Disturbances of iron homeostasis can have significant clinical consequences. Iron deficiency is the world's most prominent nutritional deficiency and anemia of chronic disease (ACD) from decreased intestinal iron absorption and impaired iron release from macrophages is common in hospitalized patients. The overall aim of this study is to help us understand the genetic basis of variation in iron metabolism between people. Inbred mice show significant variation in multiple traits including iron metabolism. We propose to identify loci underlying strain specific differences in iron metabolism through a combination of in silico SNP association and gene expression profiling. We will test candidate genes for iron related function in Zebrafish, a complementary vertebrate model. Finally, we will assess candidate genes for a role in human iron metabolism through population based studies. We have assembled a multi- disciplinary research team of iron metabolism biologists, geneticists and computational biologists to carry out the proposed study.

Public Health Relevance

Anemias from iron deficiency or chronic disease are common disorders. The overall aim of this study is to improve our understanding of iron metabolism and its variation between people in order to develop more effective therapies for these diseases.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Research Project (R01)
Project #
5R01GM083198-02
Application #
8501536
Study Section
Macromolecular Structure and Function A Study Section (MSFA)
Program Officer
Krasnewich, Donna M
Project Start
2012-07-01
Project End
2016-05-31
Budget Start
2013-06-01
Budget End
2014-05-31
Support Year
2
Fiscal Year
2013
Total Cost
$669,709
Indirect Cost
$154,028
Name
University of California Berkeley
Department
Nutrition
Type
Schools of Earth Sciences/Natur
DUNS #
124726725
City
Berkeley
State
CA
Country
United States
Zip Code
94704
Hormozdiari, Farhad; Zhu, Anthony; Kichaev, Gleb et al. (2017) Widespread Allelic Heterogeneity in Complex Traits. Am J Hum Genet 100:789-802
Bilow, Michael; Crespo, Fernando; Pan, Zhicheng et al. (2017) Simultaneous Modeling of Disease Status and Clinical Phenotypes To Increase Power in Genome-Wide Association Studies. Genetics 205:1041-1047
Fraenkel, Paula G (2017) Anemia of Inflammation: A Review. Med Clin North Am 101:285-296
Rahmani, Elior; Zaitlen, Noah; Baran, Yael et al. (2017) Correcting for cell-type heterogeneity in DNA methylation: a comprehensive evaluation. Nat Methods 14:218-219
Joo, Jong Wha J; Kang, Eun Yong; Org, Elin et al. (2016) Efficient and Accurate Multiple-Phenotype Regression Method for High Dimensional Data Considering Population Structure. Genetics 204:1379-1390
Rahmani, Elior; Zaitlen, Noah; Baran, Yael et al. (2016) Sparse PCA corrects for cell type heterogeneity in epigenome-wide association studies. Nat Methods 13:443-5
Duong, Dat; Zou, Jennifer; Hormozdiari, Farhad et al. (2016) Using genomic annotations increases statistical power to detect eGenes. Bioinformatics 32:i156-i163
Kang, Eun Yong; Martin, Lisa J; Mangul, Serghei et al. (2016) Discovering Single Nucleotide Polymorphisms Regulating Human Gene Expression Using Allele Specific Expression from RNA-seq Data. Genetics 204:1057-1064
Hormozdiari, Farhad; van de Bunt, Martijn; Segrè, Ayellet V et al. (2016) Colocalization of GWAS and eQTL Signals Detects Target Genes. Am J Hum Genet 99:1245-1260
Joo, Jong Wha J; Hormozdiari, Farhad; Han, Buhm et al. (2016) Multiple testing correction in linear mixed models. Genome Biol 17:62

Showing the most recent 10 out of 31 publications