@article {626,
	title = {LTBP3 Pathogenic Variants Predispose Individuals to Thoracic Aortic Aneurysms and Dissections.},
	journal = {Am J Hum Genet},
	volume = {102},
	year = {2018},
	month = {2018 04 05},
	pages = {706-712},
	abstract = {<p>The major diseases affecting the thoracic aorta are aneurysms and acute dissections, and pathogenic variants in 11 genes are confirmed to lead to heritable thoracic aortic disease. However, many families in which multiple members have thoracic aortic disease do not have alterations in the known aortopathy genes. Genes highly expressed in the aorta were assessed for rare variants in exome sequencing data from such families, and compound rare heterozygous variants (p.Pro45Argfs25 and p.Glu750) in LTBP3 were identified in affected members of one family. A homozygous variant (p.Asn678_Gly681delinsThrCys) that introduces an additional cysteine into an epidermal growth factor (EGF)-like domain in the corresponding protein, latent TGF-β binding protein (LTBP-3), was identified in a second family. Individuals with compound heterozygous or homozygous variants in these families have aneurysms and dissections of the thoracic aorta, as well as aneurysms of the abdominal aorta and other arteries, along with dental abnormalities and short stature. Heterozygous carriers of the p.Asn678_Gly681delinsThrCys variant have later onset of thoracic aortic disease, as well as dental abnormalities. In these families, LTBP3 variants segregated with thoracic aortic disease with a combined LOD score of 3.9. Additionally, heterozygous rare LTBP3 variants were found in individuals with early onset of acute aortic dissections, and some of these variants disrupted LTBP-3 levels or EGF-like domains. When compared to wild-type mice, Ltbp3 mice have enlarged aortic roots and ascending aortas. In summary, homozygous LTBP3 pathogenic variants predispose individuals to thoracic aortic aneurysms and dissections, along with the previously described skeletal and dental abnormalities.</p>},
	keywords = {Adult, Aged, 80 and over, Aneurysm, Dissecting, Animals, Aortic Aneurysm, Thoracic, Blood Pressure, Female, Genetic Predisposition to Disease, Homozygote, Humans, Latent TGF-beta Binding Proteins, Male, Mice, Middle Aged, Mutation, Pedigree},
	issn = {1537-6605},
	doi = {10.1016/j.ajhg.2018.03.002},
	author = {Guo, Dong-Chuan and Regalado, Ellen S and Pinard, Amelie and Chen, Jiyuan and Lee, Kwanghyuk and Rigelsky, Christina and Zilberberg, Lior and Hostetler, Ellen M and Aldred, Micheala and Wallace, Stephanie E and Prakash, Siddharth K and Leal, Suzanne M and Bamshad, Michael J and Nickerson, Deborah A and Natowicz, Marvin and Rifkin, Daniel B and Milewicz, Dianna M}
}
@article {316,
	title = {A unified method for detecting secondary trait associations with rare variants: application to sequence data.},
	journal = {PLoS Genet},
	volume = {8},
	year = {2012},
	month = {2012},
	pages = {e1003075},
	abstract = {<p>Next-generation sequencing has made possible the detection of rare variant (RV) associations with quantitative traits (QT). Due to high sequencing cost, many studies can only sequence a modest number of selected samples with extreme QT. Therefore association testing in individual studies can be underpowered. Besides the primary trait, many clinically important secondary traits are often measured. It is highly beneficial if multiple studies can be jointly analyzed for detecting associations with commonly measured traits. However, analyzing secondary traits in selected samples can be biased if sample ascertainment is not properly modeled. Some methods exist for analyzing secondary traits in selected samples, where some burden tests can be implemented. However p-values can only be evaluated analytically via asymptotic approximations, which may not be accurate. Additionally, potentially more powerful sequence kernel association tests, variable selection-based methods, and burden tests that require permutations cannot be incorporated. To overcome these limitations, we developed a unified method for analyzing secondary trait associations with RVs (STAR) in selected samples, incorporating all RV tests. Statistical significance can be evaluated either through permutations or analytically. STAR makes it possible to apply more powerful RV tests to analyze secondary trait associations. It also enables jointly analyzing multiple cohorts ascertained under different study designs, which greatly boosts power. The performance of STAR and commonly used RV association tests were comprehensively evaluated using simulation studies. STAR was also implemented to analyze a dataset from the SardiNIA project where samples with extreme low-density lipoprotein levels were sequenced. A significant association between LDLR and systolic blood pressure was identified, which is supported by pharmacogenetic studies. In summary, for sequencing studies, STAR is an important tool for detecting secondary-trait RV associations.</p>},
	keywords = {Blood Pressure, Computer Simulation, Genetic Predisposition to Disease, Genetic Variation, Genome-Wide Association Study, High-Throughput Nucleotide Sequencing, Humans, Italy, Lipoproteins, LDL, Models, Genetic, Phenotype, Quantitative Trait Loci, Software},
	issn = {1553-7404},
	doi = {10.1371/journal.pgen.1003075},
	author = {Liu, Dajiang J and Leal, Suzanne M}
}
