@article {1345, title = {A phenomics-based strategy identifies loci on APOC1, BRAP, and PLCG1 associated with metabolic syndrome phenotype domains.}, journal = {PLoS Genet}, volume = {7}, year = {2011}, month = {2011 Oct}, pages = {e1002322}, abstract = {

Despite evidence of the clustering of metabolic syndrome components, current approaches for identifying unifying genetic mechanisms typically evaluate clinical categories that do not provide adequate etiological information. Here, we used data from 19,486 European American and 6,287 African American Candidate Gene Association Resource Consortium participants to identify loci associated with the clustering of metabolic phenotypes. Six phenotype domains (atherogenic dyslipidemia, vascular dysfunction, vascular inflammation, pro-thrombotic state, central obesity, and elevated plasma glucose) encompassing 19 quantitative traits were examined. Principal components analysis was used to reduce the dimension of each domain such that >55\% of the trait variance was represented within each domain. We then applied a statistically efficient and computational feasible multivariate approach that related eight principal components from the six domains to 250,000 imputed SNPs using an additive genetic model and including demographic covariates. In European Americans, we identified 606 genome-wide significant SNPs representing 19 loci. Many of these loci were associated with only one trait domain, were consistent with results in African Americans, and overlapped with published findings, for instance central obesity and FTO. However, our approach, which is applicable to any set of interval scale traits that is heritable and exhibits evidence of phenotypic clustering, identified three new loci in or near APOC1, BRAP, and PLCG1, which were associated with multiple phenotype domains. These pleiotropic loci may help characterize metabolic dysregulation and identify targets for intervention.

}, keywords = {African Americans, Apolipoprotein C-I, Blood Glucose, Dyslipidemias, European Continental Ancestry Group, Genetic Association Studies, Genetic Predisposition to Disease, Genome, Human, Humans, Metabolic Syndrome, Obesity, Abdominal, Phenotype, Phospholipase C gamma, Polymorphism, Single Nucleotide, Quantitative Trait, Heritable, Ubiquitin-Protein Ligases, Vascular Diseases}, issn = {1553-7404}, doi = {10.1371/journal.pgen.1002322}, author = {Avery, Christy L and He, Qianchuan and North, Kari E and Ambite, Jos{\'e} L and Boerwinkle, Eric and Fornage, Myriam and Hindorff, Lucia A and Kooperberg, Charles and Meigs, James B and Pankow, James S and Pendergrass, Sarah A and Psaty, Bruce M and Ritchie, Marylyn D and Rotter, Jerome I and Taylor, Kent D and Wilkens, Lynne R and Heiss, Gerardo and Lin, Dan Yu} } @article {6591, title = {Pharmacogenetic meta-analysis of genome-wide association studies of LDL cholesterol response to statins.}, journal = {Nat Commun}, volume = {5}, year = {2014}, month = {2014 Oct 28}, pages = {5068}, abstract = {

Statins effectively lower LDL cholesterol levels in large studies and the observed interindividual response variability may be partially explained by genetic variation. Here we perform a pharmacogenetic meta-analysis of genome-wide association studies (GWAS) in studies addressing the LDL cholesterol response to statins, including up to 18,596 statin-treated subjects. We validate the most promising signals in a further 22,318 statin recipients and identify two loci, SORT1/CELSR2/PSRC1 and SLCO1B1, not previously identified in GWAS. Moreover, we confirm the previously described associations with APOE and LPA. Our findings advance the understanding of the pharmacogenetic architecture of statin response.

}, keywords = {Cholesterol, LDL, Genome-Wide Association Study, Humans, Hydroxymethylglutaryl-CoA Reductase Inhibitors, Pharmacogenetics, Polymorphism, Single Nucleotide}, issn = {2041-1723}, doi = {10.1038/ncomms6068}, author = {Postmus, Iris and Trompet, Stella and Deshmukh, Harshal A and Barnes, Michael R and Li, Xiaohui and Warren, Helen R and Chasman, Daniel I and Zhou, Kaixin and Arsenault, Benoit J and Donnelly, Louise A and Wiggins, Kerri L and Avery, Christy L and Griffin, Paula and Feng, QiPing and Taylor, Kent D and Li, Guo and Evans, Daniel S and Smith, Albert V and de Keyser, Catherine E and Johnson, Andrew D and de Craen, Anton J M and Stott, David J and Buckley, Brendan M and Ford, Ian and Westendorp, Rudi G J and Slagboom, P Eline and Sattar, Naveed and Munroe, Patricia B and Sever, Peter and Poulter, Neil and Stanton, Alice and Shields, Denis C and O{\textquoteright}Brien, Eoin and Shaw-Hawkins, Sue and Chen, Y-D Ida and Nickerson, Deborah A and Smith, Joshua D and Dub{\'e}, Marie Pierre and Boekholdt, S Matthijs and Hovingh, G Kees and Kastelein, John J P and McKeigue, Paul M and Betteridge, John and Neil, Andrew and Durrington, Paul N and Doney, Alex and Carr, Fiona and Morris, Andrew and McCarthy, Mark I and Groop, Leif and Ahlqvist, Emma and Bis, Joshua C and Rice, Kenneth and Smith, Nicholas L and Lumley, Thomas and Whitsel, Eric A and St{\"u}rmer, Til and Boerwinkle, Eric and Ngwa, Julius S and O{\textquoteright}Donnell, Christopher J and Vasan, Ramachandran S and Wei, Wei-Qi and Wilke, Russell A and Liu, Ching-Ti and Sun, Fangui and Guo, Xiuqing and Heckbert, Susan R and Post, Wendy and Sotoodehnia, Nona and Arnold, Alice M and Stafford, Jeanette M and Ding, Jingzhong and Herrington, David M and Kritchevsky, Stephen B and Eiriksdottir, Gudny and Launer, Leonore J and Harris, Tamara B and Chu, Audrey Y and Giulianini, Franco and MacFadyen, Jean G and Barratt, Bryan J and Nyberg, Fredrik and Stricker, Bruno H and Uitterlinden, Andr{\'e} G and Hofman, Albert and Rivadeneira, Fernando and Emilsson, Valur and Franco, Oscar H and Ridker, Paul M and Gudnason, Vilmundur and Liu, Yongmei and Denny, Joshua C and Ballantyne, Christie M and Rotter, Jerome I and Adrienne Cupples, L and Psaty, Bruce M and Palmer, Colin N A and Tardif, Jean-Claude and Colhoun, Helen M and Hitman, Graham and Krauss, Ronald M and Wouter Jukema, J and Caulfield, Mark J} } @article {6220, title = {Predicting stroke through genetic risk functions: the CHARGE Risk Score Project.}, journal = {Stroke}, volume = {45}, year = {2014}, month = {2014 Feb}, pages = {403-12}, abstract = {

BACKGROUND AND PURPOSE: Beyond the Framingham Stroke Risk Score, prediction of future stroke may improve with a genetic risk score (GRS) based on single-nucleotide polymorphisms associated with stroke and its risk factors.

METHODS: The study includes 4 population-based cohorts with 2047 first incident strokes from 22,720 initially stroke-free European origin participants aged >=55 years, who were followed for up to 20 years. GRSs were constructed with 324 single-nucleotide polymorphisms implicated in stroke and 9 risk factors. The association of the GRS to first incident stroke was tested using Cox regression; the GRS predictive properties were assessed with area under the curve statistics comparing the GRS with age and sex, Framingham Stroke Risk Score models, and reclassification statistics. These analyses were performed per cohort and in a meta-analysis of pooled data. Replication was sought in a case-control study of ischemic stroke.

RESULTS: In the meta-analysis, adding the GRS to the Framingham Stroke Risk Score, age and sex model resulted in a significant improvement in discrimination (all stroke: Δjoint area under the curve=0.016, P=2.3{\texttimes}10(-6); ischemic stroke: Δjoint area under the curve=0.021, P=3.7{\texttimes}10(-7)), although the overall area under the curve remained low. In all the studies, there was a highly significantly improved net reclassification index (P<10(-4)).

CONCLUSIONS: The single-nucleotide polymorphisms associated with stroke and its risk factors result only in a small improvement in prediction of future stroke compared with the classical epidemiological risk factors for stroke.

}, keywords = {Age Factors, Aged, Aged, 80 and over, Area Under Curve, Case-Control Studies, Cohort Studies, European Continental Ancestry Group, Female, Genetic Predisposition to Disease, Genome-Wide Association Study, Genotype, Humans, Male, Middle Aged, Polymorphism, Single Nucleotide, Regression Analysis, Risk Factors, ROC Curve, Sex Factors, Stroke}, issn = {1524-4628}, doi = {10.1161/STROKEAHA.113.003044}, author = {Ibrahim-Verbaas, Carla A and Fornage, Myriam and Bis, Joshua C and Choi, Seung Hoan and Psaty, Bruce M and Meigs, James B and Rao, Madhu and Nalls, Mike and Fontes, Jo{\~a}o D and O{\textquoteright}Donnell, Christopher J and Kathiresan, Sekar and Ehret, Georg B and Fox, Caroline S and Malik, Rainer and Dichgans, Martin and Schmidt, Helena and Lahti, Jari and Heckbert, Susan R and Lumley, Thomas and Rice, Kenneth and Rotter, Jerome I and Taylor, Kent D and Folsom, Aaron R and Boerwinkle, Eric and Rosamond, Wayne D and Shahar, Eyal and Gottesman, Rebecca F and Koudstaal, Peter J and Amin, Najaf and Wieberdink, Renske G and Dehghan, Abbas and Hofman, Albert and Uitterlinden, Andr{\'e} G and DeStefano, Anita L and Debette, Stephanie and Xue, Luting and Beiser, Alexa and Wolf, Philip A and DeCarli, Charles and Ikram, M Arfan and Seshadri, Sudha and Mosley, Thomas H and Longstreth, W T and van Duijn, Cornelia M and Launer, Lenore J} } @article {6814, title = {Population genomic analysis of 962 whole genome sequences of humans reveals natural selection in non-coding regions.}, journal = {PLoS One}, volume = {10}, year = {2015}, month = {2015}, pages = {e0121644}, abstract = {

Whole genome analysis in large samples from a single population is needed to provide adequate power to assess relative strengths of natural selection across different functional components of the genome. In this study, we analyzed next-generation sequencing data from 962 European Americans, and found that as expected approximately 60\% of the top 1\% of positive selection signals lie in intergenic regions, 33\% in intronic regions, and slightly over 1\% in coding regions. Several detailed functional annotation categories in intergenic regions showed statistically significant enrichment in positively selected loci when compared to the null distribution of the genomic span of ENCODE categories. There was a significant enrichment of purifying selection signals detected in enhancers, transcription factor binding sites, microRNAs and target sites, but not on lincRNA or piRNAs, suggesting different evolutionary constraints for these domains. Loci in "repressed or low activity regions" and loci near or overlapping the transcription start site were the most significantly over-represented annotations among the top 1\% of signals for positive selection.

}, keywords = {DNA, Intergenic, Genetic Loci, Humans, Metagenomics, Open Reading Frames, Polymorphism, Single Nucleotide}, issn = {1932-6203}, doi = {10.1371/journal.pone.0121644}, author = {Yu, Fuli and Lu, Jian and Liu, Xiaoming and Gazave, Elodie and Chang, Diana and Raj, Srilakshmi and Hunter-Zinck, Haley and Blekhman, Ran and Arbiza, Leonardo and Van Hout, Cris and Morrison, Alanna and Johnson, Andrew D and Bis, Joshua and Cupples, L Adrienne and Psaty, Bruce M and Muzny, Donna and Yu, Jin and Gibbs, Richard A and Keinan, Alon and Clark, Andrew G and Boerwinkle, Eric} } @article {7139, title = {Platelet-Related Variants Identified by Exomechip Meta-analysis in 157,293 Individuals.}, journal = {Am J Hum Genet}, volume = {99}, year = {2016}, month = {2016 Jul 7}, pages = {40-55}, abstract = {

Platelet production, maintenance, and clearance are tightly controlled processes indicative of platelets{\textquoteright} important roles in hemostasis and thrombosis. Platelets are common targets for primary and secondary prevention of several conditions. They are monitored clinically by complete blood counts, specifically with measurements of platelet count (PLT) and mean platelet volume (MPV). Identifying genetic effects on PLT and MPV can provide mechanistic insights into platelet biology and their role in disease. Therefore, we formed the Blood Cell Consortium (BCX) to perform a large-scale meta-analysis of Exomechip association results for PLT and MPV in 157,293 and 57,617 individuals, respectively. Using the low-frequency/rare coding variant-enriched Exomechip genotyping array, we sought to identify genetic variants associated with PLT and MPV. In addition to confirming 47 known PLT and 20 known MPV associations, we identified 32 PLT and 18 MPV associations not previously observed in the literature across the allele frequency spectrum, including rare large effect (FCER1A), low-frequency (IQGAP2, MAP1A, LY75), and common (ZMIZ2, SMG6, PEAR1, ARFGAP3/PACSIN2) variants. Several variants associated with PLT/MPV (PEAR1, MRVI1, PTGES3) were also associated with platelet reactivity. In concurrent BCX analyses, there was overlap of platelet-associated variants with red (MAP1A, TMPRSS6, ZMIZ2) and white (PEAR1, ZMIZ2, LY75) blood cell traits, suggesting common regulatory pathways with shared genetic architecture among these hematopoietic lineages. Our large-scale Exomechip analyses identified previously undocumented associations with platelet traits and further indicate that several complex quantitative hematological, lipid, and cardiovascular traits share genetic factors.

}, issn = {1537-6605}, doi = {10.1016/j.ajhg.2016.05.005}, author = {Eicher, John D and Chami, Nathalie and Kacprowski, Tim and Nomura, Akihiro and Chen, Ming-Huei and Yanek, Lisa R and Tajuddin, Salman M and Schick, Ursula M and Slater, Andrew J and Pankratz, Nathan and Polfus, Linda and Schurmann, Claudia and Giri, Ayush and Brody, Jennifer A and Lange, Leslie A and Manichaikul, Ani and Hill, W David and Pazoki, Raha and Elliot, Paul and Evangelou, Evangelos and Tzoulaki, Ioanna and Gao, He and Vergnaud, Anne-Claire and Mathias, Rasika A and Becker, Diane M and Becker, Lewis C and Burt, Amber and Crosslin, David R and Lyytik{\"a}inen, Leo-Pekka and Nikus, Kjell and Hernesniemi, Jussi and K{\"a}h{\"o}nen, Mika and Raitoharju, Emma and Mononen, Nina and Raitakari, Olli T and Lehtim{\"a}ki, Terho and Cushman, Mary and Zakai, Neil A and Nickerson, Deborah A and Raffield, Laura M and Quarells, Rakale and Willer, Cristen J and Peloso, Gina M and Abecasis, Goncalo R and Liu, Dajiang J and Deloukas, Panos and Samani, Nilesh J and Schunkert, Heribert and Erdmann, Jeanette and Fornage, Myriam and Richard, Melissa and Tardif, Jean-Claude and Rioux, John D and Dub{\'e}, Marie-Pierre and de Denus, Simon and Lu, Yingchang and Bottinger, Erwin P and Loos, Ruth J F and Smith, Albert Vernon and Harris, Tamara B and Launer, Lenore J and Gudnason, Vilmundur and Velez Edwards, Digna R and Torstenson, Eric S and Liu, Yongmei and Tracy, Russell P and Rotter, Jerome I and Rich, Stephen S and Highland, Heather M and Boerwinkle, Eric and Li, Jin and Lange, Ethan and Wilson, James G and Mihailov, Evelin and M{\"a}gi, Reedik and Hirschhorn, Joel and Metspalu, Andres and Esko, T{\~o}nu and Vacchi-Suzzi, Caterina and Nalls, Mike A and Zonderman, Alan B and Evans, Michele K and Engstr{\"o}m, Gunnar and Orho-Melander, Marju and Melander, Olle and O{\textquoteright}Donoghue, Michelle L and Waterworth, Dawn M and Wallentin, Lars and White, Harvey D and Floyd, James S and Bartz, Traci M and Rice, Kenneth M and Psaty, Bruce M and Starr, J M and Liewald, David C M and Hayward, Caroline and Deary, Ian J and Greinacher, Andreas and V{\"o}lker, Uwe and Thiele, Thomas and V{\"o}lzke, Henry and van Rooij, Frank J A and Uitterlinden, Andr{\'e} G and Franco, Oscar H and Dehghan, Abbas and Edwards, Todd L and Ganesh, Santhi K and Kathiresan, Sekar and Faraday, Nauder and Auer, Paul L and Reiner, Alex P and Lettre, Guillaume and Johnson, Andrew D} } @article {8570, title = {A principal component meta-analysis on multiple anthropometric traits identifies novel loci for body shape.}, journal = {Nat Commun}, volume = {7}, year = {2016}, month = {2016 11 23}, pages = {13357}, abstract = {

Large consortia have revealed hundreds of genetic loci associated with anthropometric traits, one trait at a time. We examined whether genetic variants affect body shape as a composite phenotype that is represented by a combination of anthropometric traits. We developed an approach that calculates averaged PCs (AvPCs) representing body shape derived from six anthropometric traits (body mass index, height, weight, waist and hip circumference, waist-to-hip ratio). The first four AvPCs explain >99\% of the variability, are heritable, and associate with cardiometabolic outcomes. We performed genome-wide association analyses for each body shape composite phenotype across 65 studies and meta-analysed summary statistics. We identify six novel loci: LEMD2 and CD47 for AvPC1, RPS6KA5/C14orf159 and GANAB for AvPC3, and ARL15 and ANP32 for AvPC4. Our findings highlight the value of using multiple traits to define complex phenotypes for discovery, which are not captured by single-trait analyses, and may shed light onto new pathways.

}, keywords = {Anthropometry, Body Size, Genome-Wide Association Study, Genotype, Humans, Models, Genetic, Principal Component Analysis}, issn = {2041-1723}, doi = {10.1038/ncomms13357}, author = {Ried, Janina S and Jeff M, Janina and Chu, Audrey Y and Bragg-Gresham, Jennifer L and van Dongen, Jenny and Huffman, Jennifer E and Ahluwalia, Tarunveer S and Cadby, Gemma and Eklund, Niina and Eriksson, Joel and Esko, T{\~o}nu and Feitosa, Mary F and Goel, Anuj and Gorski, Mathias and Hayward, Caroline and Heard-Costa, Nancy L and Jackson, Anne U and Jokinen, Eero and Kanoni, Stavroula and Kristiansson, Kati and Kutalik, Zolt{\'a}n and Lahti, Jari and Luan, Jian{\textquoteright}an and M{\"a}gi, Reedik and Mahajan, Anubha and Mangino, Massimo and Medina-G{\'o}mez, Carolina and Monda, Keri L and Nolte, Ilja M and Perusse, Louis and Prokopenko, Inga and Qi, Lu and Rose, Lynda M and Salvi, Erika and Smith, Megan T and Snieder, Harold and Stan{\v c}{\'a}kov{\'a}, Alena and Ju Sung, Yun and Tachmazidou, Ioanna and Teumer, Alexander and Thorleifsson, Gudmar and van der Harst, Pim and Walker, Ryan W and Wang, Sophie R and Wild, Sarah H and Willems, Sara M and Wong, Andrew and Zhang, Weihua and Albrecht, Eva and Couto Alves, Alexessander and Bakker, Stephan J L and Barlassina, Cristina and Bartz, Traci M and Beilby, John and Bellis, Claire and Bergman, Richard N and Bergmann, Sven and Blangero, John and Bl{\"u}her, Matthias and Boerwinkle, Eric and Bonnycastle, Lori L and Bornstein, Stefan R and Bruinenberg, Marcel and Campbell, Harry and Chen, Yii-Der Ida and Chiang, Charleston W K and Chines, Peter S and Collins, Francis S and Cucca, Fracensco and Cupples, L Adrienne and D{\textquoteright}Avila, Francesca and de Geus, Eco J C and Dedoussis, George and Dimitriou, Maria and D{\"o}ring, Angela and Eriksson, Johan G and Farmaki, Aliki-Eleni and Farrall, Martin and Ferreira, Teresa and Fischer, Krista and Forouhi, Nita G and Friedrich, Nele and Gjesing, Anette Prior and Glorioso, Nicola and Graff, Mariaelisa and Grallert, Harald and Grarup, Niels and Gr{\"a}{\ss}ler, J{\"u}rgen and Grewal, Jagvir and Hamsten, Anders and Harder, Marie Neergaard and Hartman, Catharina A and Hassinen, Maija and Hastie, Nicholas and Hattersley, Andrew Tym and Havulinna, Aki S and Heli{\"o}vaara, Markku and Hillege, Hans and Hofman, Albert and Holmen, Oddgeir and Homuth, Georg and Hottenga, Jouke-Jan and Hui, Jennie and Husemoen, Lise Lotte and Hysi, Pirro G and Isaacs, Aaron and Ittermann, Till and Jalilzadeh, Shapour and James, Alan L and J{\o}rgensen, Torben and Jousilahti, Pekka and Jula, Antti and Marie Justesen, Johanne and Justice, Anne E and K{\"a}h{\"o}nen, Mika and Karaleftheri, Maria and Tee Khaw, Kay and Keinanen-Kiukaanniemi, Sirkka M and Kinnunen, Leena and Knekt, Paul B and Koistinen, Heikki A and Kolcic, Ivana and Kooner, Ishminder K and Koskinen, Seppo and Kovacs, Peter and Kyriakou, Theodosios and Laitinen, Tomi and Langenberg, Claudia and Lewin, Alexandra M and Lichtner, Peter and Lindgren, Cecilia M and Lindstr{\"o}m, Jaana and Linneberg, Allan and Lorbeer, Roberto and Lorentzon, Mattias and Luben, Robert and Lyssenko, Valeriya and M{\"a}nnist{\"o}, Satu and Manunta, Paolo and Leach, Irene Mateo and McArdle, Wendy L and McKnight, Barbara and Mohlke, Karen L and Mihailov, Evelin and Milani, Lili and Mills, Rebecca and Montasser, May E and Morris, Andrew P and M{\"u}ller, Gabriele and Musk, Arthur W and Narisu, Narisu and Ong, Ken K and Oostra, Ben A and Osmond, Clive and Palotie, Aarno and Pankow, James S and Paternoster, Lavinia and Penninx, Brenda W and Pichler, Irene and Pilia, Maria G and Polasek, Ozren and Pramstaller, Peter P and Raitakari, Olli T and Rankinen, Tuomo and Rao, D C and Rayner, Nigel W and Ribel-Madsen, Rasmus and Rice, Treva K and Richards, Marcus and Ridker, Paul M and Rivadeneira, Fernando and Ryan, Kathy A and Sanna, Serena and Sarzynski, Mark A and Scholtens, Salome and Scott, Robert A and Sebert, Sylvain and Southam, Lorraine and Spars{\o}, Thomas Hempel and Steinthorsdottir, Valgerdur and Stirrups, Kathleen and Stolk, Ronald P and Strauch, Konstantin and Stringham, Heather M and Swertz, Morris A and Swift, Amy J and T{\"o}njes, Anke and Tsafantakis, Emmanouil and van der Most, Peter J and van Vliet-Ostaptchouk, Jana V and Vandenput, Liesbeth and Vartiainen, Erkki and Venturini, Cristina and Verweij, Niek and Viikari, Jorma S and Vitart, Veronique and Vohl, Marie-Claude and Vonk, Judith M and Waeber, G{\'e}rard and Widen, Elisabeth and Willemsen, Gonneke and Wilsgaard, Tom and Winkler, Thomas W and Wright, Alan F and Yerges-Armstrong, Laura M and Hua Zhao, Jing and Zillikens, M Carola and Boomsma, Dorret I and Bouchard, Claude and Chambers, John C and Chasman, Daniel I and Cusi, Daniele and Gansevoort, Ron T and Gieger, Christian and Hansen, Torben and Hicks, Andrew A and Hu, Frank and Hveem, Kristian and Jarvelin, Marjo-Riitta and Kajantie, Eero and Kooner, Jaspal S and Kuh, Diana and Kuusisto, Johanna and Laakso, Markku and Lakka, Timo A and Lehtim{\"a}ki, Terho and Metspalu, Andres and Nj{\o}lstad, Inger and Ohlsson, Claes and Oldehinkel, Albertine J and Palmer, Lyle J and Pedersen, Oluf and Perola, Markus and Peters, Annette and Psaty, Bruce M and Puolijoki, Hannu and Rauramaa, Rainer and Rudan, Igor and Salomaa, Veikko and Schwarz, Peter E H and Shudiner, Alan R and Smit, Jan H and S{\o}rensen, Thorkild I A and Spector, Timothy D and Stefansson, Kari and Stumvoll, Michael and Tremblay, Angelo and Tuomilehto, Jaakko and Uitterlinden, Andr{\'e} G and Uusitupa, Matti and V{\"o}lker, Uwe and Vollenweider, Peter and Wareham, Nicholas J and Watkins, Hugh and Wilson, James F and Zeggini, Eleftheria and Abecasis, Goncalo R and Boehnke, Michael and Borecki, Ingrid B and Deloukas, Panos and van Duijn, Cornelia M and Fox, Caroline and Groop, Leif C and Heid, Iris M and Hunter, David J and Kaplan, Robert C and McCarthy, Mark I and North, Kari E and O{\textquoteright}Connell, Jeffrey R and Schlessinger, David and Thorsteinsdottir, Unnur and Strachan, David P and Frayling, Timothy and Hirschhorn, Joel N and M{\"u}ller-Nurasyid, Martina and Loos, Ruth J F} } @article {7815, title = {PR interval genome-wide association meta-analysis identifies 50 loci associated with atrial and atrioventricular electrical activity.}, journal = {Nat Commun}, volume = {9}, year = {2018}, month = {2018 Jul 25}, pages = {2904}, abstract = {

Electrocardiographic PR interval measures atrio-ventricular depolarization and conduction, and abnormal PR interval is a risk factor for atrial fibrillation and heart block. Our genome-wide association study of over 92,000 European-descent individuals identifies 44 PR interval loci (34 novel). Examination of these loci reveals known and previously not-yet-reported biological processes involved in cardiac atrial electrical activity. Genes in these loci are over-represented in cardiac disease processes including heart block and atrial fibrillation. Variants in over half of the 44 loci were associated with atrial or blood transcript expression levels, or were in high linkage disequilibrium with missense variants. Six additional loci were identified either by meta-analysis of ~105,000 African and European-descent individuals and/or by pleiotropic analyses combining PR interval with heart rate, QRS interval, and atrial fibrillation. These findings implicate developmental pathways, and identify transcription factors, ion-channel genes, and cell-junction/cell-signaling proteins in atrio-ventricular conduction, identifying potential targets for drug development.

}, issn = {2041-1723}, doi = {10.1038/s41467-018-04766-9}, author = {van Setten, Jessica and Brody, Jennifer A and Jamshidi, Yalda and Swenson, Brenton R and Butler, Anne M and Campbell, Harry and Del Greco, Fabiola M and Evans, Daniel S and Gibson, Quince and Gudbjartsson, Daniel F and Kerr, Kathleen F and Krijthe, Bouwe P and Lyytik{\"a}inen, Leo-Pekka and M{\"u}ller, Christian and M{\"u}ller-Nurasyid, Martina and Nolte, Ilja M and Padmanabhan, Sandosh and Ritchie, Marylyn D and Robino, Antonietta and Smith, Albert V and Steri, Maristella and Tanaka, Toshiko and Teumer, Alexander and Trompet, Stella and Ulivi, Sheila and Verweij, Niek and Yin, Xiaoyan and Arnar, David O and Asselbergs, Folkert W and Bader, Joel S and Barnard, John and Bis, Josh and Blankenberg, Stefan and Boerwinkle, Eric and Bradford, Yuki and Buckley, Brendan M and Chung, Mina K and Crawford, Dana and den Hoed, Marcel and Denny, Josh C and Dominiczak, Anna F and Ehret, Georg B and Eijgelsheim, Mark and Ellinor, Patrick T and Felix, Stephan B and Franco, Oscar H and Franke, Lude and Harris, Tamara B and Holm, Hilma and Ilaria, Gandin and Iorio, Annamaria and K{\"a}h{\"o}nen, Mika and Kolcic, Ivana and Kors, Jan A and Lakatta, Edward G and Launer, Lenore J and Lin, Honghuang and Lin, Henry J and Loos, Ruth J F and Lubitz, Steven A and Macfarlane, Peter W and Magnani, Jared W and Leach, Irene Mateo and Meitinger, Thomas and Mitchell, Braxton D and M{\"u}nzel, Thomas and Papanicolaou, George J and Peters, Annette and Pfeufer, Arne and Pramstaller, Peter P and Raitakari, Olli T and Rotter, Jerome I and Rudan, Igor and Samani, Nilesh J and Schlessinger, David and Silva Aldana, Claudia T and Sinner, Moritz F and Smith, Jonathan D and Snieder, Harold and Soliman, Elsayed Z and Spector, Timothy D and Stott, David J and Strauch, Konstantin and Tarasov, Kirill V and Thorsteinsdottir, Unnur and Uitterlinden, Andr{\'e} G and Van Wagoner, David R and V{\"o}lker, Uwe and V{\"o}lzke, Henry and Waldenberger, Melanie and Jan Westra, Harm and Wild, Philipp S and Zeller, Tanja and Alonso, Alvaro and Avery, Christy L and Bandinelli, Stefania and Benjamin, Emelia J and Cucca, Francesco and D{\"o}rr, Marcus and Ferrucci, Luigi and Gasparini, Paolo and Gudnason, Vilmundur and Hayward, Caroline and Heckbert, Susan R and Hicks, Andrew A and Jukema, J Wouter and K{\"a}{\"a}b, Stefan and Lehtim{\"a}ki, Terho and Liu, Yongmei and Munroe, Patricia B and Parsa, Afshin and Polasek, Ozren and Psaty, Bruce M and Roden, Dan M and Schnabel, Renate B and Sinagra, Gianfranco and Stefansson, Kari and Stricker, Bruno H and van der Harst, Pim and van Duijn, Cornelia M and Wilson, James F and Gharib, Sina A and de Bakker, Paul I W and Isaacs, Aaron and Arking, Dan E and Sotoodehnia, Nona} } @article {8102, title = {Pharmacogenomics of statin-related myopathy: Meta-analysis of rare variants from whole-exome sequencing.}, journal = {PLoS One}, volume = {14}, year = {2019}, month = {2019}, pages = {e0218115}, abstract = {

AIMS: Statin-related myopathy (SRM), which includes rhabdomyolysis, is an uncommon but important adverse drug reaction because the number of people prescribed statins world-wide is large. Previous association studies of common genetic variants have had limited success in identifying a genetic basis for this adverse drug reaction. We conducted a multi-site whole-exome sequencing study to investigate whether rare coding variants confer an increased risk of SRM.

METHODS AND RESULTS: SRM 3-5 cases (N = 505) and statin treatment-tolerant controls (N = 2047) were recruited from multiple sites in North America and Europe. SRM 3-5 was defined as symptoms consistent with muscle injury and an elevated creatine phosphokinase level >4 times upper limit of normal without another likely cause of muscle injury. Whole-exome sequencing and variant calling was coordinated from two analysis centres, and results of single-variant and gene-based burden tests were meta-analysed. No genome-wide significant associations were identified. Given the large number of cases, we had 80\% power to identify a variant with minor allele frequency of 0.01 that increases the risk of SRM 6-fold at genome-wide significance.

CONCLUSIONS: In this large whole-exome sequencing study of severe statin-related muscle injury conducted to date, we did not find evidence that rare coding variants are responsible for this adverse drug reaction. Larger sample sizes would be required to identify rare variants with small effects, but it is unclear whether such findings would be clinically actionable.

}, issn = {1932-6203}, doi = {10.1371/journal.pone.0218115}, author = {Floyd, James S and Bloch, Katarzyna M and Brody, Jennifer A and Maroteau, Cyrielle and Siddiqui, Moneeza K and Gregory, Richard and Carr, Daniel F and Molokhia, Mariam and Liu, Xiaoming and Bis, Joshua C and Ahmed, Ammar and Liu, Xuan and Hallberg, P{\"a}r and Yue, Qun-Ying and Magnusson, Patrik K E and Brisson, Diane and Wiggins, Kerri L and Morrison, Alanna C and Khoury, Etienne and McKeigue, Paul and Stricker, Bruno H and Lapeyre-Mestre, Maryse and Heckbert, Susan R and Gallagher, Arlene M and Chinoy, Hector and Gibbs, Richard A and Bondon-Guitton, Emmanuelle and Tracy, Russell and Boerwinkle, Eric and Gaudet, Daniel and Conforti, Anita and van Staa, Tjeerd and Sitlani, Colleen M and Rice, Kenneth M and Maitland-van der Zee, Anke-Hilse and Wadelius, Mia and Morris, Andrew P and Pirmohamed, Munir and Palmer, Colin A N and Psaty, Bruce M and Alfirevic, Ana} } @article {9239, title = {Powerful, scalable and resource-efficient meta-analysis of rare variant associations in large whole genome sequencing studies.}, journal = {Nat Genet}, volume = {55}, year = {2023}, month = {2023 Jan}, pages = {154-164}, abstract = {

Meta-analysis of whole genome sequencing/whole exome sequencing (WGS/WES) studies provides an attractive solution to the problem of collecting large sample sizes for discovering rare variants associated with complex phenotypes. Existing rare variant meta-analysis approaches are not scalable to biobank-scale WGS data. Here we present MetaSTAAR, a powerful and resource-efficient rare variant meta-analysis framework for large-scale WGS/WES studies. MetaSTAAR accounts for relatedness and population structure, can analyze both quantitative and dichotomous traits and boosts the power of rare variant tests by incorporating multiple variant functional annotations. Through meta-analysis of four lipid traits in 30,138 ancestrally diverse samples from 14 studies of the Trans Omics for Precision Medicine (TOPMed) Program, we show that MetaSTAAR performs rare variant meta-analysis at scale and produces results comparable to using pooled data. Additionally, we identified several conditionally significant rare variant associations with lipid traits. We further demonstrate that MetaSTAAR is scalable to biobank-scale cohorts through meta-analysis of TOPMed WGS data and UK Biobank WES data of ~200,000 samples.

}, keywords = {Exome Sequencing, Genome-Wide Association Study, Lipids, Phenotype, Whole Genome Sequencing}, issn = {1546-1718}, doi = {10.1038/s41588-022-01225-6}, author = {Li, Xihao and Quick, Corbin and Zhou, Hufeng and Gaynor, Sheila M and Liu, Yaowu and Chen, Han and Selvaraj, Margaret Sunitha and Sun, Ryan and Dey, Rounak and Arnett, Donna K and Bielak, Lawrence F and Bis, Joshua C and Blangero, John and Boerwinkle, Eric and Bowden, Donald W and Brody, Jennifer A and Cade, Brian E and Correa, Adolfo and Cupples, L Adrienne and Curran, Joanne E and de Vries, Paul S and Duggirala, Ravindranath and Freedman, Barry I and G{\"o}ring, Harald H H and Guo, Xiuqing and Haessler, Jeffrey and Kalyani, Rita R and Kooperberg, Charles and Kral, Brian G and Lange, Leslie A and Manichaikul, Ani and Martin, Lisa W and McGarvey, Stephen T and Mitchell, Braxton D and Montasser, May E and Morrison, Alanna C and Naseri, Take and O{\textquoteright}Connell, Jeffrey R and Palmer, Nicholette D and Peyser, Patricia A and Psaty, Bruce M and Raffield, Laura M and Redline, Susan and Reiner, Alexander P and Reupena, Muagututi{\textquoteright}a Sefuiva and Rice, Kenneth M and Rich, Stephen S and Sitlani, Colleen M and Smith, Jennifer A and Taylor, Kent D and Vasan, Ramachandran S and Willer, Cristen J and Wilson, James G and Yanek, Lisa R and Zhao, Wei and Rotter, Jerome I and Natarajan, Pradeep and Peloso, Gina M and Li, Zilin and Lin, Xihong} } @article {9573, title = {A polygenic risk score of atrial fibrillation improves prediction of lifetime risk for heart failure.}, journal = {ESC Heart Fail}, year = {2024}, month = {2024 Jan 22}, abstract = {

AIMS: Heart failure (HF) has shared genetic architecture with its risk factors: atrial fibrillation (AF), body mass index (BMI), coronary heart disease (CHD), systolic blood pressure (SBP), and type 2 diabetes (T2D). We aim to assess the association and risk prediction performance of risk-factor polygenic risk scores (PRSs) for incident HF and its subtypes in bi-racial populations.

METHODS AND RESULTS: Five PRSs were constructed for AF, BMI, CHD, SBP, and T2D in White participants of the Atherosclerosis Risk in Communities (ARIC) study. The associations between PRSs and incident HF and its subtypes were assessed using Cox models, and the risk prediction performance of PRSs was assessed using C statistics. Replication was performed in the ARIC study Black and Cardiovascular Health Study (CHS) White participants. In 8624 ARIC study Whites, 1922 (31\% cumulative incidence) HF cases developed over 30~years of follow-up. PRSs of AF, BMI, and CHD were associated with incident HF (P~<~0.001), where PRS showed the strongest association [hazard ratio (HR): 1.47, 95\% confidence interval (CI): 1.41-1.53]. Only the addition of PRS to the ARIC study HF risk equation improved C statistics for 10~year risk prediction from 0.812 to 0.829 (∆C: 0.017, 95\% CI: 0.009-0.026). The PRS was associated with both incident HF with reduced ejection fraction (HR: 1.43, 95\% CI: 1.27-1.60) and incident HF with preserved ejection fraction (HR: 1.46, 95\% CI: 1.33-1.62). The associations between PRS and incident HF and its subtypes, as well as the improved risk prediction, were replicated in the ARIC study Blacks and the CHS Whites (P~<~0.050). Protein analyses revealed that N-terminal pro-brain natriuretic peptide and other 98 proteins were associated with PRS .

CONCLUSIONS: The PRS was associated with incident HF and its subtypes and had significant incremental value over an established HF risk prediction equation.

}, issn = {2055-5822}, doi = {10.1002/ehf2.14665}, author = {Alkis, Taryn and Luo, Xi and Wall, Katherine and Brody, Jennifer and Bartz, Traci and Chang, Patricia P and Norby, Faye L and Hoogeveen, Ron C and Morrison, Alanna C and Ballantyne, Christie M and Coresh, Josef and Boerwinkle, Eric and Psaty, Bruce M and Shah, Amil M and Yu, Bing} }