Hugues Aschard

Summary

Affiliation: Harvard University
Country: USA

Publications

  1. doi request reprint A nonparametric test to detect quantitative trait Loci where the phenotypic distribution differs by genotypes
    Hugues Aschard
    Department of Epidemiology, Harvard School of Public Health, Boston, MA 02115, USA
    Genet Epidemiol 37:323-33. 2013
  2. pmc Challenges and opportunities in genome-wide environmental interaction (GWEI) studies
    Hugues Aschard
    Department of Epidemiology, Harvard School of Public Health, Boston, MA, USA
    Hum Genet 131:1591-613. 2012
  3. pmc Combining effects from rare and common genetic variants in an exome-wide association study of sequence data
    Hugues Aschard
    1Department of Epidemiology, Harvard School of Public Health, 677 Huntington Avenue, Boston, MA 02115, USA
    BMC Proc 5:S44. 2011
  4. pmc Inclusion of gene-gene and gene-environment interactions unlikely to dramatically improve risk prediction for complex diseases
    Hugues Aschard
    Program in Molecular and Genetic Epidemiology, Harvard School of Public Health, Boston, MA 02115, USA
    Am J Hum Genet 90:962-72. 2012
  5. pmc Exploring genome-wide - dietary heme iron intake interactions and the risk of type 2 diabetes
    Louis R Pasquale
    Department of Medicine, Channing Division of Network Medicine, Brigham and Women s Hospital, Harvard Medical School Boston, MA, USA Glaucoma Service, Massachusetts Eye and Ear Infirmary Boston, MA, USA
    Front Genet 4:7. 2013
  6. pmc Genome-wide meta-analysis of joint tests for genetic and gene-environment interaction effects
    Hugues Aschard
    Program in Molecular and Genetic Epidemiology, Harvard School of Public Health, Boston, MA 02115, USA haschard hsph harvard edu
    Hum Hered 70:292-300. 2010

Detail Information

Publications6

  1. doi request reprint A nonparametric test to detect quantitative trait Loci where the phenotypic distribution differs by genotypes
    Hugues Aschard
    Department of Epidemiology, Harvard School of Public Health, Boston, MA 02115, USA
    Genet Epidemiol 37:323-33. 2013
    ..We demonstrate the potential utility of our method on real data by analyzing mammographic density genome-wide data from the Nurses' Health Study...
  2. pmc Challenges and opportunities in genome-wide environmental interaction (GWEI) studies
    Hugues Aschard
    Department of Epidemiology, Harvard School of Public Health, Boston, MA, USA
    Hum Genet 131:1591-613. 2012
    ....
  3. pmc Combining effects from rare and common genetic variants in an exome-wide association study of sequence data
    Hugues Aschard
    1Department of Epidemiology, Harvard School of Public Health, 677 Huntington Avenue, Boston, MA 02115, USA
    BMC Proc 5:S44. 2011
    ....
  4. pmc Inclusion of gene-gene and gene-environment interactions unlikely to dramatically improve risk prediction for complex diseases
    Hugues Aschard
    Program in Molecular and Genetic Epidemiology, Harvard School of Public Health, Boston, MA 02115, USA
    Am J Hum Genet 90:962-72. 2012
    ..We show that the inclusion of G-G and G-E interaction effects in risk-prediction models is unlikely to dramatically improve the discrimination ability of these models...
  5. pmc Exploring genome-wide - dietary heme iron intake interactions and the risk of type 2 diabetes
    Louis R Pasquale
    Department of Medicine, Channing Division of Network Medicine, Brigham and Women s Hospital, Harvard Medical School Boston, MA, USA Glaucoma Service, Massachusetts Eye and Ear Infirmary Boston, MA, USA
    Front Genet 4:7. 2013
    ..72) were significant for the iron metabolic pathway as a whole.Conclusions: We found no significant interactions between dietary heme iron intake and common SNPs in relation to T2D...
  6. pmc Genome-wide meta-analysis of joint tests for genetic and gene-environment interaction effects
    Hugues Aschard
    Program in Molecular and Genetic Epidemiology, Harvard School of Public Health, Boston, MA 02115, USA haschard hsph harvard edu
    Hum Hered 70:292-300. 2010
    ..There is growing interest in the study of gene-environment interactions in the context of genome-wide association studies (GWASs). These studies will likely require meta-analytic approaches to have sufficient power...