Role of Genetic Variations in Human Diseases: Past, Present, Future - Research Paper Example

Role of Genetic Variations in Human Diseases: Past, Present, Future Introduction It is now a reality that the vast majority of the human genome has been sequenced in the laboratory; however, this has been possible due to numerous conceptual and technological advances in the area of genetics and related technologies. This had been a process of evolution where over time scientists were able to elucidate the DNA double-helix structure, discover the restriction enzymes, and eventually the polymerase chain reaction (PCR). All these led to the development and automatization of DNA sequencing leading to generation of physical and genetic maps by the well discussed Human Genome Project (HGP). This led to accumulation of a wealth of knowledge about the genetics per se and its possible variations, and it took no time to find the links between complex diseases and practice of medicine, although its is still challenging to integrate genetics into the everyday practice of clinical medicine. Sufficient advances have been made to date in the area of understanding disease etiology and pathogenesis from the perspective and context of genetic variation as a driver, and with development of modern genetic laboratory technologies, it is now a reality that in the near future, there would be increasing role for genetics in the diagnosis, prevention, and treatment of complex diseases, almost all except those caused by trauma. In fact following the knowledge accumulation from the Human Genome Project, the causation of common and complex diseases in relation to genetic variation in the fields of molecular epidemiology, medicine, and pharmacogenomics was a prime research interest. This was in sharp contrast with the traditional approach of studying human diseases contemplated to be caused by relatively rare single-gene diseases, which cumulatively account for merely 10% of diseases apparent in the pediatric age group. However, in reality, the post Human Genome Project research in this field is tending to increasingly demonstrate that virtually every medical condition has a genetic component. There is, however, considerable difficulty in characterizing these conditions since there is a vast number of genetic variations and their combinations, synergistic effects of multiple causative genes, and reactions of genetic traits with environmental factors, all of which may play roles together to cause manifestations of a complex disease. Disease loci of single gene variations through Mendelian inheritance have been successfully mapped; however, delineating the genetic variations and determinants had been more difficult and is a comparatively newer area of research. Currently, significant advances in the area of Bioinformatics have increased the possibilities of successful investigations about the genetic determinants of complex diseases. As is often evident from a patient's family history, many common disorders such as hypertension, heart disease, asthma, diabetes mellitus, and mental illnesses are significantly influenced by the genetic background. These polygenic or multifactorial disorders involve the contributions of many different genes, as well as environmental factors that can modify disease risk. Cancer has a genetic basis since it results from acquired somatic mutations in genes controlling growth and differentiation. In addition, the development of many cancers is associated with a hereditary predisposition. The prevalence of genetic diseases, combined with their severity and chronic nature, imposes a great financial, social, and emotional burden on society, and therefore research in this area is strongly indicated to solve the problems of application of this science into accurate characterization of the disease processes, so a clinical and therapeutic solution for these problems are accessible to both the medical community and the patients. While traditionally and historically, genetics has focused its attention on Mendelian causation of chromosomal and metabolic disorders such as trisomy 21, Turner Syndrome and investigation of these problems through cytogenetic techniques, and some of these diseases with typical biochemical manifestations such as phenylketonuria and familial hypercholesterolemia have been investigated traditionally through biochemical analyses, recent advances in DNA diagnostic technologies have extended to encompass all areas of medicine and many other hitherto unknown complex diseases. For example, in cardiology, the molecular basis of inherited cardiomyopathies and ion channel defects that predispose to arrhythmias is being defined on a genetic basis. In the field of neurology, genetics has unmasked the pathophysiology of an enormous number of neurodegenerative disorders and their causative mechanisms. There had been dramatic evolution in the field of hematology and has provided incipient genetic descriptions of hemoglobinopathies and molecular basis of red cell membrane defects, clotting disorders, and thrombotic disorders. The most startling of all perhaps is the story of cancers and unfolding its mystery since it is now abundantly clear that neoplasia and the acquisition of metastatic potential can be described in genetic terms. Genomics as a discipline has supplied a rich resource of gene mapping data and the individual variants in each gene at the single nucleotide polymorphism (SNP) and chromosome locus levels. Genetic polymorphism occurs in the form of gross structural change, including nucleotide substitution, complete gene deletion, gene duplication, and genetic translocation where portions of similar genes are combined creating a new gene hybrid. By far, the most common form of genetic polymorphism is a single nucleotide polymorphism (SNP) where the nucleotide sequence at one specific position is changed by substitution, translocation, insertion, or deletion. Each of these changes in the gene structure introduces a variant form of the gene into the population gene pool and is designated an allele of the original gene. Thus, an allele is an inherited gene that is present in each nucleated cell of the body. Because of the diploid structure of the human genome, each cell carries two copies of each gene. Two copies of the same allele yield a homozygous genotype and any combination of two different alleles yields a heterozygous genotype. Complex Diseases and Genetic Background In many cases, improved techniques of molecular genetics have improved the feasibility and accuracy of diagnostic testing. The revealed information has enhanced the understanding of pathophysiology, and thus is opening novel strategies for therapy that includes gene and cellular therapy. It has also been observed that these new genetic concepts are beginning to clarify the pathogenesis of complex diseases previously not understood. Many different genetic defects have been associated with peripheral neuropathies; however, the final common pathway has been frequently acknowledged to be disruption of the normal folding of the myelin sheaths. Similarly several genetic causes of obesity uniformly converge on the genetically induced physiologic pathway involving gene products of the proopiomelanocortin polypeptide and the MC4R receptor. This gives a genetically valid identification method for a key mechanism for control of appetite. Genetically distinct forms of Alzheimer's disease have been described which explains formation of neurofibrillary tangles. The main theme of identification of various defective genes leading to cellular pathways that pinpoint to the key physiologic processes. Some of these examples include identification of the cystic fibrosis conductance regulator (CFTR) gene, the Duchenne muscular dystrophy (DMD) gene encoding dystrophin, and the fibroblast growth factor receptor-3 (FGFR3) gene responsible for achondroplastic dwarfism. Similarly, transgenic overexpression, and targeted gene "knockout" and "knockin" models help to unravel the physiologic function of genes. Genetic approaches have proven invaluable for the detection of many infectious pathogens and are used clinically to identify agents that are difficult to culture and identify. New genetic information is being generated at a rapid rate. This is a major challenge for clinicians and basic investigators. The terminology and techniques are evolving continuously. At the current state of affairs much genetic information resides in computer databases, which provide easy access to the expanding information about the human genome, genetic disease, and genetic testing. For example, several thousand monogenic disorders are summarized in a large, continuously evolving compendium, referred to as the Online Mendelian Inheritance in Man (OMIM) catalog. The ongoing refinement of bioinformatics is simplifying the access to this seemingly daunting task of making sense from newly evolving information. Consequently understanding the mechanisms of DNA variations leading to diseases, naturally occurring phenotypic variations, and complex biological systems are important parameters of human genetic research. The situation has further been complicated by the finding that many complex diseases and phenotypic expressions are influenced by diverse genetic and environmental factors. This has enhanced the difficulty levels of comprehension, identification, and characterization of specific genetic variations involved in specific human diseases and their phenotypes. The roles of these genetic variations in pathophysiological processes of several human diseases are of research interest. There are several evidences in research where the researchers have investigated the genetic variations in several complex human diseases. Akahoshi et al. (2006) indicated the complex genetic basis in the context of several susceptibility genes on multiple chromosomes as the causative phenomenon in systemic lupus erythematosus which is a systemic autoimmune disease. As indicated earlier, this disease and associated genetic variations involve different determinants from the genetic and environmental factors (Akahoshi et al. 2006). Similarly, Gerritsen (2005) indicates role of genomic variations in vascular genes in different human phenotypes of molecular vascular biology highlighting different activities of endothelial nitric oxide synthase and vascular endothelial growth factors. These have been correlated with several human diseases involving endothelial dysfunction such as hypertension, coronary vasospasm, smoking associated coronary atherosclerotic disease, myocardial infarction, and other vascular disorders such as placental abruption. Very difficult diseases which essentially are complex in nature have been indicted in high risk cancers, psoriasis, diabetic nephropathy, DiGeorge syndrome, and amyotrophic lateral sclerosis. The author has concluded that the molecular basis of genetic variation may delineate the contribution of these to etiology of complex human diseases (Gerritsen, 2005). Given the size and complexity of the human genome, initial efforts aimed at developing genetic maps to provide orientation and to delimit where a gene of interest may be located. A genetic map describes the order of genes and defines the position of a gene relative to other loci on the same chromosome. It is constructed by assessing how frequently two markers are inherited together or linked by association studies. Distances of the genetic map are expressed in recombination units, or centimorgans (cM). One cM corresponds to a recombination frequency of 1% between two polymorphic markers; 1 cM corresponds to approximately 1 Mb of DNA. Any polymorphic sequence variation can be useful for mapping purposes. Examples of polymorphic markers include variable number of tandem repeats (VNTRs), RFLPs, microsatellite repeats, and single nucleotide polymorphisms (SNPs). The latter two methods are now used predominantly because of the high density of markers and because they are amenable to automated procedures. Current efforts aim at creating high quality, dense SNP maps and haplotype maps or identification of linear arrangements of alleles of the human genome through the identification of as many as 500,000 SNPs. These variations, which are amenable to automated analysis with DNA chips, will greatly facilitate association and linkage studies for the elucidation of the complex interactions among multiple genes and life-style factors in multifactorial disorders. SNP patterns may ultimately become useful for the prediction of disease predisposition and pharmacogenomics. Genetic linkage refers to the fact that genes are physically connected or linked to one another along the chromosomes. Two fundamental principles are essential for understanding the concept of linkage: when two genes are close together on a chromosome, they are usually transmitted together, unless a recombination event separates them; and the odds of a crossover or recombination event between two linked genes is proportional to the distance that separates them. This indicates This indicates that genes that are further apart are more likely to undergo a recombination event than genes that are very close together. The detection of chromosomal loci that segregate with a disease by linkage can be used to identify the gene responsible for the disease through positional cloning and to predict the odds of disease gene transmission in genetic counseling. Polymorphisms are essential for linkage studies because they provide a means to distinguish the maternal and paternal chromosomes in an individual. On average, 1 out of every 1000 bp varies from one person to the next. There is usually a 99.9% identity and hence this degree of variation seems low. It also means that >3 million sequence differences exist between any two unrelated individuals and the probability that the sequence at such loci will differ on the two homologous chromosomes is high, often in th e range of >70 to 90%. Different forms of these sequence variations include VNTRs, short tandem repeats (STRs), and SNPs. Most STRs, also called polymorphic microsatellite markers, consist of di-, tri-, or tetranucleotide repeats that can be measured readily using PCR. Characterization of SNPs, using DNA chips, provides a promising means for rapid analysis of genetic variation and linkage. Although this sequence variation usually has no apparent functional consequence, it provides much of the basis for variation in genetic traits. In order to identify a chromosomal locus that segregates with a disease, it is necessary to determine the genotype or haplotype of DNA samples from one or several pedigrees. One can then assess whether certain marker alleles cosegregate with the disease. Markers that are closest to the disease gene are less likely to undergo recombination events and therefore receive a higher linkage score. Linkage is expressed as a lod or logarithm of odds score. This is defined by the ratio of the probability that the disease and marker loci are linked rather than unlinked. Lod scores of +3 (1000:1) are generally accepted as supporting linkage, whereas a score of -2 is consistent with the absence of linkage. The usefulness of this can be examined using the example of an autosomal dominant disease multiple endocrine neoplasia-1. The gene for the MEN-1 is known to be located on chromosome 11q13. Using positional cloning, the MEN1 gene was identified and shown to encode menin, a tumor suppressor. Affected individuals inherit a mutant form of the MEN1 gene, predisposing them to certain types of tumors in parathyroid, pituitary, and pancreatic islet. In the tissues that develop this tumor, a "second hit" occurs in the normal copy of the MEN1 gene. This somatic mutation may be a point mutation, a microdeletion, or loss of a chromosomal fragment which may be detected as loss of heterozygosity (LOH). Within a given family, linkage to the MEN1 gene locus can be assessed without necessarily knowing the specific mutation in the MEN1 gene. Using polymorphic STRs17 that are close to the MEN1 gene, one can assess transmission of the different MEN1 alleles and compare this pattern to development of the disorder to determine which allele is associated with risk of MEN-1. One example may explain this issue further. In a given pedigree, the affected grandfather in generation I carries alleles 3 and 4 on the chromosome with the mutated MEN1 gene and alleles 2 and 2 on his other chromosome 11. Consistent with linkage of the 3/4 genotype to the MEN1 locus, his son in generation II is affected, whereas his daughter who inherits the 2/2 genotype from her father is unaffected. In the third generation, transmission of the 3/4 genotype indicates risk of developing MEN-1, assuming that no genetic recombination between the 3/4 alleles and the MEN1 gene has occurred. After a specific mutation in the MEN1 gene is identified within a family, it is possible to track transmission of the mutation itself, thereby eliminating uncertainty caused by recombination. As the study of common and genetically complex human diseases identifies the significant contribution of heredity in their development, it is likely that more genes or genetic risk factors will be found to affect susceptibility to disease rather than the more traditionally considered causative genes. The implication of SNP in that context is to determine or predict the risk or susceptibility of a genetic disease, where adequate precautions or in future therapy can be directed to these polymorphic patterns. The human leukocyte antigen (HLA) system offers a unique example of susceptibility loci on the p arm of chromosome 6. Specific HLA antigens have been associated with various human diseases; for instance, the Bw47 antigen confers an 80–150-fold increased risk for congenital adrenal hyperplasia; the B27 antigen confers an 80–100-fold increased risk for ankylosing spondylitis; and the DR2 antigen confers a 30–100-fold increased risk for narcolepsy, a 3-fold increased risk for systemic lupus erythematosus, and a 4-fold increased risk for multiple sclerosis. The most frequent successes to date in the localization of genes underlying disease linkage analysis have been with diseases whose mode of inheritance is known. These disorders are often highly or completely penetrant and are due to a defect in a single gene, yet these Mendelian disorders are often relatively rare in the population. However, some of the most common and deadly diseases of society such as cardiovascular disease and obesity have significant genetic components. These diseases are termed “complex” because they are likely due to the interaction of multiple factors, both environmental and genetic. Susceptibility genes for such complex disorders are substantially harder to identify than genes responsible for Mendelian disorders. The significance of SNPs lies in the fact that they can alter the amino acid sequences. Amino acid sequences are heart of proteins and their functions, and therefore, may be potential disease modifiers. In the human population, there is possibility of an enormous number of single nucleotide polymorphism, which may prove to be functionally significant to cause susceptibility to a disease, and the major challenge that the science faces is to distinguish the functionally significant and potentially disease related polymorphic patterns. Now computational tools may be utilized to study genetic variations which can potentially alter the interactions and functions of cell cycle proteins while they interact with other available proteins in the milieu. There is now availability of public SNP databases which can validate the findings. There is a large significance to SNPs if the data is available from a pooled information source. SNPs are small genetic variations and when studied alone in a single individual it has little or no direct functional significance and can be interpreted as chance accumulation of small genetic changes. These mere chance mutations can assume larger significance when they are tailed across the patterns in the whole population can point to the patterns of inheritance of a disease and its evolution. Some examples of SNPs will establish its significance in the present and future genetic variation medicine. DNA chips were one of the initial methodologies proposed for SNP detection. These high-density microarrays are created when oligonucleotides are attached to a solid silicon surface in a known, ordered array. Labeled dNTPs are incorporated when performing PCR of the SNP in the individual being genotyped. This product is then hybridized to the array, the SNP PCR product that perfectly matches the correct allele hybridizing more efficiently than mismatches. The advantage of the method is the large number of different SNPs that can be assayed at once. However, for research laboratories, the cost of both constructing the chips and obtaining a “reader” can be substantial. The technique by itself is not as flexible as some others. It is probably best suited to highly repetitive assays, such as would be used in genomic screening or carrier detection, where the cost per reaction of the process and the labor required for optimizing oligonucleotides can be minimized. Advances in SNP genotyping technology are allowing ever increasing numbers of SNPs to be genotyped in single experiments. The two most common platforms are made by Affymetrix (http://www.affymetrix.com) and Illumina (http://www.illumina.com). Using the results of the Hapmap project (Altshuler et al., 2005), arrays have been developed with 10,000, 100,000, 250,000, and 500,000 SNPs. Larger arrays will undoubtedly be developed in the future. The goal of these large arrays is to interrogate a substantial portion (estimated at 50–70% for the 250,000 and 500,000 SNP arrays) of the common variation in the genome. Although they use different proprietary technologies, both systems generate SNP genotypes with very high fidelity. Sequencing is an obvious method for genotyping SNPs. However, the only sequence that is needed for genotyping is the one base pair that defines the polymorphism. In single-base-pair extension (SBE) a primer is constructed that is adjacent to the polymorphic SNP base so that the allele base lies immediately 30 to the primer (Syvanen et al., 1993). A single- or double-base sequencing reaction is then performed, with only dideoxynucleotides that match the SNP base-pair possibilities. This can then be detected directly on a sequencer or, more commonly, by a second method such as polarization. SNP is a polymorphism of a single nucleotide site. As a rule, it is represented by two allelic variants (substitutions) of a single nucleotide in a DNA sequence. At present, due to the improvement and automation of sequencing procedure, the development of DNA microarrays (Gibson 2002), and other analytical methods, these markers are extensively studied in the human genome (Wang et al. 1998) for detecting their association with different complex diseases (Lander 1996; Cargill et al. 1999; Halushka et al. 1999), and for understanding various aspects of genetic differentiation of populations and evolution of humans (Przeworski et al. 2000). According to Cargill el al. (1999), the SNP number per gene in humans ranges fromzero to 29,while the coding gene sequences on average contain four polymorphic sites (cSNPs). A typical individual must be heterozygous at about 24,000–40,000 nonsynonymous substitutions with alteration of an amino acid in an encoded protein. According to Halushka el al. (1999), the total human genome contains approximately one million SNPs, of which about 500,000 are noncoding, 200,000 synonymous coding, and 200,000, nonsynonymous coding. Based on SNPs in 75 studied human genes, recalculation of mean heterozygosity for proteins produced the estimate of 17% (Harris and Hopkinson 1972), which exceeds the value summarized by Nevo et al. (1984) from several sources (12.5%). The discovery of numerous SNPs in the human genome has made it possible to identify the effect of selection on this polymorphism. In turn, this permits explanation of molecular differences among species and determination of functional significance of different genomic regions. As shown by analyzing SNP frequencies in human gene samples, nucleotide variation in coding gene regions is considerably limited at the sites whose replacements change the amino-acid sequence of the protein molecule. These sites also exhibit a significant excess of rare alleles. In all, this suggests the action of stabilizing or purifying selection against nonsynonymous SNPs, especially those producing nonconservative amino-acid alterations. According to calculations ofHalushka et al. (1999),who examined SNPs in 75 human genes, purifying selection, together with genetic drift, eliminates 62% of nonsynonymous SNPs. Some noncoding DNA regions, such as, nontranslated sequences flanking the coding gene regions perform important regulatory functions, and their mutations must be eliminated by strong selection. SNP frequency in such sequences turned out to be several times lower than in degenerate sites of the coding region, where any substitution is synonymous and the level of variation is highest and comparable to the neutral level of variation (Sunyaev et al. 2000). In order to understand the future, some examples of application of SNPs need to be considered. The various types of genetic polymorphism generally can be classified by their resulting influence on protein expression or ultimate phenotype. Genetic polymorphism resulting in gene deletion invariably leads to loss of function and no production of the gene product. In contrast, gene duplication and multiduplication most commonly leads to increased expression of the gene product and a hyperactivity phenotype. An exception to this is duplication of an allele that includes additional structural variation leading to loss of function. Genetic translocation typically yields a nonfunctional gene. SNPs can result in various changes in the expressed protein function depending on where the polymorphism occurs in the overall gene structure. SNPs in the 50 regulatory domain may influence gene regulation. SNPs in the coding exons only influence function if there is a resulting amino acid change that alters the protein function. SNPs within the intron regions are typically silent unless the SNP alters a nucleotide critical for splicing of the RNA during maturation which typically leads to loss or decrease in protein function. For example in pharmacogenomics, persons who harbor the variant promoter allele UGT1A1*28 are predisposed to severe grades of irinotecan-induced diarrhea and neutropenia. The UGT1A1/UGT1A7 SNP appears to be a superior risk predictor. Persons harboring Factor V Leiden are predisposed to deep vein thrombosis, especially at younger ages, during pregnancy, and during the puerperium. Persons who harbor the mutant coagulant protein may never suffer thrombosis, but may be lifelong candidates for anticoagulant therapy. Carriers of factor V Leiden combined with G20210A prothrombin SNP have increased risk for thrombosis after the first episode. The reduced activity of novel allele of OATP-C gene called OATP-C*15 contains N130D and V174A SNPs; various carriers of the functionally deficient OATP-C*15 variants exhibit reduced liver uptake of rifampin andpossibly reduced capacity for rifampin-mediated induction of liver drug-metabolizing enzymes and transporters. Read More