@article {105,
	title = {Lung Function in African American Children with Asthma Is Associated with Novel Regulatory Variants of the KIT Ligand  and Gene-By-Air-Pollution Interaction.},
	journal = {Genetics},
	volume = {215},
	year = {2020},
	month = {2020 07},
	pages = {869-886},
	abstract = {<p>Baseline lung function, quantified as forced expiratory volume in the first second of exhalation (FEV), is a standard diagnostic criterion used by clinicians to identify and classify lung diseases. Using whole-genome sequencing data from the National Heart, Lung, and Blood Institute Trans-Omics for Precision Medicine project, we identified a novel genetic association with FEV on chromosome 12 in 867 African American children with asthma ( = 1.26 {\texttimes} 10, β = 0.302). Conditional analysis within 1 Mb of the tag signal (rs73429450) yielded one major and two other weaker independent signals within this peak. We explored statistical and functional evidence for all variants in linkage disequilibrium with the three independent signals and yielded nine variants as the most likely candidates responsible for the association with FEV Hi-C data and expression QTL analysis demonstrated that these variants physically interacted with  (KIT ligand, also known as ), and their minor alleles were associated with increased expression of the  gene in nasal epithelial cells. Gene-by-air-pollution interaction analysis found that the candidate variant rs58475486 interacted with past-year ambient sulfur dioxide exposure ( = 0.003, β = 0.32). This study identified a novel protective genetic association with FEV, possibly mediated through , in African American children with asthma. This is the first study that has identified a genetic association between lung function and , which has established a role in orchestrating allergic inflammation in asthma.</p>},
	issn = {1943-2631},
	doi = {10.1534/genetics.120.303231},
	author = {Mak, Angel C Y and Sajuthi, Satria and Joo, Jaehyun and Xiao, Shujie and Sleiman, Patrick M and White, Marquitta J and Lee, Eunice Y and Saef, Benjamin and Hu, Donglei and Gui, Hongsheng and Keys, Kevin L and Lurmann, Fred and Jain, Deepti and Abecasis, Goncalo and Kang, Hyun Min and Nickerson, Deborah A and Germer, Soren and Zody, Michael C and Winterkorn, Lara and Reeves, Catherine and Huntsman, Scott and Eng, Celeste and Salazar, Sandra and Oh, Sam S and Gilliland, Frank D and Chen, Zhanghua and Kumar, Rajesh and Mart{\'\i}nez, Fernando D and Wu, Ann Chen and Ziv, Elad and Hakonarson, Hakon and Himes, Blanca E and Williams, L Keoki and Seibold, Max A and Burchard, Esteban G}
}
@article {45,
	title = {Quantifying the Polygenic Contribution to Cutaneous Squamous Cell Carcinoma Risk.},
	journal = {J Invest Dermatol},
	volume = {138},
	year = {2018},
	month = {2018 Jul},
	pages = {1507-1510},
	abstract = {<p>Genetic factors play an important role in cutaneous squamous cell carcinoma risk. Genome-wide association studies have identified 21 single nucleotide polymorphisms associated with cutaneous squamous cell carcinoma risk. Yet no studies have attempted to quantify the contribution of heritability to cutaneous squamous cell carcinoma risk by calculating the population attributable risk using a combination of all discovered genetic variants. Using an additive multi-locus linear logistic model, we determined the cumulative association of these 21 genetic regions to cutaneous squamous cell carcinoma population attributable risk. We computed a multi-locus population attributable risk of 62\%, suggesting that if the effects of all the risk alleles were removed from a population, the cutaneous squamous cell carcinoma risk would drop by 62\%. Using stratified analysis, we also examined the impact of sex on polygenic risk score, and found that men have an increased relative risk throughout the spectrum of the polygenic risk score. Quantifying the impact of genetic predisposition on the proportion of cancer cases can guide future research decisions and public health policy planning.</p>},
	keywords = {Carcinoma, Squamous Cell, Female, Genetic Loci, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Linear Models, Logistic Models, Male, Models, Biological, Polymorphism, Single Nucleotide, Risk Assessment, Risk Factors, Sex Factors, Skin Neoplasms},
	issn = {1523-1747},
	doi = {10.1016/j.jid.2018.01.031},
	author = {Sordillo, Joanne E and Kraft, Peter and Wu, Ann Chen and Asgari, Maryam M}
}
