The long-term goal of this Project is to identify the genetic variation contributing to the risk of developing Alopecia Areata (AA). AA is one of the most common human autoimmune diseases, with a lifetime risk of approximately 2%. It affects approximately 4.6 million individuals in the United States alone, including males and females of all ages and ethnic groups. AA fits the paradigm of a complex or multifactorial trait, in which combinations of genetic and environmental factors combine to give rise to the final phenotype. Our lab has focused on using unbiased genome-wide approaches to identify susceptibility loci for AA. We recently pioneered the use of genome-wide family-based linkage as applied to AA for the first time, and identified four susceptibility loci in a small cohort of large, multiplex pedigrees. This study was designed to identify rare alleles with relatively large effects. In this Project, we now seek to do the converse. Here, we propose to carry out a genome-wide association study (GWAS) to identify common alleles with small effect that contribute to risk of AA, using 1000 cases and 3000 controls. All of these cases and a proportion of the controls were collected from the Alopecia Areata Registry and will be genotyped with the Illumina 550K SNP array. We will utilize a strategy that has proved successful with other GWAS and obtain the majority of our control samples from a database of shared controls. We will perform replication studies in an additional 3 independent samples of cases and controls. Each of these four studies will be analyzed independently and jointly, greatly increasing our power to detect association of disease alleles with moderate genetic effects. Once susceptibility alleles for AA have been identified, candidate genes containing the SNPs of interest will be prioritized using mRNA and protein expression patterns in the hair follicle. The positional information will be cross-referenced with information derived from expression studies in mouse models for AA. Finally, should some of the variants identified be coding-sequence SNPs, we will then analyze these candidate genes in depth, to look at mRNA and protein expression, and to formulate mechanistic links to the human disease. We expect that identification of SNPs that confer susceptibility to AA will uncover the network of pathways of disease pathogenesis and lead to new approaches for treating this disorder.

Public Health Relevance

. The long-term goal of this Application is to identify the genetic variation contributing to the risk of developing Alopecia Areata (AA). AA is a form of hair loss in which the body attacks the growing hair follicle, and can result in hair loss ranging from patches on the scalp to complete hair loss over the body. AA is one of the most common human autoimmune diseases, with a lifetime risk of approximately 2%. AA affects approximately 4.6 million individuals in the United States alone, including males and females of all ages and ethnic groups. While AA is a non-lethal skin disease, its impact as measured in the Burden of Skin Disease Report is profound as it relates to quality-of-life measures. Ultimately, it is anticipated that discovery and modulation of the genes for AA will provide novel therapeutic targets, and eventually eliminate this psychologically devastating dermatologic disorder. The studies outlined in this Application aim to systematically pinpoint common susceptibility alleles for human AA for the first time.

Agency
National Institute of Health (NIH)
Institute
National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS)
Type
Research Project (R01)
Project #
5R01AR056016-05
Application #
8324296
Study Section
Arthritis, Connective Tissue and Skin Study Section (ACTS)
Program Officer
Cibotti, Ricardo
Project Start
2008-09-19
Project End
2014-08-31
Budget Start
2012-09-01
Budget End
2014-08-31
Support Year
5
Fiscal Year
2012
Total Cost
$335,169
Indirect Cost
$126,080
Name
Columbia University (N.Y.)
Department
Dermatology
Type
Schools of Medicine
DUNS #
621889815
City
New York
State
NY
Country
United States
Zip Code
10032
Xing, Luzhou; Dai, Zhenpeng; Jabbari, Ali et al. (2014) Alopecia areata is driven by cytotoxic T lymphocytes and is reversed by JAK inhibition. Nat Med 20:1043-9
Jahoda, Colin A B; Christiano, Angela M (2011) Niche crosstalk: intercellular signals at the hair follicle. Cell 146:678-81
Petukhova, Lynn; Duvic, Madeleine; Hordinsky, Maria et al. (2010) Genome-wide association study in alopecia areata implicates both innate and adaptive immunity. Nature 466:113-7