Intrinsic chromosomal linkage and disease prediction

Abstract

An improved method is the product of an exploration for ways in which to improve the success of genomic disease prediction and presents the elements of more successful prediction tools for the identification of genomic locations of disease based on: genomic labeling it loci as determined by correlated SNP linkage as determined from several additional GWAS (Genome Wide Association Studies) databases. The Wellcome Trust T2D (type 2, adult-onset, diabetes) has played a particularly important role in developing the new tools; additionally, the development of a wellness classifier, probably in part due to counter disease mutations has proven to be a powerful new tool and concept. The result has been a substantial increase in the successful genomic prediction of disease, for example, for the Wellcome Trust data there is compelling evidence of a greater than 99% successful prediction rate.

Description

[0001]The contents of the Electronic Sequence Listings filed herewith (Sequences_ST25, txt; Size 2062 bytes: and Date of Creation: Jul. 7, 2014) is herein incorporated by reference in its entiretyBACKGROUND OF THE INVENTION1. Field of the Invention[0002]The present invention relates in general terms to DNA genotypic data that is linked to clinical diagnosis, phenotypic data. More particularly a method is presented for extracting genomic classifiers of disease risk from genomic data as obtained from micro array or gene chip assays in conjunction with their phenotypic correlates. This leads to methods of disease forecasting and individual patient disease risk prediction; as well as to devices which accomplish these goals.2. Description of the Prior Art[0003]There are almost three billion (coding and non-coding) DNA base pair in the human genome, with about 99.5% of these are shared by all homosapiens. Each somatic cell contains a maternal and a paternal contribution; so the overwhelmi...

AI Technical Summary

Benefits of technology

The invention uses microarray genotyping data to create a new and unique allelic form that can help genetic marker classification of disease risk. This may enable the development of personalized medicine, a proposed way of dealing with disease association. The discovery provides new approaches for the proper analysis and prediction of multi-marker complex diseases. The invention also emphasizes the importance of unambiguous allele locus instead of the universal use of SNP pair, which leads to a significantly enhanced discovery procedure for disease-related risk loci. The improved method uses a wellness classifier and has been developed with the help of several databases. The application of this improved method will positively influence the construction and use of gene arrays for public health, disease discovery, and standards for safe use of pharmacological drugs.

Problems solved by technology

While polymerase chain reaction (PCR) microarrays, or gene chips, have facilitated acquisition of vast quantities of genomic data, disappointment has been expressed on the lack of DNA variant linkages to human diseases particularly in the case of complex disorders (Chakravarti, 2011).

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