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1. Identification and functional characterization of G6PC2 coding variants influencing glycemic traits define an effector transcript at the G6PC2-ABCB11 locus.

Author

Anubha Mahajan, Xueling Sim, Hui Jin Ng, Alisa Manning, Manuel A Rivas, Heather M Highland, Adam E Locke, Niels Grarup, Hae Kyung Im, Pablo Cingolani, Jason Flannick, Pierre Fontanillas, Christian Fuchsberger, Kyle J Gaulton, Tanya M Teslovich, N William Rayner, Neil R Robertson, Nicola L Beer, Jana K Rundle, Jette Bork-Jensen, Claes Ladenvall, Christine Blancher, David Buck, Gemma Buck, Noël P Burtt, Stacey Gabriel, Anette P Gjesing, Christopher J Groves, Mette Hollensted, Jeroen R Huyghe, Anne U Jackson, Goo Jun, Johanne Marie Justesen, Massimo Mangino, Jacquelyn Murphy, Matt Neville, Robert Onofrio, Kerrin S Small, Heather M Stringham, Ann-Christine Syvänen, Joseph Trakalo, Goncalo Abecasis, Graeme I Bell, John Blangero, Nancy J Cox, Ravindranath Duggirala, Craig L Hanis, Mark Seielstad, James G Wilson, Cramer Christensen, Ivan Brandslund, Rainer Rauramaa, Gabriela L Surdulescu, Alex S F Doney, Lars Lannfelt, Allan Linneberg, Bo Isomaa, Tiinamaija Tuomi, Marit E Jørgensen, Torben Jørgensen, Johanna Kuusisto, Matti Uusitupa, Veikko Salomaa, Timothy D Spector, Andrew D Morris, Colin N A Palmer, Francis S Collins, Karen L Mohlke, Richard N Bergman, Erik Ingelsson, Lars Lind, Jaakko Tuomilehto, Torben Hansen, Richard M Watanabe, Inga Prokopenko, Josee Dupuis, Fredrik Karpe, Leif Groop, Markku Laakso, Oluf Pedersen, Jose C Florez, Andrew P Morris, David Altshuler, James B Meigs, Michael Boehnke, Mark I McCarthy, Cecilia M Lindgren, Anna L Gloyn, and T2D-GENES consortium and GoT2D consortium

Subjects
Genetics, QH426-470
Abstract

Genome wide association studies (GWAS) for fasting glucose (FG) and insulin (FI) have identified common variant signals which explain 4.8% and 1.2% of trait variance, respectively. It is hypothesized that low-frequency and rare variants could contribute substantially to unexplained genetic variance. To test this, we analyzed exome-array data from up to 33,231 non-diabetic individuals of European ancestry. We found exome-wide significant (P

Published
2015
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2. Novel mutations in the gene encoding ATP-binding cassette 1 in four Tangier disease kindreds

Author

Margaret E. Brousseau, Ernst J. Schaefer, Josee Dupuis, Brenda Eustace, Paul Van Eerdewegh, Allison L. Goldkamp, Lisa M. Thurston, Michael G. FitzGerald, Diane Yasek-McKenna, Gilmore O'Neill, Gretchen P. Eberhart, Barbara Weiffenbach, Jose M. Ordovas, Mason W. Freeman, Robert H. Brown, Jr., and Jessie Z. Gu

Subjects
ATP-binding cassette, apolipoprotein, cholesterol, high density lipoprotein, Tangier disease, Biochemistry, QD415-436
Abstract

Abstract: Tangier disease (TD) is an autosomal co-dominant disorder in which homozygotes have a marked deficiency of high density lipoprotein (HDL) cholesterol and, in some cases, peripheral neuropathy and premature coronary heart disease (CHD). Homozygotes are further characterized by cholesteryl ester deposition in various tissues throughout the body, most notably in those of the reticuloendothelial system. Several studies have demonstrated that the excess lipid deposition in TD is due to defective apolipoprotein-mediated efflux of cellular cholesterol and phospholipids. Although much progress has been made in our understanding of the metabolic basis of TD, the precise molecular defect had remained elusive until very recently. By positional cloning methods, we: 1) confirm the assignment of TD to chromosome 9q31, 2) provide evidence that human ATP-binding cassette-1 (hABC-1) maps to a 250 kb region on 9q31, and 3) describe novel deletion, insertion, and missense mutations in the gene encoding hABC-1 in four unrelated TD kindreds. These results establish a causal role for mutations in hABC-1 in TD and indicate that this transporter has a critical function in the regulation of intracellular lipid trafficking that dramatically affects plasma HDL cholesterol levels. —Brousseau, M. E., E. J. Schaefer, J. Dupuis, B. Eustace, P. Van Eerdewegh, A. L. Goldkamp, L. M. Thurston, M. G. FitzGerald, D. Yasek-McKenna, G. O'Neill, G. P. Eberhart, B. Weiffenbach, J. M. Ordovas, M. W. Freeman, R. H. Brown, Jr., and J. Z. Gu. Novel mutations in the gene encoding ATP-binding cassette 1 in four Tangier disease kindreds. J. Lipid Res. 2000. 41: 433–441.

Published
2000
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3. Novel loci for adiponectin levels and their influence on type 2 diabetes and metabolic traits: a multi-ethnic meta-analysis of 45,891 individuals.

Author

Zari Dastani, Marie-France Hivert, Nicholas Timpson, John R B Perry, Xin Yuan, Robert A Scott, Peter Henneman, Iris M Heid, Jorge R Kizer, Leo-Pekka Lyytikäinen, Christian Fuchsberger, Toshiko Tanaka, Andrew P Morris, Kerrin Small, Aaron Isaacs, Marian Beekman, Stefan Coassin, Kurt Lohman, Lu Qi, Stavroula Kanoni, James S Pankow, Hae-Won Uh, Ying Wu, Aurelian Bidulescu, Laura J Rasmussen-Torvik, Celia M T Greenwood, Martin Ladouceur, Jonna Grimsby, Alisa K Manning, Ching-Ti Liu, Jaspal Kooner, Vincent E Mooser, Peter Vollenweider, Karen A Kapur, John Chambers, Nicholas J Wareham, Claudia Langenberg, Rune Frants, Ko Willems-Vandijk, Ben A Oostra, Sara M Willems, Claudia Lamina, Thomas W Winkler, Bruce M Psaty, Russell P Tracy, Jennifer Brody, Ida Chen, Jorma Viikari, Mika Kähönen, Peter P Pramstaller, David M Evans, Beate St Pourcain, Naveed Sattar, Andrew R Wood, Stefania Bandinelli, Olga D Carlson, Josephine M Egan, Stefan Böhringer, Diana van Heemst, Lyudmyla Kedenko, Kati Kristiansson, Marja-Liisa Nuotio, Britt-Marie Loo, Tamara Harris, Melissa Garcia, Alka Kanaya, Margot Haun, Norman Klopp, H-Erich Wichmann, Panos Deloukas, Efi Katsareli, David J Couper, Bruce B Duncan, Margreet Kloppenburg, Linda S Adair, Judith B Borja, DIAGRAM+ Consortium, MAGIC Consortium, GLGC Investigators, MuTHER Consortium, James G Wilson, Solomon Musani, Xiuqing Guo, Toby Johnson, Robert Semple, Tanya M Teslovich, Matthew A Allison, Susan Redline, Sarah G Buxbaum, Karen L Mohlke, Ingrid Meulenbelt, Christie M Ballantyne, George V Dedoussis, Frank B Hu, Yongmei Liu, Bernhard Paulweber, Timothy D Spector, P Eline Slagboom, Luigi Ferrucci, Antti Jula, Markus Perola, Olli Raitakari, Jose C Florez, Veikko Salomaa, Johan G Eriksson, Timothy M Frayling, Andrew A Hicks, Terho Lehtimäki, George Davey Smith, David S Siscovick, Florian Kronenberg, Cornelia van Duijn, Ruth J F Loos, Dawn M Waterworth, James B Meigs, Josee Dupuis, J Brent Richards, Benjamin F Voight, Laura J Scott, Valgerdur Steinthorsdottir, Christian Dina, Ryan P Welch, Eleftheria Zeggini, Cornelia Huth, Yurii S Aulchenko, Gudmar Thorleifsson, Laura J McCulloch, Teresa Ferreira, Harald Grallert, Najaf Amin, Guanming Wu, Cristen J Willer, Soumya Raychaudhuri, Steve A McCarroll, Oliver M Hofmann, Ayellet V Segrè, Mandy van Hoek, Pau Navarro, Kristin Ardlie, Beverley Balkau, Rafn Benediktsson, Amanda J Bennett, Roza Blagieva, Eric Boerwinkle, Lori L Bonnycastle, Kristina Bengtsson Boström, Bert Bravenboer, Suzannah Bumpstead, Noël P Burtt, Guillaume Charpentier, Peter S Chines, Marilyn Cornelis, Gabe Crawford, Alex S F Doney, Katherine S Elliott, Amanda L Elliott, Michael R Erdos, Caroline S Fox, Christopher S Franklin, Martha Ganser, Christian Gieger, Niels Grarup, Todd Green, Simon Griffin, Christopher J Groves, Candace Guiducci, Samy Hadjadj, Neelam Hassanali, Christian Herder, Bo Isomaa, Anne U Jackson, Paul R V Johnson, Torben Jørgensen, Wen H L Kao, Augustine Kong, Peter Kraft, Johanna Kuusisto, Torsten Lauritzen, Man Li, Aloysius Lieverse, Cecilia M Lindgren, Valeriya Lyssenko, Michel Marre, Thomas Meitinger, Kristian Midthjell, Mario A Morken, Narisu Narisu, Peter Nilsson, Katharine R Owen, Felicity Payne, Ann-Kristin Petersen, Carl Platou, Christine Proença, Inga Prokopenko, Wolfgang Rathmann, N William Rayner, Neil R Robertson, Ghislain Rocheleau, Michael Roden, Michael J Sampson, Richa Saxena, Beverley M Shields, Peter Shrader, Gunnar Sigurdsson, Thomas Sparsø, Klaus Strassburger, Heather M Stringham, Qi Sun, Amy J Swift, Barbara Thorand, Jean Tichet, Tiinamaija Tuomi, Rob M van Dam, Timon W van Haeften, Thijs van Herpt, Jana V van Vliet-Ostaptchouk, G Bragi Walters, Michael N Weedon, Cisca Wijmenga, Jacqueline Witteman, Richard N Bergman, Stephane Cauchi, Francis S Collins, Anna L Gloyn, Ulf Gyllensten, Torben Hansen, Winston A Hide, Graham A Hitman, Albert Hofman, David J Hunter, Kristian Hveem, Markku Laakso, Andrew D Morris, Colin N A Palmer, Igor Rudan, Eric Sijbrands, Lincoln D Stein, Jaakko Tuomilehto, Andre Uitterlinden, Mark Walker, Richard M Watanabe, Goncalo R Abecasis, Bernhard O Boehm, Harry Campbell, Mark J Daly, Andrew T Hattersley, Oluf Pedersen, Inês Barroso, Leif Groop, Rob Sladek, Unnur Thorsteinsdottir, James F Wilson, Thomas Illig, Philippe Froguel, Cornelia M van Duijn, Kari Stefansson, David Altshuler, Michael Boehnke, Mark I McCarthy, Nicole Soranzo, Eleanor Wheeler, Nicole L Glazer, Nabila Bouatia-Naji, Reedik Mägi, Joshua Randall, Paul Elliott, Denis Rybin, Abbas Dehghan, Jouke Jan Hottenga, Kijoung Song, Anuj Goel, Taina Lajunen, Alex Doney, Christine Cavalcanti-Proença, Meena Kumari, Nicholas J Timpson, Carina Zabena, Erik Ingelsson, Ping An, Jeffrey O'Connell, Jian'an Luan, Amanda Elliott, Steven A McCarroll, Rosa Maria Roccasecca, François Pattou, Praveen Sethupathy, Yavuz Ariyurek, Philip Barter, John P Beilby, Yoav Ben-Shlomo, Sven Bergmann, Murielle Bochud, Amélie Bonnefond, Knut Borch-Johnsen, Yvonne Böttcher, Eric Brunner, Suzannah J Bumpstead, Yii-Der Ida Chen, Peter Chines, Robert Clarke, Lachlan J M Coin, Matthew N Cooper, Laura Crisponi, Ian N M Day, Eco J C de Geus, Jerome Delplanque, Annette C Fedson, Antje Fischer-Rosinsky, Nita G Forouhi, Maria Grazia Franzosi, Pilar Galan, Mark O Goodarzi, Jürgen Graessler, Scott Grundy, Rhian Gwilliam, Göran Hallmans, Naomi Hammond, Xijing Han, Anna-Liisa Hartikainen, Caroline Hayward, Simon C Heath, Serge Hercberg, David R Hillman, Aroon D Hingorani, Jennie Hui, Joe Hung, Marika Kaakinen, Jaakko Kaprio, Y Antero Kesaniemi, Mika Kivimaki, Beatrice Knight, Seppo Koskinen, Peter Kovacs, Kirsten Ohm Kyvik, G Mark Lathrop, Debbie A Lawlor, Olivier Le Bacquer, Cécile Lecoeur, Yun Li, Robert Mahley, Massimo Mangino, María Teresa Martínez-Larrad, Jarred B McAteer, Ruth McPherson, Christa Meisinger, David Melzer, David Meyre, Braxton D Mitchell, Sutapa Mukherjee, Silvia Naitza, Matthew J Neville, Marco Orrù, Ruth Pakyz, Giuseppe Paolisso, Cristian Pattaro, Daniel Pearson, John F Peden, Nancy L Pedersen, Andreas F H Pfeiffer, Irene Pichler, Ozren Polasek, Danielle Posthuma, Simon C Potter, Anneli Pouta, Michael A Province, Nigel W Rayner, Kenneth Rice, Samuli Ripatti, Fernando Rivadeneira, Olov Rolandsson, Annelli Sandbaek, Manjinder Sandhu, Serena Sanna, Avan Aihie Sayer, Paul Scheet, Udo Seedorf, Stephen J Sharp, Beverley Shields, Gunnar Sigurðsson, Eric J G Sijbrands, Angela Silveira, Laila Simpson, Andrew Singleton, Nicholas L Smith, Ulla Sovio, Amy Swift, Holly Syddall, Ann-Christine Syvänen, Anke Tönjes, André G Uitterlinden, Ko Willems van Dijk, Dhiraj Varma, Sophie Visvikis-Siest, Veronique Vitart, Nicole Vogelzangs, Gérard Waeber, Peter J Wagner, Andrew Walley, Kim L Ward, Hugh Watkins, Sarah H Wild, Gonneke Willemsen, Jaqueline C M Witteman, John W G Yarnell, Diana Zelenika, Björn Zethelius, Guangju Zhai, Jing Hua Zhao, M Carola Zillikens, DIAGRAM Consortium, GIANT Consortium, Global B Pgen Consortium, Ingrid B Borecki, Pierre Meneton, Patrik K E Magnusson, David M Nathan, Gordon H Williams, Kaisa Silander, Stefan R Bornstein, Peter Schwarz, Joachim Spranger, Fredrik Karpe, Alan R Shuldiner, Cyrus Cooper, Manuel Serrano-Ríos, Lars Lind, Lyle J Palmer, Paul W Franks, Shah Ebrahim, Michael Marmot, W H Linda Kao, Peter Paul Pramstaller, Alan F Wright, Michael Stumvoll, Anders Hamsten, Procardis Consortium, Thomas A Buchanan, Timo T Valle, Jerome I Rotter, Brenda W J H Penninx, Dorret I Boomsma, Antonio Cao, Angelo Scuteri, David Schlessinger, Manuela Uda, Aimo Ruokonen, Marjo-Riitta Jarvelin, Leena Peltonen, Vincent Mooser, Robert Sladek, MAGIC investigators, GLGC Consortium, Kiran Musunuru, Albert V Smith, Andrew C Edmondson, Ioannis M Stylianou, Masahiro Koseki, James P Pirruccello, Daniel I Chasman, Christopher T Johansen, Sigrid W Fouchier, Gina M Peloso, Maja Barbalic, Sally L Ricketts, Joshua C Bis, Mary F Feitosa, Marju Orho-Melander, Olle Melander, Xiaohui Li, Mingyao Li, Yoon Shin Cho, Min Jin Go, Young Jin Kim, Jong-Young Lee, Taesung Park, Kyunga Kim, Xueling Sim, Rick Twee-Hee Ong, Damien C Croteau-Chonka, Leslie A Lange, Joshua D Smith, Andreas Ziegler, Weihua Zhang, Robert Y L Zee, John B Whitfield, John R Thompson, Ida Surakka, Tim D Spector, Johannes H Smit, Juha Sinisalo, James Scott, Juha Saharinen, Chiara Sabatti, Lynda M Rose, Robert Roberts, Mark Rieder, Alex N Parker, Guillaume Pare, Christopher J O'Donnell, Markku S Nieminen, Deborah A Nickerson, Grant W Montgomery, Wendy McArdle, David Masson, Nicholas G Martin, Fabio Marroni, Gavin Lucas, Robert Luben, Marja-Liisa Lokki, Guillaume Lettre, Lenore J Launer, Edward G Lakatta, Reijo Laaksonen, Kirsten O Kyvik, Inke R König, Kay-Tee Khaw, Lee M Kaplan, Åsa Johansson, A Cecile J W Janssens, Wilmar Igl, G Kees Hovingh, Christian Hengstenberg, Aki S Havulinna, Nicholas D Hastie, Tamara B Harris, Talin Haritunians, Alistair S Hall, Leif C Groop, Elena Gonzalez, Nelson B Freimer, Jeanette Erdmann, Kenechi G Ejebe, Angela Döring, Anna F Dominiczak, Serkalem Demissie, Panagiotis Deloukas, Ulf de Faire, Gabriel Crawford, Yii-der I Chen, Mark J Caulfield, S Matthijs Boekholdt, Themistocles L Assimes, Thomas Quertermous, Mark Seielstad, Tien Y Wong, E-Shyong Tai, Alan B Feranil, Christopher W Kuzawa, Herman A Taylor, Stacey B Gabriel, Hilma Holm, Vilmundur Gudnason, Ronald M Krauss, Jose M Ordovas, Patricia B Munroe, Jaspal S Kooner, Alan R Tall, Robert A Hegele, John J P Kastelein, Eric E Schadt, David P Strachan, Muredach P Reilly, Nilesh J Samani, Heribert Schunkert, L Adrienne Cupples, Manjinder S Sandhu, Paul M Ridker, Daniel J Rader, and Sekar Kathiresan

Subjects
Genetics, QH426-470
Abstract

Circulating levels of adiponectin, a hormone produced predominantly by adipocytes, are highly heritable and are inversely associated with type 2 diabetes mellitus (T2D) and other metabolic traits. We conducted a meta-analysis of genome-wide association studies in 39,883 individuals of European ancestry to identify genes associated with metabolic disease. We identified 8 novel loci associated with adiponectin levels and confirmed 2 previously reported loci (P = 4.5×10(-8)-1.2×10(-43)). Using a novel method to combine data across ethnicities (N = 4,232 African Americans, N = 1,776 Asians, and N = 29,347 Europeans), we identified two additional novel loci. Expression analyses of 436 human adipocyte samples revealed that mRNA levels of 18 genes at candidate regions were associated with adiponectin concentrations after accounting for multiple testing (p

Published
2012
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4. Accounting for genetic effect heterogeneity in fine-mapping and improving power to detect gene-environment interactions with SharePro

Author

Wenmin Zhang, Robert Sladek, Yue Li, Hamed Najafabadi, and Josée Dupuis

Subjects
Science
Abstract

Abstract Classical gene-by-environment interaction (GxE) analysis can be used to characterize genetic effect heterogeneity but has a high multiple testing burden in the context of genome-wide association studies (GWAS). We adapt a colocalization method, SharePro, to account for effect heterogeneity in fine-mapping and identify candidates for GxE analysis with reduced multiple testing burden. SharePro demonstrates improved power for both fine-mapping and GxE analysis compared to existing methods as well as well-controlled false type I error in simulations. Using smoking status stratified GWAS summary statistics, we identify genetic effects on lung function modulated by smoking status that are not identified by existing methods. Additionally, using sex stratified GWAS summary statistics, we characterize sex differentiated genetic effects on fat distribution. In summary, we have developed an analytical framework to account for effect heterogeneity in fine-mapping and subsequently improve power for GxE analysis. The SharePro software for GxE analysis is openly available at https://github.com/zhwm/SharePro_gxe .

Published
2024
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5. Abstract 66: Clonal Hematopoiesis of Indeterminate Potential and Incident Type 2 Diabetes Risk

Author

Deirdre K Tobias, Alisa Manning, Jennifer Wessel, Sridharan Raghavan, Kenneth Westerman, Alexander G Bick, Daniel Dicorpo, Eric A Whitsel, Jason M Collins, Josee Dupuis, Mark O Goodarzi, Barbara V Howard, Leslie Lange, Simin Liu, Laura M Raffield, Alexander P Reiner, Stephen S Rich, Lesley Tinker, James Wilson, April P Carson, Ramachandran Vasan, Charles Kooperberg, Jerome I Rotter, James Meigs, and Joann E Manson

Subjects
Physiology (medical), Cardiology and Cardiovascular Medicine
Abstract

Introduction: Clonal hematopoiesis of indeterminate potential (CHIP) is an aging-related accumulation of somatic mutations in hematopoietic stem cells, leading to clonal expansion. CHIP presence has been implicated in elevated risks for coronary heart disease (CHD) and death, but its association with incident type 2 diabetes (T2D) is unknown. Hypothesis: We hypothesized that CHIP is associated with elevated risk of incident T2D. Methods: CHIP was derived from whole genome sequencing of blood DNA in NHLBI Trans-omics for Precision Medicine (TOPMed) cohorts. We analyzed 17,637 participants without prior T2D, cardiovascular disease, or cancer at blood draw, with prospective follow-up for incident T2D. We evaluated baseline prevalence of CHIP vs. no CHIP with incident T2D risk using Cox regression. We also investigated CHIP variants previously related to CHD: DNMT3A , TET2 , ASXL1 , JAK2 , and TP53 . We estimated multivariable-adjusted hazard ratios and 95% confidence intervals (HR [CI]) adjusted for age, sex, body mass index, smoking, alcohol, and education. We combined cohort estimates via fixed effects meta-analysis. Results: On average, participants were age 63.4 years (SD=11.5) and 76% female. Prevalence of CHIP was 6.0% (1,055) at baseline. There were 2,467 incident T2D cases over mean=9.8 years follow-up. Compared to those without a mutation, having CHIP was associated with a 23% higher T2D risk, both overall (combined HR=1.23; 95% CI=1.04, 1.45), and among those with CHD-related CHIP mutations (87% of total CHIP): HR=1.23 (1.03, 1.46). Although those with CHIP mutations of TET2 (HR=1.48; 1.05, 2.08) and ASXL1 (HR=1.76; 1.03, 2.99) had larger elevations in T2D risk, and DNMT3A was suggestive of increased T2D risk (HR=1.15; 0.93, 1.43), statistical power was limited for JAK2 and TP53 mutation analyses. Conclusions: CHIP was associated with higher incidence of T2D. CHIP mutations located on loci previously implicated in aging and CHD were also related to T2D, suggesting shared pathology of atherosclerosis and T2D.

Published
2023
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6. Idiopathic pulmonary fibrosis is associated with common genetic variants and limited rare variants

Author

Anna L. Peljto, Rachel Z. Blumhagen, Avram D. Walts, Jonathan Cardwell, Julia Powers, Tamera J. Corte, Joanne L. Dickinson, Ian Glaspole, Yuben P. Moodley, Martina Koziar Vasakova, Elisabeth Bendstrup, Jesper R. Davidsen, Raphael Borie, Bruno Crestani, Philippe Dieude, Francesco Bonella, Ulrich Costabel, Gunnar Gudmundsson, Seamas C. Donnelly, Jim Egan, Michael T. Henry, Michael P. Keane, Marcus P. Kennedy, Cormac McCarthy, Aoife N. McElroy, Joshua A. Olaniyi, Katherine M. A. O’Reilly, Luca Richeldi, Paolo M. Leone, Venerino Poletti, Francesco Puppo, Sara Tomassetti, Valentina Luzzi, Nurdan Kokturk, Nesrin Mogulkoc, Christine A. Fiddler, Nikhil Hirani, R. Gisli Jenkins, Toby M. Maher, Philip L. Molyneaux, Helen Parfrey, Rebecca Braybrooke, Timothy S. Blackwell, Peter D. Jackson, Steven D. Nathan, Mary K. Porteous, Kevin K. Brown, Jason D. Christie, Harold R. Collard, Oliver Eickelberg, Elena E. Foster, Kevin F. Gibson, Marilyn Glassberg, Daniel J. Kass, Jonathan A. Kropski, David Lederer, Angela L. Linderholm, Jim Loyd, Susan K. Mathai, Sydney B. Montesi, Imre Noth, Justin M. Oldham, Amy J. Palmisciano, Cristina A. Reichner, Mauricio Rojas, Jesse Roman, Neil Schluger, Barry S. Shea, Jeffrey J. Swigris, Paul J. Wolters, Yingze Zhang, Cecilia M. A. Prele, Juan I. Enghelmayer, Maria Otaola, Christopher J. Ryerson, Mauricio Salinas, Martina Sterclova, Tewodros H. Gebremariam, Marjukka Myllärniemi, Roberto G. Carbone, Haruhiko Furusawa, Masaki Hirose, Yoshikazu Inoue, Yasunari Miyazaki, Ken Ohta, Shin Ohta, Tsukasa Okamoto, Dong Soon Kim, Annie Pardo, Moises Selman, Alvaro U. Aranda, Moo Suk Park, Jong Sun Park, Jin Woo Song, Maria Molina-Molina, Lurdes Planas-Cerezales, Gunilla Westergren-Thorsson, Albert V. Smith, Ani W. Manichaikul, John S. Kim, Stephen S. Rich, Elizabeth C. Oelsner, R. Graham Barr, Jerome I. Rotter, Josee Dupuis, George O’Connor, Ramachandran S. Vasan, Michael H. Cho, Edwin K. Silverman, Marvin I. Schwarz, Mark P. Steele, Joyce S. Lee, Ivana V. Yang, Tasha E. Fingerlin, and David A. Schwartz

Subjects
Pulmonary and Respiratory Medicine, Whole Genome Sequencing, Settore MED/10 - MALATTIE DELL'APPARATO RESPIRATORIO, Critical Care and Intensive Care Medicine, Interstitial Lung Disease, TOPMed, Telomerase, Genetic Association Studies
Abstract

Rationale: Idiopathic pulmonary fibrosis is a rare, irreversible, and progressive disease of the lungs. Common genetic variants, in addition to non-genetic factors, have been consistently associated with IPF. Rare variants identified by candidate gene, family-based, and exome studies have also been reported to associate with IPF. However, the extent to which rare variants genome-wide may contribute to the risk of IPF remains unknown. Objectives: We used whole-genome sequencing to investigate the role of rare variants, genome-wide, on IPF risk. Methods: As part of the Trans-Omics for Precision Medicine Program, we sequenced 2,180 cases of IPF. Association testing focused on the aggregated effect of rare variants (minor allele frequency ≤0.01) within genes or regions. We also identified individual variants that are influential within genes and estimated the heritability of IPF based on rare and common variants. Measurements and Main Results: Rare variants in both TERT and RTEL1 were significantly associated with IPF. A single rare variant in each of the TERT and RTEL1 genes was found to consistently influence the aggregated test statistics. There was no significant evidence of association with other previously reported rare variants. The SNP-heritability of IPF was estimated to be 32% (s.e. 3%). Conclusions: Rare variants within the TERT and RTEL1 genes and well-established common variants have the largest contribution to IPF risk overall. Efforts in risk profiling or development of therapies for IPF that focus on TERT, RTEL1, common variants, and environmental risk factors are likely to have the largest impact on this complex disease.

Published
2023

7. Abstract 016: Artificially Sweetened Beverage Consumption, Plasma Metabolomics, And Risk Of Type 2 Diabetes Among US Adults

Author

Danielle E Haslam, Biqi Wang, Jun Li, Marta Guasch, Liming Liang, Clary B Clish, Joann E Manson, Deirdre K Tobias, Clemens Wittenbecher, Walter C Willett, Meir J Stampfer, Mark A Herman, Josee Dupuis, Nicola M McKeown, Vasanti S Malik, James B Meigs, Frank B Hu, and Shilpa N Bhupathiraju

Subjects
Physiology (medical), Cardiology and Cardiovascular Medicine
Abstract

Introduction: The relationship between artificially sweetened beverage (ASB) intake and type 2 diabetes (T2D) risk remains inconclusive. Few studies have evaluated whether circulating metabolites that reflect ASB consumption may unveil potential mechanisms underlying the association between ASB consumption and T2D risk. Hypothesis: We hypothesized that a novel metabolomic profile reflecting habitual ASB consumption would positively associate with incident T2D among US adults. Methods: We quantified 120 plasma metabolites with liquid chromatography-mass spectroscopy in N=3,424 Nurses’ Health Study (NHS), NHSII, and Health Professionals Follow-up Study (HPFS) discovery cohort participants, and N=1,870 Framingham Heart Study (FHS) replication cohort participants. Habitual ASB consumption (servings/day; low-calorie cola or other carbonated beverages) was estimated from food frequency questionnaires at the time of blood draw. We used elastic net regression with 10-fold-cross-validation to age- and body mass index- adjusted metabolite levels to identify a metabolite profile associated with higher ASB consumption (ln-transformed). We then derived the continuous ASB metabolomic score as the weighted sum of these metabolites and replicated the analysis in an internal testing set and FHS. Finally, we evaluated the association of quartiles (Q) of the ASB-derived metabolomic score in NHS/NHSII/HPFS and FHS cohorts with incident T2D risk after blood draw (baseline for analysis) using Cox regression models to estimate hazard ratios (HR) and 95% confidence interval (CI), adjusted for demographics, lifestyle, diet, and body mass index at blood draw. Results: The ASB-derived metabolomic profile included 61 metabolites, primarily lipids and amino acids (Pearson correlation coefficients [ r ] between ASB self-reported intake and metabolomic score: r=0.08 [95% CI: 0.05, 0.11; p p =0.001], for discovery and replication, respectively). Mean follow-up was 20 and 16 years from blood draw, including 359 and 241 confirmed incident T2D cases for NHS/NHSII/HPFS and FHS, respectively. Compared with participants in the lowest quartile of the ASB-derived metabolomic profile, higher quartiles were incrementally and significantly at higher T2D risk in NHS/NHSII/HPFS (HR [CI] for Q2, Q3, Q4 vs. Q1: 1.45 [1.04, 2.02], 1.83 [1.33, 2.52], 1.62 [1.18, 2.22], respectively; p-trend =0.003) and FHS (1.76 [1.24, 2.48], 1.82 [1.28, 2.58], 2.45 [1.77, 3.40], respectively; p-trend Conclusions: A robust metabolomic profile of ASB intake was not identified, yet the objective and replicable ASB-derived metabolomic profile was associated with higher incident T2D risk. The identified metabolites may reflect ASB intake, western dietary patterns, underlying metabolic health, and/or T2D-related pathophysiology.

Published
2022
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8. Association of large core middle cerebral artery stroke and hemorrhagic transformation with hospitalization outcomes

Author

Jack E. Pohlmann, Ivy So Yeon Kim, Benjamin Brush, Krishna M. Sambhu, Lucas Conti, Hanife Saglam, Katie Milos, Lillian Yu, Michael F. M. Cronin, Oluwafemi Balogun, Stefanos Chatzidakis, Yihan Zhang, Ludovic Trinquart, Qiuxi Huang, Stelios M. Smirnakis, Emelia J. Benjamin, Josée Dupuis, David M. Greer, and Charlene J. Ong

Subjects
Medicine, Science
Abstract

Abstract Historically, investigators have not differentiated between patients with and without hemorrhagic transformation (HT) in large core ischemic stroke at risk for life-threatening mass effect (LTME) from cerebral edema. Our objective was to determine whether LTME occurs faster in those with HT compared to those without. We conducted a two-center retrospective study of patients with ≥ 1/2 MCA territory infarct between 2006 and 2021. We tested the association of time-to-LTME and HT subtype (parenchymal, petechial) using Cox regression, controlling for age, mean arterial pressure, glucose, tissue plasminogen activator, mechanical thrombectomy, National Institute of Health Stroke Scale, antiplatelets, anticoagulation, temperature, and stroke side. Secondary and exploratory outcomes included mass effect-related death, all-cause death, disposition, and decompressive hemicraniectomy. Of 840 patients, 358 (42.6%) had no HT, 403 (48.0%) patients had petechial HT, and 79 (9.4%) patients had parenchymal HT. LTME occurred in 317 (37.7%) and 100 (11.9%) had mass effect-related deaths. Parenchymal (HR 8.24, 95% CI 5.46–12.42, p

Published
2024
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9. 73-OR: Clonal Hematopoiesis of Indeterminate Potential (CHIP), Glycemic Traits, and Type 2 Diabetes (T2D) Risk

Author

DEIRDRE K. TOBIAS, ALISA MANNING, JENNIFER WESSEL, KENNETH E. WESTERMAN, SRIDHARAN RAGHAVAN, LAURA RAFFIELD, JOSEE DUPUIS, ALEXANDER BICK, PEITAO WU, DANIEL A. DICORPO, BRUCE M. PSATY, ALANNA C. MORRISON, VASAN S. RAMACHANDRAN, L. ADRIENNE CUPPLES, LESLIE LANGE, ADOLFO CORREA, CHARLES L. KOOPERBERG, LESLEY F. TINKER, BARBARA V. HOWARD, ALEX REINER, JEROME I. ROTTER, JASON M. COLLINS, JAMES B. MEIGS, and JOANN E. MANSON

Subjects
Endocrinology, Diabetes and Metabolism, Internal Medicine
Abstract

Objective: CHIP is an aging-related accumulation of somatic mutations in hematopoietic stem cells, leading to clonal expansion. CHIP presence has been implicated in elevated atherosclerotic heart disease (CHD) and all-cause mortality, but its association with incident T2D is unknown. We hypothesize CHIP is adversely associated with glycemic traits and T2D. Methods: We included N=16,054 participants in NHLBI Trans-omics for Precision Medicine (TOPMed), without prior T2D or chronic disease at blood draw. CHIP was derived from blood DNA whole genome sequencing using the GATK MuTECT2 somatic variant caller in pre-specified leukemogenic driver mutations. We estimated CHIP overall and candidate CHD-related mutations (DNMT3A, TET2, ASXL1, JAK2) in relation to baseline glycemic traits (fasting glucose, insulin, HOMA-IR) with linear regression. We evaluated CHIP with incident T2D using Cox regression to estimate hazard ratios and 95% confidence intervals (HR [CI]). Models adjusted for age, sex, body mass index, smoking, and family history of T2D. We combined cohort-specific estimates via random effects meta-analysis with inverse variance weighting. Results: CHIP was present in n=1,088 (7%) of participants. We observed 1,853 incident T2D cases over mean=10y follow-up. Baseline fasting glucose, insulin, and HOMA-IR did not differ by CHIP status. Participants with CHIP had a higher risk of incident T2D than those without CHIP (1.27 [1.08, 1.51]), with a significant dose-response per additional CHIP mutation (p-trend=0.005). Analyses of CHD-related CHIP vs. no CHIP mutations suggested associations with higher T2D risk for DNMT3A (1.21 [0.97, 1.51]) and TET2 (1.35 [0.93, 1.97]), and ASXL1 (1.92 [0.71, 5.13]), although analyses of individual mutations were underpowered. Conclusions: CHIP is associated with a higher T2D risk. This relationship may be unrelated to baseline glycemic traits. CHIP-T2D association suggests a potential role for CHD-related pathology in T2D. Disclosure D. K. Tobias: None. D. A. Dicorpo: None. B. M. Psaty: None. A. C. Morrison: None. V. S. Ramachandran: None. L. Cupples: None. L. Lange: None. A. Correa: None. C. L. Kooperberg: None. L. F. Tinker: None. B. V. Howard: None. A. Manning: Employee; Spouse/Partner; Emulate, Inc, Stock/Shareholder; Spouse/Partner; Invitae. A. Reiner: None. J. I. Rotter: None. J. M. Collins: None. J. B. Meigs: Consultant; Self; Quest Diagnostics. J. E. Manson: None. J. Wessel: Employee; Spouse/Partner; Eli Lilly and Company. K. E. Westerman: None. S. Raghavan: None. L. Raffield: None. J. Dupuis: None. A. Bick: None. P. Wu: None. Funding National Institute of Diabetes and Digestive and Kidney Diseases (U01DK078616 to J.B.M., J.D., D.A.D., P.W.), (U01DK105554 to J.D., D.A.D.)

Published
2021
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10. La grande évasion de Roquette : D'après une histoire vraie

Author

Josée Dupuis and Josée Dupuis

Abstract

Roquette ne vit pas à la campagne et elle ne gambade pas dans un jardin fleuri. Roquette vit, comme des milliers de poules pondeuses dans un poulailler industriel, confinée dans une cage sans fenêtre. Face à cette vie de misère, Roquette n'a qu'un seul souhait : S'ÉVADER. Courageuse, elle le fait, sans imaginer toutes les aventures qui l'attendent! Tiré d'une histoire vraie, cet album aborde le courage et la persévérance d'une poule qui aspire à une vie meilleure, loin de sa cage étroite.

Published
2024

11. Rare and low-frequency exonic variants and gene-by-smoking interactions in pulmonary function

Author

Tianzhong Yang, Victoria E. Jackson, Albert V. Smith, Han Chen, Traci M. Bartz, Colleen M. Sitlani, Bruce M. Psaty, Sina A. Gharib, George T. O’Connor, Josee Dupuis, Jiayi Xu, Kurt Lohman, Y Liu, Stephen B. Kritchevsky, Patricia A. Cassano, Claudia Flexeder, Christian Gieger, Stefan Karrasch, Annette Peters, Holger Schulz, Sarah E. Harris, John M. Starr, Ian J. Deary, Ani Manichaikul, Elizabeth C. Oelsner, R. Graham Barr, Kent D. Taylor, Stephen S. Rich, Tobias N. Bonten, Dennis Mook-Kanamori, R Noordam, Ruifang Li-Gao, Marjo Riitta Järvelin, Matthias Wielscher, N. (Natalie) Terzikhan, L.B. (Lies) Lahousse, G.G.O. (Guy) Brusselle, Stefan Weiss, Ralf Ewert, Sven Gläser, Georg Homuth, Nick Shrine, Ian P. Hall, Martin D. Tobin, Stephanie J. London, Peng Wei, Alanna C. Morrison, Tianzhong Yang, Victoria E. Jackson, Albert V. Smith, Han Chen, Traci M. Bartz, Colleen M. Sitlani, Bruce M. Psaty, Sina A. Gharib, George T. O’Connor, Josee Dupuis, Jiayi Xu, Kurt Lohman, Y Liu, Stephen B. Kritchevsky, Patricia A. Cassano, Claudia Flexeder, Christian Gieger, Stefan Karrasch, Annette Peters, Holger Schulz, Sarah E. Harris, John M. Starr, Ian J. Deary, Ani Manichaikul, Elizabeth C. Oelsner, R. Graham Barr, Kent D. Taylor, Stephen S. Rich, Tobias N. Bonten, Dennis Mook-Kanamori, R Noordam, Ruifang Li-Gao, Marjo Riitta Järvelin, Matthias Wielscher, N. (Natalie) Terzikhan, L.B. (Lies) Lahousse, G.G.O. (Guy) Brusselle, Stefan Weiss, Ralf Ewert, Sven Gläser, Georg Homuth, Nick Shrine, Ian P. Hall, Martin D. Tobin, Stephanie J. London, Peng Wei, and Alanna C. Morrison

Abstract

Genome-wide association studies have identified numerous common genetic variants associated with spirometric measures of pulmonary function, including forced expiratory volume in one second (FEV1), forced vital capacity, and their ratio. However, variants with lower minor allele frequencies are less explored. We conducted a large-scale gene-smoking interaction meta-analysis on exonic rare and low-frequency variants involving 44,429 individuals of European ancestry in the discovery stage and sought replication in the UK BiLEVE study with 45,133 European ancestry samples and UK Biobank study with 59,478 samples. We leveraged data on cigarette smoking, the major environmental risk factor for reduced lung function, by testing gene-by-smoking interaction effects only and simultaneously testing the genetic main effects and interaction effects. The most statistically significant signal that replicated was a previously reported low-frequency signal in GPR126, distinct from common variant associations in this gene. Although only nominal replication was obtained for a top rare variant signal rs142935352 in one of the two studies, interaction and joint tests for current smoking and PDE3B were si

Published
2021
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12. Trans-ancestry genetic study of type 2 diabetes highlights the power of diverse populations for discovery and translation

Author

Anubha Mahajan, Cassandra N Spracklen, Weihua Zhang, Maggie CY Ng, Lauren E Petty, Hidetoshi Kitajima, Grace Z Yu, Sina Rüeger, Leo Speidel, Young Jin Kim, Momoko Horikoshi, Josep M Mercader, Daniel Taliun, Sanghoon Moon, Soo-Heon Kwak, Neil R Robertson, Nigel W Rayner, Marie Loh, Bong-Jo Kim, Joshua Chiou, Irene Miguel-Escalada, Pietro della Briotta Parolo, Kuang Lin, Fiona Bragg, Michael H Preuss, Fumihiko Takeuchi, Jana Nano, Xiuqing Guo, Amel Lamri, Masahiro Nakatochi, Robert A Scott, Jung-Jin Lee, Alicia Huerta-Chagoya, Mariaelisa Graff, Jin-Fang Chai, Esteban J Parra, Jie Yao, Lawrence F Bielak, Yasuharu Tabara, Yang Hai, Valgerdur Steinthorsdottir, James P Cook, Mart Kals, Niels Grarup, Ellen M Schmidt, Ian Pan, Tamar Sofer, Matthias Wuttke, Chloe Sarnowski, Christian Gieger, Darryl Nousome, Stella Trompet, Jirong Long, Meng Sun, Lin Tong, Wei-Min Chen, Meraj Ahmad, Raymond Noordam, Victor JY Lim, Claudia HT Tam, Yoonjung Yoonie Joo, Chien-Hsiun Chen, Laura M Raffield, Cécile Lecoeur, Nisa M Maruthur, Bram Peter Prins, Aude Nicolas, Lisa R Yanek, Guanjie Chen, Richard A Jensen, Salman Tajuddin, Edmond Kabagambe, Ping An, Anny H Xiang, Hyeok Sun Choi, Brian E Cade, Jingyi Tan, Fernando Abaitua, Linda S Adair, Adebowale Adeyemo, Carlos A Aguilar-Salinas, Masato Akiyama, Sonia S Anand, Alain Bertoni, Zheng Bian, Jette Bork-Jensen, Ivan Brandslund, Jennifer A Brody, Chad M Brummett, Thomas A Buchanan, Mickaël Canouil, Juliana CN Chan, Li-Ching Chang, Miao-Li Chee, Ji Chen, Shyh-Huei Chen, Yuan-Tsong Chen, Zhengming Chen, Lee-Ming Chuang, Mary Cushman, Swapan K Das, H. Janaka de Silva, George Dedoussis, Latchezar Dimitrov, Ayo P Doumatey, Shufa Du, Qing Duan, Kai-Uwe Eckardt, Leslie S Emery, Daniel S Evans, Michele K Evans, Krista Fischer, James S Floyd, Ian Ford, Myriam Fornage, Oscar H Franco, Timothy M Frayling, Barry I Freedman, Christian Fuchsberger, Pauline Genter, Hertzel C Gerstein, Vilmantas Giedraitis, Clicerio González-Villalpando, Maria Elena González-Villalpando, Mark O Goodarzi, Penny Gordon-Larsen, David Gorkin, Myron Gross, Yu Guo, Sophie Hackinger, Sohee Han, Andrew T Hattersley, Christian Herder, Annie-Green Howard, Willa Hsueh, Mengna Huang, Wei Huang, Yi-Jen Hung, Mi Yeong Hwang, Chii-Min Hwu, Sahoko Ichihara, Mohammad Arfan Ikram, Martin Ingelsson, Md. Tariqul Islam, Masato Isono, Hye-Mi Jang, Farzana Jasmine, Guozhi Jiang, Jost B Jonas, Marit E Jørgensen, Torben Jørgensen, Yoichiro Kamatani, Fouad R Kandeel, Anuradhani Kasturiratne, Tomohiro Katsuya, Varinderpal Kaur, Takahisa Kawaguchi, Jacob M Keaton, Abel N Kho, Chiea-Chuen Khor, Muhammad G Kibriya, Duk-Hwan Kim, Katsuhiko Kohara, Jennifer Kriebel, Florian Kronenberg, Johanna Kuusisto, Kristi Läll, Leslie A Lange, Myung-Shik Lee, Nanette R Lee, Aaron Leong, Liming Li, Yun Li, Ruifang Li-Gao, Symen Ligthart, Cecilia M Lindgren, Allan Linneberg, Ching-Ti Liu, Jianjun Liu, Adam E Locke, Tin Louie, Jian’an Luan, Andrea O Luk, Xi Luo, Jun Lv, Valeriya Lyssenko, Vasiliki Mamakou, K Radha Mani, Thomas Meitinger, Andres Metspalu, Andrew D Morris, Girish N. Nadkarni, Jerry L Nadler, Michael A Nalls, Uma Nayak, Ioanna Ntalla, Yukinori Okada, Lorena Orozco, Sanjay R Patel, Mark A Pereira, Annette Peters, Fraser J Pirie, Bianca Porneala, Gauri Prasad, Sebastian Preissl, Laura J Rasmussen-Torvik, Alexander P Reiner, Michael Roden, Rebecca Rohde, Katheryn Roll, Charumathi Sabanayagam, Maike Sander, Kevin Sandow, Naveed Sattar, Sebastian Schönherr, Claudia Schurmann, Mohammad Shahriar, Jinxiu Shi, Dong Mun Shin, Daniel Shriner, Jennifer A Smith, Wing Yee So, Alena Stančáková, Adrienne M Stilp, Konstantin Strauch, Ken Suzuki, Atsushi Takahashi, Kent D Taylor, Barbara Thorand, Gudmar Thorleifsson, Unnur Thorsteinsdottir, Brian Tomlinson, Jason M Torres, Fuu-Jen Tsai, Jaakko Tuomilehto, Teresa Tusie-Luna, Miriam S Udler, Adan Valladares-Salgado, Rob M van Dam, Jan B van Klinken, Rohit Varma, Marijana Vujkovic, Niels Wacher-Rodarte, Ellie Wheeler, Eric A Whitsel, Ananda R Wickremasinghe, Konstantin Willems van Dijk, Daniel R Witte, Chittaranjan S Yajnik, Ken Yamamoto, Toshimasa Yamauchi, Loïc Yengo, Kyungheon Yoon, Canqing Yu, Jian-Min Yuan, Salim Yusuf, Liang Zhang, Wei Zheng, null FinnGen, Leslie J Raffel, Michiya Igase, Eli Ipp, Susan Redline, Yoon Shin Cho, Lars Lind, Michael A Province, Craig L Hanis, Patricia A Peyser, Erik Ingelsson, Alan B Zonderman, Bruce M Psaty, Ya-Xing Wang, Charles N Rotimi, Diane M Becker, Fumihiko Matsuda, Yongmei Liu, Eleftheria Zeggini, Mitsuhiro Yokota, Stephen S Rich, Charles Kooperberg, James S Pankow, James C Engert, Yii-Der Ida Chen, Philippe Froguel, James G Wilson, Wayne HH Sheu, Sharon LR Kardia, Jer-Yuarn Wu, M Geoffrey Hayes, Ronald CW Ma, Tien-Yin Wong, Leif Groop, Dennis O Mook-Kanamori, Giriraj R Chandak, Francis S Collins, Dwaipayan Bharadwaj, Guillaume Paré, Michèle M Sale, Habibul Ahsan, Ayesha A Motala, Xiao-Ou Shu, Kyong-Soo Park, J Wouter Jukema, Miguel Cruz, Roberta McKean-Cowdin, Harald Grallert, Ching-Yu Cheng, Erwin P Bottinger, Abbas Dehghan, E-Shyong Tai, Josee Dupuis, Norihiro Kato, Markku Laakso, Anna Köttgen, Woon-Puay Koh, Colin NA Palmer, Simin Liu, Goncalo Abecasis, Jaspal S Kooner, Ruth JF Loos, Kari E North, Christopher A Haiman, Jose C Florez, Danish Saleheen, Torben Hansen, Oluf Pedersen, Reedik Mägi, Claudia Langenberg, Nicholas J Wareham, Shiro Maeda, Takashi Kadowaki, Juyoung Lee, Iona Y Millwood, Robin G Walters, Kari Stefansson, Simon R Myers, Jorge Ferrer, Kyle J Gaulton, James B Meigs, Karen L Mohlke, Anna L Gloyn, Donald W Bowden, Jennifer E Below, John C Chambers, Xueling Sim, Michael Boehnke, Jerome I Rotter, Mark I McCarthy, and Andrew P Morris

Subjects
0303 health sciences, Transferability, Translation (biology), Type 2 diabetes, Biology, medicine.disease, 03 medical and health sciences, 0302 clinical medicine, Evolutionary biology, Global health, medicine, Genetic risk, Gene, 030217 neurology & neurosurgery, 030304 developmental biology, Genetic association
Abstract

We assembled an ancestrally diverse collection of genome-wide association studies of type 2 diabetes (T2D) in 180,834 cases and 1,159,055 controls (48.9% non-European descent). We identified 277 loci at genome-wide significance (p-8), including 237 attaining a more stringent trans-ancestry threshold (p-9), which were delineated to 338 distinct association signals. Trans-ancestry meta-regression offered substantial enhancements to fine-mapping, with 58.6% of associations more precisely localised due to population diversity, and 54.4% of signals resolved to a single variant with >50% posterior probability. This improved fine-mapping enabled systematic assessment of candidate causal genes and molecular mechanisms through which T2D associations are mediated, laying foundations for functional investigations. Trans-ancestry genetic risk scores enhanced transferability across diverse populations, providing a step towards more effective clinical translation to improve global health.

Published
2020
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13. Multi-tissue epigenetic analysis identifies distinct associations underlying insulin resistance and Alzheimer’s disease at CPT1A locus

Author

Chloé Sarnowski, Tianxiao Huan, Yiyi Ma, Roby Joehanes, Alexa Beiser, Charles S. DeCarli, Nancy L. Heard-Costa, Daniel Levy, Honghuang Lin, Ching-Ti Liu, Chunyu Liu, James B. Meigs, Claudia L. Satizabal, Jose C. Florez, Marie-France Hivert, Josée Dupuis, Philip L. De Jager, David A. Bennett, Sudha Seshadri, and Alanna C. Morrison

Subjects
Epigenetics, Insulin resistance, Alzheimer’s disease, FHS, ROSMAP, DNA methylation, Medicine, Genetics, QH426-470
Abstract

Abstract Background Insulin resistance (IR) is a major risk factor for Alzheimer’s disease (AD) dementia. The mechanisms by which IR predisposes to AD are not well-understood. Epigenetic studies may help identify molecular signatures of IR associated with AD, thus improving our understanding of the biological and regulatory mechanisms linking IR and AD. Methods We conducted an epigenome-wide association study of IR, quantified using the homeostatic model assessment of IR (HOMA-IR) and adjusted for body mass index, in 3,167 participants from the Framingham Heart Study (FHS) without type 2 diabetes at the time of blood draw used for methylation measurement. We identified DNA methylation markers associated with IR at the genome-wide level accounting for multiple testing (P

Published
2023
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14. Bronchial epithelial gene expression and interstitial lung abnormalities

Author

Aravind A. Menon, Minyi Lee, Xu Ke, Rachel K. Putman, Takuya Hino, Jonathan A. Rose, Fenghai Duan, Samuel Y. Ash, Michael H. Cho, George T. O’Connor, Josée Dupuis, Hiroto Hatabu, Marc E. Lenburg, Ehab S. Billatos, Gary M. Hunninghake, and the DECAMP Investigators

Subjects
Interstitial lung abnormalities, ILA, Gene expression, Interstitial lung disease, Lung fibrosis, Diseases of the respiratory system, RC705-779
Abstract

Abstract Introduction Interstitial lung abnormalities (ILA) often represent early fibrotic changes that can portend a progressive fibrotic phenotype. In particular, the fibrotic subtype of ILA is associated with increased mortality and rapid decline in lung function. Understanding the differential gene expression that occurs in the lungs of participants with fibrotic ILA may provide insight into development of a useful biomarker for early detection and therapeutic targets for progressive pulmonary fibrosis. Methods Measures of ILA and gene expression data were available in 213 participants in the Detection of Early Lung Cancer Among Military Personnel (DECAMP1 and DECAMP2) cohorts. ILA was defined using Fleischner Society guidelines and determined by sequential reading of computed tomography (CT) scans. Primary analysis focused on comparing gene expression in ILA with usual interstitial pneumonia (UIP) pattern with those with no ILA. Results ILA was present in 51 (24%) participants, of which 16 (7%) were subtyped as ILA with a UIP pattern. One gene, pro platelet basic protein (PPBP) and seventeen pathways (e.g. TNF-α signalling) were significantly differentially expressed between those with a probable or definite UIP pattern of ILA compared to those without ILA. 16 of these 17 pathways, but no individual gene, met significance when comparing those with ILA to those without ILA. Conclusion Our study demonstrates that abnormal inflammatory processes are apparent in the bronchial airway gene expression profiles of smokers with and without lung cancer with ILA. Future studies with larger and more diverse populations will be needed to confirm these findings.

Published
2023
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15. Genome Analyses of >200,000 Individuals Identify 58 Loci for Chronic Inflammation and Highlight Pathways that Link Inflammation and Complex Disorders

Author

Symen Ligthart, Ahmad Vaez, Urmo Võsa, Maria G. Stathopoulou, Paul S. de Vries, Bram P. Prins, Peter J. Van der Most, Toshiko Tanaka, Elnaz Naderi, Lynda M. Rose, Ying Wu, Robert Karlsson, Maja Barbalic, Honghuang Lin, René Pool, Gu Zhu, Aurélien Macé, Carlo Sidore, Stella Trompet, Massimo Mangino, Maria Sabater-Lleal, John P. Kemp, Ali Abbasi, Tim Kacprowski, Niek Verweij, Albert V. Smith, Tao Huang, Carola Marzi, Mary F. Feitosa, Kurt K. Lohman, Marcus E. Kleber, Yuri Milaneschi, Christian Mueller, Mahmudul Huq, Efthymia Vlachopoulou, Leo-Pekka Lyytikäinen, Christopher Oldmeadow, Joris Deelen, Markus Perola, Jing Hua Zhao, Bjarke Feenstra, Marzyeh Amini, Jari Lahti, Katharina E. Schraut, Myriam Fornage, Bhoom Suktitipat, Wei-Min Chen, Xiaohui Li, Teresa Nutile, Giovanni Malerba, Jian’an Luan, Tom Bak, Nicholas Schork, Fabiola Del Greco M., Elisabeth Thiering, Anubha Mahajan, Riccardo E. Marioni, Evelin Mihailov, Joel Eriksson, Ayse Bilge Ozel, Weihua Zhang, Maria Nethander, Yu-Ching Cheng, Stella Aslibekyan, Wei Ang, Ilaria Gandin, Loïc Yengo, Laura Portas, Charles Kooperberg, Edith Hofer, Kumar B. Rajan, Claudia Schurmann, Wouter den Hollander, Tarunveer S. Ahluwalia, Jing Zhao, Harmen H.M. Draisma, Ian Ford, Nicholas Timpson, Alexander Teumer, Hongyan Huang, Simone Wahl, YongMei Liu, Jie Huang, Hae-Won Uh, Frank Geller, Peter K. Joshi, Lisa R. Yanek, Elisabetta Trabetti, Benjamin Lehne, Diego Vozzi, Marie Verbanck, Ginevra Biino, Yasaman Saba, Ingrid Meulenbelt, Jeff R. O’Connell, Markku Laakso, Franco Giulianini, Patrik K.E. Magnusson, Christie M. Ballantyne, Jouke Jan Hottenga, Grant W. Montgomery, Fernando Rivadineira, Rico Rueedi, Maristella Steri, Karl-Heinz Herzig, David J. Stott, Cristina Menni, Mattias Frånberg, Beate St. Pourcain, Stephan B. Felix, Tune H. Pers, Stephan J.L. Bakker, Peter Kraft, Annette Peters, Dhananjay Vaidya, Graciela Delgado, Johannes H. Smit, Vera Großmann, Juha Sinisalo, Ilkka Seppälä, Stephen R. Williams, Elizabeth G. Holliday, Matthijs Moed, Claudia Langenberg, Katri Räikkönen, Jingzhong Ding, Harry Campbell, Michele M. Sale, Yii-Der I. Chen, Alan L. James, Daniela Ruggiero, Nicole Soranzo, Catharina A. Hartman, Erin N. Smith, Gerald S. Berenson, Christian Fuchsberger, Dena Hernandez, Carla M.T. Tiesler, Vilmantas Giedraitis, David Liewald, Krista Fischer, Dan Mellström, Anders Larsson, Yunmei Wang, William R. Scott, Matthias Lorentzon, John Beilby, Kathleen A. Ryan, Craig E. Pennell, Dragana Vuckovic, Beverly Balkau, Maria Pina Concas, Reinhold Schmidt, Carlos F. Mendes de Leon, Erwin P. Bottinger, Margreet Kloppenburg, Lavinia Paternoster, Michael Boehnke, A.W. Musk, Gonneke Willemsen, David M. Evans, Pamela A.F. Madden, Mika Kähönen, Zoltán Kutalik, Magdalena Zoledziewska, Ville Karhunen, Stephen B. Kritchevsky, Naveed Sattar, Genevieve Lachance, Robert Clarke, Tamara B. Harris, Olli T. Raitakari, John R. Attia, Diana van Heemst, Eero Kajantie, Rossella Sorice, Giovanni Gambaro, Robert A. Scott, Andrew A. Hicks, Luigi Ferrucci, Marie Standl, Cecilia M. Lindgren, John M. Starr, Magnus Karlsson, Lars Lind, Jun Z. Li, John C. Chambers, Trevor A. Mori, Eco J.C.N. de Geus, Andrew C. Heath, Nicholas G. Martin, Juha Auvinen, Brendan M. Buckley, Anton J.M. de Craen, Melanie Waldenberger, Konstantin Strauch, Thomas Meitinger, Rodney J. Scott, Mark McEvoy, Marian Beekman, Cristina Bombieri, Paul M. Ridker, Karen L. Mohlke, Nancy L. Pedersen, Alanna C. Morrison, Dorret I. Boomsma, John B. Whitfield, David P. Strachan, Albert Hofman, Peter Vollenweider, Francesco Cucca, Marjo-Riitta Jarvelin, J. Wouter Jukema, Tim D. Spector, Anders Hamsten, Tanja Zeller, André G. Uitterlinden, Matthias Nauck, Vilmundur Gudnason, Lu Qi, Harald Grallert, Ingrid B. Borecki, Jerome I. Rotter, Winfried März, Philipp S. Wild, Marja-Liisa Lokki, Michael Boyle, Veikko Salomaa, Mads Melbye, Johan G. Eriksson, James F. Wilson, Brenda W.J.H. Penninx, Diane M. Becker, Bradford B. Worrall, Greg Gibson, Ronald M. Krauss, Marina Ciullo, Gianluigi Zaza, Nicholas J. Wareham, Albertine J. Oldehinkel, Lyle J. Palmer, Sarah S. Murray, Peter P. Pramstaller, Stefania Bandinelli, Joachim Heinrich, Erik Ingelsson, Ian J. Deary, Reedik Mägi, Liesbeth Vandenput, Pim van der Harst, Karl C. Desch, Jaspal S. Kooner, Claes Ohlsson, Caroline Hayward, Terho Lehtimäki, Alan R. Shuldiner, Donna K. Arnett, Lawrence J. Beilin, Antonietta Robino, Philippe Froguel, Mario Pirastu, Tine Jess, Wolfgang Koenig, Ruth J.F. Loos, Denis A. Evans, Helena Schmidt, George Davey Smith, P. Eline Slagboom, Gudny Eiriksdottir, Andrew P. Morris, Bruce M. Psaty, Russell P. Tracy, Ilja M. Nolte, Eric Boerwinkle, Sophie Visvikis-Siest, Alex P. Reiner, Myron Gross, Joshua C. Bis, Lude Franke, Oscar H. Franco, Emelia J. Benjamin, Daniel I. Chasman, Josée Dupuis, Harold Snieder, Abbas Dehghan, Behrooz Z. Alizadeh, H. Marike Boezen, Gerjan Navis, Marianne Rots, Morris Swertz, Bruce H.R. Wolffenbuttel, Cisca Wijmenga, Emelia Benjamin, Tarunveer Singh Ahluwalia, James Meigs, Russell Tracy, Josh Bis, Nathan Pankratz, Alex Rainer, James G. Wilson, Josee Dupuis, Bram Prins, Urmo Vaso, Maria Stathopoulou, Terho Lehtimaki, Yalda Jamshidi, Sophie Siest, Andre G. Uitterlinden, Mohammadreza Abdollahi, Renate Schnabel, Ursula M. Schick, Aldi Kraja, Yi-Hsiang Hsu, Daniel S. Tylee, Alyson Zwicker, Rudolf Uher, George Davey-Smith, Andrew Hicks, Cornelia M. van Duijn, Cavin Ward-Caviness, J. Rotter, Ken Rice, Leslie Lange, Eco de Geus, Kari Matti Makela, David Stacey, Johan Eriksson, Tim M. Frayling, Eline P. Slagboom, Erasmus University Medical Center [Rotterdam] (Erasmus MC), University Medical Center Groningen [Groningen] (UMCG), University of Isfahan, University of Tartu, Interactions Gène-Environnement en Physiopathologie Cardio-Vasculaire (IGE-PCV), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Lorraine (UL), The University of Texas Health Science Center at Houston (UTHealth), National Institute on Aging [Bethesda, USA] (NIA), National Institutes of Health [Bethesda] (NIH), Brigham and Women's Hospital [Boston], University of North Carolina [Chapel Hill] (UNC), University of North Carolina System (UNC), Department of Medical Epidemiology and Biostatistics (MEB), Karolinska Institutet [Stockholm], University of Split, Boston University School of Medicine (BUSM), Boston University [Boston] (BU), Process & Energy Laboratory, Delft University of Technology (TU Delft), Grand Lyon : communauté urbaine de Lyon, Interuniversity Cardiology Institute Netherlands, Department of Twin Research and Genetic Epidemiology, King's College London, London, Huazhong University of Science and Technology [Wuhan] (HUST), Division of Statistical Genomics, Washington University School of Medicine, Department of Psychiatry, VU University Medical Center [Amsterdam], Institut fuer Theoretische Physik (Institut fuer Theoretische Physik), Universität Heidelberg [Heidelberg] = Heidelberg University, Molecular Epidemiology, MRC Epidemiology Unit, Institute of Metabolic Science, Addenbrooke's Hospital, Mahidol University [Bangkok], Northwest A and F University, Laboratoire d'Optimisation des Systèmes Industriels (LOSI), Institut Charles Delaunay (ICD), Université de Technologie de Troyes (UTT)-Centre National de la Recherche Scientifique (CNRS)-Université de Technologie de Troyes (UTT)-Centre National de la Recherche Scientifique (CNRS), Institute of Genetics and Biophysics, CNR, Naples, Università degli studi di Verona = University of Verona (UNIVR), Department of Molecular Medicine [Scripps Research Institute], The Scripps Research Institute [La Jolla, San Diego], Department of Physics, Indian Institute of Technology Kanpur (IIT Kanpur), Deptartment of Medical Biochemistry and Microbiology, Uppsala University, Department of Electrical and Computer Engineering [Waterloo] (ECE), University of Waterloo [Waterloo], University of Maryland School of Medicine, University of Maryland System, Institut National de l'Environnement Industriel et des Risques (INERIS), Institute of Pop. Genetics, CNR, Sassari, Interfaculty Institute for Genetics and Functional Genomics, Universität Greifswald - University of Greifswald, IT University of Copenhagen (ITU), Robertson Centre for Biostatistics, University of Glasgow, Centre for Causal Analyses in Translational Epidemiology, University of Bristol [Bristol]-Medical Research Council, King‘s College London, Jinan University [Guangzhou], Institute of Oceanology [China], School Medicine, University of Pittsburgh (PITT), Pennsylvania Commonwealth System of Higher Education (PCSHE)-Pennsylvania Commonwealth System of Higher Education (PCSHE), General Internal Medicine, Johns Hopkins School of Medicine, Johns Hopkins University School of Medicine [Baltimore], Shardna life science Pula Cagliari, Section Molecular Epidemiology, Leiden University Medical Center (LUMC), Department of Medicine, University of Eastern Finland-Kuopio University Hospital, Medstar Research Institute, Department of Cardiology, Ernst-Moritz-Arndt University, Center for Biological Sequence Analysis [Lyngby], Danmarks Tekniske Universitet = Technical University of Denmark (DTU), Department of Internal Medicine, University of Groningen and University Medical Center Groningen, Department of Epidemiology, Harvard School of Public Health, German Research Center for Environmental Health - Helmholtz Center München (GmbH), Metacohorts Consortium, INEOS Technologies (SWITZERLAND), MRC Epidemiology Unit, University of Cambridge [UK] (CAM)-Institute of Metabolic Science, University of Edinburgh, School of Population Health [Crawley, Western Australia], The University of Western Australia (UWA), Institute of Genetics and Biophysics, National Research Council of Italy | Consiglio Nazionale delle Ricerche (CNR), The Scripps Translational Science Institute and Scripps Health, Tulane Center for Cardiovascular Health, Tulane University Health Sciences Center, Centre for Population Health Sciences, Genomic Research Laboratory, Service of Infectious Disease, Hôpitaux Universitaires de Genève (HUG), Infectious diseases division, Department of internal medicine, Washington University in Saint Louis (WUSTL), Luleå University of Technology (LUT), Recherche en épidémiologie et biostatistique, Université Paris-Sud - Paris 11 (UP11)-Institut National de la Santé et de la Recherche Médicale (INSERM), Austrian Institute of Technology [Vienna] (AIT), Icahn School of Medicine at Mount Sinai [New York] (MSSM), Department of Rheumatology and Clinical Epidemiology, Leiden University Medical Center (LUMC), Department of Rheumatology and Clinical Epidemiology [Leiden University Medical Center] (LUMC), Leiden University Medical Center (LUMC), Universiteit Leiden-Universiteit Leiden-Leiden University Medical Center (LUMC), Universiteit Leiden-Universiteit Leiden, Department of Biostatistics and Center for Statistical Genetics, University of Michigan [Ann Arbor], University of Michigan System-University of Michigan System, University of Virginia, Tampere University Hospital, Department of Medical Genetics, Université de Lausanne = University of Lausanne (UNIL), Department of Pathological Biochemistry, Royal Infirmary, Oxford University, University of Oxford, University of Newcastle [Callaghan, Australia] (UoN), Department of neurology, Institute of Metabolic Science, MRC, The Wellcome Trust Centre for Human Genetics [Oxford], Uppsala Universitet [Uppsala], QIMR Berghofer Medical Research Institute, Institute of Genetic Epidemiology [Neuherberg, Germany], Institute of Human Genetics, Helmholtz Zentrum München = German Research Center for Environmental Health, Schizophrenia Research Institute [Sydney], Department of Genetics, University of North Carolina System (UNC)-University of North Carolina System (UNC), Vrije Universiteit Brussel (VUB), Population Health Sciences and Education, St George's University of London, Centre Hospitalier Universitaire Vaudois [Lausanne] (CHUV), Institute of Health Sciences and Biocenter Oulu, University of Oulu, Medizinische Klinik und Poliklinik, Johannes Gutenberg - Universität Mainz = Johannes Gutenberg University (JGU), Institute of Clinical Chemistry and Laboratory Medicine, Icelandic Heart Association, Heart Preventive Clinic and Research Institute, Departments of Epidemiology and Nutrition, Institute of Epidemiology [Neuherberg] (EPI), Medical University Graz, Transplantation Laboratory [Helsinki], Haartman Institute [Helsinki], Faculty of Medecine [Helsinki], Helsingin yliopisto = Helsingfors universitet = University of Helsinki-Helsingin yliopisto = Helsingfors universitet = University of Helsinki-Faculty of Medecine [Helsinki], Helsingin yliopisto = Helsingfors universitet = University of Helsinki-Helsingin yliopisto = Helsingfors universitet = University of Helsinki, Department of Chronic Disease Prevention, National Institute for Health and Welfare [Helsinki], Dept. of Epidemiology Research, Statens Serum Institut [Copenhagen], CLinical Psychology, Genetics and Pathology, Geriatric Rehabilitation Unit, Azienda Sanitaria Firenze, Center For Narcolepsy, Stanford University, Centre for Bone and Arthritis Research, University of Gothenburg (GU)-Institute of Medicine, MRC Human Gentics Unit, Inst Genet and Mol Med, Western General Hospital, Edinburgh, University of Maryland School of Medicine [Baltimore, MD, USA], Génétique des maladies multifactorielles (GMM), Université de Lille, Droit et Santé-Centre National de la Recherche Scientifique (CNRS), Department of Physics [Stockholm], Stockholm University, University of Bristol [Bristol], Universiteit Leiden, Department of Epidemiology, University of Washington, University of Washington [Seattle], Department of Epidemiology [Rotterdam], University of Groningen [Groningen], Dutch Initiative on Crohn and Colitis (ICC), Icelandic Heart Association [Kopavogur, Iceland] (IHA), Department of Physiology and Biophysics [Jackson, MS, USA], University of Southern Mississippi (USM), Human Genetics Branch, National Institutes of Health [Bethesda] (NIH)-National Institute of Mental Health (NIMH), Faculty of Medicine and Life Sciences [Tampere], University of Tampere [Finland], German Center for Cardiovascular Research (DZHK), Berlin Institute of Health (BIH), MRC Centre for Neuropsychiatric Genetics and Genomics, Medical Research Council-Cardiff University, Department of Social Medicine, School of Medicine [Los Angeles], University of California [Los Angeles] (UCLA), University of California (UC)-University of California (UC), Department of Medicine [Aurora, CO, USA], University of Colorado [Denver], Institute for Molecular Medicine Finland [Helsinki] (FIMM), Helsinki Institute of Life Science (HiLIFE), Mathematical Institute [Oxford] (MI), Institute of Psychiatry, Psychology & Neuroscience, King's College London, LifeLines Cohort Study, CHARGE Inflammation Working Group, Ligthart, S., Vaez, A., Vosa, U., Stathopoulou, M. G., de Vries, P. S., Prins, B. P., Van der Most, P. J., Tanaka, T., Naderi, E., Rose, L. M., Wu, Y., Karlsson, R., Barbalic, M., Lin, H., Pool, R., Zhu, G., Mace, A., Sidore, C., Trompet, S., Mangino, M., Sabater-Lleal, M., Kemp, J. P., Abbasi, A., Kacprowski, T., Verweij, N., Smith, A. V., Huang, T., Marzi, C., Feitosa, M. F., Lohman, K. K., Kleber, M. E., Milaneschi, Y., Mueller, C., Huq, M., Vlachopoulou, E., Lyytikainen, L. -P., Oldmeadow, C., Deelen, J., Perola, M., Zhao, J. H., Feenstra, B., Alizadeh, B. Z., Boezen, H. M., Franke, L., van der Harst, P., Navis, G., Rots, M., Snieder, H., Swertz, M., Wolffenbuttel, B. H. R., Wijmenga, C., Amini, M., Benjamin, E., Chasman, D. I., Dehghan, A., Ahluwalia, T. S., Meigs, J., Tracy, R., Bis, J., Eiriksdottir, G., Pankratz, N., Gross, M., Rainer, A., Wilson, J. G., Psaty, B. M., Dupuis, J., Prins, B., Vaso, U., Stathopoulou, M., Lehtimaki, T., Koenig, W., Jamshidi, Y., Siest, S., Uitterlinden, A. G., Abdollahi, M., Schnabel, R., Schick, U. M., Nolte, I. M., Kraja, A., Hsu, Y. -H., Tylee, D. S., Zwicker, A., Uher, R., Davey-Smith, G., Morrison, A. C., Hicks, A., van Duijn, C. M., Ward-Caviness, C., Boerwinkle, E., Rotter, J., Rice, K., Lange, L., de Geus, E., Morris, A. P., Makela, K. M., Stacey, D., Eriksson, J., Frayling, T. M., Slagboom, E. P., Lahti, J., Schraut, K. E., Fornage, M., Suktitipat, B., Chen, W. -M., Li, X., Nutile, T., Malerba, G., Luan, J., Bak, T., Schork, N., Del Greco, M. F., Thiering, E., Mahajan, A., Marioni, R. E., Mihailov, E., Ozel, A. B., Zhang, W., Nethander, M., Cheng, Y. -C., Aslibekyan, S., Ang, W., Gandin, I., Yengo, L., Portas, L., Kooperberg, C., Hofer, E., Rajan, K. B., Schurmann, C., den Hollander, W., Zhao, J., Draisma, H. H. M., Ford, I., Timpson, N., Teumer, A., Huang, H., Wahl, S., Liu, Y., Huang, J., Uh, H. -W., Geller, F., Joshi, P. K., Yanek, L. R., Trabetti, E., Lehne, B., Vozzi, D., Verbanck, M., Biino, G., Saba, Y., Meulenbelt, I., O'Connell, J. R., Laakso, M., Giulianini, F., Magnusson, P. K. E., Ballantyne, C. M., Hottenga, J. J., Montgomery, G. W., Rivadineira, F., Rueedi, R., Steri, M., Herzig, K. -H., Stott, D. J., Menni, C., Franberg, M., S, t. Pourcain B., Felix, S. B., Pers, T. H., Bakker, S. J. L., Kraft, P., Peters, A., Vaidya, D., Delgado, G., Smit, J. H., Grossmann, V., Sinisalo, J., Seppala, I., Williams, S. R., Holliday, E. G., Moed, M., Langenberg, C., Raikkonen, K., Ding, J., Campbell, H., Sale, M. M., Chen, Y. -D. I., James, A. L., Ruggiero, D., Soranzo, N., Hartman, C. A., Smith, E. N., Berenson, G. S., Fuchsberger, C., Hernandez, D., Tiesler, C. M. T., Giedraitis, V., Liewald, D., Fischer, K., Mellstrom, D., Larsson, A., Wang, Y., Scott, W. R., Lorentzon, M., Beilby, J., Ryan, K. A., Pennell, C. E., Vuckovic, D., Balkau, B., Concas, M. P., Schmidt, R., Mendes de Leon, C. F., Bottinger, E. P., Kloppenburg, M., Paternoster, L., Boehnke, M., Musk, A. W., Willemsen, G., Evans, D. M., Madden, P. A. F., Kahonen, M., Kutalik, Z., Zoledziewska, M., Karhunen, V., Kritchevsky, S. B., Sattar, N., Lachance, G., Clarke, R., Harris, T. B., Raitakari, O. T., Attia, J. R., van Heemst, D., Kajantie, E., Sorice, R., Gambaro, G., Scott, R. A., Hicks, A. A., Ferrucci, L., Standl, M., Lindgren, C. M., Starr, J. M., Karlsson, M., Lind, L., Li, J. Z., Chambers, J. C., Mori, T. A., de Geus, E. J. C. N., Heath, A. C., Martin, N. G., Auvinen, J., Buckley, B. M., de Craen, A. J. M., Waldenberger, M., Strauch, K., Meitinger, T., Scott, R. J., Mcevoy, M., Beekman, M., Bombieri, C., Ridker, P. M., Mohlke, K. L., Pedersen, N. L., Boomsma, D. I., Whitfield, J. B., Strachan, D. P., Hofman, A., Vollenweider, P., Cucca, F., Jarvelin, M. -R., Jukema, J. W., Spector, T. D., Hamsten, A., Zeller, T., Nauck, M., Gudnason, V., Qi, L., Grallert, H., Borecki, I. B., Rotter, J. I., Marz, W., Wild, P. S., Lokki, M. -L., Boyle, M., Salomaa, V., Melbye, M., Eriksson, J. G., Wilson, J. F., Penninx, B. W. J. H., Becker, D. M., Worrall, B. B., Gibson, G., Krauss, R. M., Ciullo, M., Zaza, G., Wareham, N. J., Oldehinkel, A. J., Palmer, L. J., Murray, S. S., Pramstaller, P. P., Bandinelli, S., Heinrich, J., Ingelsson, E., Deary, I. J., Magi, R., Vandenput, L., Desch, K. C., Kooner, J. S., Ohlsson, C., Hayward, C., Shuldiner, A. R., Arnett, D. K., Beilin, L. J., Robino, A., Froguel, P., Pirastu, M., Jess, T., Loos, R. J. F., Evans, D. A., Schmidt, H., Slagboom, P. E., Tracy, R. P., Visvikis-Siest, S., Reiner, A. P., Bis, J. C., Franco, O. H., Benjamin, E. J., AGEM - Amsterdam Gastroenterology Endocrinology Metabolism, Graduate School, Epidemiology, Internal Medicine, Groningen Institute for Organ Transplantation (GIOT), Lifestyle Medicine (LM), Groningen Kidney Center (GKC), Interdisciplinary Centre Psychopathology and Emotion regulation (ICPE), Cardiovascular Centre (CVC), Life Course Epidemiology (LCE), Groningen Institute for Gastro Intestinal Genetics and Immunology (3GI), Stem Cell Aging Leukemia and Lymphoma (SALL), Real World Studies in PharmacoEpidemiology, -Genetics, -Economics and -Therapy (PEGET), VU University medical center, Psychiatry, Amsterdam Neuroscience - Mood, Anxiety, Psychosis, Stress & Sleep, APH - Mental Health, APH - Methodology, APH - Digital Health, Biological Psychology, APH - Personalized Medicine, APH - Health Behaviors & Chronic Diseases, Universität Heidelberg [Heidelberg], University of Verona (UNIVR), Department of Molecular and Experimental Medicine, The Scripps Research Institute, The Scripps Research Institute, Université Grenoble Alpes - UFR Sciences de l'Homme et de la Société (UGA UFR SHS), Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), IT University of Copenhagen, Technical University of Denmark [Lyngby] (DTU), Consiglio Nazionale delle Ricerche (CNR), University of Virginia [Charlottesville], Université de Lausanne (UNIL), University of Oxford [Oxford], University of Newcastle [Australia] (UoN), Centre d'économie industrielle i3 (CERNA i3), Centre National de la Recherche Scientifique (CNRS)-MINES ParisTech - École nationale supérieure des mines de Paris, Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL), Helmholtz-Zentrum München (HZM), Laboratoire Interuniversitaire des Systèmes Atmosphériques (LISA (UMR_7583)), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris Diderot - Paris 7 (UPD7)-Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12)-Centre National de la Recherche Scientifique (CNRS), Universitätsmedizin der Johannes-Gutenberg Universität Mainz, University of Helsinki-University of Helsinki-Faculty of Medecine [Helsinki], University of Helsinki-University of Helsinki, Cardiff University-Medical Research Council, University of California-University of California, and DE CARVALHO, Philippe

Subjects
0301 basic medicine, Male, Netherlands Twin Register (NTR), Bipolar Disorder, LD SCORE REGRESSION, [SDV]Life Sciences [q-bio], Genome-wide association study, [SDV.GEN] Life Sciences [q-bio]/Genetics, Body Mass Index, inflammatory disorder, 80 and over, WIDE ASSOCIATION, EPIDEMIOLOGY, ta318, International HapMap Project, Child, Genetics (clinical), 2. Zero hunger, Genetics, Genetics & Heredity, Aged, 80 and over, [SDV.MHEP] Life Sciences [q-bio]/Human health and pathology, C-reactive proteingenome-wide association studyinflammationMendelian randomizationinflammatory disordersDEPICTcoronary artery diseaseschizophreniasystem biology, system biology, DEPICT, Mendelian Randomization Analysis, 11 Medical And Health Sciences, Middle Aged, C-reactive protein, coronary artery disease, genome-wide association study, inflammation, inflammatory disorders, Mendelian randomization, schizophrenia, Adolescent, Adult, Aged, Biomarkers, C-Reactive Protein, Female, Genetic Loci, Genome-Wide Association Study, Humans, Inflammation, Liver, Metabolic Networks and Pathways, Schizophrenia, Young Adult, 3. Good health, [SDV] Life Sciences [q-bio], Medical genetics, Biomarker (medicine), Life Sciences & Biomedicine, Human, medicine.medical_specialty, CHARGE Inflammation Working Group, Biology, IMMUNITY, ta3111, Article, 03 medical and health sciences, SDG 3 - Good Health and Well-being, medicine, CORONARY-HEART-DISEASE, Mendelian Randomization Analysi, 1000 Genomes Project, METAANALYSIS, Genetic association, [SDV.GEN]Life Sciences [q-bio]/Genetics, Science & Technology, ta1184, Metabolic Networks and Pathway, Biomarker, INSTRUMENTS, 06 Biological Sciences, 030104 developmental biology, [SDV.MHEP]Life Sciences [q-bio]/Human health and pathology, LifeLines Cohort Study
Abstract

International audience; C-reactive protein (CRP) is a sensitive biomarker of chronic low-grade inflammation and is associated with multiple complex diseases. The genetic determinants of chronic inflammation remain largely unknown, and the causal role of CRP in several clinical outcomes is debated. We performed two genome-wide association studies (GWASs), on HapMap and 1000 Genomes imputed data, of circulating amounts of CRP by using data from 88 studies comprising 204,402 European individuals. Additionally, we performed in silico functional analyses and Mendelian randomization analyses with several clinical outcomes. The GWAS meta-analyses of CRP revealed 58 distinct genetic loci (p < 5 × 10-8). After adjustment for body mass index in the regression analysis, the associations at all except three loci remained. The lead variants at the distinct loci explained up to 7.0% of the variance in circulating amounts of CRP. We identified 66 gene sets that were organized in two substantially correlated clusters, one mainly composed of immune pathways and the other characterized by metabolic pathways in the liver. Mendelian randomization analyses revealed a causal protective effect of CRP on schizophrenia and a risk-increasing effect on bipolar disorder. Our findings provide further insights into the biology of inflammation and could lead to interventions for treating inflammation and its clinical consequences.Copyright © 2018 American Society of Human Genetics. All rights reserved.

Published
2018
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16. Large-scale exome array summary statistics resources for glycemic traits to aid effector gene prioritization [version 1; peer review: 2 approved]

Author

Natasha H. J. Ng, Sara M. Willems, Jian'an Luan, Rebecca S. Fine, Juan Fernandez, Jennifer Wessel, Eleanor Wheeler, Gaelle Marenne, Hidetoshi Kitajima, Hanieh Yaghootkar, Xueling Sim, Ian J. Deary, Sai Chen, Shuai Wang, Yii-Der Ida Chen, Caroline Hayward, Yuning Chen, Jennifer L. Asimit, Claudia Langenberg, Tibor V. Varga, Archie Campbell, Rona J. Strawbridge, Shuang Feng, Tarunveer S. Ahluwalia, Erica L. Kleinbrink, Emil V. Appel, Ping An, Lawrence F. Bielak, Dan E. Arking, Jennifer A. Brody, Nathan A. Bihlmeyer, David Porteous, Ayse Demirkan, Audrey Y. Chu, Franco Giulianini, James S. Floyd, Stefan Gustafsson, Xiuqing Guo, Johanna Jakobsdottir, Anne U. Jackson, Stavroula Kanoni, Richard A. Jensen, Igor Rudan, Man Li, Sirkka Keinanen-Kiukaanniemi, Alisa K. Manning, Yingchang Lu, Karina Meidtner, Jonathan Marten, Giorgio Pistis, Taulant Muka, Kenneth M. Rice, Bram Prins, Albert Vernon Smith, Serena Sanna, Lorraine Southam, Jennifer A. Smith, Vinicius Tragante, Heather M. Stringham, Helen R. Warren, Sander W. van der Laan, Andrianos M. Yiorkas, Jie Yao, Wei Zhao, Weihua Zhang, Heather M. Highland, Mariaelisa Graff, Eirini Marouli, Anne E. Justice, Wesam A. Alhejily, Saima Afaq, Folkert W. Asselbergs, Najaf Amin, Michiel L. Bots, Lori L. Bonnycastle, Ji Chen, Ivan Brandslund, Abbas Dehghan, John Danesh, Tapani Ebeling, Jessica D. Faul, Aliki-Eleni Farmaki, Steve Franks, Paul W. Franks, Anette P. Gjesing, Andreas Fritsche, Göran Hallmans, Mark O. Goodarzi, Karl-Heinz Herzig, Tamara B. Harris, Min A Jhun, Marie-France Hivert, Marit E. Jørgensen, Torben Jørgensen, Eero Kajantie, Pekka Jousilahti, Sharon L.R. Kardia, Maria Karaleftheri, Heikki A. Koistinen, Leena Kinnunen, Peter Kovacs, Pirjo Komulainen, Markku Laakso, Johanna Kuusisto, Aaron Leong, Lenore J. Launer, Jocelyn E. Manning Fox, Jaana Lindström, Nisa M. Maruthur, Satu Männistö, Antonella Mulas, Leena Moilanen, Matthew Neville, Mike A. Nalls, Alison Pattie, James S. Pankow, Hannu Puolijoki, Eva R.B. Petersen, Paul Redmond, Asif Rasheed, Michael Roden, Frida Renström, Juha Saltevo, Danish Saleheen, Sylvain Sebert, Kai Savonen, Alena Stančáková, Kerrin S. Small, Konstantin Strauch, Jakob Stokholm, Betina H. Thuesen, Juha Auvinen, E-Shyong Tai, Emmanouil Tsafantakis, Anke Tönjes, Jaakko Tuomilehto, Tiinamaija Tuomi, Marja Vääräsmäki, Matti Uusitupa, Magdalena Zoledziewska, Ilonca Vaartjes, Beverley Balkau, Goncalo Abecasis, Alexandra I. Blakemore, Hans Bisgaard, Heiner Boeing, Ruth J.F. Loos, Matthias Blüher, Klaus Bønnelykke, Eric Boerwinkle, Mark J. Caulfield, Erwin P. Bottinger, Daniel I. Chasman, John C. Chambers, Francis S. Collins, Ching-Yu Cheng, Francesco Cucca, Josef Coresh, George Dedoussis, Gert J. de Borst, Hester M. den Ruijter, Panos Deloukas, Ele Ferrannini, Michele K. Evans, Harald Grallert, Oscar H. Franco, Arfan Ikram, Joel N. Hirschhorn, Fredrik Karpe, Erik Ingelsson, Wieland Kiess, Carolina Medina-Gomez, Kay-Tee Kaw, Antje Körner, Jaspal S. Kooner, Cecilia M. Lindgren, Timo Lakka, Ching-Ti Liu, Leonard Lipovich, Patrick E. MacDonald, Jun Liu, Andrew D. Morris, Karen L. Mohlke, Alison Murray, Patricia B. Munroe, Gerard Pasterkamp, Colin N. A . Palmer, Patricia A. Peyser, Oluf Pedersen, Paul M. Ridker, Rainer Rauramaa, Patrik Rorsman, Olov Rolandsson, Veikko Salomaa, Frits R. Rosendaal, Robert Sladek, Matthias B. Schulze, Michael Stumvoll, Timothy D. Spector, Mark Walker, Cornelia M. van Duijn, David R. Weir, Nick J. Wareham, Tien Yin Wong, James G. Wilson, Alan B. Zonderman, Eleftheria Zeggini, Andrew P. Morris, Jerome I. Rotter, Jose C. Florez, Michael Boehnke, James B. Meigs, Mark I. McCarthy, Robert A. Scott, Anubha Mahajan, Inês Barroso, Anna L. Gloyn, Michael A. Province, Niels Grarup, Ruifang Li-Gao, Jette Bork-Jensen, Yongmei Liu, Allan Linneberg, Leslie A. Lange, Sandosh Padmanabhan, Gail Davies, Lars Lind, Bruce M. Psaty, Tea Skaaby, Torben Hansen, Ozren Polasek, John M. Starr, Dennis O. Mook-Kanamori, Vilmundur Gudnason, Kent D. Taylor, Marjo-Riitta Järvelin, Renée de Mutsert, Paul Elliott, Josée Dupuis, Blair H. Smith, and Andrew T. Hattersley

Subjects
exome chip, glycaemic traits, genetic discovery, effector genes, summary statistics resources, eng, Medicine, Science
Abstract

Background Genome-wide association studies for glycemic traits have identified hundreds of loci associated with these biomarkers of glucose homeostasis. Despite this success, the challenge remains to link variant associations to genes, and underlying biological pathways. Methods To identify coding variant associations which may pinpoint effector genes at both novel and previously established genome-wide association loci, we performed meta-analyses of exome-array studies for four glycemic traits: glycated hemoglobin (HbA1c, up to 144,060 participants), fasting glucose (FG, up to 129,665 participants), fasting insulin (FI, up to 104,140) and 2hr glucose post-oral glucose challenge (2hGlu, up to 57,878). In addition, we performed network and pathway analyses. Results Single-variant and gene-based association analyses identified coding variant associations at more than 60 genes, which when combined with other datasets may be useful to nominate effector genes. Network and pathway analyses identified pathways related to insulin secretion, zinc transport and fatty acid metabolism. HbA1c associations were strongly enriched in pathways related to blood cell biology. Conclusions Our results provided novel glycemic trait associations and highlighted pathways implicated in glycemic regulation. Exome-array summary statistic results are being made available to the scientific community to enable further discoveries.

Published
2023
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17. Association Between Whole Blood–Derived Mitochondrial DNA Copy Number, Low‐Density Lipoprotein Cholesterol, and Cardiovascular Disease Risk

Author

Xue Liu, Xianbang Sun, Yuankai Zhang, Wenqing Jiang, Meng Lai, Kerri L. Wiggins, Laura M. Raffield, Lawrence F. Bielak, Wei Zhao, Achilleas Pitsillides, Jeffrey Haessler, Yinan Zheng, Thomas W. Blackwell, Jie Yao, Xiuqing Guo, Yong Qian, Bharat Thyagarajan, Nathan Pankratz, Stephen S. Rich, Kent D. Taylor, Patricia A. Peyser, Susan R. Heckbert, Sudha Seshadri, Eric Boerwinkle, Megan L. Grove, Nicholas B. Larson, Jennifer A. Smith, Ramachandran S. Vasan, Annette L. Fitzpatrick, Myriam Fornage, Jun Ding, April P. Carson, Goncalo Abecasis, Josée Dupuis, Alexander Reiner, Charles Kooperberg, Lifang Hou, Bruce M. Psaty, James G. Wilson, Daniel Levy, Jerome I. Rotter, Joshua C. Bis, Claudia L. Satizabal, Dan E. Arking, and Chunyu Liu

Subjects
cardiometabolic risk factors, cardiovascular disease, low‐density lipoprotein cholesterol, Mendelian randomization, mitochondrial DNA copy number, vascular atherosclerosis, Diseases of the circulatory (Cardiovascular) system, RC666-701
Abstract

Background The relationship between mitochondrial DNA copy number (mtDNA CN) and cardiovascular disease remains elusive. Methods and Results We performed cross‐sectional and prospective association analyses of blood‐derived mtDNA CN and cardiovascular disease outcomes in 27 316 participants in 8 cohorts of multiple racial and ethnic groups with whole‐genome sequencing. We also performed Mendelian randomization to explore causal relationships of mtDNA CN with coronary heart disease (CHD) and cardiometabolic risk factors (obesity, diabetes, hypertension, and hyperlipidemia). P

Published
2023
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18. Whole genome sequence analyses of brain imaging measures in the Framingham Study

Author

David Tirschwell, Claudia L Satizabal, Amol Shetty, Josee Dupuis, Joanne Curran, Alexa Beiser, Chloé Sarnowski, Sean David, Tamar Sofer, Shabnam Salimi, L. Adrienne Cupples, Sudha Seshadri, Vasan Ramachandran, and Biswapriya Misra

Subjects
0301 basic medicine, Male, Neuroimaging, Genome-wide association study, Biology, Genome, Article, 03 medical and health sciences, 0302 clinical medicine, Framingham Heart Study, Genetic variation, medicine, Humans, Prospective Studies, Gene, Aged, Genetics, Brain, Genetic Variation, DNA, Organ Size, Middle Aged, medicine.disease, Magnetic Resonance Imaging, 3. Good health, Minor allele frequency, 030104 developmental biology, Phenotype, Massachusetts, Dementia, Female, Neurology (clinical), Alzheimer's disease, Sequence Analysis, 030217 neurology & neurosurgery, Genome-Wide Association Study
Abstract

ObjectiveWe sought to identify rare variants influencing brain imaging phenotypes in the Framingham Heart Study by performing whole genome sequence association analyses within the Trans-Omics for Precision Medicine Program.MethodsWe performed association analyses of cerebral and hippocampal volumes and white matter hyperintensity (WMH) in up to 2,180 individuals by testing the association of rank-normalized residuals from mixed-effect linear regression models adjusted for sex, age, and total intracranial volume with individual variants while accounting for familial relatedness. We conducted gene-based tests for rare variants using (1) a sliding-window approach, (2) a selection of functional exonic variants, or (3) all variants.ResultsWe detected new loci in 1p21 for cerebral volume (minor allele frequency [MAF] 0.005, p = 10−8) and in 16q23 for hippocampal volume (MAF 0.05, p = 2.7 × 10−8). Previously identified associations in 12q24 for hippocampal volume (rs7294919, p = 4.4 × 10−4) and in 17q25 for WMH (rs7214628, p = 2.0 × 10−3) were confirmed. Gene-based tests detected associations (p ≤ 2.3 × 10−6) in new loci for cerebral (5q13, 8p12, 9q31, 13q12-q13, 15q24, 17q12, 19q13) and hippocampal volumes (2p12) and WMH (3q13, 4p15) including Alzheimer disease– (UNC5D) and Parkinson disease–associated genes (GBA). Pathway analyses evidenced enrichment of associated genes in immunity, inflammation, and Alzheimer disease and Parkinson disease pathways.ConclusionsWhole genome sequence–wide search reveals intriguing new loci associated with brain measures. Replication of novel loci is needed to confirm these findings.

Published
2017

19. Assisted clustering of gene expression data using regulatory data from partially overlapping sets of individuals

Author

Wenqing Jiang, Roby Joehanes, Daniel Levy, George T O’Connor, and Josée Dupuis

Subjects
Multi-omics data integration, Gene expression, Clustering, DNA methylation, Genotype, Framingham Heart Study, Biotechnology, TP248.13-248.65, Genetics, QH426-470
Abstract

Abstract Background As omics measurements profiled on different molecular layers are interconnected, integrative approaches that incorporate the regulatory effect from multi-level omics data are needed. When the multi-level omics data are from the same individuals, gene expression (GE) clusters can be identified using information from regulators like genetic variants and DNA methylation. When the multi-level omics data are from different individuals, the choice of integration approaches is limited. Methods We developed an approach to improve GE clustering from microarray data by integrating regulatory data from different but partially overlapping sets of individuals. We achieve this through (1) decomposing gene expression into the regulated component and the other component that is not regulated by measured factors, (2) optimizing the clustering goodness-of-fit objective function. We do not require the availability of different omics measurements on all individuals. A certain amount of individual overlap between GE data and the regulatory data is adequate for modeling the regulation, thus improving GE clustering. Results A simulation study shows that the performance of the proposed approach depends on the strength of the GE-regulator relationship, degree of missingness, data dimensionality, sample size, and the number of clusters. Across the various simulation settings, the proposed method shows competitive performance in terms of accuracy compared to the alternative K-means clustering method, especially when the clustering structure is due mostly to the regulated component, rather than the unregulated component. We further validate the approach with an application to 8,902 Framingham Heart Study participants with data on up to 17,873 genes and regulation information of DNA methylation and genotype from different but partially overlapping sets of participants. We identify clustering structures of genes associated with pulmonary function while incorporating the predicted regulation effect from the measured regulators. We further investigate the over-representation of these GE clusters in pathways of other diseases that may be related to lung function and respiratory health. Conclusion We propose a novel approach for clustering GE with the assistance of regulatory data that allowed for different but partially overlapping sets of individuals to be included in different omics data.

Published
2022
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20. Leveraging family history in genetic association analyses of binary traits

Author

Yixin Zhang, James B. Meigs, Ching-Ti Liu, Josée Dupuis, and Chloé Sarnowski

Subjects
Family history, GWAS, Meta-analysis, Biotechnology, TP248.13-248.65, Genetics, QH426-470
Abstract

Abstract Background Considering relatives’ health history in logistic regression for case–control genome-wide association studies (CC-GWAS) may provide new information that increases accuracy and power to detect disease associated genetic variants. We conducted simulations and analyzed type 2 diabetes (T2D) data from the Framingham Heart Study (FHS) to compare two methods, liability threshold model conditional on both case–control status and family history (LT-FH) and Fam-meta, which incorporate family history into CC-GWAS. Results In our simulation scenario of trait with modest T2D heritability (h2 = 0.28), variant minor allele frequency ranging from 1% to 50%, and 1% of phenotype variance explained by the genetic variants, Fam-meta had the highest overall power, while both methods incorporating family history were more powerful than CC-GWAS. All three methods had controlled type I error rates, while LT-FH was the most conservative with a lower-than-expected error rate. In addition, we observed a substantial increase in power of the two familial history methods compared to CC-GWAS when the prevalence of the phenotype increased with age. Furthermore, we showed that, when only the phenotypes of more distant relatives were available, Fam-meta still remained more powerful than CC-GWAS, confirming that leveraging disease history of both close and distant relatives can increase power of association analyses. Using FHS data, we confirmed the well-known association of TCF7L2 region with T2D at the genome-wide threshold of P-value

Published
2022
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21. Whole genome sequence association analysis of fasting glucose and fasting insulin levels in diverse cohorts from the NHLBI TOPMed program

Author

Daniel DiCorpo, Sheila M. Gaynor, Emily M. Russell, Kenneth E. Westerman, Laura M. Raffield, Timothy D. Majarian, Peitao Wu, Chloé Sarnowski, Heather M. Highland, Anne Jackson, Natalie R. Hasbani, Paul S. de Vries, Jennifer A. Brody, Bertha Hidalgo, Xiuqing Guo, James A. Perry, Jeffrey R. O’Connell, Samantha Lent, May E. Montasser, Brian E. Cade, Deepti Jain, Heming Wang, Ricardo D’Oliveira Albanus, Arushi Varshney, Lisa R. Yanek, Leslie Lange, Nicholette D. Palmer, Marcio Almeida, Juan M. Peralta, Stella Aslibekyan, Abigail S. Baldridge, Alain G. Bertoni, Lawrence F. Bielak, Chung-Shiuan Chen, Yii-Der Ida Chen, Won Jung Choi, Mark O. Goodarzi, James S. Floyd, Marguerite R. Irvin, Rita R. Kalyani, Tanika N. Kelly, Seonwook Lee, Ching-Ti Liu, Douglas Loesch, JoAnn E. Manson, Ryan L. Minster, Take Naseri, James S. Pankow, Laura J. Rasmussen-Torvik, Alexander P. Reiner, Muagututi’a Sefuiva Reupena, Elizabeth Selvin, Jennifer A. Smith, Daniel E. Weeks, Huichun Xu, Jie Yao, Wei Zhao, Stephen Parker, Alvaro Alonso, Donna K. Arnett, John Blangero, Eric Boerwinkle, Adolfo Correa, L. Adrienne Cupples, Joanne E. Curran, Ravindranath Duggirala, Jiang He, Susan R. Heckbert, Sharon L. R. Kardia, Ryan W. Kim, Charles Kooperberg, Simin Liu, Rasika A. Mathias, Stephen T. McGarvey, Braxton D. Mitchell, Alanna C. Morrison, Patricia A. Peyser, Bruce M. Psaty, Susan Redline, Alan R. Shuldiner, Kent D. Taylor, Ramachandran S. Vasan, Karine A. Viaud-Martinez, Jose C. Florez, James G. Wilson, Robert Sladek, Stephen S. Rich, Jerome I. Rotter, Xihong Lin, Josée Dupuis, James B. Meigs, Jennifer Wessel, and Alisa K. Manning

Subjects
Biology (General), QH301-705.5
Abstract

This study of 23,000 non-diabetic individuals highlights loci associated with fasting glucose and fasting insulin in diverse cohorts with whole genome sequence data.

Published
2022
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23. Genetic association tests in family samples for multi-category phenotypes

Author

Shuai Wang, James B. Meigs, and Josée Dupuis

Subjects
EGEE, Score test, Wald test, Framingham heart study, Family samples, Categorical, Biotechnology, TP248.13-248.65, Genetics, QH426-470
Abstract

Abstract Background Advancements in statistical methods and sequencing technology have led to numerous novel discoveries in human genetics in the past two decades. Among phenotypes of interest, most attention has been given to studying genetic associations with continuous or binary traits. Efficient statistical methods have been proposed and are available for both types of traits under different study designs. However, for multinomial categorical traits in related samples, there is a lack of efficient statistical methods and software. Results We propose an efficient score test to analyze a multinomial trait in family samples, in the context of genome-wide association/sequencing studies. An alternative Wald statistic is also proposed. We also extend the methodology to be applicable to ordinal traits. We performed extensive simulation studies to evaluate the type-I error of the score test, Wald test compared to the multinomial logistic regression for unrelated samples, under different allele frequency and study designs. We also evaluate the power of these methods. Results show that both the score and Wald tests have a well-controlled type-I error rate, but the multinomial logistic regression has an inflated type-I error rate when applied to family samples. We illustrated the application of the score test with an application to the Framingham Heart Study to uncover genetic variants associated with diabesity, a multi-category phenotype. Conclusion Both proposed tests have correct type-I error rate and similar power. However, because the Wald statistics rely on computer-intensive estimation, it is less efficient than the score test in terms of applications to large-scale genetic association studies. We provide computer implementation for both multinomial and ordinal traits.

Published
2021
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25. Quantitative pupillometry and radiographic markers of intracranial midline shift: A pilot study

Author

Ivy So Yeon Kim, Oluwafemi O. Balogun, Brenton R. Prescott, Hanife Saglam, DaiWai M. Olson, Kinley Speir, Sonja E. Stutzman, Nathan Schneider, Veronica Aguilera, Bethany L. Lussier, Stelios M. Smirnakis, Josée Dupuis, Asim Mian, David M. Greer, and Charlene J. Ong

Subjects
pupillometry, neurocritical care, herniation, radiology, midline shift, Neurology. Diseases of the nervous system, RC346-429
Abstract

BackgroundAsymmetric pupil reactivity or size can be early clinical indicators of midbrain compression due to supratentorial ischemic stroke or primary intraparenchymal hemorrhage (IPH). Radiographic midline shift is associated with worse functional outcomes and life-saving interventions. Better understanding of quantitative pupil characteristics would be a non–invasive, safe, and cost-effective way to improve identification of life-threatening mass effect and resource utilization of emergent radiographic imaging. We aimed to better characterize the association between midline shift at various anatomic levels and quantitative pupil characteristics.MethodsWe conducted a multicenter retrospective study of brain CT images within 75 min of a quantitative pupil observation from patients admitted to Neuro-ICUs between 2016 and 2020 with large (>1/3 of the middle cerebral artery territory) acute supratentorial ischemic stroke or primary IPH > 30 mm3. For each image, we measured midline shift at the septum pellucidum (MLS-SP), pineal gland shift (PGS), the ratio of the ipsilateral to contralateral midbrain width (IMW/CMW), and other exploratory markers of radiographic shift/compression. Pupil reactivity was measured using an automated infrared pupillometer (NeurOptics®, Inc.), specifically the proprietary algorithm for Neurological Pupil Index® (NPi). We used rank-normalization and linear mixed-effects models, stratified by diagnosis and hemorrhagic conversion, to test associations of radiographic markers of shift and asymmetric pupil reactivity (Diff NPi), adjusting for age, lesion volume, Glasgow Coma Scale, and osmotic medications.ResultsOf 53 patients with 74 CT images, 26 (49.1%) were female, and median age was 67 years. MLS-SP and PGS were greater in patients with IPH, compared to patients with ischemic stroke (6.2 v. 4.0 mm, 5.6 v. 3.4 mm, respectively). We found no significant associations between pupil reactivity and the radiographic markers of shift when adjusting for confounders. However, we found potentially relevant relationships between MLS-SP and Diff NPi in our IPH cohort (β = 0.11, SE 0.04, P = 0.01), and PGS and Diff NPi in the ischemic stroke cohort (β = 0.16, SE 0.09, P = 0.07).ConclusionWe found the relationship between midline shift and asymmetric pupil reactivity may differ between IPH and ischemic stroke. Our study may serve as necessary preliminary data to guide further prospective investigation into how clinical manifestations of radiographic midline shift differ by diagnosis and proximity to the midbrain.

Published
2022
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26. Causal relationship between obesity and vitamin D status: bi-directional Mendelian randomization analysis of multiple cohorts

Author

Benjamin Voight, Guillaume Pare, Ruth Loos, Michael Preuss, Åsa Johansson, Eco De Geus, Michael Weedon, Marjo-Riitta Jarvelin, Joyce Van Meurs, Torben Jørgensen, Kirsi Pietiläinen, Nicole Glazer, Mattias Lorentzon, Braxton Mitchell, Nicole Soranzo, Patricia Munroe, Ozren Polasek, Elisabeth Thiering, Marika Kaakinen, Carla Vogel, Jennie Hui, Elina Hypponen, ROBERTO ELOSUA, Amanda Bennett, Michael Stumvoll, Andrew Hattersley, Peter P Pramstaller, Lambertus Kiemeney, Sophie Visvikis-Siest, Vilmundur Gudnason, John Whittaker, Aroon Hingorani, Thor Aspelund, Dale Nyholt, Mary Feitosa, Vimal Karani, Mika Kähönen, Lachlan Coin, Malcolm Dunlop, Josee Dupuis, Terho Lehtimäki, Peter Visscher, Katja Aben, Daniel Witte, Cyrus Cooper, Stefan Pilz, Willem Ouwehand, Eleanor Wheeler, Peter Kovacs, Debbie A Lawlor, Kevin Jacobs, Evropi Theodoratou, Hana Lango Allen, Rosanda Mulic, Rui Li, Stephen Kritchevsky, Philippe Froguel, Soumya Raychaudhuri, Cornelia Van Duijn, Andrew Wood, Chiara Lanzani, Tonu Esko, Sadaf Farooqi, Reedik Mägi, Gerard Waeber, Claes Ohlsson, André Scherag, Marcus Kleber, Thomas Meitinger, Lina Zgaga, Denise Houston, Karl Michaëlsson, Robert Weyant, Thomas Wang, Paul Elliott, Robert Luben, Albert Vernon Smith, MANUELA UDA, Gonneke Willemsen, Mark McCarthy, Cecilia Lindgren, Olle Melander, Igor Rudan, Maris Teder-Laving, Liesbeth Vandenput, Vimaleswaran, K, Berry, Dj, Lu, C, Tikkanen, E, Pilz, S, Hiraki, Lt, Cooper, Jd, Dastani, Z, Li, R, Houston, Dk, Wood, Ar, Michaëlsson, K, Vandenput, L, Zgaga, L, YERGES ARMSTRONG, Lm, Mccarthy, Mi, Dupuis, J, Kaakinen, M, Kleber, Me, Jameson, K, Arden, N, Raitakari, O, Viikari, J, Lohman, Kk, Ferrucci, L, Melhus, H, Ingelsson, E, Byberg, L, Lind, L, Lorentzon, M, Salomaa, V, Campbell, H, Dunlop, M, Mitchell, Bd, Herzig, Kh, Pouta, A, Hartikainen, Al, Manunta, Paolo, Streeten, Ea, Theodoratou, E, Jula, A, Wareham, Nj, Ohlsson, C, Frayling, Tm, Kritchevsky, Sb, Spector, Td, Richards, Jb, Lehtimäki, T, Ouwehand, Wh, Kraft, P, Cooper, C, März, W, Power, C, Loos, Rj, Wang, Tj, Järvelin, Mr, Whittaker, Jc, Hingorani, Ad, Hyppönen, E., Council, Medical Research, Biological Psychology, EMGO+ - Lifestyle, Overweight and Diabetes, Institute for Molecular Medicine Finland, Haartman Institute (-2014), Transplantation Laboratory, Vimaleswaran, Karani S, Berry, Diane J, Lu, Chen, Tikkanen, Emmi, Hyppönen, Elina, Genetic Investigation of Anthropometric Traits (GIANT) Consortium, Hinney, Anke (Beitragende*r), Scherag, Susann (Beitragende*r), Hebebrand, Johannes (Beitragende*r), Epidemiology and Data Science, Psychiatry, EMGO - Lifestyle, overweight and diabetes, Genetic Investigation of Anthropometric Traits-GIANT Consortium, Speliotes, E.K., Willer, C.J., Berndt, S.I., Monda, K.L., Thorleifsson, G., Jackson, A.U., Allen, H.L., Lindgren, C.M., Jian'an, L., Mägi, R., Randall, J.C., Vedantam, S., Winkler, T.W., Qi, L., Workalemahu, T., Heid, I.M., Steinthorsdottir, V., Stringham, H.M., Weedon, M.N., Wheeler, E., Wood, A.R., Ferreira, T., Weyant, R.J., Segrè, A.V., Estrada, K., Liang, L., Nemesh, J., Park, J.H., Gustafsson, S., Kilpeläinen, T.O., Yang, J., Bouatia-Naji, N., Tõnu, E., Feitosa, M.F., Kutalik, Z., Mangino, M., Raychaudhuri, S., Scherag, A., Smith, A.V., Welch, R., Zhao, J.H., Aben, K.K., Absher, D.M., Amin, N., Dixon, A.L., Fisher, E., Glazer, N.L., Goddard, M.E., Heard-Costa, N.L., Hoesel, V., Hottenga, J.J., Johansson, Å., Johnson, T., Ketkar, S., Lamina, C., Li, S., Moffatt, M.F., Myers, R.H., Narisu, N., Perry, J.R., Peters, M.J., Preuss, M., Ripatti, S., Rivadeneira, F., Sandholt, C., Scott, L.J., Timpson, N.J., Tyrer, J.P., van Wingerden, S., Watanabe, R.M., White, C.C., Wiklund, F., Barlassina, C., Chasman, D.I., Cooper, M.N., Jansson, J.O., Lawrence, R.W., Pellikka, N., Prokopenko, I., Shi, J., Thiering, E., Alavere, H., Alibrandi, M.T., Almgren, P., Arnold, A.M., Aspelund, T., Atwood, L.D., Balkau, B., Balmforth, A.J., Bennett, A.J., Ben-Shlomo, Y., Bergman, R.N., Bergmann, S., Biebermann, H., Blakemore, A.I., Boes, T., Bonnycastle, L.L., Bornstein, S.R., Brown, M.J., Buchanan, T.A., Busonero, F., Campbell, H., Cappuccio, F.P., Cavalcanti-Proença, C., Chen, Y.D., Chen, C.M., Chines, P.S., Clarke, R., Coin, L., Connell, J., Day, I.N., Heijer, M., Duan, J., Ebrahim, S., Elliott, P., Elosua, R., Eiriksdottir, G., Erdos, M.R., Eriksson, J.G., Facheris, M.F., Felix, S.B., Fischer-Posovszky, P., Folsom, A.R., Friedrich, N., Freimer, N.B., Fu, M., Gaget, S., Gejman, P.V., Geus, E.J., Gieger, C., Gjesing, A.P., Goel, A., Goyette, P., Grallert, H., Gräßler, J., Greenawalt, D.M., Groves, C.J., Gudnason, V., Guiducci, C., Hartikainen, A.L., Hassanali, N., Hall, A.S., Havulinna, A.S., Hayward, C., Heath, A.C., Hengstenberg, C., Hicks, A.A., Hinney, A., Hofman, A., Homuth, G., Hui, J., Igl, W., Iribarren, C., Isomaa, B., Jacobs, K.B., Jarick, I., Jewell, E., John, U., Jørgensen, T., Jousilahti, P., Jula, A., Kaakinen, M., Kajantie, E., Kaplan, L.M., Kathiresan, S., Kettunen, J., Kinnunen, L., Knowles, J.W., Kolcic, I., König, I.R., Koskinen, S., Kovacs, P., Kuusisto, J., Kraft, P., Kvaløy, K., Laitinen, J., Lantieri, O., Lanzani, C., Launer, L.J., Lecoeur, C., Lehtimäki, T., Lettre, G., Liu, J., Lokki, M.L., Lorentzon, M., Luben, R.N., Ludwig, B., Manunta, P., Marek, D., Marre, M., Martin, N.G., McArdle, W.L., McCarthy, A., McKnight, B., Meitinger, T., Melander, O., Meyre, D., Midthjell, K., Montgomery, G.W., Morken, M.A., Morris, A.P., Mulic, R., Ngwa, J.S., Nelis, M., Neville, M.J., Nyholt, D.R., O'Donnell, C.J., O'Rahilly, S., Ong, K.K., Oostra, B., Paré, G., Parker, A.N., Perola, M., Pichler, I., Pietiläinen, K.H., Platou, C.G., Polasek, O., Pouta, A., Rafelt, S., Raitakari, O., Rayner, N.W., Ridderstråle, M., Rief, W., Ruokonen, A., Robertson, N.R., Rzehak, P., Salomaa, V., Sanders, A.R., Sandhu, M.S., Sanna, S., Saramies, J., Savolainen, M.J., Scherag, S., Schipf, S., Schreiber, S., Schunkert, H., Silander, K., Sinisalo, J., Siscovick, D.S., Smit, J.H., Soranzo, N., Sovio, U., Stephens, J., Surakka, I., Swift, AJ., Tammesoo, M.L., Tardif, J.C., Teder-Laving, M., Teslovich, T.M., Thompson, J.R., Thomson, B., Tönjes, A., Tuomi, T., van Meurs, J.B., van Ommen, G.J., Vatin, V., Viikari, J., Visvikis-Siest, S., Vitart, V., Vogel, C.I., Voight, B.F., Waite, L.L., Wallaschofski, H., Walters, G.B., Widen, E., Wiegand, S., Wild, S.H., Willemsen, G., Witte, D.R., Witteman, J.C., Xu, J., Zhang, Q., Zgaga, L., Ziegler, A., Zitting, P., Beilby, J.P., Farooqi, I.S., Hebebrand, J., Huikuri, H.V., James, AL., Kähönen, M., Levinson, D.F., Macciardi, F., Nieminen, M.S., Ohlsson, C., Palmer, L.J., Ridker, P.M., Stumvoll, M., Beckmann, J.S., Boeing, H., Boerwinkle, E., Boomsma, D.I., Caulfield, M.J., Chanock, S.J., Collins, F.S., Cupples, L.A., Smith, G.D., Erdmann, J., Froguel, P., Grönberg, H., Gyllensten, U., Hall, P., Hansen, T., Harris, T.B., Hattersley, A.T., Hayes, R.B., Heinrich, J., Hu, F.B., Hveem, K., Illig, T., Jarvelin, M.R., Kaprio, J., Karpe, F., Khaw, K.T., Kiemeney, L.A., Krude, H., Laakso, M., Lawlor, D.A., Metspalu, A., Munroe, P.B., Ouwehand, W.H., Pedersen, O., Penninx, B.W., Peters, A., Pramstaller, P.P., Quertermous, T., Reinehr, T., Rissanen, A., Rudan, I., Samani, N.J., Schwarz, P.E., Shuldiner, A.R., Spector, T.D., Tuomilehto, J., Uda, M., Uitterlinden, A., Valle, T.T., Wabitsch, M., Waeber, G., Wareham, N.J., Watkins, H., Wilson, J.F., Wright, A.F., Zillikens, M.C., Chatterjee, N., McCarroll, S.A., Purcell, S., Schadt, E.E., Visscher, P.M., Assimes, T.L., Borecki, I.B., Deloukas, P., Fox, C.S., Groop, L.C., Haritunians, T., Hunter, D.J., Kaplan, R.C., Mohlke, K.L., O'Connell, J.R., Peltonen, L., Schlessinger, D., Strachan, D.P., van Duijn, C.M., Wichmann, H.E., Frayling, T.M., Thorsteinsdottir, U., Abecasis, G.R., Barroso, I., Boehnke, M., Stefansson, K., North, K.E., McCarthy, M.I., Hirschhorn, J.N., Ingelsson, E., Loos, R.J., Medical Research Council (MRC), and National Institute for Health Research

Subjects
Male, Netherlands Twin Register (NTR), Medicin och hälsovetenskap, obesity, 25-HYDROXYVITAMIN D, D INSUFFICIENCY, Epidemiology, Medizin, vitamin D, Aetiology, screening and detection [ONCOL 5], Medical and Health Sciences, Gastroenterology, Body Mass Index, chemistry.chemical_compound, 0302 clinical medicine, Risk Factors, GENETIC-VARIANTS, Medicine, 030212 general & internal medicine, Vitamin D, 2. Zero hunger, Genetics, Aged, 80 and over, Evidence-Based Medicine, Confounding, 11 Medical And Health Sciences, General Medicine, Middle Aged, 3. Good health, PREVALENCE, Europe, Phenotype, Genetic Epidemiology, Biological Markers, Female, Life Sciences & Biomedicine, Research Article, Vitamin, Adult, medicine.medical_specialty, vitamin D deficiency, genetic variants, Genetic Investigation of Anthropometric Traits-GIANT Consortium, European Continental Ancestry Group, 030209 endocrinology & metabolism, Single-nucleotide polymorphism, body mass index, Polymorphism, Single Nucleotide, Risk Assessment, White People, COMMON OBESITY, 03 medical and health sciences, D DEFICIENCY, Medicine, General & Internal, SDG 3 - Good Health and Well-being, General & Internal Medicine, Internal medicine, Mendelian randomization, Vitamin D and neurology, INSTRUMENTAL VARIABLES, Humans, Genetic Predisposition to Disease, Obesity, GENOME-WIDE ASSOCIATION, Biology, Molecular epidemiology Aetiology, screening and detection [NCEBP 1], Aged, Science & Technology, Population Biology, business.industry, CARDIOVASCULAR-DISEASE RISK, ta3121, Mendelian Randomization Analysis, medicine.disease, Vitamin D Deficiency, BODY-MASS INDEX, chemistry, Genetic epidemiology, 3121 General medicine, internal medicine and other clinical medicine, Multivariate Analysis, North America, Genetic Polymorphism, Linear Models, business, Body mass index, Population Genetics, Biomarkers
Abstract

A mendelian randomization study based on data from multiple cohorts conducted by Karani Santhanakrishnan Vimaleswaran and colleagues re-examines the causal nature of the relationship between vitamin D levels and obesity., Background Obesity is associated with vitamin D deficiency, and both are areas of active public health concern. We explored the causality and direction of the relationship between body mass index (BMI) and 25-hydroxyvitamin D [25(OH)D] using genetic markers as instrumental variables (IVs) in bi-directional Mendelian randomization (MR) analysis. Methods and Findings We used information from 21 adult cohorts (up to 42,024 participants) with 12 BMI-related SNPs (combined in an allelic score) to produce an instrument for BMI and four SNPs associated with 25(OH)D (combined in two allelic scores, separately for genes encoding its synthesis or metabolism) as an instrument for vitamin D. Regression estimates for the IVs (allele scores) were generated within-study and pooled by meta-analysis to generate summary effects. Associations between vitamin D scores and BMI were confirmed in the Genetic Investigation of Anthropometric Traits (GIANT) consortium (n = 123,864). Each 1 kg/m2 higher BMI was associated with 1.15% lower 25(OH)D (p = 6.52×10−27). The BMI allele score was associated both with BMI (p = 6.30×10−62) and 25(OH)D (−0.06% [95% CI −0.10 to −0.02], p = 0.004) in the cohorts that underwent meta-analysis. The two vitamin D allele scores were strongly associated with 25(OH)D (p≤8.07×10−57 for both scores) but not with BMI (synthesis score, p = 0.88; metabolism score, p = 0.08) in the meta-analysis. A 10% higher genetically instrumented BMI was associated with 4.2% lower 25(OH)D concentrations (IV ratio: −4.2 [95% CI −7.1 to −1.3], p = 0.005). No association was seen for genetically instrumented 25(OH)D with BMI, a finding that was confirmed using data from the GIANT consortium (p≥0.57 for both vitamin D scores). Conclusions On the basis of a bi-directional genetic approach that limits confounding, our study suggests that a higher BMI leads to lower 25(OH)D, while any effects of lower 25(OH)D increasing BMI are likely to be small. Population level interventions to reduce BMI are expected to decrease the prevalence of vitamin D deficiency. Please see later in the article for the Editors' Summary, Editors' Summary Background Obesity—having an unhealthy amount of body fat—is increasing worldwide. In the US, for example, a third of the adult population is now obese. Obesity is defined as having a body mass index (BMI, an indicator of body fat calculated by dividing a person's weight in kilograms by their height in meters squared) of more than 30.0 kg/m2. Although there is a genetic contribution to obesity, people generally become obese by consuming food and drink that contains more energy than they need for their daily activities. Thus, obesity can be prevented by having a healthy diet and exercising regularly. Compared to people with a healthy weight, obese individuals have an increased risk of developing diabetes, heart disease and stroke, and tend to die younger. They also have a higher risk of vitamin D deficiency, another increasingly common public health concern. Vitamin D, which is essential for healthy bones as well as other functions, is made in the skin after exposure to sunlight but can also be obtained through the diet and through supplements. Why Was This Study Done? Observational studies cannot prove that obesity causes vitamin D deficiency because obese individuals may share other characteristics that reduce their circulating 25-hydroxy vitamin D [25(OH)D] levels (referred to as confounding). Moreover, observational studies cannot indicate whether the larger vitamin D storage capacity of obese individuals (vitamin D is stored in fatty tissues) lowers their 25(OH)D levels or whether 25(OH)D levels influence fat accumulation (reverse causation). If obesity causes vitamin D deficiency, monitoring and treating vitamin D deficiency might alleviate some of the adverse health effects of obesity. Conversely, if low vitamin D levels cause obesity, encouraging people to take vitamin D supplements might help to control the obesity epidemic. Here, the researchers use bi-directional “Mendelian randomization” to examine the direction and causality of the relationship between BMI and 25(OH)D. In Mendelian randomization, causality is inferred from associations between genetic variants that mimic the influence of a modifiable environmental exposure and the outcome of interest. Because gene variants do not change over time and are inherited randomly, they are not prone to confounding and are free from reverse causation. Thus, if a lower vitamin D status leads to obesity, genetic variants associated with lower 25(OH)D concentrations should be associated with higher BMI, and if obesity leads to a lower vitamin D status, then genetic variants associated with higher BMI should be associated with lower 25(OH)D concentrations. What Did the Researchers Do and Find? The researchers created a “BMI allele score” based on 12 BMI-related gene variants and two “25(OH)D allele scores,” which are based on gene variants that affect either 25(OH)D synthesis or breakdown. Using information on up to 42,024 participants from 21 studies, the researchers showed that the BMI allele score was associated with both BMI and with 25(OH)D levels among the study participants. Based on this information, they calculated that each 10% increase in BMI will lead to a 4.2% decrease in 25(OH)D concentrations. By contrast, although both 25(OH)D allele scores were strongly associated with 25(OH)D levels, neither score was associated with BMI. This lack of an association between 25(OH)D allele scores and obesity was confirmed using data from more than 100,000 individuals involved in 46 studies that has been collected by the GIANT (Genetic Investigation of Anthropometric Traits) consortium. What Do These Findings Mean? These findings suggest that a higher BMI leads to a lower vitamin D status whereas any effects of low vitamin D status on BMI are likely to be small. That is, these findings provide evidence for obesity as a causal factor in the development of vitamin D deficiency but not for vitamin D deficiency as a causal factor in the development of obesity. These findings suggest that population-level interventions to reduce obesity should lead to a reduction in the prevalence of vitamin D deficiency and highlight the importance of monitoring and treating vitamin D deficiency as a means of alleviating the adverse influences of obesity on health. Additional Information Please access these Web sites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1001383. The US Centers for Disease Control and Prevention provides information on all aspects of overweight and obesity (in English and Spanish); a data brief provides information about the vitamin D status of the US population The World Health Organization provides information on obesity (in several languages) The UK National Health Service Choices website provides detailed information about obesity and a link to a personal story about losing weight; it also provides information about vitamin D The International Obesity Taskforce provides information about the global obesity epidemic The US Department of Agriculture's ChooseMyPlate.gov website provides a personal healthy eating plan; the Weight-control Information Network is an information service provided for the general public and health professionals by the US National Institute of Diabetes and Digestive and Kidney Diseases (in English and Spanish) The US Office of Dietary Supplements provides information about vitamin D (in English and Spanish) MedlinePlus has links to further information about obesity and about vitamin D (in English and Spanish) Wikipedia has a page on Mendelian randomization (note: Wikipedia is a free online encyclopedia that anyone can edit; available in several languages) Overview and details of the collaborative large-scale genetic association study (D-CarDia) provide information about vitamin D and the risk of cardiovascular disease, diabetes and related traits

Published
2013
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27. Mapping gene and gene pathways associated with coronary artery disease: a CARDIoGRAM exome and multi-ancestry UK biobank analysis

Author

Praveen Hariharan and Josée Dupuis

Subjects
Medicine, Science
Abstract

Abstract Coronary artery disease (CAD) genome-wide association studies typically focus on single nucleotide variants (SNVs), and many potentially associated SNVs fail to reach the GWAS significance threshold. We performed gene and pathway-based association (GBA) tests on publicly available Coronary ARtery DIsease Genome wide Replication and Meta-analysis consortium Exome (n = 120,575) and multi ancestry pan UK Biobank study (n = 442,574) summary data using versatile gene-based association study (VEGAS2) and Multi-marker analysis of genomic annotation (MAGMA) to identify novel genes and pathways associated with CAD. We included only exonic SNVs and excluded regulatory regions. VEGAS2 and MAGMA ranked genes and pathways based on aggregated SNV test statistics. We used Bonferroni corrected gene and pathway significance threshold at 3.0 × 10–6 and 1.0 × 10–5, respectively. We also report the top one percent of ranked genes and pathways. We identified 17 top enriched genes with four genes (PCSK9, FAM177, LPL, ARGEF26), reaching statistical significance (p ≤ 3.0 × 10–6) using both GBA tests in two GWAS studies. In addition, our analyses identified ten genes (DUSP13, KCNJ11, CD300LF/RAB37, SLCO1B1, LRRFIP1, QSER1, UBR2, MOB3C, MST1R, and ABCC8) with previously unreported associations with CAD, although none of the single SNV associations within the genes were genome-wide significant. Among the top 1% non-lipid pathways, we detected pathways regulating coagulation, inflammation, neuronal aging, and wound healing.

Published
2021
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28. Abstract P002: Evidence For Smoking Dependent Genetic Effects on C-reactive Protein Levels in a Multi-ethnic Cohort Setting: The Care Consortium

Author

Jaclyn Ellis, Jeremy Walston, Josee Dupuis, Emma Larkin, Maja Barbalic, Brendan Keating, Jon P. Durda, Ervin Fox, Cameron Palmer, Yan Meng, Taylor Young, Renate Schnabel, Vasan Ramachandran, James Pankow, Guillaume Lettre, Ethan Lange, Christie Ballantyne, Myron Gross, James Wilson, Nora Nock, George Papanicolaou, Russell Tracy, Alex Reiner, Emelia Benjamin, and Leslie Lange

Subjects
Physiology (medical), Cardiology and Cardiovascular Medicine
Abstract

INTRODUCTION: C-reactive protein (CRP) is a heritable biomarker of systemic inflammation and a predictor of cardiovascular disease (CVD). Cigarette smoking is a major risk factor in the development of CVD and has been shown to affect circulating levels of CRP. Therefore, we sought to determine how this important environmental exposure may influence genetic associations with CRP in a multi-ethnic setting. METHODS: Using the ITMAT Broad-CARe (IBC) SNP array, a custom 50,000 SNP gene-centric array having dense coverage of over 2,000 candidate genes for CVD pathways, we performed a meta-analysis of up to 26,065 participants of European descent and 7,584 participants of African descent for association with log-CRP level within smoking status stratum. The 2 smoking strata were: never smokers and ever smokers (comprising of current and former smokers). We conducted IBC-wide association scans for CRP within cohort-, race- and smoking-stratum and meta-analyzed by race. Samples were from the Candidate gene Association Resource (CARe) cohorts (Atherosclerosis Risk in Communities Study, Framingham Heart Study, Cardiovascular Health Study, Cleveland Family Study , Coronary Artery Risk Development in Young Adults Study, Jackson Heart Study, and Multi-Ethnic Study of Atherosclerosis Study). Results were considered to be panel wide statistically significant if p RESULTS: The overall sample size for ever smokers (never smokers) was 11,698 (10,344) in European Americans and 3,448 (4,330) in African Americans. The per-allele beta coefficients for genes previously established to be associated with CRP and present on the IBC chip ( CRP, APOE, GCKR, IL6R, LEPR, HNF1A, NLRP3 ) were very similar in magnitude between smoking strata in European Americans. However, in the African Americans, the estimated per-allele CRP and IL6R betas were 2-times larger for the ever smokers as compared to the never smokers. In the European American analysis, one gene not previously reported for association with CRP reached IBC-wide significance for a CRP-lowering effect in the never smokers ( GSTT1 , p=4.8E-07 for SNP rs405597 ), but not in the ever smokers (p=0.078). CONCLUSION: This large scale candidate gene based meta-analysis identified one novel locus for CRP ( GSTT1 ) associated with serum CRP levels in those reporting having never regularly smoked. Polymorphisms in GSTT1 , which plays a role in detoxification, have previously been reported to interact with smoking for other phenotypes including birth weight and colorectal cancer. We also observed evidence that smoking modifies the effects for previously established loci CRP and IL6R in African Americans. These results may identify important context genetic specific effects that influence chronic inflammation.

Published
2012
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29. Common Variants at 10 Genomic Loci Influence Hemoglobin A(1C) Levels via Glycemic and Nonglycemic Pathways

Author

Daniel Barnes, Benjamin Voight, Amelie Bonnefond, Ruth Loos, Eco De Geus, Alexander Teumer, Goncalo Abecasis, Nicole Soranzo, Serena Sanna, Ozren Polasek, Juliane Winkelmann, Augustine Kong, ROBERTO ELOSUA, Michael Stumvoll, David Altshuler, Udo Seedorf, Ines Barroso, Felicity Payne, Nabila Bouatia-Naji, Christian Gieger, Robert Sladek, Sophie Gallina, Mariano Dei, Claudia Langenberg, Josee Dupuis, Man Li, James Pankow, Sally Ricketts, Mark Fleming, James F Wilson, Eleanor Wheeler, Peter Kovacs, Alexandre Stewart, Inga Prokopenko, Philippe Froguel, Panos Deloukas, Nita Forouhi, Jeanette Erdmann, Matthew Heeney, Reedik Mägi, Patrik Magnusson, Marcus Kleber, Thomas Meitinger, Massimo Mangino, Caroline Hayward, MANUELA UDA, Christa Meisinger, Rona Strawbridge, Manuel Serrano Ríos, Ida Surakka, Anuj Goel, Gonneke Willemsen, Konrad Oexle, Mark McCarthy, Olle Melander, Muredach Reilly, Igor Rudan, Alistair Hall, Hugh Watkins, Biological Psychology, EMGO+ - Lifestyle, Overweight and Diabetes, Department of Chemical Engineering [Stanford], Stanford University, École nationale supérieure d'architecture de Nantes (ENSA Nantes), Génétique des maladies multifactorielles (GMM), Université de Lille, Droit et Santé-Centre National de la Recherche Scientifique (CNRS), Évolution, Écologie et Paléontologie (Evo-Eco-Paleo) - UMR 8198 (Evo-Eco-Paléo), Université de Lille-Centre National de la Recherche Scientifique (CNRS), and Évolution, Écologie et Paléontologie (Evo-Eco-Paleo) - UMR 8198 (Evo-Eco-Paléo (EEP))

Subjects
Netherlands Twin Register (NTR), medicine.medical_specialty, BLOOD-CELLS, endocrine system diseases, Endocrinology, Diabetes and Metabolism, [SDV]Life Sciences [q-bio], 030209 endocrinology & metabolism, Genome-wide association study, Single-nucleotide polymorphism, Biology, 03 medical and health sciences, chemistry.chemical_compound, 0302 clinical medicine, SDG 3 - Good Health and Well-being, FASTING GLUCOSE-LEVELS, Polymorphism (computer science), Internal medicine, Diabetes mellitus, Genetic variation, Internal Medicine, medicine, ddc:610, ComputingMilieux_MISCELLANEOUS, 030304 developmental biology, Genetic association, NONSPHEROCYTIC HEMOLYTIC-ANEMIA, 0303 health sciences, RECLASSIFICATION, MTNR1B, nutritional and metabolic diseases, ASSOCIATION, medicine.disease, GENETIC HEMOCHROMATOSIS, POLYMORPHISM, 3. Good health, PREVALENCE, Hemoglobin A, Endocrinology, chemistry, Glycated hemoglobin, TYPE-2 DIABETES RISK
Abstract

OBJECTIVE Glycated hemoglobin (HbA1c), used to monitor and diagnose diabetes, is influenced by average glycemia over a 2- to 3-month period. Genetic factors affecting expression, turnover, and abnormal glycation of hemoglobin could also be associated with increased levels of HbA1c. We aimed to identify such genetic factors and investigate the extent to which they influence diabetes classification based on HbA1c levels. RESEARCH DESIGN AND METHODS We studied associations with HbA1c in up to 46,368 nondiabetic adults of European descent from 23 genome-wide association studies (GWAS) and 8 cohorts with de novo genotyped single nucleotide polymorphisms (SNPs). We combined studies using inverse-variance meta-analysis and tested mediation by glycemia using conditional analyses. We estimated the global effect of HbA1c loci using a multilocus risk score, and used net reclassification to estimate genetic effects on diabetes screening. RESULTS Ten loci reached genome-wide significant association with HbA1c, including six new loci near FN3K (lead SNP/P value, rs1046896/P = 1.6 × 10−26), HFE (rs1800562/P = 2.6 × 10−20), TMPRSS6 (rs855791/P = 2.7 × 10−14), ANK1 (rs4737009/P = 6.1 × 10−12), SPTA1 (rs2779116/P = 2.8 × 10−9) and ATP11A/TUBGCP3 (rs7998202/P = 5.2 × 10−9), and four known HbA1c loci: HK1 (rs16926246/P = 3.1 × 10−54), MTNR1B (rs1387153/P = 4.0 × 10−11), GCK (rs1799884/P = 1.5 × 10−20) and G6PC2/ABCB11 (rs552976/P = 8.2 × 10−18). We show that associations with HbA1c are partly a function of hyperglycemia associated with 3 of the 10 loci (GCK, G6PC2 and MTNR1B). The seven nonglycemic loci accounted for a 0.19 (% HbA1c) difference between the extreme 10% tails of the risk score, and would reclassify ∼2% of a general white population screened for diabetes with HbA1c. CONCLUSIONS GWAS identified 10 genetic loci reproducibly associated with HbA1c. Six are novel and seven map to loci where rarer variants cause hereditary anemias and iron storage disorders. Common variants at these loci likely influence HbA1c levels via erythrocyte biology, and confer a small but detectable reclassification of diabetes diagnosis by HbA1c.

Published
2010
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30. Determinants of penetrance and variable expressivity in monogenic metabolic conditions across 77,184 exomes

Author

Julia K. Goodrich, Moriel Singer-Berk, Rachel Son, Abigail Sveden, Jordan Wood, Eleina England, Joanne B. Cole, Ben Weisburd, Nick Watts, Lizz Caulkins, Peter Dornbos, Ryan Koesterer, Zachary Zappala, Haichen Zhang, Kristin A. Maloney, Andy Dahl, Carlos A. Aguilar-Salinas, Gil Atzmon, Francisco Barajas-Olmos, Nir Barzilai, John Blangero, Eric Boerwinkle, Lori L. Bonnycastle, Erwin Bottinger, Donald W. Bowden, Federico Centeno-Cruz, John C. Chambers, Nathalie Chami, Edmund Chan, Juliana Chan, Ching-Yu Cheng, Yoon Shin Cho, Cecilia Contreras-Cubas, Emilio Córdova, Adolfo Correa, Ralph A. DeFronzo, Ravindranath Duggirala, Josée Dupuis, Ma Eugenia Garay-Sevilla, Humberto García-Ortiz, Christian Gieger, Benjamin Glaser, Clicerio González-Villalpando, Ma Elena Gonzalez, Niels Grarup, Leif Groop, Myron Gross, Christopher Haiman, Sohee Han, Craig L. Hanis, Torben Hansen, Nancy L. Heard-Costa, Brian E. Henderson, Juan Manuel Malacara Hernandez, Mi Yeong Hwang, Sergio Islas-Andrade, Marit E. Jørgensen, Hyun Min Kang, Bong-Jo Kim, Young Jin Kim, Heikki A. Koistinen, Jaspal Singh Kooner, Johanna Kuusisto, Soo-Heon Kwak, Markku Laakso, Leslie Lange, Jong-Young Lee, Juyoung Lee, Donna M. Lehman, Allan Linneberg, Jianjun Liu, Ruth J. F. Loos, Valeriya Lyssenko, Ronald C. W. Ma, Angélica Martínez-Hernández, James B. Meigs, Thomas Meitinger, Elvia Mendoza-Caamal, Karen L. Mohlke, Andrew D. Morris, Alanna C. Morrison, Maggie C. Y. Ng, Peter M. Nilsson, Christopher J. O’Donnell, Lorena Orozco, Colin N. A. Palmer, Kyong Soo Park, Wendy S. Post, Oluf Pedersen, Michael Preuss, Bruce M. Psaty, Alexander P. Reiner, Cristina Revilla-Monsalve, Stephen S. Rich, Jerome I. Rotter, Danish Saleheen, Claudia Schurmann, Xueling Sim, Rob Sladek, Kerrin S. Small, Wing Yee So, Timothy D. Spector, Konstantin Strauch, Tim M. Strom, E. Shyong Tai, Claudia H. T. Tam, Yik Ying Teo, Farook Thameem, Brian Tomlinson, Russell P. Tracy, Tiinamaija Tuomi, Jaakko Tuomilehto, Teresa Tusié-Luna, Rob M. van Dam, Ramachandran S. Vasan, James G. Wilson, Daniel R. Witte, Tien-Yin Wong, AMP-T2D-GENES Consortia, Noël P. Burtt, Noah Zaitlen, Mark I. McCarthy, Michael Boehnke, Toni I. Pollin, Jason Flannick, Josep M. Mercader, Anne O’Donnell-Luria, Samantha Baxter, Jose C. Florez, Daniel G. MacArthur, and Miriam S. Udler

Subjects
Science
Abstract

Penetrance of variants in monogenic disease and clinical utility of common polygenic variation has not been well explored on a large-scale. Here, the authors use exome sequencing data from 77,184 individuals to generate penetrance estimates and assess the utility of polygenic variation in risk prediction of monogenic variants.

Published
2021
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31. Approximate conditional phenotype analysis based on genome wide association summary statistics

Author

Peitao Wu, Biqi Wang, Steven A. Lubitz, Emelia J. Benjamin, James B. Meigs, and Josée Dupuis

Subjects
Medicine, Science
Abstract

Abstract Because single genetic variants may have pleiotropic effects, one trait can be a confounder in a genome-wide association study (GWAS) that aims to identify loci associated with another trait. A typical approach to address this issue is to perform an additional analysis adjusting for the confounder. However, obtaining conditional results can be time-consuming. We propose an approximate conditional phenotype analysis based on GWAS summary statistics, the covariance between outcome and confounder, and the variant minor allele frequency (MAF). GWAS summary statistics and MAF are taken from GWAS meta-analysis results while the traits covariance may be estimated by two strategies: (i) estimates from a subset of the phenotypic data; or (ii) estimates from published studies. We compare our two strategies with estimates using individual level data from the full GWAS sample (gold standard). A simulation study for both binary and continuous traits demonstrates that our approximate approach is accurate. We apply our method to the Framingham Heart Study (FHS) GWAS and to large-scale cardiometabolic GWAS results. We observed a high consistency of genetic effect size estimates between our method and individual level data analysis. Our approach leads to an efficient way to perform approximate conditional analysis using large-scale GWAS summary statistics.

Published
2021
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32. Sex-dimorphic genetic effects and novel loci for fasting glucose and insulin variability

Author

Vasiliki Lagou, Reedik Mägi, Jouke- Jan Hottenga, Harald Grallert, John R. B. Perry, Nabila Bouatia-Naji, Letizia Marullo, Denis Rybin, Rick Jansen, Josine L. Min, Antigone S. Dimas, Anna Ulrich, Liudmila Zudina, Jesper R. Gådin, Longda Jiang, Alessia Faggian, Amélie Bonnefond, Joao Fadista, Maria G. Stathopoulou, Aaron Isaacs, Sara M. Willems, Pau Navarro, Toshiko Tanaka, Anne U. Jackson, May E. Montasser, Jeff R. O’Connell, Lawrence F. Bielak, Rebecca J. Webster, Richa Saxena, Jeanette M. Stafford, Beate St Pourcain, Nicholas J. Timpson, Perttu Salo, So-Youn Shin, Najaf Amin, Albert V. Smith, Guo Li, Niek Verweij, Anuj Goel, Ian Ford, Paul C. D. Johnson, Toby Johnson, Karen Kapur, Gudmar Thorleifsson, Rona J. Strawbridge, Laura J. Rasmussen-Torvik, Tõnu Esko, Evelin Mihailov, Tove Fall, Ross M. Fraser, Anubha Mahajan, Stavroula Kanoni, Vilmantas Giedraitis, Marcus E. Kleber, Günther Silbernagel, Julia Meyer, Martina Müller-Nurasyid, Andrea Ganna, Antti-Pekka Sarin, Loic Yengo, Dmitry Shungin, Jian’an Luan, Momoko Horikoshi, Ping An, Serena Sanna, Yvonne Boettcher, N. William Rayner, Ilja M. Nolte, Tatijana Zemunik, Erik van Iperen, Peter Kovacs, Nicholas D. Hastie, Sarah H. Wild, Stela McLachlan, Susan Campbell, Ozren Polasek, Olga Carlson, Josephine Egan, Wieland Kiess, Gonneke Willemsen, Johanna Kuusisto, Markku Laakso, Maria Dimitriou, Andrew A. Hicks, Rainer Rauramaa, Stefania Bandinelli, Barbara Thorand, Yongmei Liu, Iva Miljkovic, Lars Lind, Alex Doney, Markus Perola, Aroon Hingorani, Mika Kivimaki, Meena Kumari, Amanda J. Bennett, Christopher J. Groves, Christian Herder, Heikki A. Koistinen, Leena Kinnunen, Ulf de Faire, Stephan J. L. Bakker, Matti Uusitupa, Colin N. A. Palmer, J. Wouter Jukema, Naveed Sattar, Anneli Pouta, Harold Snieder, Eric Boerwinkle, James S. Pankow, Patrik K. Magnusson, Ulrika Krus, Chiara Scapoli, Eco J. C. N. de Geus, Matthias Blüher, Bruce H. R. Wolffenbuttel, Michael A. Province, Goncalo R. Abecasis, James B. Meigs, G. Kees Hovingh, Jaana Lindström, James F. Wilson, Alan F. Wright, George V. Dedoussis, Stefan R. Bornstein, Peter E. H. Schwarz, Anke Tönjes, Bernhard R. Winkelmann, Bernhard O. Boehm, Winfried März, Andres Metspalu, Jackie F. Price, Panos Deloukas, Antje Körner, Timo A. Lakka, Sirkka M. Keinanen-Kiukaanniemi, Timo E. Saaristo, Richard N. Bergman, Jaakko Tuomilehto, Nicholas J. Wareham, Claudia Langenberg, Satu Männistö, Paul W. Franks, Caroline Hayward, Veronique Vitart, Jaakko Kaprio, Sophie Visvikis-Siest, Beverley Balkau, David Altshuler, Igor Rudan, Michael Stumvoll, Harry Campbell, Cornelia M. van Duijn, Christian Gieger, Thomas Illig, Luigi Ferrucci, Nancy L. Pedersen, Peter P. Pramstaller, Michael Boehnke, Timothy M. Frayling, Alan R. Shuldiner, Patricia A. Peyser, Sharon L. R. Kardia, Lyle J. Palmer, Brenda W. Penninx, Pierre Meneton, Tamara B. Harris, Gerjan Navis, Pim van der Harst, George Davey Smith, Nita G. Forouhi, Ruth J. F. Loos, Veikko Salomaa, Nicole Soranzo, Dorret I. Boomsma, Leif Groop, Tiinamaija Tuomi, Albert Hofman, Patricia B. Munroe, Vilmundur Gudnason, David S. Siscovick, Hugh Watkins, Cecile Lecoeur, Peter Vollenweider, Anders Franco-Cereceda, Per Eriksson, Marjo-Riitta Jarvelin, Kari Stefansson, Anders Hamsten, George Nicholson, Fredrik Karpe, Emmanouil T. Dermitzakis, Cecilia M. Lindgren, Mark I. McCarthy, Philippe Froguel, Marika A. Kaakinen, Valeriya Lyssenko, Richard M. Watanabe, Erik Ingelsson, Jose C. Florez, Josée Dupuis, Inês Barroso, Andrew P. Morris, Inga Prokopenko, and Meta-Analyses of Glucose and Insulin-related traits Consortium (MAGIC)

Subjects
Science
Abstract

Sex differences in fasting glucose and insulin have been identified, but the genetic loci underlying these differences have not. Here, the authors perform a meta-analysis of genome-wide association studies to detect sex-specific and sex-dimorphic loci associated with fasting glucose and insulin.

Published
2021
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33. A genome-wide association study of bronchodilator response in participants of European and African ancestry from six independent cohorts

Author

Jessica D. Gereige, Hanfei Xu, Victor E. Ortega, Michael H. Cho, Ming Liu, Phuwanat Sakornsakolpat, Edwin K. Silverman, Terri H. Beaty, Bruce E. Miller, Per Bakke, Amund Gulsvik, Craig P. Hersh, Jarrett D. Morrow, Elizabeth J. Ampleford, Gregory A. Hawkins, Eugene R. Bleecker, Deborah A. Meyers, Stephen P. Peters, Juan C. Celedón, Kelan Tantisira, Jiang Li, Josée Dupuis, and George T. O'Connor

Subjects
Medicine
Abstract

Introduction Bronchodilator response (BDR) is a measurement of acute bronchodilation in response to short-acting β2-agonists, with a heritability between 10 and 40%. Identifying genetic variants associated with BDR may lead to a better understanding of its complex pathophysiology. Methods We performed a genome-wide association study (GWAS) of BDR in six adult cohorts with participants of European ancestry (EA) and African ancestry (AA) including community cohorts and cohorts ascertained on the basis of obstructive pulmonary disease. Validation analysis was carried out in two paediatric asthma cohorts. Results A total of 10 623 EA and 3597 AA participants were included in the analyses. No single nucleotide polymorphism (SNP) was associated with BDR at the conventional genome-wide significance threshold (p

Published
2022
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34. Dexmedetomidine and Other Analgosedatives Alter Pupil Characteristics in Critically Ill Patients

Author

Wang Pong Chan, BS, BA, Brenton R. Prescott, MS, Megan E. Barra, PharmD, David Y. Chung, MD, PhD, Ivy S. Kim, MPH, Hanife Saglam, MD, Meghan R. Hutch, BS, Min Shin, PhD, Sahar F. Zafar, MD, MBBS, Emelia J. Benjamin, MD, ScM, Stelios M. Smirnakis, MD, PhD, Josée Dupuis, PhD, David M. Greer, MD, MA, and Charlene J. Ong, MD, MPHS

Subjects
Medical emergencies. Critical care. Intensive care. First aid, RC86-88.9
Abstract

OBJECTIVES:. In critically ill patients with neurologic disease, pupil examination abnormalities can signify evolving intracranial pathology. Analgesic and sedative medications (analgosedatives) target pupillary pathways, but it remains unknown how analgosedatives alter pupil findings in the clinical care setting. We assessed dexmedetomidine and other analgosedative associations with pupil reactivity and size in a heterogeneous cohort of critically ill patients with acute intracranial pathology. DESIGN:. Retrospective cohort study. SETTING:. Two neurologic ICUs between 2016 and 2018. PATIENTS:. Critically ill adult patients with pupil measurements within 60 minutes of analgosedative administration. Patients with a history of intrinsic retinal pathology, extracranial injury, inaccessible brain imaging, or no Glasgow Coma Scale (GCS) data were excluded. INTERVENTIONS:. None. MEASUREMENTS AND MAIN RESULTS:. We used mixed-effects linear regression accounting for intrapatient correlations and adjusting for sex, age, GCS score, radiographic mass effect, medication confounders, and ambient light. We tested the association between an initiation or increased IV infusion of dexmedetomidine and pupil reactivity (Neurologic Pupil Index [NPi]) and resting pupil size (mm) obtained using NeurOptics NPi—200 (NeurOptics, Irvine, CA) pupillometer. Of our 221 patients with 9,897 pupil observations (median age, 60 [interquartile range, 50–68]; 59% male), 37 patients (166 pupil observations) were exposed to dexmedetomidine. Dexmedetomidine was associated with higher average NPi (β = 0.18 per 1 unit increase in rank-normalized NPi ± 0.04; p < 0.001) and smaller pupil size (β = –0.25 ± 0.05; p < 0.001). Exploratory analyses revealed that acetaminophen was associated with higher average NPi (β = 0.04 ± 0.02; p = 0.02) and that most IV infusion analgosedatives including propofol, fentanyl, and midazolam were associated with smaller pupil size. CONCLUSIONS:. Dexmedetomidine is associated with higher pupil reactivity (high NPi) and smaller pupil size in a cohort of critically ill patients with neurologic injury. Familiarity with expected pupil changes following analgosedative administration is important for accurate interpretation of pupil examination findings, facilitating optimal management of patients with acute intracranial pathology.

Published
2022
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35. Cerebral small vessel disease genomics and its implications across the lifespan

Author

Muralidharan Sargurupremraj, Hideaki Suzuki, Xueqiu Jian, Chloé Sarnowski, Tavia E. Evans, Joshua C. Bis, Gudny Eiriksdottir, Saori Sakaue, Natalie Terzikhan, Mohamad Habes, Wei Zhao, Nicola J. Armstrong, Edith Hofer, Lisa R. Yanek, Saskia P. Hagenaars, Rajan B. Kumar, Erik B. van den Akker, Rebekah E. McWhirter, Stella Trompet, Aniket Mishra, Yasaman Saba, Claudia L. Satizabal, Gregory Beaudet, Laurent Petit, Ami Tsuchida, Laure Zago, Sabrina Schilling, Sigurdur Sigurdsson, Rebecca F. Gottesman, Cora E. Lewis, Neelum T. Aggarwal, Oscar L. Lopez, Jennifer A. Smith, Maria C. Valdés Hernández, Jeroen van der Grond, Margaret J. Wright, Maria J. Knol, Marcus Dörr, Russell J. Thomson, Constance Bordes, Quentin Le Grand, Marie-Gabrielle Duperron, Albert V. Smith, David S. Knopman, Pamela J. Schreiner, Denis A. Evans, Jerome I. Rotter, Alexa S. Beiser, Susana Muñoz Maniega, Marian Beekman, Julian Trollor, David J. Stott, Meike W. Vernooij, Katharina Wittfeld, Wiro J. Niessen, Aicha Soumaré, Eric Boerwinkle, Stephen Sidney, Stephen T. Turner, Gail Davies, Anbupalam Thalamuthu, Uwe Völker, Mark A. van Buchem, R. Nick Bryan, Josée Dupuis, Mark E. Bastin, David Ames, Alexander Teumer, Philippe Amouyel, John B. Kwok, Robin Bülow, Ian J. Deary, Peter R. Schofield, Henry Brodaty, Jiyang Jiang, Yasuharu Tabara, Kazuya Setoh, Susumu Miyamoto, Kazumichi Yoshida, Manabu Nagata, Yoichiro Kamatani, Fumihiko Matsuda, Bruce M. Psaty, David A. Bennett, Philip L. De Jager, Thomas H. Mosley, Perminder S. Sachdev, Reinhold Schmidt, Helen R. Warren, Evangelos Evangelou, David-Alexandre Trégouët, International Network against Thrombosis (INVENT) Consortium, International Headache Genomics Consortium (IHGC), Mohammad A. Ikram, Wei Wen, Charles DeCarli, Velandai K. Srikanth, J. Wouter Jukema, Eline P. Slagboom, Sharon L. R. Kardia, Yukinori Okada, Bernard Mazoyer, Joanna M. Wardlaw, Paul A. Nyquist, Karen A. Mather, Hans J. Grabe, Helena Schmidt, Cornelia M. Van Duijn, Vilmundur Gudnason, William T. Longstreth, Lenore J. Launer, Mark Lathrop, Sudha Seshadri, Christophe Tzourio, Hieab H. Adams, Paul M. Matthews, Myriam Fornage, and Stéphanie Debette

Subjects
Science
Abstract

White matter hyperintensities (WMH) are a common brain-imaging feature of cerebral small vessel disease. Here, the authors carry out a GWAS and followup analyses for WMH-volume, implicating several variants with potential for risk stratification and drug targeting.

Published
2020
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36. Whole genome sequence analysis of pulmonary function and COPD in 19,996 multi-ethnic participants

Author

Xutong Zhao, Dandi Qiao, Chaojie Yang, Silva Kasela, Wonji Kim, Yanlin Ma, Nick Shrine, Chiara Batini, Tamar Sofer, Sarah A. Gagliano Taliun, Phuwanat Sakornsakolpat, Pallavi P. Balte, Dmitry Prokopenko, Bing Yu, Leslie A. Lange, Josée Dupuis, Brian E. Cade, Jiwon Lee, Sina A. Gharib, Michelle Daya, Cecelia A. Laurie, Ingo Ruczinski, L. Adrienne Cupples, Laura R. Loehr, Traci M. Bartz, Alanna C. Morrison, Bruce M. Psaty, Ramachandran S. Vasan, James G. Wilson, Kent D. Taylor, Peter Durda, W. Craig Johnson, Elaine Cornell, Xiuqing Guo, Yongmei Liu, Russell P. Tracy, Kristin G. Ardlie, François Aguet, David J. VanDenBerg, George J. Papanicolaou, Jerome I. Rotter, Kathleen C. Barnes, Deepti Jain, Deborah A. Nickerson, Donna M. Muzny, Ginger A. Metcalf, Harshavardhan Doddapaneni, Shannon Dugan-Perez, Namrata Gupta, Stacey Gabriel, Stephen S. Rich, George T. O’Connor, Susan Redline, Robert M. Reed, Cathy C. Laurie, Martha L. Daviglus, Liana K. Preudhomme, Kristin M. Burkart, Robert C. Kaplan, Louise V. Wain, Martin D. Tobin, Stephanie J. London, Tuuli Lappalainen, Elizabeth C. Oelsner, Goncalo R. Abecasis, Edwin K. Silverman, R. Graham Barr, NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium, TOPMed Lung Working Group, Michael H. Cho, and Ani Manichaikul

Subjects
Science
Abstract

Chronic obstructive pulmonary disease is a leading cause of morbidity and mortality. Here, the authors analyse whole genome sequence data and find new loci associated with lung function and COPD.

Published
2020
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37. Analysis of brain region-specific co-expression networks reveals clustering of established and novel genes associated with Alzheimer disease

Author

Daniel Lancour, Josée Dupuis, Richard Mayeux, Jonathan L. Haines, Margaret A. Pericak-Vance, Gerard C. Schellenberg, Mark Crovella, Lindsay A. Farrer, and Simon Kasif

Subjects
Alzheimer disease, Gene network analysis, Brain regions, Genome-wide association study, EPS8, HSPA2, Neurosciences. Biological psychiatry. Neuropsychiatry, RC321-571, Neurology. Diseases of the nervous system, RC346-429
Abstract

Abstract Background Identifying and understanding the functional role of genetic risk factors for Alzheimer disease (AD) has been complicated by the variability of genetic influences across brain regions and confounding with age-related neurodegeneration. Methods A gene co-expression network was constructed using data obtained from the Allen Brain Atlas for multiple brain regions (cerebral cortex, cerebellum, and brain stem) in six individuals. Gene network analyses were seeded with 52 reproducible (i.e., established) AD (RAD) genes. Genome-wide association study summary data were integrated with the gene co-expression results and phenotypic information (i.e., memory and aging-related outcomes) from gene knockout studies in Drosophila to generate rankings for other genes that may have a role in AD. Results We found that co-expression of the RAD genes is strongest in the cortical regions where neurodegeneration due to AD is most severe. There was significant evidence for two novel AD-related genes including EPS8 (FDR p = 8.77 × 10−3) and HSPA2 (FDR p = 0.245). Conclusions Our findings indicate that AD-related risk factors are potentially associated with brain region-specific effects on gene expression that can be detected using a gene network approach.

Published
2020
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38. An integrative cross-omics analysis of DNA methylation sites of glucose and insulin homeostasis

Author

Jun Liu, Elena Carnero-Montoro, Jenny van Dongen, Samantha Lent, Ivana Nedeljkovic, Symen Ligthart, Pei-Chien Tsai, Tiphaine C. Martin, Pooja R. Mandaviya, Rick Jansen, Marjolein J. Peters, Liesbeth Duijts, Vincent W. V. Jaddoe, Henning Tiemeier, Janine F. Felix, Gonneke Willemsen, Eco J. C. de Geus, Audrey Y. Chu, Daniel Levy, Shih-Jen Hwang, Jan Bressler, Rahul Gondalia, Elias L. Salfati, Christian Herder, Bertha A. Hidalgo, Toshiko Tanaka, Ann Zenobia Moore, Rozenn N. Lemaitre, Min A Jhun, Jennifer A. Smith, Nona Sotoodehnia, Stefania Bandinelli, Luigi Ferrucci, Donna K. Arnett, Harald Grallert, Themistocles L. Assimes, Lifang Hou, Andrea Baccarelli, Eric A. Whitsel, Ko Willems van Dijk, Najaf Amin, André G. Uitterlinden, Eric J. G. Sijbrands, Oscar H. Franco, Abbas Dehghan, Tim D. Spector, Josée Dupuis, Marie-France Hivert, Jerome I. Rotter, James B. Meigs, James S. Pankow, Joyce B. J. van Meurs, Aaron Isaacs, Dorret I. Boomsma, Jordana T. Bell, Ayşe Demirkan, and Cornelia M. van Duijn

Subjects
Science
Abstract

Our understanding of the functional link between differential DNA methylation and type 2 diabetes and obesity remains limited. Here the authors present a blood-based EWAS of fasting glucose and insulin among 4808 non-diabetic Europeans and identify nine CpGs not previously implicated in glucose, insulin homeostasis and diabetes.

Published
2019
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39. Adipocyte hyperplasia: the primary mechanism of supraspinatus intramuscular fat accumulation after a complete rotator cuff tendon tear: a study in the rabbit

Author

Guy Trudel, Hans K. Uhthoff, Kayleigh Wong, Josée Dupuis, and Odette Laneuville

Subjects
adipocytes, fat clumps, hyperplasia, hypertrophy, Diseases of the endocrine glands. Clinical endocrinology, RC648-665, Cytology, QH573-671, Physiology, QP1-981
Abstract

Intramuscular fat (IMF) accumulates in muscles of the rotator cuff after tendon tear. The number and cross-sectional area of fat clumps and of adipocytes were quantified on osmium tetroxide stained sections of the proximal, middle and distal quarters of SSP muscles 4, 8 and 12 weeks after SSP tendon division in a rabbit model. Linear mixed-effects models were fitted to the data and statistical significance was evaluated by ANOVA. Both the number (P0.01). IMF accumulation was more important in the distal quarter of detached SSP muscle near tendon sectioning and characterized by increases of the number (P0.01). Interestingly, the number of adipocytes in the distal quarter increased (P

Published
2019
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40. Epigenome-wide association study on diffusing capacity of the lung

Author

Natalie Terzikhan, Hanfei Xu, Ahmed Edris, Ken R. Bracke, Fien M. Verhamme, Bruno H.C. Stricker, Josée Dupuis, Lies Lahousse, George T. O'Connor, and Guy G. Brusselle

Subjects
Medicine
Abstract

Background Epigenetics may play an important role in the pathogenesis of lung diseases. However, little is known about the epigenetic factors that influence impaired gas exchange at the lung. Aim To identify the epigenetic signatures of the diffusing capacity of the lung measured by carbon monoxide uptake (the diffusing capacity of the lung for carbon monoxide (DLCO)). Methods An epigenome-wide association study (EWAS) was performed on diffusing capacity, measured by carbon monoxide uptake (DLCO) and per alveolar volume (VA) (as DLCO/VA), using the single-breath technique in 2674 individuals from two population-based cohort studies. These were the Rotterdam Study (RS, the “discovery panel”) and the Framingham Heart Study (FHS, the “replication panel”). We assessed the clinical relevance of our findings by investigating the identified sites in whole blood and by lung tissue specific gene expression. Results We identified and replicated two CpG sites (cg05575921 and cg05951221) that were significantly associated with DLCO/VA and one (cg05575921) suggestively associated with DLCO. Furthermore, we found a positive association between aryl hydrocarbon receptor repressor (AHRR) gene (cg05575921) hypomethylation and gene expression of exocyst complex component 3 (EXOC3) in whole blood. We confirmed that the expression of EXOC3 in lung tissue is positively associated with DLCO/VA and DLCO. Conclusions We report on epigenome-wide associations with diffusing capacity in the general population. Our results suggest EXOC3 to be an excellent candidate, through which smoking-induced hypomethylation of AHRR might affect pulmonary gas exchange.

Published
2021
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41. Beverage Consumption and Longitudinal Changes in Lipoprotein Concentrations and Incident Dyslipidemia in US Adults: The Framingham Heart Study

Author

Danielle E. Haslam, Gina M. Peloso, Mark A. Herman, Josée Dupuis, Alice H. Lichtenstein, Caren E. Smith, and Nicola M. McKeown

Subjects
carbohydrates, dyslipidemia, fruit juice, low‐calorie sweetened beverages, nutrition, observational study, Diseases of the circulatory (Cardiovascular) system, RC666-701
Abstract

Background Limited data are available on the prospective relationship between beverage consumption and plasma lipid and lipoprotein concentrations. Two major sources of sugar in the US diet are sugar‐sweetened beverages (SSBs) and 100% fruit juices. Low‐calorie sweetened beverages are common replacements. Methods and Results Fasting plasma lipoprotein concentrations were measured in the FOS (Framingham Offspring Study) (1991–2014; N=3146) and Generation Three (2002–2001; N=3584) cohorts. Beverage intakes were estimated from food frequency questionnaires and grouped into 5 intake categories. Mixed‐effect linear regression models were used to examine 4‐year changes in lipoprotein measures, and Cox proportional hazard models were used to estimate hazard ratios for incident dyslipidemia, adjusting for potential confounding factors. We found that regular (>1 serving per day) versus low (

Published
2020
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42. Smoking-by-genotype interaction in type 2 diabetes risk and fasting glucose.

Author

Peitao Wu, Denis Rybin, Lawrence F Bielak, Mary F Feitosa, Nora Franceschini, Yize Li, Yingchang Lu, Jonathan Marten, Solomon K Musani, Raymond Noordam, Sridharan Raghavan, Lynda M Rose, Karen Schwander, Albert V Smith, Salman M Tajuddin, Dina Vojinovic, Najaf Amin, Donna K Arnett, Erwin P Bottinger, Ayse Demirkan, Jose C Florez, Mohsen Ghanbari, Tamara B Harris, Lenore J Launer, Jingmin Liu, Jun Liu, Dennis O Mook-Kanamori, Alison D Murray, Mike A Nalls, Patricia A Peyser, André G Uitterlinden, Trudy Voortman, Claude Bouchard, Daniel Chasman, Adolfo Correa, Renée de Mutsert, Michele K Evans, Vilmundur Gudnason, Caroline Hayward, Linda Kao, Sharon L R Kardia, Charles Kooperberg, Ruth J F Loos, Michael M Province, Tuomo Rankinen, Susan Redline, Paul M Ridker, Jerome I Rotter, David Siscovick, Blair H Smith, Cornelia van Duijn, Alan B Zonderman, D C Rao, James G Wilson, Josée Dupuis, James B Meigs, Ching-Ti Liu, and Jason L Vassy

Subjects
Medicine, Science
Abstract

Smoking is a potentially causal behavioral risk factor for type 2 diabetes (T2D), but not all smokers develop T2D. It is unknown whether genetic factors partially explain this variation. We performed genome-environment-wide interaction studies to identify loci exhibiting potential interaction with baseline smoking status (ever vs. never) on incident T2D and fasting glucose (FG). Analyses were performed in participants of European (EA) and African ancestry (AA) separately. Discovery analyses were conducted using genotype data from the 50,000-single-nucleotide polymorphism (SNP) ITMAT-Broad-CARe (IBC) array in 5 cohorts from from the Candidate Gene Association Resource Consortium (n = 23,189). Replication was performed in up to 16 studies from the Cohorts for Heart Aging Research in Genomic Epidemiology Consortium (n = 74,584). In meta-analysis of discovery and replication estimates, 5 SNPs met at least one criterion for potential interaction with smoking on incident T2D at p

Published
2020
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43. Evaluation of a phenotype imputation approach using GAW20 simulated data

Author

Yuning Chen, Gina M. Peloso, and Josée Dupuis

Subjects
Medicine, Science
Abstract

Abstract Statistical power, which is the probability of correctly rejecting a false null hypothesis, is a limitation of genome-wide association studies (GWAS). Sample size is a major component of statistical power that can be easily affected by missingness in phenotypic data and restrain the ability to detect associated single-nucleotide polymorphisms (SNPs) with small effect sizes. Although some phenotypes are hard to collect because of cost and loss to follow-up, correlated phenotypes that are easily collected can be leveraged for association analysis. In this paper, we evaluate a phenotype imputation method that incorporates family structure and correlation between multiple phenotypes using GAW20 simulated data. The distribution of missing values is derived using information contained in the missing sample’s relatives and additional correlated phenotypes. We show that this imputation method can improve power in the association analysis compared with excluding observations with missing data, while achieving the correct Type I error rate. We also examine factors that may affect the imputation accuracy.

Published
2018
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44. Comparison of novel and existing methods for detecting differentially methylated regions

Author

Samantha Lent, Hanfei Xu, Lan Wang, Zhe Wang, Chloé Sarnowski, Marie-France Hivert, and Josée Dupuis

Subjects
Epigenetics, DNA methylation, Differentially methylated regions, Genetics, QH426-470
Abstract

Abstract Background Single-probe analyses in epigenome-wide association studies (EWAS) have identified associations between DNA methylation and many phenotypes, but do not take into account information from neighboring probes. Methods to detect differentially methylated regions (DMRs) (clusters of neighboring probes associated with a phenotype) may provide more power to detect associations between DNA methylation and diseases or phenotypes of interest. Results We proposed a novel approach, GlobalP, and perform comparisons with 3 methods—DMRcate, Bumphunter, and comb-p—to identify DMRs associated with log triglycerides (TGs) in real GAW20 data before and after fenofibrate treatment. We applied these methods to the summary statistics from an EWAS performed on the methylation data. Comb-p, DMRcate, and GlobalP detected very similar DMRs near the gene CPT1A on chromosome 11 in both the pre- and posttreatment data. In addition, GlobalP detected 2 DMRs before fenofibrate treatment in the genes ETV6 and ABCG1. Bumphunter identified several DMRs on chromosomes 1 and 20, which did not overlap with DMRs detected by other methods. Conclusions Our novel method detected the same DMR identified by two existing methods and detected two additional DMRs not identified by any of the existing methods we compared.

Published
2018
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45. Investigation of parent-of-origin effects induced by fenofibrate treatment on triglycerides levels

Author

Chloé Sarnowski, Samantha Lent, and Josée Dupuis

Subjects
Triglycerides, Fenofibrate treatment, Epigenetics, Parent-of-origin effects, DNA methylation, Genetics, QH426-470
Abstract

Abstract Background Genome-wide association studies performed on triglycerides (TGs) have not accounted for epigenetic mechanisms that may partially explain trait heritability. Results Parent-of-origin (POO) effect association analyses using an agnostic approach or a candidate approach were performed for pretreatment TG levels, posttreatment TG levels, and pre- and posttreatment TG-level differences in the real GAW20 family data set. We detected 22 genetic variants with suggestive POO effects with at least 1 phenotype (P ≤ 10− 5). We evaluated the association of these 22 significant genetic variants showing POO effects with close DNA methylation probes associated with TGs. A total of 18 DNA methylation probes located in the vicinity of the 22 SNPs were associated with at least 1 phenotype and 6 SNP-probe pairs were associated with DNA methylation probes at the nominal level of P

Published
2018
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46. Multiethnic meta-analysis identifies ancestry-specific and cross-ancestry loci for pulmonary function

Author

Annah B. Wyss, Tamar Sofer, Mi Kyeong Lee, Natalie Terzikhan, Jennifer N. Nguyen, Lies Lahousse, Jeanne C. Latourelle, Albert Vernon Smith, Traci M. Bartz, Mary F. Feitosa, Wei Gao, Tarunveer S. Ahluwalia, Wenbo Tang, Christopher Oldmeadow, Qing Duan, Kim de Jong, Mary K. Wojczynski, Xin-Qun Wang, Raymond Noordam, Fernando Pires Hartwig, Victoria E. Jackson, Tianyuan Wang, Ma’en Obeidat, Brian D. Hobbs, Tianxiao Huan, Hongsheng Gui, Margaret M. Parker, Donglei Hu, Lauren S. Mogil, Gleb Kichaev, Jianping Jin, Mariaelisa Graff, Tamara B. Harris, Ravi Kalhan, Susan R. Heckbert, Lavinia Paternoster, Kristin M. Burkart, Yongmei Liu, Elizabeth G. Holliday, James G. Wilson, Judith M. Vonk, Jason L. Sanders, R. Graham Barr, Renée de Mutsert, Ana Maria Baptista Menezes, Hieab H. H. Adams, Maarten van den Berge, Roby Joehanes, Albert M. Levin, Jennifer Liberto, Lenore J. Launer, Alanna C. Morrison, Colleen M. Sitlani, Juan C. Celedón, Stephen B. Kritchevsky, Rodney J. Scott, Kaare Christensen, Jerome I. Rotter, Tobias N. Bonten, Fernando César Wehrmeister, Yohan Bossé, Shujie Xiao, Sam Oh, Nora Franceschini, Jennifer A. Brody, Robert C. Kaplan, Kurt Lohman, Mark McEvoy, Michael A. Province, Frits R. Rosendaal, Kent D. Taylor, David C. Nickle, L. Keoki Williams, Esteban G. Burchard, Heather E. Wheeler, Don D. Sin, Vilmundur Gudnason, Kari E. North, Myriam Fornage, Bruce M. Psaty, Richard H. Myers, George O’Connor, Torben Hansen, Cathy C. Laurie, Patricia A. Cassano, Joohon Sung, Woo Jin Kim, John R. Attia, Leslie Lange, H. Marike Boezen, Bharat Thyagarajan, Stephen S. Rich, Dennis O. Mook-Kanamori, Bernardo Lessa Horta, André G. Uitterlinden, Hae Kyung Im, Michael H. Cho, Guy G. Brusselle, Sina A. Gharib, Josée Dupuis, Ani Manichaikul, and Stephanie J. London

Subjects
Science
Abstract

Pulmonary function is influenced by environmental factors, lifestyle, and genetics. Here, in a multiethnic GWAS meta-analysis for pulmonary function traits, the authors identify over 50 additional genetic loci, a subset of which are specific for European, African, Asian, or Hispanic/Latino ancestry.

Published
2018
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47. Genome-wide association study in 79,366 European-ancestry individuals informs the genetic architecture of 25-hydroxyvitamin D levels

Author

Xia Jiang, Paul F. O’Reilly, Hugues Aschard, Yi-Hsiang Hsu, J. Brent Richards, Josée Dupuis, Erik Ingelsson, David Karasik, Stefan Pilz, Diane Berry, Bryan Kestenbaum, Jusheng Zheng, Jianan Luan, Eleni Sofianopoulou, Elizabeth A. Streeten, Demetrius Albanes, Pamela L. Lutsey, Lu Yao, Weihong Tang, Michael J. Econs, Henri Wallaschofski, Henry Völzke, Ang Zhou, Chris Power, Mark I. McCarthy, Erin D. Michos, Eric Boerwinkle, Stephanie J. Weinstein, Neal D. Freedman, Wen-Yi Huang, Natasja M. Van Schoor, Nathalie van der Velde, Lisette C. P. G. M. de Groot, Anke Enneman, L. Adrienne Cupples, Sarah L. Booth, Ramachandran S. Vasan, Ching-Ti Liu, Yanhua Zhou, Samuli Ripatti, Claes Ohlsson, Liesbeth Vandenput, Mattias Lorentzon, Johan G. Eriksson, M. Kyla Shea, Denise K. Houston, Stephen B. Kritchevsky, Yongmei Liu, Kurt K. Lohman, Luigi Ferrucci, Munro Peacock, Christian Gieger, Marian Beekman, Eline Slagboom, Joris Deelen, Diana van Heemst, Marcus E. Kleber, Winfried März, Ian H. de Boer, Alexis C. Wood, Jerome I. Rotter, Stephen S. Rich, Cassianne Robinson-Cohen, Martin den Heijer, Marjo-Riitta Jarvelin, Alana Cavadino, Peter K. Joshi, James F. Wilson, Caroline Hayward, Lars Lind, Karl Michaëlsson, Stella Trompet, M. Carola Zillikens, Andre G. Uitterlinden, Fernando Rivadeneira, Linda Broer, Lina Zgaga, Harry Campbell, Evropi Theodoratou, Susan M. Farrington, Maria Timofeeva, Malcolm G. Dunlop, Ana M. Valdes, Emmi Tikkanen, Terho Lehtimäki, Leo-Pekka Lyytikäinen, Mika Kähönen, Olli T. Raitakari, Vera Mikkilä, M. Arfan Ikram, Naveed Sattar, J. Wouter Jukema, Nicholas J. Wareham, Claudia Langenberg, Nita G. Forouhi, Thomas E. Gundersen, Kay-Tee Khaw, Adam S. Butterworth, John Danesh, Timothy Spector, Thomas J. Wang, Elina Hyppönen, Peter Kraft, and Douglas P. Kiel

Subjects
Science
Abstract

Vitamin D deficiency is associated with multiple human pathologic conditions. In a genome-wide association study of 79,366 individuals, Jiang et al. replicate four and identify two new genetic loci for serum levels of 25-hydroxyvitamin D and find evidence for a shared genetic basis with autoimmune diseases.

Published
2018
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48. Publisher Correction: Sex-dimorphic genetic effects and novel loci for fasting glucose and insulin variability

Author

Vasiliki Lagou, Reedik Mägi, Jouke- Jan Hottenga, Harald Grallert, John R. B. Perry, Nabila Bouatia-Naji, Letizia Marullo, Denis Rybin, Rick Jansen, Josine L. Min, Antigone S. Dimas, Anna Ulrich, Liudmila Zudina, Jesper R. Gådin, Longda Jiang, Alessia Faggian, Amélie Bonnefond, Joao Fadista, Maria G. Stathopoulou, Aaron Isaacs, Sara M. Willems, Pau Navarro, Toshiko Tanaka, Anne U. Jackson, May E. Montasser, Jeff R. O’Connell, Lawrence F. Bielak, Rebecca J. Webster, Richa Saxena, Jeanette M. Stafford, Beate St Pourcain, Nicholas J. Timpson, Perttu Salo, So-Youn Shin, Najaf Amin, Albert V. Smith, Guo Li, Niek Verweij, Anuj Goel, Ian Ford, Paul C. D. Johnson, Toby Johnson, Karen Kapur, Gudmar Thorleifsson, Rona J. Strawbridge, Laura J. Rasmussen-Torvik, Tõnu Esko, Evelin Mihailov, Tove Fall, Ross M. Fraser, Anubha Mahajan, Stavroula Kanoni, Vilmantas Giedraitis, Marcus E. Kleber, Günther Silbernagel, Julia Meyer, Martina Müller-Nurasyid, Andrea Ganna, Antti-Pekka Sarin, Loic Yengo, Dmitry Shungin, Jian’an Luan, Momoko Horikoshi, Ping An, Serena Sanna, Yvonne Boettcher, N. William Rayner, Ilja M. Nolte, Tatijana Zemunik, Erik van Iperen, Peter Kovacs, Nicholas D. Hastie, Sarah H. Wild, Stela McLachlan, Susan Campbell, Ozren Polasek, Olga Carlson, Josephine Egan, Wieland Kiess, Gonneke Willemsen, Johanna Kuusisto, Markku Laakso, Maria Dimitriou, Andrew A. Hicks, Rainer Rauramaa, Stefania Bandinelli, Barbara Thorand, Yongmei Liu, Iva Miljkovic, Lars Lind, Alex Doney, Markus Perola, Aroon Hingorani, Mika Kivimaki, Meena Kumari, Amanda J. Bennett, Christopher J. Groves, Christian Herder, Heikki A. Koistinen, Leena Kinnunen, Ulf de Faire, Stephan J. L. Bakker, Matti Uusitupa, Colin N. A. Palmer, J. Wouter Jukema, Naveed Sattar, Anneli Pouta, Harold Snieder, Eric Boerwinkle, James S. Pankow, Patrik K. Magnusson, Ulrika Krus, Chiara Scapoli, Eco J. C. N. de Geus, Matthias Blüher, Bruce H. R. Wolffenbuttel, Michael A. Province, Goncalo R. Abecasis, James B. Meigs, G. Kees Hovingh, Jaana Lindström, James F. Wilson, Alan F. Wright, George V. Dedoussis, Stefan R. Bornstein, Peter E. H. Schwarz, Anke Tönjes, Bernhard R. Winkelmann, Bernhard O. Boehm, Winfried März, Andres Metspalu, Jackie F. Price, Panos Deloukas, Antje Körner, Timo A. Lakka, Sirkka M. Keinanen-Kiukaanniemi, Timo E. Saaristo, Richard N. Bergman, Jaakko Tuomilehto, Nicholas J. Wareham, Claudia Langenberg, Satu Männistö, Paul W. Franks, Caroline Hayward, Veronique Vitart, Jaakko Kaprio, Sophie Visvikis-Siest, Beverley Balkau, David Altshuler, Igor Rudan, Michael Stumvoll, Harry Campbell, Cornelia M. van Duijn, Christian Gieger, Thomas Illig, Luigi Ferrucci, Nancy L. Pedersen, Peter P. Pramstaller, Michael Boehnke, Timothy M. Frayling, Alan R. Shuldiner, Patricia A. Peyser, Sharon L. R. Kardia, Lyle J. Palmer, Brenda W. Penninx, Pierre Meneton, Tamara B. Harris, Gerjan Navis, Pim van der Harst, George Davey Smith, Nita G. Forouhi, Ruth J. F. Loos, Veikko Salomaa, Nicole Soranzo, Dorret I. Boomsma, Leif Groop, Tiinamaija Tuomi, Albert Hofman, Patricia B. Munroe, Vilmundur Gudnason, David S. Siscovick, Hugh Watkins, Cecile Lecoeur, Peter Vollenweider, Anders Franco-Cereceda, Per Eriksson, Marjo-Riitta Jarvelin, Kari Stefansson, Anders Hamsten, George Nicholson, Fredrik Karpe, Emmanouil T. Dermitzakis, Cecilia M. Lindgren, Mark I. McCarthy, Philippe Froguel, Marika A. Kaakinen, Valeriya Lyssenko, Richard M. Watanabe, Erik Ingelsson, Jose C. Florez, Josée Dupuis, Inês Barroso, Andrew P. Morris, Inga Prokopenko, and Meta-Analyses of Glucose and Insulin-related traits Consortium (MAGIC)

Subjects
Science
Abstract

A Correction to this paper has been published: https://doi.org/10.1038/s41467-021-21276-3

Published
2021
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49. Genome-wide association study of subclinical interstitial lung disease in MESA

Author

Ani Manichaikul, Xin-Qun Wang, Li Sun, Josée Dupuis, Alain C. Borczuk, Jennifer N. Nguyen, Ganesh Raghu, Eric A. Hoffman, Suna Onengut-Gumuscu, Emily A. Farber, Joel D. Kaufman, Dan Rabinowitz, Karen D. Hinckley Stukovsky, Steven M. Kawut, Gary M. Hunninghake, George R. Washko, George T. O’Connor, Stephen S. Rich, R. Graham Barr, and David J. Lederer

Subjects
Interstitial lung disease, Genetics, Genome-wide association study, Epidemiology, Diseases of the respiratory system, RC705-779
Abstract

Abstract Background We conducted a genome-wide association study (GWAS) of subclinical interstitial lung disease (ILD), defined as high attenuation areas (HAA) on CT, in the population-based Multi-Ethnic Study of Atherosclerosis Study. Methods We measured the percentage of high attenuation areas (HAA) in the lung fields on cardiac CT scan defined as voxels with CT attenuation values between -600 and -250 HU. Genetic analyses were performed in MESA combined across race/ethnic groups: non-Hispanic White (n = 2,434), African American (n = 2,470), Hispanic (n = 2,065) and Chinese (n = 702), as well as stratified by race/ethnicity. Results Among 7,671 participants, regions at genome-wide significance were identified for basilar peel-core ratio of HAA in FLJ35282 downstream of ANRIL (rs7852363, P = 2.1x10−9) and within introns of SNAI3-AS1 (rs140142658, P = 9.6x10−9) and D21S2088E (rs3079677, P = 2.3x10−8). Within race/ethnic groups, 18 additional loci were identified at genome-wide significance, including genes related to development (FOXP4), cell adhesion (ALCAM) and glycosylation (GNPDA2, GYPC, GFPT1 and FUT10). Among these loci, SNP rs6844387 near GNPDA2 demonstrated nominal evidence of replication in analysis of n = 1,959 participants from the Framingham Heart Study (P = 0.029). FOXP4 region SNP rs2894439 demonstrated evidence of validation in analysis of n = 228 White ILD cases from the Columbia ILD Study compared to race/ethnicity-matched controls from MESA (one-sided P = 0.007). In lung tissue from 15 adults with idiopathic pulmonary fibrosis compared to 15 adults without lung disease. ANRIL (P = 0.001), ALCAM (P = 0.03) and FOXP4 (P = 0.046) were differentially expressed. Conclusions Our results suggest novel roles for protein glycosylation and cell cycle disinhibition by long non-coding RNA in the pathogenesis of ILD.

Published
2017
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50. ProxECAT: Proxy External Controls Association Test. A new case-control gene region association test using allele frequencies from public controls.

Author

Audrey E Hendricks, Stephen C Billups, Hamish N C Pike, I Sadaf Farooqi, Eleftheria Zeggini, Stephanie A Santorico, Inês Barroso, and Josée Dupuis

Subjects
Genetics, QH426-470
Abstract

A primary goal of the recent investment in sequencing is to detect novel genetic associations in health and disease improving the development of treatments and playing a critical role in precision medicine. While this investment has resulted in an enormous total number of sequenced genomes, individual studies of complex traits and diseases are often smaller and underpowered to detect rare variant genetic associations. Existing genetic resources such as the Exome Aggregation Consortium (>60,000 exomes) and the Genome Aggregation Database (~140,000 sequenced samples) have the potential to be used as controls in these studies. Fully utilizing these and other existing sequencing resources may increase power and could be especially useful in studies where resources to sequence additional samples are limited. However, to date, these large, publicly available genetic resources remain underutilized, or even misused, in large part due to the lack of statistical methods that can appropriately use this summary level data. Here, we present a new method to incorporate external controls in case-control analysis called ProxECAT (Proxy External Controls Association Test). ProxECAT estimates enrichment of rare variants within a gene region using internally sequenced cases and external controls. We evaluated ProxECAT in simulations and empirical analyses of obesity cases using both low-depth of coverage (7x) whole-genome sequenced controls and ExAC as controls. We find that ProxECAT maintains the expected type I error rate with increased power as the number of external controls increases. With an accompanying R package, ProxECAT enables the use of publicly available allele frequencies as external controls in case-control analysis.

Published
2018
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