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Research Article

Presymptomatic Risk Assessment for Chronic Non-Communicable Diseases

  • Badri Padhukasahasram equal contributor mail,

    equal contributor Contributed equally to this work with: Badri Padhukasahasram, Eran Halperin

    bpadhuka@ucdavis.edu

    Affiliation: Navigenics, Foster City, California, United States of America

    Current address: Section on Ecology and Evolution and Genome Center, University of California Davis, Davis, California, United States of America

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  • Eran Halperin equal contributor,

    equal contributor Contributed equally to this work with: Badri Padhukasahasram, Eran Halperin

    Affiliation: Navigenics, Foster City, California, United States of America

    Current address: Blavatnik School of Computer Science, Department of Molecular Microbiology and Biotechnology, Tel-Aviv, University, Tel-Aviv, Israel; International Computer Science Institute, Berkeley, California, United States of America

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  • Jennifer Wessel,

    Affiliation: Navigenics, Foster City, California, United States of America

    Current address: School of Medicine, Indiana University, Indianapolis, Indiana, United States of America

    X
  • Daryl J. Thomas,

    Affiliation: Navigenics, Foster City, California, United States of America

    Current address: Life Technologies, Foster City, California, United States of America

    X
  • Elana Silver,

    Affiliation: Navigenics, Foster City, California, United States of America

    X
  • Heather Trumbower,

    Affiliation: Navigenics, Foster City, California, United States of America

    X
  • Michele Cargill,

    Affiliation: Navigenics, Foster City, California, United States of America

    Current address: Locus Development, San Francisco, California, United States America

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  • Dietrich A. Stephan

    Affiliations: Navigenics, Foster City, California, United States of America, Institute for Individualized Health, Palo Alto, California, United States of America, The Cancer Genome Institute, Philadelphia, Pennsylvania, United States of America, Children's Hospital Informatics Program, Children's Hospital Boston, Boston, Massachusetts, United States of America

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  • Published: December 31, 2010
  • DOI: 10.1371/journal.pone.0014338

Reader Comments (7)

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Generalization

Posted by bpadhuka on 18 Feb 2012 at 20:16 GMT

In the second model, a variant of the previous model, we assume that , where G1 is normally distributed with standard deviation σG1, and is Binomially distributed. In this case, Xi corresponds to SNPs with large effects and G1 represents many other small genetic effects; if there are enough small genetic effects, we expect that the asymptotic behavior of their sum would be according to a normal distribution. By setting the parameters λ, σG1 and p appropriately, we can control the relative risks of the large effect SNPs. We tune these parameters such that the relative risks are close to values observed in Table 1 (see below). As for the previous model, we can show that when G is known (but E is unknown) and the relative risks of the large effect SNPs and risk-allele frequencies are fixed, the area under the ROC curve for the second model only depends on the heritability and the average lifetime risk of the disease (see below).
http://plosone.org/article/info:doi/10.1371/journal.pone.0014338#article1.body1.sec4.sec6.p2

This theoretical disease model can be made more general by allowing the genetic variable of a particular SNP to take any 3 arbitrary values corresponding to the 3 possible genotypes (instead of 0, LAMBDAi, and 2LAMBDAi as in the current variant for the NN, RN and RR genotypes respectively say X0(i), X1(i) and X2(i)).

No competing interests declared.

Generalization

bpadhuka replied to bpadhuka on 26 May 2012 at 08:01 GMT

In addition, we can relax the Hardy-Weinberg equilibrium assumption for the genotype frequencies. See the following
link for more details about this model:
https://sourceforge.net/p...

Competing interests declared: I am the first author of this paper.