@article {8838, title = {BinomiRare: A robust test for association of a rare genetic variant with a binary outcome for mixed models and any case-control proportion.}, journal = {HGG Adv}, volume = {2}, year = {2021}, month = {2021 Jul 08}, abstract = {

Whole-genome sequencing (WGS) and whole-exome sequencing studies have become increasingly available and are being used to identify rare genetic variants associated with health and disease outcomes. Investigators routinely use mixed models to account for genetic relatedness or other clustering variables (e.g., family or household) when testing genetic associations. However, no existing tests of the association of a rare variant with a binary outcome in the presence of correlated data control the type 1 error where there are (1) few individuals harboring the rare allele, (2) a small proportion of cases relative to controls, and (3) covariates to adjust for. Here, we address all three issues in developing a framework for testing rare variant association with a binary trait in individuals harboring at least one risk allele. In this framework, we estimate outcome probabilities under the null hypothesis and then use them, within the individuals with at least one risk allele, to test variant associations. We extend the BinomiRare test, which was previously proposed for independent observations, and develop the Conway-Maxwell-Poisson (CMP) test and study their properties in simulations. We show that the BinomiRare test always controls the type 1 error, while the CMP test sometimes does not. We then use the BinomiRare test to test the association of rare genetic variants in target genes with small-vessel disease (SVD) stroke, short sleep, and venous thromboembolism (VTE), in whole-genome sequence data from the Trans-Omics for Precision Medicine (TOPMed) program.

}, issn = {2666-2477}, doi = {10.1016/j.xhgg.2021.100040}, author = {Sofer, Tamar and Lee, Jiwon and Kurniansyah, Nuzulul and Jain, Deepti and Laurie, Cecelia A and Gogarten, Stephanie M and Conomos, Matthew P and Heavner, Ben and Hu, Yao and Kooperberg, Charles and Haessler, Jeffrey and Vasan, Ramachandran S and Cupples, L Adrienne and Coombes, Brandon J and Seyerle, Amanda and Gharib, Sina A and Chen, Han and O{\textquoteright}Connell, Jeffrey R and Zhang, Man and Gottlieb, Daniel J and Psaty, Bruce M and Longstreth, W T and Rotter, Jerome I and Taylor, Kent D and Rich, Stephen S and Guo, Xiuqing and Boerwinkle, Eric and Morrison, Alanna C and Pankow, James S and Johnson, Andrew D and Pankratz, Nathan and Reiner, Alex P and Redline, Susan and Smith, Nicholas L and Rice, Kenneth M and Schifano, Elizabeth D} } @article {8920, title = {Whole-genome association analyses of sleep-disordered breathing phenotypes in the NHLBI TOPMed program.}, journal = {Genome Med}, volume = {13}, year = {2021}, month = {2021 08 26}, pages = {136}, abstract = {

BACKGROUND: Sleep-disordered breathing is a common disorder associated with significant morbidity. The genetic architecture of sleep-disordered breathing remains poorly understood. Through the NHLBI Trans-Omics for Precision Medicine (TOPMed) program, we performed the first whole-genome sequence analysis of sleep-disordered breathing.

METHODS: The study sample was comprised of 7988 individuals of diverse ancestry. Common-variant and pathway analyses included an additional 13,257 individuals. We examined five complementary traits describing different aspects of sleep-disordered breathing: the apnea-hypopnea index, average oxyhemoglobin desaturation per event, average and minimum oxyhemoglobin saturation across the sleep episode, and the percentage of sleep with oxyhemoglobin saturation < 90\%. We adjusted for age, sex, BMI, study, and family structure using MMSKAT and EMMAX mixed linear model approaches. Additional bioinformatics analyses were performed with MetaXcan, GIGSEA, and ReMap.

RESULTS: We identified a multi-ethnic set-based rare-variant association (p = 3.48 {\texttimes} 10) on chromosome X with ARMCX3. Additional rare-variant associations include ARMCX3-AS1, MRPS33, and C16orf90. Novel common-variant loci were identified in the NRG1 and SLC45A2 regions, and previously associated loci in the IL18RAP and ATP2B4 regions were associated with novel phenotypes. Transcription factor binding site enrichment identified associations with genes implicated with respiratory and craniofacial traits. Additional analyses identified significantly associated pathways.

CONCLUSIONS: We have identified the first gene-based rare-variant associations with objectively measured sleep-disordered breathing traits. Our results increase the understanding of the genetic architecture of sleep-disordered breathing and highlight associations in genes that modulate lung development, inflammation, respiratory rhythmogenesis, and HIF1A-mediated hypoxic response.

}, issn = {1756-994X}, doi = {10.1186/s13073-021-00917-8}, author = {Cade, Brian E and Lee, Jiwon and Sofer, Tamar and Wang, Heming and Zhang, Man and Chen, Han and Gharib, Sina A and Gottlieb, Daniel J and Guo, Xiuqing and Lane, Jacqueline M and Liang, Jingjing and Lin, Xihong and Mei, Hao and Patel, Sanjay R and Purcell, Shaun M and Saxena, Richa and Shah, Neomi A and Evans, Daniel S and Hanis, Craig L and Hillman, David R and Mukherjee, Sutapa and Palmer, Lyle J and Stone, Katie L and Tranah, Gregory J and Abecasis, Goncalo R and Boerwinkle, Eric A and Correa, Adolfo and Cupples, L Adrienne and Kaplan, Robert C and Nickerson, Deborah A and North, Kari E and Psaty, Bruce M and Rotter, Jerome I and Rich, Stephen S and Tracy, Russell P and Vasan, Ramachandran S and Wilson, James G and Zhu, Xiaofeng and Redline, Susan} }