Chemistry: molecular biology and microbiology – Measuring or testing process involving enzymes or... – Involving nucleic acid
Reexamination Certificate
2000-10-25
2002-11-05
Benzion, Gary (Department: 1637)
Chemistry: molecular biology and microbiology
Measuring or testing process involving enzymes or...
Involving nucleic acid
C435S091200, C536S024330, C536S022100
Reexamination Certificate
active
06475736
ABSTRACT:
BACKGROUND OF THE INVENTION
This application describes methods for the genetic analysis of biologically, medically and economically significant traits in mammals and other organisms, including humans. Genetic analysis refers to the determination of the nucleotide sequence of a gene or genes of interest in a subject organism, including methods for analysis of one site of sequence variation (i.e. genotyping methods) and methods for analysis of a collection of sequence variations (haplotyping methods). Genetic analysis further includes methods for correlating sequence variation with disease risk, diagnosis, prognosis or therapeutic management.
The use of novel genotyping and haplotyping methods for genetic analysis of the apolipoprotein E (ApoE) gene are described. These methods entail use of novel ApoE DNA sequence polymorphisms and haplotypes. The ApoE alleles and genetic analysis methods of this application will allow more sensitive measurement of the contribution of ApoE genetic variation to medically important phenotypes such as risk of heart disease, risk of Alzheimer's disease and response to various therapeutic interventions, including pharmacotherapy.
This application also describes new methods for genotyping a DNA sample based on analysis of the mass of cleaved DNA fragments using mass spectrometry. These genotyping methods are better suited to the present and future requirements of DNA testing than current genotyping methods as a result of improved accuracy, decreased set-up and reagent costs, reduced complexity and excellent compatibility with automation.
At present, DNA diagnostic testing is largely concerned with identification of rare polymorphisms related to Mendelian traits. These tests have been in use for well over a decade. In the future genetic testing will come into much wider clinical and research use, as a means of making predictive, diagnostic, prognostic and pharmacogenetic assessments. These new genetic tests will in many cases involve multigenic conditions, where the correlation of genotype and phenotype is significantly more complex than for Mendelian phenotypes. To produce genetic tests with the requisite accuracy will require new methods that can simultaneously track multiple DNA sequence variations at low cost and high speed, without compromising accuracy. Many tests will be evaluated in the clinical research setting but only a small fraction will become major diagnostic tests; the clinical research process will reveal that most polymorphisms lack significant functional effects. The genetic analysis methods described in this application are relatively inexpensive to set up and run, while providing extremely high accuracy, and, most important, enabling sophisticated genetic analysis. They are therefore optimally suited to the exigencies of genetic test development in coming years.
The association of specific genotypes with disease risk, prognosis, and diagnosis as well as selection of optimal therapy for disease are some of the benefits expected to ensue from the human genome project. At present, the most common type of genetic study design for testing the association of genotypes with medically important phenotypes is a case control study where allele frequencies are measured in one or more phenotypically defined groups of cases and compared to allele frequencies in controls. (Alternatively, phenotype frequencies in two or more genotypically defined groups are compared.) The majority of such published genetic association studies have focused on measuring the contribution of a single polymorphic site (usually a single nucleotide polymorphism, abbreviated SNP) to variation in a medically important phenotype or phenotypes. In these studies one polymorphism serves as a proxy for all variation in a gene (or even a cluster of adjacent genes).
The limitations of such single polymorphism association analysis are becoming increasingly apparent. Recent articles (e.g. Terwilliger, J. and K. M Weiss. Linkage disequilibrium mapping of complex disease: fantasy or reality?
Current Opinion in Biotechnology
9: 578-594, 1998) have drawn attention to the low quality of most association studies using single polymorphic sites (evidenced by their low degree of reproducibility). Some of the reasons for the lack of reproducibility of many association studies are apparent. In particular, the extent of human DNA polymorphism—most genes contain 10 or more polymorphic sites, and many genes contain over 100 polymorphic sites—is such that a single polymorphic site can only rarely serve as a reliable proxy for all variation in a gene (which typically covers at least several thousand nucleotides and can extend over 1,000,000 nucleotides). Even in cases where one polymorphic site is responsible for significant biological variation, there is no reliable method for identifying such a site. The haplotyping and genetic analysis methods described in this application provide a systematic way to identify such polymorphic sites.
Several recent studies have begun to outline the extent of human molecular genetic variation. For example, a comprehensive survey of genetic variation in the human lipoprotein lipase (LPL) gene (Nickerson, D. A., et al.
Nature Genetics
19: 233-240, 1998; Clark, A. G., et al.
American Journal of Human Genetics
63: 595∝612, 1998) compared 71 human subjects and found 88 varying sites in a 9.7 kb region. On average any two versions of the gene differed at 17 sites. This and other studies show that sequence variation may be present at approximately 1 in 100 nucleotides when 50 to 100 unrelated subjects are compared. The implications of the this data are that, in order to create genetic diagnostic tests of sufficient specificity and selectivity to justify widespread medical use, more sophisticated methods are needed for measuring human genetic variation.
Beyond tests that measure the status of a single polymorphic site, the next level of sophisication in genetic testing is to genotype two or more polymorphic sites and keep track of the genotypes at each of the polymorphic sites when calculating the association between genotypes and phenotypes (e.g. using multiple regression methods). However, this approach, while an improvement on the single polymorphism method in terms of considering possible interactions between polymorphisms, is limited in power as the number of polymorphic sites increases. The reason is that the number of genetic subgroups that must be compared increases exponentially as the number of polymorphic sites increases. In a medical study of fixed size this has the effect of dramatically increasing the number of groups that must be compared, while reducing the size of each subgroup to a small number. The consequence of these effects is an unacceptable loss of statistical power. Consider, for example, a clinical study of a gene that contains 10 variable sites. If each site is biallelic then there are 2
10
=1024 possible combinations of polymorphic sites. If the study population is 500 subjects then it is likely that many genetically defined subgroups will contain only a small number of subjects. Thus, consideration of multiple polymorphisms (as can be determined from DNA sequence data, for example) does not get at the problem that the DNA sequence from a diploid subject does not sufficiently constrain the sequence of the subject's two chromosomes to be very useful for statistical analysis. Only direct determination of the DNA sequence on each chromosome (a haplotype) can constrain the number of genetic variables in each subject to two (allele 1 and allele 2), while accounting for all, or preferably at least a substantial subset of, the polymorphisms.
A much more powerful measure of variation in a DNA segment, then, is a haplotype—that is, the set of polymorphisms that are found on a single chromosome. Because of the evolutionary history of human populations, only a small fraction of all possible haplotypes (given a set of polymorphic sites at a locus) actually occur at appreciable frequency. For example, in a gene with 10
Benzion Gary
Chunduru Suryaprabha
Fish & Richardson P.C.
Variagenics Inc.
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