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Use of GWAS to predict targets associated with cancer in African Americans
Author(s) -
Kittles Rick
Publication year - 2013
Publication title -
the faseb journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.709
H-Index - 277
eISSN - 1530-6860
pISSN - 0892-6638
DOI - 10.1096/fasebj.27.1_supplement.460.2
Subject(s) - personalized medicine , human genetic variation , genome wide association study , precision medicine , leverage (statistics) , human genome , genetic variation , disease , pharmacogenetics , human genetics , genetic association , biology , computational biology , genome , data science , genetics , medicine , computer science , gene , single nucleotide polymorphism , artificial intelligence , genotype , pathology
Understanding genetic and environment interactions that may influence cancer is the cornerstone of a personalized medicine approach built on diagnostics, risk assessment/risk modification, pharmacogenetics and biology. Although genetic and personalized medicine can influence clinical decision making, currently most genetic information is based on populations of European ancestry. Additional human genome research must include diverse populations in order to assess the impact DNA sequence variation and environmental influences have on human disease risk. Within this talk, I present a brief overview of human genome variation and discuss how we leverage genetic variation for mapping genes for disease. Examples of genome‐wide associations and admixture mapping studies are explored and linked to several cancer disparities and health outcomes among communities of color. We must be poised to take take advantage of genetic studies in diverse populations in order to move closer to a more inclusive personalized medicine goal.