@article {6788, title = {Rare and low-frequency variants and their association with plasma levels of fibrinogen, FVII, FVIII, and vWF.}, journal = {Blood}, volume = {126}, year = {2015}, month = {2015 Sep 10}, pages = {e19-29}, abstract = {

Fibrinogen, coagulation factor VII (FVII), and factor VIII (FVIII) and its carrier von Willebrand factor (vWF) play key roles in hemostasis. Previously identified common variants explain only a small fraction of the trait heritabilities, and additional variations may be explained by associations with rarer variants with larger effects. The aim of this study was to identify low-frequency (minor allele frequency [MAF] >=0.01 and <0.05) and rare (MAF <0.01) variants that influence plasma concentrations of these 4 hemostatic factors by meta-analyzing exome chip data from up to 76,000 participants of 4 ancestries. We identified 12 novel associations of low-frequency (n = 2) and rare (n = 10) variants across the fibrinogen, FVII, FVIII, and vWF traits that were independent of previously identified associations. Novel loci were found within previously reported genes and had effect sizes much larger than and independent of previously identified common variants. In addition, associations at KCNT1, HID1, and KATNB1 identified new candidate genes related to hemostasis for follow-up replication and functional genomic analysis. Newly identified low-frequency and rare-variant associations accounted for modest amounts of trait variance and therefore are unlikely to increase predicted trait heritability but provide new information for understanding individual variation in hemostasis pathways.

}, keywords = {Cohort Studies, Factor VII, Factor VIII, Fibrinogen, Gene Frequency, Genetic Association Studies, Genetic Variation, Humans, Nerve Tissue Proteins, Polymorphism, Single Nucleotide, Potassium Channels, von Willebrand Factor}, issn = {1528-0020}, doi = {10.1182/blood-2015-02-624551}, author = {Huffman, Jennifer E and de Vries, Paul S and Morrison, Alanna C and Sabater-Lleal, Maria and Kacprowski, Tim and Auer, Paul L and Brody, Jennifer A and Chasman, Daniel I and Chen, Ming-Huei and Guo, Xiuqing and Lin, Li-An and Marioni, Riccardo E and M{\"u}ller-Nurasyid, Martina and Yanek, Lisa R and Pankratz, Nathan and Grove, Megan L and de Maat, Moniek P M and Cushman, Mary and Wiggins, Kerri L and Qi, Lihong and Sennblad, Bengt and Harris, Sarah E and Polasek, Ozren and Riess, Helene and Rivadeneira, Fernando and Rose, Lynda M and Goel, Anuj and Taylor, Kent D and Teumer, Alexander and Uitterlinden, Andr{\'e} G and Vaidya, Dhananjay and Yao, Jie and Tang, Weihong and Levy, Daniel and Waldenberger, Melanie and Becker, Diane M and Folsom, Aaron R and Giulianini, Franco and Greinacher, Andreas and Hofman, Albert and Huang, Chiang-Ching and Kooperberg, Charles and Silveira, Angela and Starr, John M and Strauch, Konstantin and Strawbridge, Rona J and Wright, Alan F and McKnight, Barbara and Franco, Oscar H and Zakai, Neil and Mathias, Rasika A and Psaty, Bruce M and Ridker, Paul M and Tofler, Geoffrey H and V{\"o}lker, Uwe and Watkins, Hugh and Fornage, Myriam and Hamsten, Anders and Deary, Ian J and Boerwinkle, Eric and Koenig, Wolfgang and Rotter, Jerome I and Hayward, Caroline and Dehghan, Abbas and Reiner, Alex P and O{\textquoteright}Donnell, Christopher J and Smith, Nicholas L} } @article {7145, title = {An Empirical Comparison of Joint and Stratified Frameworks for Studying G {\texttimes} E Interactions: Systolic Blood Pressure and Smoking in the CHARGE Gene-Lifestyle Interactions Working Group.}, journal = {Genet Epidemiol}, volume = {40}, year = {2016}, month = {2016 Jul}, pages = {404-15}, abstract = {

Studying gene-environment (G {\texttimes} E) interactions is important, as they extend our knowledge of the genetic architecture of complex traits and may help to identify novel variants not detected via analysis of main effects alone. The main statistical framework for studying G {\texttimes} E interactions uses a single regression model that includes both the genetic main and G {\texttimes} E interaction effects (the "joint" framework). The alternative "stratified" framework combines results from genetic main-effect analyses carried out separately within the exposed and unexposed groups. Although there have been several investigations using theory and simulation, an empirical comparison of the two frameworks is lacking. Here, we compare the two frameworks using results from genome-wide association studies of systolic blood pressure for 3.2 million low frequency and 6.5 million common variants across 20 cohorts of European ancestry, comprising 79,731 individuals. Our cohorts have sample sizes ranging from 456 to 22,983 and include both family-based and population-based samples. In cohort-specific analyses, the two frameworks provided similar inference for population-based cohorts. The agreement was reduced for family-based cohorts. In meta-analyses, agreement between the two frameworks was less than that observed in cohort-specific analyses, despite the increased sample size. In meta-analyses, agreement depended on (1) the minor allele frequency, (2) inclusion of family-based cohorts in meta-analysis, and (3) filtering scheme. The stratified framework appears to approximate the joint framework well only for common variants in population-based cohorts. We conclude that the joint framework is the preferred approach and should be used to control false positives when dealing with low-frequency variants and/or family-based cohorts.

}, issn = {1098-2272}, doi = {10.1002/gepi.21978}, author = {Sung, Yun Ju and Winkler, Thomas W and Manning, Alisa K and Aschard, Hugues and Gudnason, Vilmundur and Harris, Tamara B and Smith, Albert V and Boerwinkle, Eric and Brown, Michael R and Morrison, Alanna C and Fornage, Myriam and Lin, Li-An and Richard, Melissa and Bartz, Traci M and Psaty, Bruce M and Hayward, Caroline and Polasek, Ozren and Marten, Jonathan and Rudan, Igor and Feitosa, Mary F and Kraja, Aldi T and Province, Michael A and Deng, Xuan and Fisher, Virginia A and Zhou, Yanhua and Bielak, Lawrence F and Smith, Jennifer and Huffman, Jennifer E and Padmanabhan, Sandosh and Smith, Blair H and Ding, Jingzhong and Liu, Yongmei and Lohman, Kurt and Bouchard, Claude and Rankinen, Tuomo and Rice, Treva K and Arnett, Donna and Schwander, Karen and Guo, Xiuqing and Palmas, Walter and Rotter, Jerome I and Alfred, Tamuno and Bottinger, Erwin P and Loos, Ruth J F and Amin, Najaf and Franco, Oscar H and van Duijn, Cornelia M and Vojinovic, Dina and Chasman, Daniel I and Ridker, Paul M and Rose, Lynda M and Kardia, Sharon and Zhu, Xiaofeng and Rice, Kenneth and Borecki, Ingrid B and Rao, Dabeeru C and Gauderman, W James and Cupples, L Adrienne} } @article {7264, title = {Meta-analysis identifies common and rare variants influencing blood pressure and overlapping with metabolic trait loci.}, journal = {Nat Genet}, volume = {48}, year = {2016}, month = {2016 Oct}, pages = {1162-70}, abstract = {

Meta-analyses of association results for blood pressure using exome-centric single-variant and gene-based tests identified 31 new loci in a discovery stage among 146,562 individuals, with follow-up and meta-analysis in 180,726 additional individuals (total n = 327,288). These blood pressure-associated loci are enriched for known variants for cardiometabolic traits. Associations were also observed for the aggregation of rare and low-frequency missense variants in three genes, NPR1, DBH, and PTPMT1. In addition, blood pressure associations at 39 previously reported loci were confirmed. The identified variants implicate biological pathways related to cardiometabolic traits, vascular function, and development. Several new variants are inferred to have roles in transcription or as hubs in protein-protein interaction networks. Genetic risk scores constructed from the identified variants were strongly associated with coronary disease and myocardial infarction. This large collection of blood pressure-associated loci suggests new therapeutic strategies for hypertension, emphasizing a link with cardiometabolic risk.

}, issn = {1546-1718}, doi = {10.1038/ng.3660}, author = {Liu, Chunyu and Kraja, Aldi T and Smith, Jennifer A and Brody, Jennifer A and Franceschini, Nora and Bis, Joshua C and Rice, Kenneth and Morrison, Alanna C and Lu, Yingchang and Weiss, Stefan and Guo, Xiuqing and Palmas, Walter and Martin, Lisa W and Chen, Yii-Der Ida and Surendran, Praveen and Drenos, Fotios and Cook, James P and Auer, Paul L and Chu, Audrey Y and Giri, Ayush and Zhao, Wei and Jakobsdottir, Johanna and Lin, Li-An and Stafford, Jeanette M and Amin, Najaf and Mei, Hao and Yao, Jie and Voorman, Arend and Larson, Martin G and Grove, Megan L and Smith, Albert V and Hwang, Shih-Jen and Chen, Han and Huan, Tianxiao and Kosova, Gulum and Stitziel, Nathan O and Kathiresan, Sekar and Samani, Nilesh and Schunkert, Heribert and Deloukas, Panos and Li, Man and Fuchsberger, Christian and Pattaro, Cristian and Gorski, Mathias and Kooperberg, Charles and Papanicolaou, George J and Rossouw, Jacques E and Faul, Jessica D and Kardia, Sharon L R and Bouchard, Claude and Raffel, Leslie J and Uitterlinden, Andr{\'e} G and Franco, Oscar H and Vasan, Ramachandran S and O{\textquoteright}Donnell, Christopher J and Taylor, Kent D and Liu, Kiang and Bottinger, Erwin P and Gottesman, Omri and Daw, E Warwick and Giulianini, Franco and Ganesh, Santhi and Salfati, Elias and Harris, Tamara B and Launer, Lenore J and D{\"o}rr, Marcus and Felix, Stephan B and Rettig, Rainer and V{\"o}lzke, Henry and Kim, Eric and Lee, Wen-Jane and Lee, I-Te and Sheu, Wayne H-H and Tsosie, Krystal S and Edwards, Digna R Velez and Liu, Yongmei and Correa, Adolfo and Weir, David R and V{\"o}lker, Uwe and Ridker, Paul M and Boerwinkle, Eric and Gudnason, Vilmundur and Reiner, Alexander P and van Duijn, Cornelia M and Borecki, Ingrid B and Edwards, Todd L and Chakravarti, Aravinda and Rotter, Jerome I and Psaty, Bruce M and Loos, Ruth J F and Fornage, Myriam and Ehret, Georg B and Newton-Cheh, Christopher and Levy, Daniel and Chasman, Daniel I} }