic testing (GT) as a methodological basis for PM, as well as the concept of a “genetic passport,” were formulated by us in 2000 [5, 6, 37].

The genomes of all people, except for identical twins, are different. Pronounced population, ethnic, and, most importantly, individual genome features in translatable parts of genes (exons), as well as in their noncoding sequences (intergenic spaces and introns), are caused by mutations leading to genetic polymorphism (GP). The latter is usually defined as a mendelian trait occurring in the population, at least in two variants, with a frequency of not less than 1% for each one [10]. GPs may be quantitative or qualitative.

The key role in the study of GP is played by the international project for the study of the haploid human genome – Haploid Map (HapMap).

According to research in the prevalence of diseases in twin pairs and medical genetics data, only about 1.5% of human diseases are directly linked to mutations. These are so-called hereditary diseases. Accuracy in the molecular diagnosis of hereditary diseases is very high and approaches 100%.

In past decades the search for candidate genes has been performed by means of two approaches: the analysis of association and analysis of linkage.

Many diagnostic centers in Russia currently widely use molecular methods for the diagnosis of genetic diseases and detection of heterozygous carriage of pathological mutations in families at high risk for the preliminary diagnosis of diseases with a late manifestation and for personal identification (genomic fingerprinting). Gradually, genetic testing for predictive medicine is gaining in strength. Obviously, data on both the genome of individuals and entire families and, gradually, individual and family DNA databases are being created. Such an individual DNA database is a “genetic passport (pass).”

Testing for gene associations, i.e. the search for candidate genes coupled with a variety of MDs, is already widespread throughout the world, including at leading laboratories and genetic centers in Russia. According to international reports, thousands of polymorphic sites are tested daily to determine associations with diseases [28]. About 100 major candidate genes, each of which contains several polymorphic sites that affect the function of the gene and its products, have already been identified or are under study for common MDs.

The method of analysis of association (see Section 3) at best permits to reveal the most obvious, in terms of the pathogenesis of the disease, candidates genes and conduct a comparative analysis of allele frequencies in cohorts of patients and population controls.

Currently, there are already about 1,024 clinical genetic tests of MDs and there are more than 300 genetic tests that are in the pre-clinical and clinical trials stages [33]. For many MDs, some “major” genes have already been identified. Their involvement in a particular pathology has been confirmed by research on representative groups of patients in many laboratories. Such MDs include, for example, Alzheimer’s disease (AROE4), type-2 diabetes (PPARG, TCF7L2, KCNJ11), senile macular degeneration of the retina (CFH), systemic lupus erythematosus (JRF5), prostate cancer (region JF1H), type-1 diabetes (IL2RA, CD25, PTPN22), autoimmune thyroiditis (CTLA4), hirschsprung disease (RET), Crohn’s disease (NOD2, CARD15), and rheumatoid arthritis (PTPN22) [8, 34]. Nevertheless, the attitude toward GT remains quite skeptical, largely because of the absence of definite statistical evidence of the reliability of GT results.

The evaluation of genetic testing results should be conducted considering already existing knowledge about the gene networks of specific MDs, the population, gender, and age characteristics of the frequency of polymorphic alleles of the studied genes [37]. Considering the probabilistic nature of forecasts based on the genetic testing of hereditary predisposition to MDs, some assistance in assessing the risk of a hereditary predisposition can already provide a fairly simple method of score evaluation, which is used in some western countries (Harvard School of Public Health) and is already used in some Russian centers conducting genetic testing [38, 39, 40]. The essence of the method is as follows: each genotype variant is estimated on conditional points depending on whether the alleles identified are protective or predispose to the development of pathology. To this end, alleles with altered functional activity of the gene are assigned 1 point, while normal (frequent), wild-type alleles are assigned 0 point. Then, the points corresponding to genotype for every tested candidate gene are recorded, summed up, and divided by the number of tested genes. So, the risk of developing the disease could be conditionally evaluated as medium, low, or high. In the presence of pathogenetically complex MDs, including several different metabolic chains, the calculation is conducted for each gene network separately and the estimates obtained are added up. Some variants of score evaluations, in addition to the calculation of points corresponding to genotypes, also include conditional points of various exogenous factors (harmful effects, habit, medication intake, etc.), anthropometric values, as well as physical activity, sex, weight [26].

GT may offer real benefits only if it is accompanied by full consultation with a qualified clinical geneticist, with the provision of relevant recommendations to the physician and patient. GT may have practical value if the following conditions are fulfilled: (1) the results of GT are based on the analysis of genes whose association with the corresponding disease is shown in the population of the particular region; (2) the subject is a family member at high risk, where there is already a patient with this pathology; and (3) the GT data are subjected to adequate statistical analysis. Effective use of such information is largely determined by the level of genetic knowledge of physicians, their ability to apply the data to the diagnosis, prevention and treatment of diseases, as well as the willingness of the patient to follow the recommendations of physicians based on the results of genetic testing. [39]. But even under these conditions, GT results concerning hereditary predisposition should be interpreted very cautiously. When possible, GT should be complemented with an appropriate biochemical analysis allowing to evaluate the functional activity of the studied genes. It should be required that more objective information be obtained by testing the genes controlling only a single metabolic process; ie, the genes belonging to the same gene network. Thus, already today on the basis of genetic testing the functional conditions of the following systems can be assessed objectively: the detoxification system, blood coagulation, lipid or carbohydrate metabolism, the renin-angiotensin system, and others. Assessing the outcome and prognosis of hereditary predisposition to MDs caused by damage to several gene networks is much more difficult.

Thanks to impressive advances in genomics, the emergence of new, highly effective methods of molecular analysis, the search for marker genes associated with MDs has rapidly developed. As a result, (1) thousands of new marker genes, the allelic variants of which predispose to the development of pathological processes, have been identified; (2) the genetic panels of the most frequent chronic diseases has been established; and (3) marker genes defining the severity of the disease and predisposition to some complications are being identified.

The authors express their deep appreciation to the researcher of the Department of Biomedical Genetics, University Medical Center of Utrecht (Netherlands) A.P. Zhernakova for her valuable advice on the manuscript and the possibility to use her data concerning GWAS of a number of autoimmune diseases.

 

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