@article {6178, title = {Association of genetic loci with sleep apnea in European Americans and African-Americans: the Candidate Gene Association Resource (CARe).}, journal = {PLoS One}, volume = {7}, year = {2012}, month = {2012}, pages = {e48836}, abstract = {

Although obstructive sleep apnea (OSA) is known to have a strong familial basis, no genetic polymorphisms influencing apnea risk have been identified in cross-cohort analyses. We utilized the National Heart, Lung, and Blood Institute (NHLBI) Candidate Gene Association Resource (CARe) to identify sleep apnea susceptibility loci. Using a panel of 46,449 polymorphisms from roughly 2,100 candidate genes on a customized Illumina iSelect chip, we tested for association with the apnea hypopnea index (AHI) as well as moderate to severe OSA (AHI>=15) in 3,551 participants of the Cleveland Family Study and two cohorts participating in the Sleep Heart Health Study.Among 647 African-Americans, rs11126184 in the pleckstrin (PLEK) gene was associated with OSA while rs7030789 in the lysophosphatidic acid receptor 1 (LPAR1) gene was associated with AHI using a chip-wide significance threshold of p-value<2{\texttimes}10(-6). Among 2,904 individuals of European ancestry, rs1409986 in the prostaglandin E2 receptor (PTGER3) gene was significantly associated with OSA. Consistency of effects between rs7030789 and rs1409986 in LPAR1 and PTGER3 and apnea phenotypes were observed in independent clinic-based cohorts.Novel genetic loci for apnea phenotypes were identified through the use of customized gene chips and meta-analyses of cohort data with replication in clinic-based samples. The identified SNPs all lie in genes associated with inflammation suggesting inflammation may play a role in OSA pathogenesis.

}, keywords = {Adult, African Americans, Aged, Alleles, European Continental Ancestry Group, Female, Genetic Association Studies, Genetic Loci, Genetic Predisposition to Disease, Genotype, Humans, Male, Middle Aged, Phenotype, Polymorphism, Single Nucleotide, Polysomnography, Sleep Apnea, Obstructive}, issn = {1932-6203}, doi = {10.1371/journal.pone.0048836}, author = {Patel, Sanjay R and Goodloe, Robert and De, Gourab and Kowgier, Matthew and Weng, Jia and Buxbaum, Sarah G and Cade, Brian and Fulop, Tibor and Gharib, Sina A and Gottlieb, Daniel J and Hillman, David and Larkin, Emma K and Lauderdale, Diane S and Li, Li and Mukherjee, Sutapa and Palmer, Lyle and Zee, Phyllis and Zhu, Xiaofeng and Redline, Susan} } @article {6860, title = {Integrative pathway genomics of lung function and airflow obstruction.}, journal = {Hum Mol Genet}, volume = {24}, year = {2015}, month = {2015 Dec 1}, pages = {6836-48}, abstract = {

Chronic respiratory disorders are important contributors to the global burden of disease. Genome-wide association studies (GWASs) of lung function measures have identified several trait-associated loci, but explain only a modest portion of the phenotypic variability. We postulated that integrating pathway-based methods with GWASs of pulmonary function and airflow obstruction would identify a broader repertoire of genes and processes influencing these traits. We performed two independent GWASs of lung function and applied gene set enrichment analysis to one of the studies and validated the results using the second GWAS. We identified 131 significantly enriched gene sets associated with lung function and clustered them into larger biological modules involved in diverse processes including development, immunity, cell signaling, proliferation and arachidonic acid. We found that enrichment of gene sets was not driven by GWAS-significant variants or loci, but instead by those with less stringent association P-values. Next, we applied pathway enrichment analysis to a meta-analyzed GWAS of airflow obstruction. We identified several biologic modules that functionally overlapped with those associated with pulmonary function. However, differences were also noted, including enrichment of extracellular matrix (ECM) processes specifically in the airflow obstruction study. Network analysis of the ECM module implicated a candidate gene, matrix metalloproteinase 10 (MMP10), as a putative disease target. We used a knockout mouse model to functionally validate MMP10{\textquoteright}s role in influencing lung{\textquoteright}s susceptibility to cigarette smoke-induced emphysema. By integrating pathway analysis with population-based genomics, we unraveled biologic processes underlying pulmonary function traits and identified a candidate gene for obstructive lung disease.

}, keywords = {Airway Obstruction, Animals, Cell Proliferation, European Continental Ancestry Group, Genetic Predisposition to Disease, Genome-Wide Association Study, Genomics, Humans, Immune System, Lung, Male, Metabolic Networks and Pathways, Mice, Phenotype, Polymorphism, Single Nucleotide, Signal Transduction}, issn = {1460-2083}, doi = {10.1093/hmg/ddv378}, author = {Gharib, Sina A and Loth, Daan W and Soler Artigas, Maria and Birkland, Timothy P and Wilk, Jemma B and Wain, Louise V and Brody, Jennifer A and Obeidat, Ma{\textquoteright}en and Hancock, Dana B and Tang, Wenbo and Rawal, Rajesh and Boezen, H Marike and Imboden, Medea and Huffman, Jennifer E and Lahousse, Lies and Alves, Alexessander C and Manichaikul, Ani and Hui, Jennie and Morrison, Alanna C and Ramasamy, Adaikalavan and Smith, Albert Vernon and Gudnason, Vilmundur and Surakka, Ida and Vitart, Veronique and Evans, David M and Strachan, David P and Deary, Ian J and Hofman, Albert and Gl{\"a}ser, Sven and Wilson, James F and North, Kari E and Zhao, Jing Hua and Heckbert, Susan R and Jarvis, Deborah L and Probst-Hensch, Nicole and Schulz, Holger and Barr, R Graham and Jarvelin, Marjo-Riitta and O{\textquoteright}Connor, George T and K{\"a}h{\"o}nen, Mika and Cassano, Patricia A and Hysi, Pirro G and Dupuis, Jos{\'e}e and Hayward, Caroline and Psaty, Bruce M and Hall, Ian P and Parks, William C and Tobin, Martin D and London, Stephanie J} } @article {8400, title = {Chronic obstructive pulmonary disease and related phenotypes: polygenic risk scores in population-based and case-control cohorts.}, journal = {Lancet Respir Med}, volume = {8}, year = {2020}, month = {2020 07}, pages = {696-708}, abstract = {

BACKGROUND: Genetic factors influence chronic obstructive pulmonary disease (COPD) risk, but the individual variants that have been identified have small effects. We hypothesised that a polygenic risk score using additional variants would predict COPD and associated phenotypes.

METHODS: We constructed a polygenic risk score using a genome-wide association study of lung function (FEV and FEV/forced vital capacity [FVC]) from the UK Biobank and SpiroMeta. We tested this polygenic risk score in nine cohorts of multiple ethnicities for an association with moderate-to-severe COPD (defined as FEV/FVC <0{\textperiodcentered}7 and FEV <80\% of predicted). Associations were tested using logistic regression models, adjusting for age, sex, height, smoking pack-years, and principal components of genetic ancestry. We assessed predictive performance of models by area under the curve. In a subset of studies, we also studied quantitative and qualitative CT imaging phenotypes that reflect parenchymal and airway pathology, and patterns of reduced lung growth.

FINDINGS: The polygenic risk score was associated with COPD in European (odds ratio [OR] per SD 1{\textperiodcentered}81 [95\% CI 1{\textperiodcentered}74-1{\textperiodcentered}88] and non-European (1{\textperiodcentered}42 [1{\textperiodcentered}34-1{\textperiodcentered}51]) populations. Compared with the first decile, the tenth decile of the polygenic risk score was associated with COPD, with an OR of 7{\textperiodcentered}99 (6{\textperiodcentered}56-9{\textperiodcentered}72) in European ancestry and 4{\textperiodcentered}83 (3{\textperiodcentered}45-6{\textperiodcentered}77) in non-European ancestry cohorts. The polygenic risk score was superior to previously described genetic risk scores and, when combined with clinical risk factors (ie, age, sex, and smoking pack-years), showed improved prediction for COPD compared with a model comprising clinical risk factors alone (AUC 0{\textperiodcentered}80 [0{\textperiodcentered}79-0{\textperiodcentered}81] vs 0{\textperiodcentered}76 [0{\textperiodcentered}75-0{\textperiodcentered}76]). The polygenic risk score was associated with CT imaging phenotypes, including wall area percent, quantitative and qualitative measures of emphysema, local histogram emphysema patterns, and destructive emphysema subtypes. The polygenic risk score was associated with a reduced lung growth pattern.

INTERPRETATION: A risk score comprised of genetic variants can identify a small subset of individuals at markedly increased risk for moderate-to-severe COPD, emphysema subtypes associated with cigarette smoking, and patterns of reduced lung growth.

FUNDING: US National Institutes of Health, Wellcome Trust.

}, keywords = {Adult, Case-Control Studies, Cohort Studies, Female, Forced Expiratory Volume, Genome-Wide Association Study, Humans, Male, Middle Aged, Phenotype, Pulmonary Disease, Chronic Obstructive, Risk Factors, Vital Capacity}, issn = {2213-2619}, doi = {10.1016/S2213-2600(20)30101-6}, author = {Moll, Matthew and Sakornsakolpat, Phuwanat and Shrine, Nick and Hobbs, Brian D and DeMeo, Dawn L and John, Catherine and Guyatt, Anna L and McGeachie, Michael J and Gharib, Sina A and Obeidat, Ma{\textquoteright}en and Lahousse, Lies and Wijnant, Sara R A and Brusselle, Guy and Meyers, Deborah A and Bleecker, Eugene R and Li, Xingnan and Tal-Singer, Ruth and Manichaikul, Ani and Rich, Stephen S and Won, Sungho and Kim, Woo Jin and Do, Ah Ra and Washko, George R and Barr, R Graham and Psaty, Bruce M and Bartz, Traci M and Hansel, Nadia N and Barnes, Kathleen and Hokanson, John E and Crapo, James D and Lynch, David and Bakke, Per and Gulsvik, Amund and Hall, Ian P and Wain, Louise and Weiss, Scott T and Silverman, Edwin K and Dudbridge, Frank and Tobin, Martin D and Cho, Michael H} }