Methods Of Genetic Analysis
How Scientists Conclude if a Disease is Genetically Determinst or not?
At times it becomes difficult for clinician to determine the cause of a disease, especially if the disease is heritable and its symptoms are a part of the presentation put forward by genetically determined traits of a disorder. The presence of many affected members in a family suggests its genetic etiology. However, to determine that a disease has a definite genetic basis, it should exhibit a specific pattern of inheritance (dominant, recessive or X-linked, etc.).
When the gene responsible for disease is transmitted from one generation to the next it follows specific laws of mendelian inheritance. Though this is true for the diseases which are due to single gene (monogenic) defects, genetic diseases are also determined due to the action of many genes (polygenic) acting together.
Not only this, some diseases result out of interactions between many genes and environmental factors (multifactorial). The genetic basis for multifactorial diseases is difficult to work out. Scientists use many techniques to demonstrate the genetic basis of disease. The following methods are used for evaluation of genetic diseases. Some of them are described very superficially here.
Identification Of Heritable Dental Pathology
In case of a dentist noticing a disease, the etiological basis of which is not known or clearly defined, he should carefully identify its unique characteristics. He should take a careful family history. If the family history reveals that many other family members are also affected with same disease he should become suspicious about the genetic predisposition of the disease. Thus familial aggregation of a disease is the first step in the identification of a genetic correlation of the disease.
Read and Learn More Genetics in Dentistry Notes
Segregation Analysis
The next step leads the investigator to determine the pattern of inheritance of the disease. This begins with a necessary step of drawing the family pedigree. Members of the family spread in many generations (both on maternal and paternal sides) are interviewed. In the pedigree chart the affected and nonaffected members are symbolically represented.
On the basis of pedigree one can define the mode of inheritance of the disease, i.e. whether the disease is autosomal dominant, recessive, X-linked, polygenetic or multifactorial in its pattern of inheritance. This kind of study is known as segregation analysis. Thus segregation analysis is the method to determine the mode of inheritance of a particular phenotype from the family data. The aim of the segregation analysis is to find out the effect of a single gene or so-called major gene in the pedigree.
Segregation analysis is the statistical method for determining the mode to inheritance of a particular trait from family data particularly those traits that are determined by a single gene (major gene) (Townsend et al, 1998). Segregation analysis tells us whether the gene responsible for disease is a dominant or recessive in character and whether it is present on an autosome or a sex chromosome.
This kind of analysis holds good for single gene inheritance (Mendelian inheritance) but not ideal for the interpretation of multifactorial disease inheritance because the analysis fails to discriminate between effects exerted by the genetic causes and those by the environmental sources that together cause the disease (Diehl et al, 1999 and Elston, 1981). Segregation analysis does not find the gene responsible for the disease.
The characteristic of multifactorial inheritance is that the proportion of affected persons who are near relatives of each other (in an extended family tree) is greater than the incidence of the multifactorial disease, in isolation, in the general population. However, the incidence of persons affected with multifactorial diseases is much less when compared to single gene inheritance.
In this kind of inheritance the dosage of polygenes differs amongst the individual affected persons or between families. Polygenic inheritance shows continuous phenotypic variation of the disease (as in case of periodontitis variation may range from mild to sever disease). While on other hand monogenic inheritance show either the presence or absence of the disease in absolute terms.
The analyses of multifactorial traits in human populations have been confined to the determination of the observed variation into genetic and environ- mental components based on comparisons between relatives (i.e. parents and offspring, siblings, half sibs and twins).
For the phenotype variability (Vp) of a trait, the variability between individuals is considered to be the result of a combination between genetic variance (Vg) and environmental variance (V.), i.e. VpV+Vg The heritable estimate can be calculated as the ratio of V. Vg/Vp and is represented in terms of percentage, i.e.0 to 100% (Townsend et al, 1998). With the increasing computer usage models have been developed to detect the contribution of individual genetic locus as compared to polygenic and environmental effects.
Twin Studies
In case of multifactorial diseases where genetic and environmental factors play important role in the causation of the disease, twin studies are useful. Human twins are of two basic categories: monozygotic or identical twins resulting from a single ovum fertilized by a single sperm and dizygotic where two ova are fertilized by two sperms.
Monozygotic twins are genetically identical (they have same genes) while dizygotic twins share 50% of their genes. Thus monozygotic twins should show the same phenotype, as their genotype is identical. If there is some difference in the phenotype of these twins it may be due to the influence imposed by different environmental factors only. On the other hand, differences between dizygotic twins are both due to genetic and environmental variables.
Presence or absence of the trait or disease (in a large number) in the two categories of twins is calculated in percentage. The genetic component involved in the causation of a disease is confirmed if the percentage of the twin pairs in which both the twins are affected is greater for monozygotic twins as compared to dizygotic twins.
If the percentage of disease occurring in both the monozygotic twins is 42% and in dizygotic twins only 6%, it indicates that genetics plays an important role in the development of the disease. A very large number of twin pairs are needed for twin studies, which are reared together in the same environment. The development of new-sophisticated genetic modeling methods has made it possible to estimate the genetic and environmental parameters and specify interactions between them.
The genetic basis of a disease can also be tested in monozygotic twins who are separated after birth and reared in two different environments (Bouchard et al, 1990). In these twins all the similarity will be due to common genes and all the dissimilarity will be due to environmental factors.
So if both the twins of a pair are suffering from the same disease while living apart, it is due to gene linked effects and if only one of them suffers from a disease it may be due to environmental concerns. Thus this kind of a study overcomes the problem of twins displaying similarities because of their common environment.
The genetic and environmental effects can also be studied in the off-springs of monozygotic twins (Porter, 1990). The off-springs of monozygotic twins can be considered as half-sibs though they are socially first cousins. This monozygous half-sib model offers a powerful tool to estimate the genetic and environmental disease risk in families. This kind of a study also tells us about maternal effects on the progeny (as mothers are different, though fathers are also different but they have same genetic constitution).
Linkage Analysis
Once evidence of the effects of a major gene(s) has been detected and established, the next logical step is to identify the location of gene(s) within the genome. Linkage analysis is used to map a disease (mutant) gene to its specific location on a chromosome. This mode of analysis takes the help of many families containing multiple diseased individuals.
Genotypes are determined for affected and unaffected individuals of the family. The linkage analysis is usually made between two genes out of which one is a mutant gene causing disease and other gene acting as a marker gene. The marker gene is characterized by detectable polymorphism. It is important that these two genes, i.e. marker gene and disease gene (mutant gene) should be linked as a result of being in close physical proximity.
In the method of linkage analysis segregation of the disease with the polymorphic marker is studied for each chromosome. Eventually a marker is identified which co-segregates with the disease gene more often than would be expected by chance. This proves that disease gene is linked, i.e. present on the same chromosome on which the specific marker is situated.
However, application of these methods to identify the genetic basis of dental disorders has been limited because of difficulties in obtaining large family pedigrees and also in identifying polymorphic marker genes (Conneally et al, 1980 and White and Lalouel, 1987) in relation to dental diseases.
Next step is to determine the linkage distance between the two genes. This can be achieved by calculating the recombination frequency (see box). For example if a pedigree shows only one recombinant offspring and seven nonrecombinant (linked) out of eight offspring, then the recombination frequency is calculated to be 0.125 (12.5 %) and the distance between two genes is equal to 12.5 CM (centi Morgan).
Lod (logarithm of odd) score method is used to calculate the linkage and map the distance between two linked genes (see box). With a high LOD score and a low recombination fraction the researcher can be fairly certain that the gene responsible for the disease has been localized.
Once the location of the disease causing gene is mapped on the chromosome, one can sequence this area and can identify the gene. Investigators also come to identify the type of mutation involved in the disease. Next step in the final identification of this gene is to study the gene in both the affected and nonaffected individuals of the family. If the mutation is found in all the affected members but absent in all nonaffected individuals it can be made sure that the gene responsible for the disease is identified.
Linkage analysis has been extremely useful in the identification of genes responsible for diseases with simple mendelian inheritance such as hypodontia. The application of linkage analysis to complex disorders (multifactorial diseases) without obvious patterns of Mendelian inheritance has been much less successful because complex diseases are most likely influenced by genetic heterogeneity (multiple genetic causes leading to the same disease) and also by environmental factors.
In spite of this many multifactorial diseases have been identified by linkage analysis. A gene that influences a multifactorial trait (quantitative trait) is termed quantitative trait locus (QTL). As several genes determine the traits in a multifactorial disease, many QTLs will be involved together with various environmental effects. If the genes are linked to well- designed genetic markers (RFLPs, microsatellites or SNPs), these genes related to multifactorial traits can be mapped.
Association Studies
Association studies have been widely employed to attempt to identify genetic basis of complex (multifactorial) diseases.
Two general approaches have been used to investigate the molecular genetics of complex diseases: candidate gene approaches and whole genome screens (genome-wide association studies).
In the candidate gene approach method, association analysis of genetic polymorphisms has been mostly performed in a case-control setting with unrelated affected subjects compared with unrelated unaffected subjects. Significant differences in allele frequencies between cases and controls are taken as evidence for involvement of an allele in disease susceptibility.
Genome-wide Association Studies
A genome-wide association study is an approach that involves scanning markers rapidly across the complete sets of DNA, or genomes, across a large number of people to find genetic variations associated with a particular disease (Morley et al, 2004). Once new genetic associations are identified, researchers can use the information to develop better strategies to detect, treat and prevent diseases.
Such studies are particularly useful in finding genetic variations that contribute to common yet complex diseases such as asthma, cancer, diabetes, heart disease and mental illnesses.
Genome-wide association studies are relatively new ways to identify genes involved in human disease. This method searches the genome by scanning for small variations called single nucleotide polymorphisms or SNPs (see box), which occur more frequently in people with a particular disease than in people without the disease. Each study can look at hundreds or thousands of SNPs at the same time.
Researchers use data from this type of study to pinpoint genes that may contribute to a person’s risk of developing a certain disease. In case a positive association is found between a particular disease and particular markers, the SNPs, and if the same markers are also detected in a healthy person, he or she may be predicted to be at risk of developing the disease in future.
Genome-wide association studies examine SNPs across the genome; they represent a promising way to study complex and yet common diseases in which several genetic variations are attributed to the risk of development of the disease in a person. This approach has already identified SNPs related to several complex conditions including diabetes, heart abnormalities, Parkinson’s disease, and Crohn’s disease.
Researchers hope that future genome-wide association studies will identify variations that affect a person’s response to certain drugs and influence interactions between a person’s genes and the environment.
Method to Carry out the Genome-wide Association Studies
To carry out a genome-wide association study, researchers use two groups of participants: people with the disease being studied and similar people without the disease. Researchers obtain DNA from each participant by drawing a blood sample.
The complete set of DNA (or genome) is then purified from the blood, placed on tiny chips and scanned on automated laboratory machines. The machines quickly survey each participant’s genome for strategically selected markers of genetic variation, which are called single nucleotide polymorphisms, or SNPs.
If certain genetic variations are found to be significantly more frequent in people with the disease compared to people without disease, the variations are said to be “associated” with the disease. The associated genetic variations can serve as powerful pointers to the region of the human genome where the disease-causing problem resides.
Now researchers need to sequence the DNA base pairs in that particular region of the genome, to identify the exact gene involved or associated with the disease.