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2. Genetic and clinical determinants of abdominal aortic diameter: genome-wide association studies, exome array data and Mendelian randomization study

Author

Portilla-Fernandez, Eliana, Klarin, Derek, Hwang, Shih-Jen, Biggs, Mary L, Bis, Joshua C, Weiss, Stefan, Rospleszcz, Susanne, Natarajan, Pradeep, Hoffmann, Udo, Rogers, Ian S, Truong, Quynh A, Völker, Uwe, Dörr, Marcus, Bülow, Robin, Criqui, Michael H, Allison, Matthew, Ganesh, Santhi K, Yao, Jie, Waldenberger, Melanie, Bamberg, Fabian, Rice, Kenneth M, Essers, Jeroen, Kapteijn, Daniek MC, van der Laan, Sander W, de Knegt, Rob J, Ghanbari, Mohsen, Felix, Janine F, Ikram, M Arfan, Kavousi, Maryam, Uitterlinden, Andre G, Roks, Anton JM, Danser, AH Jan, Tsao, Philip S, Damrauer, Scott M, Guo, Xiuqing, Rotter, Jerome I, Psaty, Bruce M, Kathiresan, Sekar, Völzke, Henry, Peters, Annette, Johnson, Craig, Strauch, Konstantin, Meitinger, Thomas, O’Donnell, Christopher J, Dehghan, Abbas, and Program, VA Million Veteran

Subjects
Prevention, Human Genome, Cardiovascular, Genetics, Clinical Research, 2.1 Biological and endogenous factors, Aetiology, Exome, Genome-Wide Association Study, Humans, Mendelian Randomization Analysis, Polymorphism, Single Nucleotide, Triglycerides, VA Million Veteran Program, Biological Sciences, Medical and Health Sciences, Genetics & Heredity
Abstract

Progressive dilation of the infrarenal aortic diameter is a consequence of the ageing process and is considered the main determinant of abdominal aortic aneurysm (AAA). We aimed to investigate the genetic and clinical determinants of abdominal aortic diameter (AAD). We conducted a meta-analysis of genome-wide association studies in 10 cohorts (n = 13 542) imputed to the 1000 Genome Project reference panel including 12 815 subjects in the discovery phase and 727 subjects [Partners Biobank cohort 1 (PBIO)] as replication. Maximum anterior-posterior diameter of the infrarenal aorta was used as AAD. We also included exome array data (n = 14 480) from seven epidemiologic studies. Single-variant and gene-based associations were done using SeqMeta package. A Mendelian randomization analysis was applied to investigate the causal effect of a number of clinical risk factors on AAD. In genome-wide association study (GWAS) on AAD, rs74448815 in the intronic region of LDLRAD4 reached genome-wide significance (beta = -0.02, SE = 0.004, P-value = 2.10 × 10-8). The association replicated in the PBIO1 cohort (P-value = 8.19 × 10-4). In exome-array single-variant analysis (P-value threshold = 9 × 10-7), the lowest P-value was found for rs239259 located in SLC22A20 (beta = 0.007, P-value = 1.2 × 10-5). In the gene-based analysis (P-value threshold = 1.85 × 10-6), PCSK5 showed an association with AAD (P-value = 8.03 × 10-7). Furthermore, in Mendelian randomization analyses, we found evidence for genetic association of pulse pressure (beta = -0.003, P-value = 0.02), triglycerides (beta = -0.16, P-value = 0.008) and height (beta = 0.03, P-value

Published
2022

4. Association of inflammatory cytokines with lung function, chronic lung diseases, and COVID-19

Author

Rontogianni, Marina O., Gill, Dipender, Bouras, Emmanouil, Asimakopoulos, Alexandros-Georgios, Tzoulaki, Ioanna, Karhunen, Ville, Lehtimäki, Terho, Raitakari, Olli, Wielscher, Matthias, Salomaa, Veikko, Jalkanen, Sirpa, Salmi, Marko, Timonen, Markku, Yarmolinsky, James, Chen, Jing, Tobin, Martin D., Izquierdo, Abril G., Herzig, Karl-Heinz, Ioannides, Anne E., Jarvelin, Marjo-Riitta, Dehghan, Abbas, and Tsilidis, Konstantinos K.

Published
2024
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6. Understanding the complex genetic architecture connecting rheumatoid arthritis, osteoporosis and inflammation: discovering causal pathways

Author

Kasher, Melody, Williams, Frances MK, Freidin, Maxim B, Malkin, Ida, Cherny, Stacey S, Benjamin, Emelia, Chasman, Daniel I, Dehghan, Abbas, Ahluwalia, Tarunveer Singh, Meigs, James, Tracy, Russell, Alizadeh, Behrooz Z, Ligthart, Symen, Bis, Josh, Eiriksdottir, Gudny, Pankratz, Nathan, Gross, Myron, Rainer, Alex, Snieder, Harold, Wilson, James G, Psaty, Bruce M, Dupuis, Josee, Prins, Bram, Vaso, Urmo, Stathopoulou, Maria, Franke, Lude, Lehtimaki, Terho, Koenig, Wolfgang, Jamshidi, Yalda, Siest, Sophie, Abbasi, Ali, Uitterlinden, Andre G, Abdollahi, Mohammadreza, Schnabel, Renate, Schick, Ursula M, Nolte, Ilja M, Kraja, Aldi, Hsu, Yi-Hsiang, Tylee, Daniel S, Zwicker, Alyson, Uher, Rudolf, Davey-Smith, George, Morrison, Alanna C, Hicks, Andrew, van Duijn, Cornelia M, Ward-Caviness, Cavin, Boerwinkle, Eric, Rotter, J, Rice, Ken, Lange, Leslie, Perola, Markus, de Geus, Eco, Morris, Andrew P, Makela, Kari Matti, Stacey, David, Eriksson, Johan, Frayling, Tim M, Slagboom, Eline P, and Livshits, Gregory

Subjects
Aging, Autoimmune Disease, Arthritis, Osteoporosis, Human Genome, Heart Disease, Cardiovascular, Rheumatoid Arthritis, Genetics, 2.1 Biological and endogenous factors, Aetiology, Inflammatory and immune system, Arthritis, Rheumatoid, C-Reactive Protein, Genome-Wide Association Study, Humans, Inflammation, Mendelian Randomization Analysis, Polymorphism, Single Nucleotide, CHARGE Inflammation Working Group, Biological Sciences, Medical and Health Sciences, Genetics & Heredity
Abstract

Rheumatoid arthritis (RA) and osteoporosis (OP) are two comorbid complex inflammatory conditions with evidence of shared genetic background and causal relationships. We aimed to clarify the genetic architecture underlying RA and various OP phenotypes while additionally considering an inflammatory component, C-reactive protein (CRP). Genome-wide association study summary statistics were acquired from the GEnetic Factors for OSteoporosis Consortium, Cohorts for Heart and Aging Research Consortium and UK Biobank. Mendelian randomization (MR) was used to detect the presence of causal relationships. Colocalization analysis was performed to determine shared genetic variants between CRP and OP phenotypes. Analysis of pleiotropy between traits owing to shared causal single nucleotide polymorphisms (SNPs) was performed using PL eiotropic A nalysis under CO mposite null hypothesis (PLACO). MR analysis was suggestive of horizontal pleiotropy between RA and OP traits. RA was a significant causal risk factor for CRP (β = 0.027, 95% confidence interval = 0.016-0.038). There was no evidence of CRP→OP causal relationship, but horizontal pleiotropy was apparent. Colocalization established shared genomic regions between CRP and OP, including GCKR and SERPINA1 genes. Pleiotropy arising from shared causal SNPs revealed through the colocalization analysis was all confirmed by PLACO. These genes were found to be involved in the same molecular function 'protein binding' (GO:0005515) associated with RA, OP and CRP. We identified three major components explaining the epidemiological relationship among RA, OP and inflammation: (1) Pleiotropy explains a portion of the shared genetic relationship between RA and OP, albeit polygenically; (2) RA contributes to CRP elevation and (3) CRP, which is influenced by RA, demonstrated pleiotropy with OP.

Published
2022

7. Multi‐phenotype analyses of hemostatic traits with cardiovascular events reveal novel genetic associations

Author

Temprano‐Sagrera, Gerard, Sitlani, Colleen M, Bone, William P, Martin‐Bornez, Miguel, Voight, Benjamin F, Morrison, Alanna C, Damrauer, Scott M, de Vries, Paul S, Smith, Nicholas L, Sabater‐Lleal, Maria, Dehghan, Abbas, Heath, Adam S, Reiner, Alex P, Johnson, Andrew, Richmond, Anne, Peters, Annette, van Hylckama Vlieg, Astrid, McKnight, Barbara, Psaty, Bruce M, Hayward, Caroline, Ward‐Caviness, Cavin, O’Donnell, Christopher, Chasman, Daniel, Strachan, David P, Tregouet, David A, Mook‐Kanamori, Dennis, Gill, Dipender, Thibord, Florian, Asselbergs, Folkert W, Leebeek, Frank WG, Rosendaal, Frits R, Davies, Gail, Homuth, Georg, Temprano, Gerard, Campbell, Harry, Taylor, Herman A, Bressler, Jan, Huffman, Jennifer E, Rotter, Jerome I, Yao, Jie, Wilson, James F, Bis, Joshua C, Hahn, Julie M, Desch, Karl C, Wiggins, Kerri L, Raffield, Laura M, Bielak, Lawrence F, Yanek, Lisa R, Kleber, Marcus E, Mueller, Martina, Kavousi, Maryam, Mangino, Massimo, Liu, Melissa, Brown, Michael R, Conomos, Matthew P, Jhun, Min‐A, Chen, Ming‐Huei, de Maat, Moniek PM, Pankratz, Nathan, Peyser, Patricia A, Elliot, Paul, Wei, Peng, Wild, Philipp S, Morange, Pierre E, van der Harst, Pim, Yang, Qiong, Le, Ngoc‐Quynh, Marioni, Riccardo, Li, Ruifang, Cox, Simon R, Trompet, Stella, Felix, Stephan B, Völker, Uwe, Tang, Weihong, Koenig, Wolfgang, Jukema, J Wouter, Guo, Xiuqing, Lindstrom, Sara, Wang, Lu, Smith, Erin N, Gordon, William, de Andrade, Mariza, Brody, Jennifer A, Pattee, Jack W, Haessler, Jeffrey, Brumpton, Ben M, Chasman, Daniel I, Suchon, Pierre, Turman, Constance, Germain, Marine, MacDonald, James, and Braekkan, Sigrid K

Subjects
Genetics, Biotechnology, Human Genome, Atherosclerosis, Prevention, Cardiovascular, Hematology, 2.1 Biological and endogenous factors, Aetiology, Cardiovascular Diseases, Factor XI, Genetic Predisposition to Disease, Genome-Wide Association Study, Hemostasis, Hemostatics, Humans, Phenotype, Polymorphism, Single Nucleotide, Tissue Plasminogen Activator, blood coagulation, cardiovascular diseases, genetic pleiotropy, genome-wide association study, hemostasis, Cardiorespiratory Medicine and Haematology, Clinical Sciences, Cardiovascular System & Hematology
Abstract

BackgroundMulti-phenotype analysis of genetically correlated phenotypes can increase the statistical power to detect loci associated with multiple traits, leading to the discovery of novel loci. This is the first study to date to comprehensively analyze the shared genetic effects within different hemostatic traits, and between these and their associated disease outcomes.ObjectivesTo discover novel genetic associations by combining summary data of correlated hemostatic traits and disease events.MethodsSummary statistics from genome wide-association studies (GWAS) from seven hemostatic traits (factor VII [FVII], factor VIII [FVIII], von Willebrand factor [VWF] factor XI [FXI], fibrinogen, tissue plasminogen activator [tPA], plasminogen activator inhibitor 1 [PAI-1]) and three major cardiovascular (CV) events (venous thromboembolism [VTE], coronary artery disease [CAD], ischemic stroke [IS]), were combined in 27 multi-trait combinations using metaUSAT. Genetic correlations between phenotypes were calculated using Linkage Disequilibrium Score Regression (LDSC). Newly associated loci were investigated for colocalization. We considered a significance threshold of 1.85 × 10-9 obtained after applying Bonferroni correction for the number of multi-trait combinations performed (n = 27).ResultsAcross the 27 multi-trait analyses, we found 4 novel pleiotropic loci (XXYLT1, KNG1, SUGP1/MAU2, TBL2/MLXIPL) that were not significant in the original individual datasets, were not described in previous GWAS for the individual traits, and that presented a common associated variant between the studied phenotypes.ConclusionsThe discovery of four novel loci contributes to the understanding of the relationship between hemostasis and CV events and elucidate common genetic factors between these traits.

Published
2022

13. A multitrait genetic study of hemostatic factors and hemorrhagic transformation after stroke treatment

Author

Dehghan, Abbas, Heath, Adam S., Morrison, Alanna C., Reiner, Alex P., Johnson, Andrew, Richmond, Anne, Peters, Annette, van Hylckama Vlieg, Astrid, McKnight, Barbara, Psaty, Bruce M., Hayward, Caroline, Ward-Caviness, Cavin, O’Donnell, Christopher, Chasman, Daniel, Strachan, David P., Tregouet, David A., Mook-Kanamori, Dennis, Gill, Dipender, Thibord, Florian, Asselbergs, Folkert W., Leebeek, Frank W.G., Rosendaal, Frits R., Davies, Gail, Homuth, Georg, Temprano, Gerard, Campbell, Harry, Taylor, Herman A., Bressler, Jan, Huffman, Jennifer E., Rotter, Jerome I., Yao, Jie, Wilson, James F., Bis, Joshua C., Hahn, Julie M., Desch, Karl C., Wiggins, Kerri L., Díez-Ahijado, Laia, Raffield, Laura M., Bielak, Lawrence F., Yanek, Lisa R., Kleber, Marcus E., Sabater-Lleal, Maria, Mueller, Martina, Kavousi, Maryam, Mangino, Massimo, Conomos, Matthew P., Liu, Melissa, Brown, Michael R., Jhun, Min-A, Chen, Ming-Huei, de Maat, Moniek P.M., Pankratz, Nathan, Smith, Nicholas L., Peyser, Patricia A., Elliot, Paul, de Vries, Paul S., Wei, Peng, Wild, Philipp S., Morange, Pierre E., van der Harst, Pim, Yang, Qiong, Marioni, Riccardo, Li, Ruifang, Damrauer, Scott M., Cox, Simon R., Trompet, Stella, Felix, Stephan B., Völker, Uwe, Tang, Weihong, Koenig, Wolfgang, Jukema, J. Wouter, Guo, Xiuqing, Gallego-Fabrega, Cristina, Temprano-Sagrera, Gerard, Cárcel-Márquez, Jara, Muiño, Elena, Cullell, Natalia, Lledós, Miquel, Llucià-Carol, Laia, Martin-Campos, Jesús M., Sobrino, Tomás, Castillo, José, Millán, Mònica, Muñoz-Narbona, Lucía, López-Cancio, Elena, Ribó, Marc, Alvarez-Sabin, Jose, Jiménez-Conde, Jordi, Roquer, Jaume, Tur, Silvia, Obach, Victor, Arenillas, Juan F., Segura, Tomas, Serrano-Heras, Gemma, Marti-Fabregas, Joan, Freijo-Guerrero, Marimar, Moniche, Francisco, Castellanos, Maria del Mar, and Fernández-Cadenas, Israel

Published
2024
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14. Association between circulating inflammatory markers and adult cancer risk: a Mendelian randomization analysis

Author

Landi, Maria Teresa, Stevens, Victoria, Wang, Ying, Albanes, Demetrios, Caporaso, Neil, Brennan, Paul, Amos, Christopher I., Shete, Sanjay, Hung, Rayjean J., Bickeböller, Heike, Risch, Angela, Houlston, Richard, Lam, Stephen, Tardon, Adonina, Chen, Chu, Bojesen, Stig E., Johansson, Mattias, Wichmann, H-Erich, Christiani, David, Rennert, Gadi, Arnold, Susanne, Field, John K., Le Marchand, Loic, Melander, Olle, Brunnström, Hans, Liu, Geoffrey, Andrew, Angeline, Kiemeney, Lambertus A., Shen, Hongbing, Zienolddiny, Shan, Grankvist, Kjell, Johansson, Mikael, Teare, M. Dawn, Hong, Yun-Chul, Yuan, Jian-Min, Lazarus, Philip, Schabath, Matthew B., Aldrich, Melinda C., Eeles, Rosalind A., Haiman, Christopher A., Kote-Jarai, Zsofia, Schumacher, Fredrick R., Benlloch, Sara, Al Olama, Ali Amin, Muir, Kenneth R., Berndt, Sonja I., Conti, David V., Wiklund, Fredrik, Chanock, Stephen, Tangen, Catherine M., Batra, Jyotsna, Clements, Judith A., Grönberg, Henrik, Pashayan, Nora, Schleutker, Johanna, Albanes, Demetrius, Weinstein, Stephanie J., Wolk, Alicja, West, Catharine M.L., Mucci, Lorelei A., Cancel-Tassin, Géraldine, Koutros, Stella, Sørensen, Karina Dalsgaard, Grindedal, Eli Marie, Neal, David E., Hamdy, Freddie C., Donovan, Jenny L., Travis, Ruth C., Hamilton, Robert J., Ingles, Sue Ann, Rosenstein, Barry S., Lu, Yong-Jie, Giles, Graham G., MacInnis, Robert J., Kibel, Adam S., Vega, Ana, Kogevinas, Manolis, Penney, Kathryn L., Park, Jong Y., Stanfrod, Janet L., Cybulski, Cezary, Nordestgaard, Børge G., Nielsen, Sune F., Brenner, Hermann, Maier, Christiane, Logothetis, Christopher J., John, Esther M., Teixeira, Manuel R., Neuhausen, Susan L., De Ruyck, Kim, Razack, Azad, Newcomb, Lisa F., Lessel, Davor, Kaneva, Radka, Usmani, Nawaid, Claessens, Frank, Townsend, Paul A., Castelao, Jose Esteban, Roobol, Monique J., Menegaux, Florence, Khaw, Kay-Tee, Cannon-Albright, Lisa, Pandha, Hardev, Thibodeau, Stephen N., Hunter, David J., Kraft, Peter, Blot, William J., Riboli, Elio, Yarmolinsky, James, Robinson, Jamie W., Mariosa, Daniela, Karhunen, Ville, Huang, Jian, Dimou, Niki, Murphy, Neil, Burrows, Kimberley, Bouras, Emmanouil, Smith-Byrne, Karl, Lewis, Sarah J., Galesloot, Tessel E., Vermeulen, Sita, Martin, Paul, Hou, Lifang, Newcomb, Polly A., White, Emily, Wu, Anna H., Le Marchand, Loïc, Phipps, Amanda I., Buchanan, Daniel D., Zhao, Sizheng Steven, Gill, Dipender, Chanock, Stephen J., Purdue, Mark P., Davey Smith, George, Herzig, Karl-Heinz, Järvelin, Marjo-Riitta, Amos, Chris I., Dehghan, Abbas, Gunter, Marc J., Tsilidis, Kostas K., and Martin, Richard M.

Published
2024
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16. Whole-genome analysis of plasma fibrinogen reveals population-differentiated genetic regulators with putative liver roles

Author

Huffman, Jennifer E., Nicholas, Jayna, Hahn, Julie, Heath, Adam S., Raffield, Laura M., Yanek, Lisa R., Brody, Jennifer A., Thibord, Florian, Almasy, Laura, Bartz, Traci M., Bielak, Lawrence F., Bowler, Russell P., Carrasquilla, Germán D., Chasman, Daniel I., Chen, Ming-Huei, Emmert, David B., Ghanbari, Mohsen, Haessler, Jeffrey, Hottenga, Jouke-Jan, Kleber, Marcus E., Le, Ngoc-Quynh, Lee, Jiwon, Lewis, Joshua P., Li-Gao, Ruifang, Luan, Jian'an, Malmberg, Anni, Mangino, Massimo, Marioni, Riccardo E., Martinez-Perez, Angel, Pankratz, Nathan, Polasek, Ozren, Richmond, Anne, Rodriguez, Benjamin A. T., Rotter, Jerome I., Steri, Maristella, Suchon, Pierre, Trompet, Stella, Weiss, Stefan, Zare, Marjan, Auer, Paul, Cho, Michael H., Christofidou, Paraskevi, Davies, Gail, de Geus, Eco, Deleuze, Jean-François, Delgado, Graciela E., Ekunwe, Lynette, Faraday, Nauder, Gögele, Martin, Greinacher, Andreas, Gao, He, Howard, Tom, Joshi, Peter K., Kilpeläinen, Tuomas O., Lahti, Jari, Linneberg, Allan, Naitza, Silvia, Noordam, Raymond, Paüls-Vergés, Ferran, Rich, Stephen S., Rosendaal, Frits R., Rudan, Igor, Ryan, Kathleen A., Souto, Juan Carlos, van Rooij, Frank J. A., Wang, Heming, Zhao, Wei, Becker, Lewis C., Beswick, Andrew, Brown, Michael R., Cade, Brian E., Campbell, Harry, Cho, Kelly, Crapo, James D., Curran, Joanne E., de Maat, Moniek P. M., Doyle, Margaret, Elliott, Paul, Floyd, James S., Fuchsberger, Christian, Grarup, Niels, Guo, Xiuqing, Harris, Sarah E., Hou, Lifang, Kolcic, Ivana, Kooperberg, Charles, Menni, Cristina, Nauck, Matthias, O'Connell, Jeffrey R., Orrù, Valeria, Psaty, Bruce M., Räikkönen, Katri, Smith, Jennifer A., Soria, Jose Manuel, Stott, David J., van Hylckama Vlieg, Astrid, Watkins, Hugh, Willemsen, Gonneke, Wilson, Peter W. F., Ben-Shlomo, Yoav, Blangero, John, Boomsma, Dorret, Cox, Simon R., Dehghan, Abbas, Eriksson, Johan G., Fiorillo, Edoardo, Fornage, Myriam, Hansen, Torben, Hayward, Caroline, Ikram, M. Arfan, Jukema, J. Wouter, Kardia, Sharon L. R., Lange, Leslie A., März, Winfried, Mathias, Rasika A., Mitchell, Braxton D., Mook-Kanamori, Dennis O., Morange, Pierre-Emmanuel, Pedersen, Oluf, Pramstaller, Peter P., Redline, Susan, Reiner, Alexander, Ridker, Paul M., Silverman, Edwin K., Spector, Tim D., Völker, Uwe, Wareham, Nicholas J., Wilson, James F., Yao, Jie, Trégouët, David-Alexandre, Johnson, Andrew D., Wolberg, Alisa S., de Vries, Paul S., Sabater-Lleal, Maria, Morrison, Alanna C., and Smith, Nicholas L.

Published
2024
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17. Genetic analysis in European ancestry individuals identifies 517 loci associated with liver enzymes

Author

Pazoki, Raha, Vujkovic, Marijana, Elliott, Joshua, Evangelou, Evangelos, Gill, Dipender, Ghanbari, Mohsen, van der Most, Peter J, Pinto, Rui Climaco, Wielscher, Matthias, Farlik, Matthias, Zuber, Verena, de Knegt, Robert J, Snieder, Harold, Uitterlinden, André G, Lynch, Julie A, Jiang, Xiyun, Said, Saredo, Kaplan, David E, Lee, Kyung Min, Serper, Marina, Carr, Rotonya M, Tsao, Philip S, Atkinson, Stephen R, Dehghan, Abbas, Tzoulaki, Ioanna, Ikram, M Arfan, Herzig, Karl-Heinz, Järvelin, Marjo-Riitta, Alizadeh, Behrooz Z, O’Donnell, Christopher J, Saleheen, Danish, Voight, Benjamin F, Chang, Kyong-Mi, Thursz, Mark R, and Elliott, Paul

Subjects
Cardiovascular, Digestive Diseases, Heart Disease, Liver Disease, Genetics, 2.1 Biological and endogenous factors, Aetiology, Oral and gastrointestinal, Metabolic and endocrine, Good Health and Well Being, Aged, Alanine Transaminase, Alkaline Phosphatase, Cardiovascular Diseases, Cohort Studies, Databases, Genetic, Female, Gene Expression Regulation, Enzymologic, Genetic Predisposition to Disease, Genetic Testing, Genome-Wide Association Study, Humans, Insulin Resistance, Lipid Metabolism, Liver, Male, Mendelian Randomization Analysis, Metabolic Diseases, Middle Aged, Polymorphism, Single Nucleotide, Risk Factors, White People, gamma-Glutamyltransferase, Lifelines Cohort Study, VA Million Veteran Program
Abstract

Serum concentration of hepatic enzymes are linked to liver dysfunction, metabolic and cardiovascular diseases. We perform genetic analysis on serum levels of alanine transaminase (ALT), alkaline phosphatase (ALP) and gamma-glutamyl transferase (GGT) using data on 437,438 UK Biobank participants. Replication in 315,572 individuals from European descent from the Million Veteran Program, Rotterdam Study and Lifeline study confirms 517 liver enzyme SNPs. Genetic risk score analysis using the identified SNPs is strongly associated with serum activity of liver enzymes in two independent European descent studies (The Airwave Health Monitoring study and the Northern Finland Birth Cohort 1966). Gene-set enrichment analysis using the identified SNPs highlights involvement in liver development and function, lipid metabolism, insulin resistance, and vascular formation. Mendelian randomization analysis shows association of liver enzyme variants with coronary heart disease and ischemic stroke. Genetic risk score for elevated serum activity of liver enzymes is associated with higher fat percentage of body, trunk, and liver and body mass index. Our study highlights the role of molecular pathways regulated by the liver in metabolic disorders and cardiovascular disease.

Published
2021

18. Genome-wide association and Mendelian randomisation analysis provide insights into the pathogenesis of heart failure.

Author

Shah, Sonia, Henry, Albert, Roselli, Carolina, Lin, Honghuang, Sveinbjörnsson, Garðar, Fatemifar, Ghazaleh, Hedman, Åsa K, Wilk, Jemma B, Morley, Michael P, Chaffin, Mark D, Helgadottir, Anna, Verweij, Niek, Dehghan, Abbas, Almgren, Peter, Andersson, Charlotte, Aragam, Krishna G, Ärnlöv, Johan, Backman, Joshua D, Biggs, Mary L, Bloom, Heather L, Brandimarto, Jeffrey, Brown, Michael R, Buckbinder, Leonard, Carey, David J, Chasman, Daniel I, Chen, Xing, Chen, Xu, Chung, Jonathan, Chutkow, William, Cook, James P, Delgado, Graciela E, Denaxas, Spiros, Doney, Alexander S, Dörr, Marcus, Dudley, Samuel C, Dunn, Michael E, Engström, Gunnar, Esko, Tõnu, Felix, Stephan B, Finan, Chris, Ford, Ian, Ghanbari, Mohsen, Ghasemi, Sahar, Giedraitis, Vilmantas, Giulianini, Franco, Gottdiener, John S, Gross, Stefan, Guðbjartsson, Daníel F, Gutmann, Rebecca, Haggerty, Christopher M, van der Harst, Pim, Hyde, Craig L, Ingelsson, Erik, Jukema, J Wouter, Kavousi, Maryam, Khaw, Kay-Tee, Kleber, Marcus E, Køber, Lars, Koekemoer, Andrea, Langenberg, Claudia, Lind, Lars, Lindgren, Cecilia M, London, Barry, Lotta, Luca A, Lovering, Ruth C, Luan, Jian'an, Magnusson, Patrik, Mahajan, Anubha, Margulies, Kenneth B, März, Winfried, Melander, Olle, Mordi, Ify R, Morgan, Thomas, Morris, Andrew D, Morris, Andrew P, Morrison, Alanna C, Nagle, Michael W, Nelson, Christopher P, Niessner, Alexander, Niiranen, Teemu, O'Donoghue, Michelle L, Owens, Anjali T, Palmer, Colin NA, Parry, Helen M, Perola, Markus, Portilla-Fernandez, Eliana, Psaty, Bruce M, Regeneron Genetics Center, Rice, Kenneth M, Ridker, Paul M, Romaine, Simon PR, Rotter, Jerome I, Salo, Perttu, Salomaa, Veikko, van Setten, Jessica, Shalaby, Alaa A, Smelser, Diane T, Smith, Nicholas L, Stender, Steen, and Stott, David J

Subjects
Regeneron Genetics Center, Humans, Atrial Fibrillation, Cardiomyopathies, Microfilament Proteins, Adaptor Proteins, Signal Transducing, Carrier Proteins, Muscle Proteins, Risk Factors, Case-Control Studies, Ventricular Function, Left, Cyclin-Dependent Kinase Inhibitor p21, Apoptosis Regulatory Proteins, Coronary Artery Disease, Heart Failure, Genome-Wide Association Study, Mendelian Randomization Analysis, Adaptor Proteins, Signal Transducing, Ventricular Function, Left
Abstract

Heart failure (HF) is a leading cause of morbidity and mortality worldwide. A small proportion of HF cases are attributable to monogenic cardiomyopathies and existing genome-wide association studies (GWAS) have yielded only limited insights, leaving the observed heritability of HF largely unexplained. We report results from a GWAS meta-analysis of HF comprising 47,309 cases and 930,014 controls. Twelve independent variants at 11 genomic loci are associated with HF, all of which demonstrate one or more associations with coronary artery disease (CAD), atrial fibrillation, or reduced left ventricular function, suggesting shared genetic aetiology. Functional analysis of non-CAD-associated loci implicate genes involved in cardiac development (MYOZ1, SYNPO2L), protein homoeostasis (BAG3), and cellular senescence (CDKN1A). Mendelian randomisation analysis supports causal roles for several HF risk factors, and demonstrates CAD-independent effects for atrial fibrillation, body mass index, and hypertension. These findings extend our knowledge of the pathways underlying HF and may inform new therapeutic strategies.

Published
2020

19. Genetic loci associated with prevalent and incident myocardial infarction and coronary heart disease in the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium

Author

Hahn, Julie, Fu, Yi-Ping, Brown, Michael R, Bis, Joshua C, de Vries, Paul S, Feitosa, Mary F, Yanek, Lisa R, Weiss, Stefan, Giulianini, Franco, Smith, Albert Vernon, Guo, Xiuqing, Bartz, Traci M, Becker, Diane M, Becker, Lewis C, Boerwinkle, Eric, Brody, Jennifer A, Chen, Yii-Der Ida, Franco, Oscar H, Grove, Megan, Harris, Tamara B, Hofman, Albert, Hwang, Shih-Jen, Kral, Brian G, Launer, Lenore J, Markus, Marcello RP, Rice, Kenneth M, Rich, Stephen S, Ridker, Paul M, Rivadeneira, Fernando, Rotter, Jerome I, Sotoodehnia, Nona, Taylor, Kent D, Uitterlinden, André G, Völker, Uwe, Völzke, Henry, Yao, Jie, Chasman, Daniel I, Dörr, Marcus, Gudnason, Vilmundur, Mathias, Rasika A, Post, Wendy, Psaty, Bruce M, Dehghan, Abbas, O’Donnell, Christopher J, and Morrison, Alanna C

Subjects
Epidemiology, Biological Sciences, Health Sciences, Genetics, Heart Disease, Heart Disease - Coronary Heart Disease, Human Genome, Aging, Clinical Research, Cardiovascular, 2.4 Surveillance and distribution, Aetiology, 2.1 Biological and endogenous factors, Good Health and Well Being, Coronary Artery Disease, Cross-Sectional Studies, Europe, Genetic Loci, Genome-Wide Association Study, Humans, Myocardial Infarction, Polymorphism, Single Nucleotide, Prospective Studies, White People, General Science & Technology
Abstract

BackgroundGenome-wide association studies have identified multiple genomic loci associated with coronary artery disease, but most are common variants in non-coding regions that provide limited information on causal genes and etiology of the disease. To overcome the limited scope that common variants provide, we focused our investigation on low-frequency and rare sequence variations primarily residing in coding regions of the genome.Methods and resultsUsing samples of individuals of European ancestry from ten cohorts within the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium, both cross-sectional and prospective analyses were conducted to examine associations between genetic variants and myocardial infarction (MI), coronary heart disease (CHD), and all-cause mortality following these events. For prevalent events, a total of 27,349 participants of European ancestry, including 1831 prevalent MI cases and 2518 prevalent CHD cases were used. For incident cases, a total of 55,736 participants of European ancestry were included (3,031 incident MI cases and 5,425 incident CHD cases). There were 1,860 all-cause deaths among the 3,751 MI and CHD cases from six cohorts that contributed to the analysis of all-cause mortality. Single variant and gene-based analyses were performed separately in each cohort and then meta-analyzed for each outcome. A low-frequency intronic variant (rs988583) in PLCL1 was significantly associated with prevalent MI (OR = 1.80, 95% confidence interval: 1.43, 2.27; P = 7.12 × 10-7). We conducted gene-based burden tests for genes with a cumulative minor allele count (cMAC) ≥ 5 and variants with minor allele frequency (MAF) < 5%. TMPRSS5 and LDLRAD1 were significantly associated with prevalent MI and CHD, respectively, and RC3H2 and ANGPTL4 were significantly associated with incident MI and CHD, respectively. No loci were significantly associated with all-cause mortality following a MI or CHD event.ConclusionThis study identified one known locus (ANGPTL4) and four new loci (PLCL1, RC3H2, TMPRSS5, and LDLRAD1) associated with cardiovascular disease risk that warrant further investigation.

Published
2020

20. DNA methylation analysis is used to identify novel genetic loci associated with circulating fibrinogen levels in blood

Author

Hahn, Julie, Bressler, Jan, Domingo-Relloso, Arce, Chen, Ming-Huei, McCartney, Daniel L., Teumer, Alexander, van Dongen, Jenny, Kleber, Marcus E., Aïssi, Dylan, Swenson, Brenton R., Yao, Jie, Zhao, Wei, Huang, Jian, Xia, Yujing, Brown, Michael R., Costeira, Ricardo, de Geus, Eco J.C., Delgado, Graciela E., Dobson, Dre'Von A., Elliott, Paul, Grabe, Hans J., Guo, Xiuqing, Harris, Sarah E., Huffman, Jennifer E., Kardia, Sharon L.R., Liu, Yongmei, Lorkowski, Stefan, Marioni, Riccardo E., Nauck, Matthias, Ratliff, Scott M., Sabater-Lleal, Maria, Spector, Tim D., Suchon, Pierre, Taylor, Kent D., Thibord, Florian, Trégouët, David-Alexandre, Wiggins, Kerri L., Willemsen, Gonneke, Bell, Jordana T., Boomsma, Dorret I., Cole, Shelley A., Cox, Simon R., Dehghan, Abbas, Greinacher, Andreas, Haack, Karin, März, Winfried, Morange, Pierre-Emmanuel, Rotter, Jerome I., Sotoodehnia, Nona, Tellez-Plaza, Maria, Navas-Acien, Ana, Smith, Jennifer A., Johnson, Andrew D., Fornage, Myriam, Smith, Nicholas L., Wolberg, Alisa S., Morrison, Alanna C., and de Vries, Paul S.

Published
2023
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22. Blood Leukocyte DNA Methylation Predicts Risk of Future Myocardial Infarction and Coronary Heart Disease

Author

Agha, Golareh, Mendelson, Michael M, Ward-Caviness, Cavin K, Joehanes, Roby, Huan, TianXiao, Gondalia, Rahul, Salfati, Elias, Brody, Jennifer A, Fiorito, Giovanni, Bressler, Jan, Chen, Brian H, Ligthart, Symen, Guarrera, Simonetta, Colicino, Elena, Just, Allan C, Wahl, Simone, Gieger, Christian, Vandiver, Amy R, Tanaka, Toshiko, Hernandez, Dena G, Pilling, Luke C, Singleton, Andrew B, Sacerdote, Carlotta, Krogh, Vittorio, Panico, Salvatore, Tumino, Rosario, Li, Yun, Zhang, Guosheng, Stewart, James D, Floyd, James S, Wiggins, Kerri L, Rotter, Jerome I, Multhaup, Michael, Bakulski, Kelly, Horvath, Steven, Tsao, Philip S, Absher, Devin M, Vokonas, Pantel, Hirschhorn, Joel, Fallin, M Daniele, Liu, Chunyu, Bandinelli, Stefania, Boerwinkle, Eric, Dehghan, Abbas, Schwartz, Joel D, Psaty, Bruce M, Feinberg, Andrew P, Hou, Lifang, Ferrucci, Luigi, Sotoodehnia, Nona, Matullo, Giuseppe, Peters, Annette, Fornage, Myriam, Assimes, Themistocles L, Whitsel, Eric A, Levy, Daniel, and Baccarelli, Andrea A

Subjects
Human Genome, Heart Disease, Clinical Research, Prevention, Heart Disease - Coronary Heart Disease, Atherosclerosis, Cardiovascular, Genetics, Adult, Aged, Cohort Studies, Coronary Disease, CpG Islands, DNA Methylation, Europe, Female, Genome-Wide Association Study, Humans, Incidence, Leukocytes, Male, Middle Aged, Myocardial Infarction, Population Groups, Prognosis, Prospective Studies, Risk, United States, coronary artery disease, coronary heart disease, epigenetics, genomics, gene expression regulation, Cardiorespiratory Medicine and Haematology, Clinical Sciences, Public Health and Health Services, Cardiovascular System & Hematology
Abstract

BackgroundDNA methylation is implicated in coronary heart disease (CHD), but current evidence is based on small, cross-sectional studies. We examined blood DNA methylation in relation to incident CHD across multiple prospective cohorts.MethodsNine population-based cohorts from the United States and Europe profiled epigenome-wide blood leukocyte DNA methylation using the Illumina Infinium 450k microarray, and prospectively ascertained CHD events including coronary insufficiency/unstable angina, recognized myocardial infarction, coronary revascularization, and coronary death. Cohorts conducted race-specific analyses adjusted for age, sex, smoking, education, body mass index, blood cell type proportions, and technical variables. We conducted fixed-effect meta-analyses across cohorts.ResultsAmong 11 461 individuals (mean age 64 years, 67% women, 35% African American) free of CHD at baseline, 1895 developed CHD during a mean follow-up of 11.2 years. Methylation levels at 52 CpG (cytosine-phosphate-guanine) sites were associated with incident CHD or myocardial infarction (false discovery rate

Published
2019

23. Author Correction: Study of 300,486 individuals identifies 148 independent genetic loci influencing general cognitive function.

Author

Davies, Gail, Lam, Max, Harris, Sarah E, Trampush, Joey W, Luciano, Michelle, Hill, W David, Hagenaars, Saskia P, Ritchie, Stuart J, Marioni, Riccardo E, Fawns-Ritchie, Chloe, Liewald, David CM, Okely, Judith A, Ahola-Olli, Ari V, Barnes, Catriona LK, Bertram, Lars, Bis, Joshua C, Burdick, Katherine E, Christoforou, Andrea, DeRosse, Pamela, Djurovic, Srdjan, Espeseth, Thomas, Giakoumaki, Stella, Giddaluru, Sudheer, Gustavson, Daniel E, Hayward, Caroline, Hofer, Edith, Ikram, M Arfan, Karlsson, Robert, Knowles, Emma, Lahti, Jari, Leber, Markus, Li, Shuo, Mather, Karen A, Melle, Ingrid, Morris, Derek, Oldmeadow, Christopher, Palviainen, Teemu, Payton, Antony, Pazoki, Raha, Petrovic, Katja, Reynolds, Chandra A, Sargurupremraj, Muralidharan, Scholz, Markus, Smith, Jennifer A, Smith, Albert V, Terzikhan, Natalie, Thalamuthu, Anbupalam, Trompet, Stella, van der Lee, Sven J, Ware, Erin B, Windham, B Gwen, Wright, Margaret J, Yang, Jingyun, Yu, Jin, Ames, David, Amin, Najaf, Amouyel, Philippe, Andreassen, Ole A, Armstrong, Nicola J, Assareh, Amelia A, Attia, John R, Attix, Deborah, Avramopoulos, Dimitrios, Bennett, David A, Böhmer, Anne C, Boyle, Patricia A, Brodaty, Henry, Campbell, Harry, Cannon, Tyrone D, Cirulli, Elizabeth T, Congdon, Eliza, Conley, Emily Drabant, Corley, Janie, Cox, Simon R, Dale, Anders M, Dehghan, Abbas, Dick, Danielle, Dickinson, Dwight, Eriksson, Johan G, Evangelou, Evangelos, Faul, Jessica D, Ford, Ian, Freimer, Nelson A, Gao, He, Giegling, Ina, Gillespie, Nathan A, Gordon, Scott D, Gottesman, Rebecca F, Griswold, Michael E, Gudnason, Vilmundur, Harris, Tamara B, Hartmann, Annette M, Hatzimanolis, Alex, Heiss, Gerardo, Holliday, Elizabeth G, Joshi, Peter K, Kähönen, Mika, Kardia, Sharon LR, Karlsson, Ida, and Kleineidam, Luca

Abstract

Christina M. Lill, who contributed to analysis of data, was inadvertently omitted from the author list in the originally published version of this article. This has now been corrected in both the PDF and HTML versions of the article.

Published
2019

24. Genome-Wide Association Transethnic Meta-Analyses Identifies Novel Associations Regulating Coagulation Factor VIII and von Willebrand Factor Plasma Levels

Author

Sabater-Lleal, Maria, Huffman, Jennifer E, de Vries, Paul S, Marten, Jonathan, Mastrangelo, Michael A, Song, Ci, Pankratz, Nathan, Ward-Caviness, Cavin K, Yanek, Lisa R, Trompet, Stella, Delgado, Graciela E, Guo, Xiuqing, Bartz, Traci M, Martinez-Perez, Angel, Germain, Marine, de Haan, Hugoline G, Ozel, Ayse B, Polasek, Ozren, Smith, Albert V, Eicher, John D, Reiner, Alex P, Tang, Weihong, Davies, Neil M, Stott, David J, Rotter, Jerome I, Tofler, Geoffrey H, Boerwinkle, Eric, de Maat, Moniek PM, Kleber, Marcus E, Welsh, Paul, Brody, Jennifer A, Chen, Ming-Huei, Vaidya, Dhananjay, Soria, José Manuel, Suchon, Pierre, van Hylckama Vlieg, Astrid, Desch, Karl C, Kolcic, Ivana, Joshi, Peter K, Launer, Lenore J, Harris, Tamara B, Campbell, Harry, Rudan, Igor, Becker, Diane M, Li, Jun Z, Rivadeneira, Fernando, Uitterlinden, André G, Hofman, Albert, Franco, Oscar H, Cushman, Mary, Psaty, Bruce M, Morange, Pierre-Emmanuel, McKnight, Barbara, Chong, Michael R, Fernandez-Cadenas, Israel, Rosand, Jonathan, Lindgren, Arne, Consortium, INVENT Consortium MEGASTROKE Consortium of the International Stroke Genetics, Gudnason, Vilmundur, Wilson, James F, Hayward, Caroline, Ginsburg, David, Fornage, Myriam, Rosendaal, Frits R, Souto, Juan Carlos, Becker, Lewis C, Jenny, Nancy S, März, Winfried, Jukema, J Wouter, Dehghan, Abbas, Trégouët, David-Alexandre, Morrison, Alanna C, Johnson, Andrew D, O’Donnell, Christopher J, Strachan, David P, Lowenstein, Charles J, and Smith, Nicholas L

Subjects
Epidemiology, Health Sciences, Hematology, Biotechnology, Rare Diseases, Genetics, Human Genome, Aetiology, 2.1 Biological and endogenous factors, Blood, Cardiovascular, Arterial Occlusive Diseases, Biomarkers, Blood Coagulation, Blood Coagulation Disorders, Inherited, Factor VIII, Genetic Loci, Genetic Markers, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Mendelian Randomization Analysis, Phenotype, Ribosomal Protein L3, Risk Factors, Venous Thrombosis, von Willebrand Factor, cardiovascular diseases, factor VIII, genome-wide association studies, genetics, risk factors, von Willebrand factor, INVENT Consortium, MEGASTROKE Consortium of the International Stroke Genetics Consortium, Cardiorespiratory Medicine and Haematology, Clinical Sciences, Public Health and Health Services, Cardiovascular System & Hematology, Cardiovascular medicine and haematology, Clinical sciences, Sports science and exercise
Abstract

BackgroundFactor VIII (FVIII) and its carrier protein von Willebrand factor (VWF) are associated with risk of arterial and venous thrombosis and with hemorrhagic disorders. We aimed to identify and functionally test novel genetic associations regulating plasma FVIII and VWF.MethodsWe meta-analyzed genome-wide association results from 46 354 individuals of European, African, East Asian, and Hispanic ancestry. All studies performed linear regression analysis using an additive genetic model and associated ≈35 million imputed variants with natural log-transformed phenotype levels. In vitro gene silencing in cultured endothelial cells was performed for candidate genes to provide additional evidence on association and function. Two-sample Mendelian randomization analyses were applied to test the causal role of FVIII and VWF plasma levels on the risk of arterial and venous thrombotic events.ResultsWe identified 13 novel genome-wide significant ( P≤2.5×10-8) associations, 7 with FVIII levels ( FCHO2/TMEM171/TNPO1, HLA, SOX17/RP1, LINC00583/NFIB, RAB5C-KAT2A, RPL3/TAB1/SYNGR1, and ARSA) and 11 with VWF levels ( PDHB/PXK/KCTD6, SLC39A8, FCHO2/TMEM171/TNPO1, HLA, GIMAP7/GIMAP4, OR13C5/NIPSNAP, DAB2IP, C2CD4B, RAB5C-KAT2A, TAB1/SYNGR1, and ARSA), beyond 10 previously reported associations with these phenotypes. Functional validation provided further evidence of association for all loci on VWF except ARSA and DAB2IP. Mendelian randomization suggested causal effects of plasma FVIII activity levels on venous thrombosis and coronary artery disease risk and plasma VWF levels on ischemic stroke risk.ConclusionsThe meta-analysis identified 13 novel genetic loci regulating FVIII and VWF plasma levels, 10 of which we validated functionally. We provide some evidence for a causal role of these proteins in thrombotic events.

Published
2019

25. An integrative cross-omics analysis of DNA methylation sites of glucose and insulin homeostasis

Author

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

Subjects
Biological Sciences, Genetics, Nutrition, Diabetes, Human Genome, Obesity, 2.1 Biological and endogenous factors, Aetiology, Metabolic and endocrine, Adult, Aged, Aged, 80 and over, Computer Simulation, CpG Islands, DNA Methylation, Diabetes Mellitus, Type 2, Epigenesis, Genetic, Epigenomics, Female, Gene Expression Profiling, Gene Expression Regulation, Genome-Wide Association Study, Glucose, Homeostasis, Humans, Insulin, Male, Metabolic Networks and Pathways, Middle Aged, Polymorphism, Single Nucleotide, Young Adult
Abstract

Despite existing reports on differential DNA methylation in type 2 diabetes (T2D) and obesity, our understanding of its functional relevance remains limited. Here we show the effect of differential methylation in the early phases of T2D pathology by a blood-based epigenome-wide association study of 4808 non-diabetic Europeans in the discovery phase and 11,750 individuals in the replication. We identify CpGs in LETM1, RBM20, IRS2, MAN2A2 and the 1q25.3 region associated with fasting insulin, and in FCRL6, SLAMF1, APOBEC3H and the 15q26.1 region with fasting glucose. In silico cross-omics analyses highlight the role of differential methylation in the crosstalk between the adaptive immune system and glucose homeostasis. The differential methylation explains at least 16.9% of the association between obesity and insulin. Our study sheds light on the biological interactions between genetic variants driving differential methylation and gene expression in the early pathogenesis of T2D.

Published
2019

26. Mendelian randomization evaluation of causal effects of fibrinogen on incident coronary heart disease

Author

Ward-Caviness, Cavin K, de Vries, Paul S, Wiggins, Kerri L, Huffman, Jennifer E, Yanek, Lisa R, Bielak, Lawrence F, Giulianini, Franco, Guo, Xiuqing, Kleber, Marcus E, Kacprowski, Tim, Groß, Stefan, Petersman, Astrid, Smith, George Davey, Hartwig, Fernando P, Bowden, Jack, Hemani, Gibran, Müller-Nuraysid, Martina, Strauch, Konstantin, Koenig, Wolfgang, Waldenberger, Melanie, Meitinger, Thomas, Pankratz, Nathan, Boerwinkle, Eric, Tang, Weihong, Fu, Yi-Ping, Johnson, Andrew D, Song, Ci, de Maat, Moniek PM, Uitterlinden, André G, Franco, Oscar H, Brody, Jennifer A, McKnight, Barbara, Chen, Yii-Der Ida, Psaty, Bruce M, Mathias, Rasika A, Becker, Diane M, Peyser, Patricia A, Smith, Jennifer A, Bielinski, Suzette J, Ridker, Paul M, Taylor, Kent D, Yao, Jie, Tracy, Russell, Delgado, Graciela, Trompet, Stella, Sattar, Naveed, Jukema, J Wouter, Becker, Lewis C, Kardia, Sharon LR, Rotter, Jerome I, März, Winfried, Dörr, Marcus, Chasman, Daniel I, Dehghan, Abbas, O’Donnell, Christopher J, Smith, Nicholas L, Peters, Annette, and Morrison, Alanna C

Subjects
Epidemiology, Biological Sciences, Health Sciences, Genetics, Heart Disease, Cardiovascular, Prevention, Human Genome, Heart Disease - Coronary Heart Disease, Alleles, Coronary Disease, Fibrinogen, Genetic Pleiotropy, Genetic Variation, Genome-Wide Association Study, Humans, Incidence, Mendelian Randomization Analysis, Models, Genetic, Multivariate Analysis, Myocardial Infarction, Odds Ratio, General Science & Technology
Abstract

BackgroundFibrinogen is an essential hemostatic factor and cardiovascular disease risk factor. Early attempts at evaluating the causal effect of fibrinogen on coronary heart disease (CHD) and myocardial infraction (MI) using Mendelian randomization (MR) used single variant approaches, and did not take advantage of recent genome-wide association studies (GWAS) or multi-variant, pleiotropy robust MR methodologies.Methods and findingsWe evaluated evidence for a causal effect of fibrinogen on both CHD and MI using MR. We used both an allele score approach and pleiotropy robust MR models. The allele score was composed of 38 fibrinogen-associated variants from recent GWAS. Initial analyses using the allele score used a meta-analysis of 11 European-ancestry prospective cohorts, free of CHD and MI at baseline, to examine incidence CHD and MI. We also applied 2 sample MR methods with data from a prevalent CHD and MI GWAS. Results are given in terms of the hazard ratio (HR) or odds ratio (OR), depending on the study design, and associated 95% confidence interval (CI). In single variant analyses no causal effect of fibrinogen on CHD or MI was observed. In multi-variant analyses using incidence CHD cases and the allele score approach, the estimated causal effect (HR) of a 1 g/L higher fibrinogen concentration was 1.62 (CI = 1.12, 2.36) when using incident cases and the allele score approach. In 2 sample MR analyses that accounted for pleiotropy, the causal estimate (OR) was reduced to 1.18 (CI = 0.98, 1.42) and 1.09 (CI = 0.89, 1.33) in the 2 most precise (smallest CI) models, out of 4 models evaluated. In the 2 sample MR analyses for MI, there was only very weak evidence of a causal effect in only 1 out of 4 models.ConclusionsA small causal effect of fibrinogen on CHD is observed using multi-variant MR approaches which account for pleiotropy, but not single variant MR approaches. Taken together, results indicate that even with large sample sizes and multi-variant approaches MR analyses still cannot exclude the null when estimating the causal effect of fibrinogen on CHD, but that any potential causal effect is likely to be much smaller than observed in epidemiological studies.

Published
2019

27. Blood pressure-lowering treatment for prevention of major cardiovascular diseases in people with and without type 2 diabetes: an individual participant-level data meta-analysis

Author

Agodoa, L, Algra, A, Asselbergs, F W, Beckett, N, Berge, E, Black, H, Brouwers, F P J, Brown, M, Bulpitt, C J, Byington, B, Cutler, J, Devereaux, R B, Dwyer, J, Estacio, R, Fagard, R, Fox, K, Fukui, T, Imai, Y, Ishii, M, Julius, S, Kanno, Y, Kjeldsen, S E, Kostis, J, Kuramoto, K, Lanke, J, Lewis, E, Lewis, J, Lievre, M, Lindholm, L H, Lueders, S, MacMahon, S, Mancia, G, Matsuzaki, M, Mehlum, M H, Nissen, S, Ogawa, H, Ogihara, T, Ohkubo, T, Palmer, C, Patel, A, Pfeffer, M, Poulter, N R, Rakugi, H, Reboldi, G, Reid, C, Remuzzi, G, Ruggenenti, P, Saruta, T, Schrader, J, Schrier, R, Sever, P, Sleight, P, Staessen, J A, Suzuki, H, Thijs, L, Ueshima, K, Umemoto, S, van Gilst, W H, Verdecchia, P, Wachtell, K, Whelton, P, Wing, L, Yui, Y, Yusuf, S, Zanchetti, A, Zhang, Z Y, Anderson, C, Baigent, C, Brenner, BM, Collins, R, de Zeeuw, D, Lubsen, J, Malacco, E, Neal, B, Perkovic, V, Pitt, B, Rodgers, A, Rothwell, P, Salimi-Khorshidi, G, Sundström, J, Turnbull, F, Viberti, G, Wang, J, Nazarzadeh, Milad, Bidel, Zeinab, Canoy, Dexter, Copland, Emma, Bennett, Derrick A, Dehghan, Abbas, Davey Smith, George, Holman, Rury R, Woodward, Mark, Gupta, Ajay, Adler, Amanda I, Wamil, Malgorzata, Sattar, Naveed, Cushman, William C, McManus, Richard J, Teo, Koon, Davis, Barry R, Chalmers, John, Pepine, Carl J, and Rahimi, Kazem

Published
2022
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28. Multi-ancestry genetic study of type 2 diabetes highlights the power of diverse populations for discovery and translation

Author

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

Published
2022
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29. Circulating inflammatory cytokines and risk of five cancers: a Mendelian randomization analysis

Author

Bouras, Emmanouil, Karhunen, Ville, Gill, Dipender, Huang, Jian, Haycock, Philip C., Gunter, Marc J., Johansson, Mattias, Brennan, Paul, Key, Tim, Lewis, Sarah J., Martin, Richard M., Murphy, Neil, Platz, Elizabeth A., Travis, Ruth, Yarmolinsky, James, Zuber, Verena, Martin, Paul, Katsoulis, Michail, Freisling, Heinz, Nøst, Therese Haugdahl, Schulze, Matthias B., Dossus, Laure, Hung, Rayjean J., Amos, Christopher I., Ahola-Olli, Ari, Palaniswamy, Saranya, Männikkö, Minna, Auvinen, Juha, Herzig, Karl-Heinz, Keinänen-Kiukaanniemi, Sirkka, Lehtimäki, Terho, Salomaa, Veikko, Raitakari, Olli, Salmi, Marko, Jalkanen, Sirpa, Jarvelin, Marjo-Riitta, Dehghan, Abbas, and Tsilidis, Konstantinos K.

Published
2022
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30. Genome-wide associations of aortic distensibility suggest causality for aortic aneurysms and brain white matter hyperintensities

Author

Francis, Catherine M., Futschik, Matthias E., Huang, Jian, Bai, Wenjia, Sargurupremraj, Muralidharan, Teumer, Alexander, Breteler, Monique M. B., Petretto, Enrico, Ho, Amanda S. R., Amouyel, Philippe, Engelter, Stefan T., Bülow, Robin, Völker, Uwe, Völzke, Henry, Dörr, Marcus, Imtiaz, Mohammed-Aslam, Aziz, N. Ahmad, Lohner, Valerie, Ware, James S., Debette, Stephanie, Elliott, Paul, Dehghan, Abbas, and Matthews, Paul M.

Published
2022
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31. Exploring the causal effect of maternal pregnancy adiposity on offspring adiposity: Mendelian randomisation using polygenic risk scores

Author

Bond, Tom A., Richmond, Rebecca C., Karhunen, Ville, Cuellar-Partida, Gabriel, Borges, Maria Carolina, Zuber, Verena, Couto Alves, Alexessander, Mason, Dan, Yang, Tiffany C., Gunter, Marc J., Dehghan, Abbas, Tzoulaki, Ioanna, Sebert, Sylvain, Evans, David M., Lewin, Alex M., O’Reilly, Paul F., Lawlor, Deborah A., and Järvelin, Marjo-Riitta

Published
2022
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32. DNA methylation signature of chronic low-grade inflammation and its role in cardio-respiratory diseases

Author

Wielscher, Matthias, Mandaviya, Pooja R., Kuehnel, Brigitte, Joehanes, Roby, Mustafa, Rima, Robinson, Oliver, Zhang, Yan, Bodinier, Barbara, Walton, Esther, Mishra, Pashupati P., Schlosser, Pascal, Wilson, Rory, Tsai, Pei-Chien, Palaniswamy, Saranya, Marioni, Riccardo E., Fiorito, Giovanni, Cugliari, Giovanni, Karhunen, Ville, Ghanbari, Mohsen, Psaty, Bruce M., Loh, Marie, Bis, Joshua C., Lehne, Benjamin, Sotoodehnia, Nona, Deary, Ian J., Chadeau-Hyam, Marc, Brody, Jennifer A., Cardona, Alexia, Selvin, Elizabeth, Smith, Alicia K., Miller, Andrew H., Torres, Mylin A., Marouli, Eirini, Gào, Xin, van Meurs, Joyce B. J., Graf-Schindler, Johanna, Rathmann, Wolfgang, Koenig, Wolfgang, Peters, Annette, Weninger, Wolfgang, Farlik, Matthias, Zhang, Tao, Chen, Wei, Xia, Yujing, Teumer, Alexander, Nauck, Matthias, Grabe, Hans J., Doerr, Macus, Lehtimäki, Terho, Guan, Weihua, Milani, Lili, Tanaka, Toshiko, Fisher, Krista, Waite, Lindsay L., Kasela, Silva, Vineis, Paolo, Verweij, Niek, van der Harst, Pim, Iacoviello, Licia, Sacerdote, Carlotta, Panico, Salvatore, Krogh, Vittorio, Tumino, Rosario, Tzala, Evangelia, Matullo, Giuseppe, Hurme, Mikko A., Raitakari, Olli T., Colicino, Elena, Baccarelli, Andrea A., Kähönen, Mika, Herzig, Karl-Heinz, Li, Shengxu, Conneely, Karen N., Kooner, Jaspal S., Köttgen, Anna, Heijmans, Bastiaan T., Deloukas, Panos, Relton, Caroline, Ong, Ken K., Bell, Jordana T., Boerwinkle, Eric, Elliott, Paul, Brenner, Hermann, Beekman, Marian, Levy, Daniel, Waldenberger, Melanie, Chambers, John C., Dehghan, Abbas, and Järvelin, Marjo-Riitta

Published
2022
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37. Differential and shared genetic effects on kidney function between diabetic and non-diabetic individuals

Author

Winkler, Thomas W., Rasheed, Humaira, Teumer, Alexander, Gorski, Mathias, Rowan, Bryce X., Stanzick, Kira J., Thomas, Laurent F., Tin, Adrienne, Hoppmann, Anselm, Chu, Audrey Y., Tayo, Bamidele, Thio, Chris H. L., Cusi, Daniele, Chai, Jin-Fang, Sieber, Karsten B., Horn, Katrin, Li, Man, Scholz, Markus, Cocca, Massimiliano, Wuttke, Matthias, van der Most, Peter J., Yang, Qiong, Ghasemi, Sahar, Nutile, Teresa, Li, Yong, Pontali, Giulia, Günther, Felix, Dehghan, Abbas, Correa, Adolfo, Parsa, Afshin, Feresin, Agnese, de Vries, Aiko P. J., Zonderman, Alan B., Smith, Albert V., Oldehinkel, Albertine J., De Grandi, Alessandro, Rosenkranz, Alexander R., Franke, Andre, Teren, Andrej, Metspalu, Andres, Hicks, Andrew A., Morris, Andrew P., Tönjes, Anke, Morgan, Anna, Podgornaia, Anna I., Peters, Annette, Körner, Antje, Mahajan, Anubha, Campbell, Archie, Freedman, Barry I., Spedicati, Beatrice, Ponte, Belen, Schöttker, Ben, Brumpton, Ben, Banas, Bernhard, Krämer, Bernhard K., Jung, Bettina, Åsvold, Bjørn Olav, Smith, Blair H., Ning, Boting, Penninx, Brenda W. J. H., Vanderwerff, Brett R., Psaty, Bruce M., Kammerer, Candace M., Langefeld, Carl D., Hayward, Caroline, Spracklen, Cassandra N., Robinson-Cohen, Cassianne, Hartman, Catharina A., Lindgren, Cecilia M., Wang, Chaolong, Sabanayagam, Charumathi, Heng, Chew-Kiat, Lanzani, Chiara, Khor, Chiea-Chuen, Cheng, Ching-Yu, Fuchsberger, Christian, Gieger, Christian, Shaffer, Christian M., Schulz, Christina-Alexandra, Willer, Cristen J., Chasman, Daniel I., Gudbjartsson, Daniel F., Ruggiero, Daniela, Toniolo, Daniela, Czamara, Darina, Porteous, David J., Waterworth, Dawn M., Mascalzoni, Deborah, Mook-Kanamori, Dennis O., Reilly, Dermot F., Daw, E. Warwick, Hofer, Edith, Boerwinkle, Eric, Salvi, Erika, Bottinger, Erwin P., Tai, E-Shyong, Catamo, Eulalia, Rizzi, Federica, Guo, Feng, Rivadeneira, Fernando, Guilianini, Franco, Sveinbjornsson, Gardar, Ehret, Georg, Waeber, Gerard, Biino, Ginevra, Girotto, Giorgia, Pistis, Giorgio, Nadkarni, Girish N., Delgado, Graciela E., Montgomery, Grant W., Snieder, Harold, Campbell, Harry, White, Harvey D., Gao, He, Stringham, Heather M., Schmidt, Helena, Li, Hengtong, Brenner, Hermann, Holm, Hilma, Kirsten, Holgen, Kramer, Holly, Rudan, Igor, Nolte, Ilja M., Tzoulaki, Ioanna, Olafsson, Isleifur, Martins, Jade, Cook, James P., Wilson, James F., Halbritter, Jan, Felix, Janine F., Divers, Jasmin, Kooner, Jaspal S., Lee, Jeannette Jen-Mai, O’Connell, Jeffrey, Rotter, Jerome I., Liu, Jianjun, Xu, Jie, Thiery, Joachim, Ärnlöv, Johan, Kuusisto, Johanna, Jakobsdottir, Johanna, Tremblay, Johanne, Chambers, John C., Whitfield, John B., Gaziano, John M., Marten, Jonathan, Coresh, Josef, Jonas, Jost B., Mychaleckyj, Josyf C., Christensen, Kaare, Eckardt, Kai-Uwe, Mohlke, Karen L., Endlich, Karlhans, Dittrich, Katalin, Ryan, Kathleen A., Rice, Kenneth M., Taylor, Kent D., Ho, Kevin, Nikus, Kjell, Matsuda, Koichi, Strauch, Konstantin, Miliku, Kozeta, Hveem, Kristian, Lind, Lars, Wallentin, Lars, Yerges-Armstrong, Laura M., Raffield, Laura M., Phillips, Lawrence S., Launer, Lenore J., Lyytikäinen, Leo-Pekka, Lange, Leslie A., Citterio, Lorena, Klaric, Lucija, Ikram, M. Arfan, Ising, Marcus, Kleber, Marcus E., Francescatto, Margherita, Concas, Maria Pina, Ciullo, Marina, Piratsu, Mario, Orho-Melander, Marju, Laakso, Markku, Loeffler, Markus, Perola, Markus, de Borst, Martin H., Gögele, Martin, Bianca, Martina La, Lukas, Mary Ann, Feitosa, Mary F., Biggs, Mary L., Wojczynski, Mary K., Kavousi, Maryam, Kanai, Masahiro, Akiyama, Masato, Yasuda, Masayuki, Nauck, Matthias, Waldenberger, Melanie, Chee, Miao-Li, Chee, Miao-Ling, Boehnke, Michael, Preuss, Michael H., Stumvoll, Michael, Province, Michael A., Evans, Michele K., O’Donoghue, Michelle L., Kubo, Michiaki, Kähönen, Mika, Kastarinen, Mika, Nalls, Mike A., Kuokkanen, Mikko, Ghanbari, Mohsen, Bochud, Murielle, Josyula, Navya Shilpa, Martin, Nicholas G., Tan, Nicholas Y. Q., Palmer, Nicholette D., Pirastu, Nicola, Schupf, Nicole, Verweij, Niek, Hutri-Kähönen, Nina, Mononen, Nina, Bansal, Nisha, Devuyst, Olivier, Melander, Olle, Raitakari, Olli T., Polasek, Ozren, Manunta, Paolo, Gasparini, Paolo, Mishra, Pashupati P., Sulem, Patrick, Magnusson, Patrik K. E., Elliott, Paul, Ridker, Paul M., Hamet, Pavel, Svensson, Per O., Joshi, Peter K., Kovacs, Peter, Pramstaller, Peter P., Rossing, Peter, Vollenweider, Peter, van der Harst, Pim, Dorajoo, Rajkumar, Sim, Ralene Z. H., Burkhardt, Ralph, Tao, Ran, Noordam, Raymond, Mägi, Reedik, Schmidt, Reinhold, de Mutsert, Renée, Rueedi, Rico, van Dam, Rob M., Carroll, Robert J., Gansevoort, Ron T., Loos, Ruth J. F., Felicita, Sala Cinzia, Sedaghat, Sanaz, Padmanabhan, Sandosh, Freitag-Wolf, Sandra, Pendergrass, Sarah A., Graham, Sarah E., Gordon, Scott D., Hwang, Shih-Jen, Kerr, Shona M., Vaccargiu, Simona, Patil, Snehal B., Hallan, Stein, Bakker, Stephan J. L., Lim, Su-Chi, Lucae, Susanne, Vogelezang, Suzanne, Bergmann, Sven, Corre, Tanguy, Ahluwalia, Tarunveer S., Lehtimäki, Terho, Boutin, Thibaud S., Meitinger, Thomas, Wong, Tien-Yin, Bergler, Tobias, Rabelink, Ton J., Esko, Tõnu, Haller, Toomas, Thorsteinsdottir, Unnur, Völker, Uwe, Foo, Valencia Hui Xian, Salomaa, Veikko, Vitart, Veronique, Giedraitis, Vilmantas, Gudnason, Vilmundur, Jaddoe, Vincent W. V., Huang, Wei, Zhang, Weihua, Wei, Wen Bin, Kiess, Wieland, März, Winfried, Koenig, Wolfgang, Lieb, Wolfgang, Gao, Xin, Sim, Xueling, Wang, Ya Xing, Friedlander, Yechiel, Tham, Yih-Chung, Kamatani, Yoichiro, Okada, Yukinori, Milaneschi, Yuri, Yu, Zhi, Stark, Klaus J., Stefansson, Kari, Böger, Carsten A., Hung, Adriana M., Kronenberg, Florian, Köttgen, Anna, Pattaro, Cristian, and Heid, Iris M.

Published
2022
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38. A multi-omics study of circulating phospholipid markers of blood pressure

Author

Liu, Jun, de Vries, Paul S., Del Greco M., Fabiola, Johansson, Åsa, Schraut, Katharina E., Hayward, Caroline, van Dijk, Ko Willems, Franco, Oscar. H., Hicks, Andrew A., Vitart, Veronique, Rudan, Igor, Campbell, Harry, Polašek, Ozren, Pramstaller, Peter P., Wilson, James F., Gyllensten, Ulf, van Duijn, Cornelia M., Dehghan, Abbas, and Demirkan, Ayşe

Published
2022
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40. Neural EGFL like 1 as a novel gene for Trabecular Bone Score in older adults: The Bushehr Elderly Health (BEH) program.

Author

Bidkhori, Mohammad, Akbarzadeh, Mahdi, Fahimfar, Noushin, Jahangiri, Mina, Seddiq, Sahar, Larijani, Bagher, Nabipour, Iraj, Mohammad Amoli, Mahsa, Panahi, Nekoo, Dehghan, Abbas, Holakouie-Naieni, Kourosh, and Ostovar, Afshin

Subjects
GENETIC risk score, SINGLE nucleotide polymorphisms, CANCELLOUS bone, TYPE 2 diabetes, BODY mass index
Abstract

Neural EGFL like 1 (NELL-1), is a secreted glycoprotein and stimulates osteogenic cell differentiation and bone mineralization. This study aimed to explore the relationship between NELL-1 and Trabecular Bone Score (TBS) as a novel tool for the evaluation of osteoporosis in an elderly population-based cohort study in Iran. A single-locus analysis was performed on TBS using data from 2,071 participants in the Bushehr Elderly Health (BEH) Program. The study investigated 376 independent single nucleotide polymorphisms (SNPs) within the NELL-1 on chromosome 11p15.1. The association between SNPs and the mean TBS L1 to L4 was analyzed through an additive model. Significant variants in the additive model (PFDR<0.05) were further examined within dominant, recessive, over-dominant, and co-dominant models. Multiple linear regression was employed to assess the relationship between the genetic risk score (GRS) derived from significant SNPs and TBS. Three SNPs within the NELL-1 showed a statistically significant association with TBS after adjusting for age and sex. The associations for rs1901945 (β = 0.013, PFDR = 0.0007), rs1584851 (β = -0.011, PFDR = 0.0003), and rs58028601 (β = 0.011, PFDR = 0.0003) were significant in the additive model. Additionally, significant results were observed for rs1901945 and rs58028601 in the dominant model (P<0.05). The GRS showed a statistically significant relationship with TBS, considering adjustments for age, sex, Body Mass Index, type 2 diabetes, and smoking (β = 0.077, P = 1.7×10−5). This study highlights the association of NELL-1 with TBS, underscoring its potential as a candidate for further research and personalized medicine concerning the impact of this gene on bone quality. [ABSTRACT FROM AUTHOR]

Published
2024
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41. Genetic correlations among psychiatric and immune‐related phenotypes based on genome‐wide association data

Author

Tylee, Daniel S, Sun, Jiayin, Hess, Jonathan L, Tahir, Muhammad A, Sharma, Esha, Malik, Rainer, Worrall, Bradford B, Levine, Andrew J, Martinson, Jeremy J, Nejentsev, Sergey, Speed, Doug, Fischer, Annegret, Mick, Eric, Walker, Brian R, Crawford, Andrew, Grant, Struan FA, Polychronakos, Constantin, Bradfield, Jonathan P, Sleiman, Patrick MA, Hakonarson, Hakon, Ellinghaus, Eva, Elder, James T, Tsoi, Lam C, Trembath, Richard C, Barker, Jonathan N, Franke, Andre, Dehghan, Abbas, Team, The 23 and Me Research, Consortium, The Inflammation Working Group of the CHARGE, Consortium, The METASTROKE Consortium of the International Stroke Genetics, Registry, The Netherlands Twin, Group, The neuroCHARGE Working, Consortium, The Obsessive Compulsive and Tourette Syndrome Working Group of the Psychiatric Genomics, Faraone, Stephen V, and Glatt, Stephen J

Subjects
Pharmacology and Pharmaceutical Sciences, Biological Sciences, Biomedical and Clinical Sciences, Genetics, Serious Mental Illness, Human Genome, Genetic Testing, Brain Disorders, Schizophrenia, Digestive Diseases, Prevention, Mental Health, Clinical Research, Autoimmune Disease, 2.1 Biological and endogenous factors, Aetiology, Mental health, Autoimmune Diseases, Comorbidity, Databases, Factual, Female, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Linkage Disequilibrium, Male, Mental Disorders, Multifactorial Inheritance, Polymorphism, Single Nucleotide, White People, allergy, anorexia nervosa, attention deficit-hyperactivity disorder, autoimmune disorder, bipolar disorder, celiac disease, childhood ear infection, C-reactive protein, Crohn's disease, genetic correlation, genome-wide association, hypothyroidism, major depression, neuroticism, obsessive schizophrenia, primary biliary cirrhosis, rheumatoid arthritis, smoking, systemic lupus erythematosus, Tourette syndrome, tuberculosis susceptibility, type 1 diabetes, ulcerative colitis, and Me Research Team, Inflammation Working Group of the CHARGE Consortium, METASTROKE Consortium of the International Stroke Genetics Consortium, Netherlands Twin Registry, neuroCHARGE Working Group, Obsessive Compulsive and Tourette Syndrome Working Group of the Psychiatric Genomics Consortium, Clinical Sciences, Neurosciences, Clinical sciences
Abstract

Individuals with psychiatric disorders have elevated rates of autoimmune comorbidity and altered immune signaling. It is unclear whether these altered immunological states have a shared genetic basis with those psychiatric disorders. The present study sought to use existing summary-level data from previous genome-wide association studies to determine if commonly varying single nucleotide polymorphisms are shared between psychiatric and immune-related phenotypes. We estimated heritability and examined pair-wise genetic correlations using the linkage disequilibrium score regression (LDSC) and heritability estimation from summary statistics methods. Using LDSC, we observed significant genetic correlations between immune-related disorders and several psychiatric disorders, including anorexia nervosa, attention deficit-hyperactivity disorder, bipolar disorder, major depression, obsessive compulsive disorder, schizophrenia, smoking behavior, and Tourette syndrome. Loci significantly mediating genetic correlations were identified for schizophrenia when analytically paired with Crohn's disease, primary biliary cirrhosis, systemic lupus erythematosus, and ulcerative colitis. We report significantly correlated loci and highlight those containing genome-wide associations and candidate genes for respective disorders. We also used the LDSC method to characterize genetic correlations among the immune-related phenotypes. We discuss our findings in the context of relevant genetic and epidemiological literature, as well as the limitations and caveats of the study.

Published
2018

42. Study of 300,486 individuals identifies 148 independent genetic loci influencing general cognitive function.

Author

Davies, Gail, Lam, Max, Harris, Sarah E, Trampush, Joey W, Luciano, Michelle, Hill, W David, Hagenaars, Saskia P, Ritchie, Stuart J, Marioni, Riccardo E, Fawns-Ritchie, Chloe, Liewald, David CM, Okely, Judith A, Ahola-Olli, Ari V, Barnes, Catriona LK, Bertram, Lars, Bis, Joshua C, Burdick, Katherine E, Christoforou, Andrea, DeRosse, Pamela, Djurovic, Srdjan, Espeseth, Thomas, Giakoumaki, Stella, Giddaluru, Sudheer, Gustavson, Daniel E, Hayward, Caroline, Hofer, Edith, Ikram, M Arfan, Karlsson, Robert, Knowles, Emma, Lahti, Jari, Leber, Markus, Li, Shuo, Mather, Karen A, Melle, Ingrid, Morris, Derek, Oldmeadow, Christopher, Palviainen, Teemu, Payton, Antony, Pazoki, Raha, Petrovic, Katja, Reynolds, Chandra A, Sargurupremraj, Muralidharan, Scholz, Markus, Smith, Jennifer A, Smith, Albert V, Terzikhan, Natalie, Thalamuthu, Anbupalam, Trompet, Stella, van der Lee, Sven J, Ware, Erin B, Windham, B Gwen, Wright, Margaret J, Yang, Jingyun, Yu, Jin, Ames, David, Amin, Najaf, Amouyel, Philippe, Andreassen, Ole A, Armstrong, Nicola J, Assareh, Amelia A, Attia, John R, Attix, Deborah, Avramopoulos, Dimitrios, Bennett, David A, Böhmer, Anne C, Boyle, Patricia A, Brodaty, Henry, Campbell, Harry, Cannon, Tyrone D, Cirulli, Elizabeth T, Congdon, Eliza, Conley, Emily Drabant, Corley, Janie, Cox, Simon R, Dale, Anders M, Dehghan, Abbas, Dick, Danielle, Dickinson, Dwight, Eriksson, Johan G, Evangelou, Evangelos, Faul, Jessica D, Ford, Ian, Freimer, Nelson A, Gao, He, Giegling, Ina, Gillespie, Nathan A, Gordon, Scott D, Gottesman, Rebecca F, Griswold, Michael E, Gudnason, Vilmundur, Harris, Tamara B, Hartmann, Annette M, Hatzimanolis, Alex, Heiss, Gerardo, Holliday, Elizabeth G, Joshi, Peter K, Kähönen, Mika, Kardia, Sharon LR, Karlsson, Ida, and Kleineidam, Luca

Subjects
Humans, Neurodegenerative Diseases, Genetic Predisposition to Disease, Cognition, Reaction Time, Mental Disorders, Multifactorial Inheritance, Polymorphism, Single Nucleotide, Adolescent, Adult, Aged, Aged, 80 and over, Middle Aged, Young Adult, Genetic Loci, Neurodevelopmental Disorders, Prevention, Behavioral and Social Science, Mental Health, Neurosciences, Biotechnology, Genetics, Human Genome, Neurological, Mental health
Abstract

General cognitive function is a prominent and relatively stable human trait that is associated with many important life outcomes. We combine cognitive and genetic data from the CHARGE and COGENT consortia, and UK Biobank (total N = 300,486; age 16-102) and find 148 genome-wide significant independent loci (P

Published
2018

43. DNA Methylation Analysis Identifies Loci for Blood Pressure Regulation.

Author

Richard, Melissa A, Huan, Tianxiao, Ligthart, Symen, Gondalia, Rahul, Jhun, Min A, Brody, Jennifer A, Irvin, Marguerite R, Marioni, Riccardo, Shen, Jincheng, Tsai, Pei-Chien, Montasser, May E, Jia, Yucheng, Syme, Catriona, Salfati, Elias L, Boerwinkle, Eric, Guan, Weihua, Mosley, Thomas H, Bressler, Jan, Morrison, Alanna C, Liu, Chunyu, Mendelson, Michael M, Uitterlinden, André G, van Meurs, Joyce B, BIOS Consortium, Franco, Oscar H, Zhang, Guosheng, Li, Yun, Stewart, James D, Bis, Joshua C, Psaty, Bruce M, Chen, Yii-Der Ida, Kardia, Sharon LR, Zhao, Wei, Turner, Stephen T, Absher, Devin, Aslibekyan, Stella, Starr, John M, McRae, Allan F, Hou, Lifang, Just, Allan C, Schwartz, Joel D, Vokonas, Pantel S, Menni, Cristina, Spector, Tim D, Shuldiner, Alan, Damcott, Coleen M, Rotter, Jerome I, Palmas, Walter, Liu, Yongmei, Paus, Tomáš, Horvath, Steve, O'Connell, Jeffrey R, Guo, Xiuqing, Pausova, Zdenka, Assimes, Themistocles L, Sotoodehnia, Nona, Smith, Jennifer A, Arnett, Donna K, Deary, Ian J, Baccarelli, Andrea A, Bell, Jordana T, Whitsel, Eric, Dehghan, Abbas, Levy, Daniel, and Fornage, Myriam

Subjects
BIOS Consortium, Humans, Nerve Tissue Proteins, Cross-Sectional Studies, DNA Methylation, Epigenesis, Genetic, CpG Islands, Blood Pressure, Quantitative Trait Loci, Aged, Middle Aged, Genetic Variation, Genome-Wide Association Study, Mendelian Randomization Analysis, Tetraspanins, DNA methylation, Mendelian randomization, blood pressure, epigenome-wide association study, gene expression, sequence variation, Epigenesis, Genetic, Genetics & Heredity, Biological Sciences, Medical and Health Sciences
Abstract

Genome-wide association studies have identified hundreds of genetic variants associated with blood pressure (BP), but sequence variation accounts for a small fraction of the phenotypic variance. Epigenetic changes may alter the expression of genes involved in BP regulation and explain part of the missing heritability. We therefore conducted a two-stage meta-analysis of the cross-sectional associations of systolic and diastolic BP with blood-derived genome-wide DNA methylation measured on the Infinium HumanMethylation450 BeadChip in 17,010 individuals of European, African American, and Hispanic ancestry. Of 31 discovery-stage cytosine-phosphate-guanine (CpG) dinucleotides, 13 replicated after Bonferroni correction (discovery: N = 9,828, p < 1.0 × 10-7; replication: N = 7,182, p  30%) and independent of known BP genetic variants, explaining an additional 1.4% and 2.0% of the interindividual variation in systolic and diastolic BP, respectively. Bidirectional Mendelian randomization among up to 4,513 individuals of European ancestry from 4 cohorts suggested that methylation at cg08035323 (TAF1B-YWHAQ) influences BP, while BP influences methylation at cg00533891 (ZMIZ1), cg00574958 (CPT1A), and cg02711608 (SLC1A5). Gene expression analyses further identified six genes (TSPAN2, SLC7A11, UNC93B1, CPT1A, PTMS, and LPCAT3) with evidence of triangular associations between methylation, gene expression, and BP. Additional integrative Mendelian randomization analyses of gene expression and DNA methylation suggested that the expression of TSPAN2 is a putative mediator of association between DNA methylation at cg23999170 and BP. These findings suggest that heritable DNA methylation plays a role in regulating BP independently of previously known genetic variants.

Published
2017

44. Inflammatory Diseases, Inflammatory Biomarkers, and Alzheimer Disease: An Observational Analysis and Mendelian Randomization.

Author

Huang, Jian, Su, Bowen, Karhunen, Ville, Gill, Dipender, Zuber, Verena, Ahola-Olli, Ari, Palaniswamy, Saranya, Auvinen, Juha, Herzig, Karl-Heinz, Keinänen-Kiukaanniemi, Sirkka, Salmi, Marko, Jalkanen, Sirpa, Lehtimäki, Terho, Salomaa, Veikko, Raitakari, Olli T., Matthews, Paul M., Elliott, Paul, Tsilidis, Konstantinos K., Jarvelin, Marjo-riitta, Tzoulaki, Ioanna, and Dehghan, Abbas

Published
2022
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45. 203 Cumulative incidence of coronary heart disease (CHD) among UK South Asians – results of the prospective follow-up of the London life sciences population (LOLIPOP) cohort of 25,372 participants, at 20 years

Author

Kooner, Angad, primary, Kooner, Jaspal Singh, additional, Kooner, Ishminder Kaur, additional, Misra, Shivani, additional, Dehghan, Abbas, additional, Elliott, Paul, additional, Zhang, Weihua, additional, and Chambers, John, additional

Published
2024
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48. Meta-analysis of epigenome-wide association studies of carotid intima-media thickness

Author

Portilla-Fernández, Eliana, Hwang, Shih-Jen, Wilson, Rory, Maddock, Jane, Hill, W. David, Teumer, Alexander, Mishra, Pashupati P., Brody, Jennifer A., Joehanes, Roby, Ligthart, Symen, Ghanbari, Mohsen, Kavousi, Maryam, Roks, Anton J. M., Danser, A. H. Jan, Levy, Daniel, Peters, Annette, Ghasemi, Sahar, Schminke, Ulf, Dörr, Marcus, Grabe, Hans J., Lehtimäki, Terho, Kähönen, Mika, Hurme, Mikko A., Bartz, Traci M., Sotoodehnia, Nona, Bis, Joshua C., Thiery, Joachim, Koenig, Wolfgang, Ong, Ken K., Bell, Jordana T., Meisinger, Christine, Wardlaw, Joanna M., Starr, John M., Seissler, Jochen, Then, Cornelia, Rathmann, Wolfgang, Ikram, M. Arfan, Psaty, Bruce M., Raitakari, Olli T., Völzke, Henry, Deary, Ian J., Wong, Andrew, Waldenberger, Melanie, O’Donnell, Christopher J., and Dehghan, Abbas

Published
2021
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49. Causal Effect of Plasminogen Activator Inhibitor Type 1 on Coronary Heart Disease

Author

Song, Ci, Burgess, Stephen, Eicher, John D, O'Donnell, Christopher J, Johnson, Andrew D, Huang, Jie, Sabater‐Lleal, Maria, Asselbergs, Folkert W, Tregouet, David, Shin, So‐Youn, Ding, Jingzhong, Baumert, Jens, Oudot‐Mellakh, Tiphaine, Folkersen, Lasse, Smith, Nicholas L, Williams, Scott M, Ikram, Mohammad A, Kleber, Marcus E, Becker, Diane M, Truong, Vinh, Mychaleckyj, Josyf C, Tang, Weihong, Yang, Qiong, Sennblad, Bengt, Moore, Jason H, Williams, Frances MK, Dehghan, Abbas, Silbernagel, Günther, Schrijvers, Elisabeth MC, Smith, Shelly, Karakas, Mahir, Tofler, Geoffrey H, Silveira, Angela, Navis, Gerjan J, Lohman, Kurt, Chen, Ming‐Huei, Peters, Annette, Goel, Anuj, Hopewell, Jemma C, Chambers, John C, Saleheen, Danish, Lundmark, Per, Psaty, Bruce M, Strawbridge, Rona J, Boehm, Bernhard O, Carter, Angela M, Meisinger, Christa, Peden, John F, Bis, Joshua C, McKnight, Barbara, Öhrvik, John, Taylor, Kent, Franzosi, Maria Grazia, Seedorf, Udo, Collins, Rory, Franco‐Cereceda, Anders, Syvänen, Ann‐Christine, Goodall, Alison H, Yanek, Lisa R, Cushman, Mary, Müller‐Nurasyid, Martina, Folsom, Aaron R, Basu, Saonli, Matijevic, Nena, van Gilst, Wiek H, Kooner, Jaspal S, Hofman, Albert, Danesh, John, Clarke, Robert, Meigs, James B, Kathiresan, Sekar, Reilly, Muredach P, Klopp, Norman, Harris, Tamara B, Winkelmann, Bernhard R, Grant, Peter J, Hillege, Hans L, Watkins, Hugh, Spector, Timothy D, Becker, Lewis C, Tracy, Russell P, März, Winfried, Uitterlinden, Andre G, Eriksson, Per, Cambien, Francois, Morange, Pierre‐Emmanuel, Koenig, Wolfgang, Soranzo, Nicole, van der Harst, Pim, Liu, Yongmei, Hamsten, Anders, Ehret, Georg B, Munroe, Patricia B, Rice, Kenneth M, Bochud, Murielle, Chasman, Daniel I, Smith, Albert V, Tobin, Martin D, and Verwoert, Germaine C

Subjects
Clinical Research, Heart Disease - Coronary Heart Disease, Cardiovascular, Heart Disease, Aging, Biomarkers, Blood Glucose, Coronary Disease, Fibrinolysis, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Incidence, Lipoproteins, HDL, Mendelian Randomization Analysis, Multivariate Analysis, Observational Studies as Topic, Odds Ratio, Plasminogen Activator Inhibitor 1, Polymorphism, Single Nucleotide, Risk Assessment, Risk Factors, coronary heart disease, genome-wide association study, Mendelian randomization, plasminogen activator inhibitor type 1, single nucleotide polymorphism, genome‐wide association study, Cardiorespiratory Medicine and Haematology
Abstract

Plasminogen activator inhibitor type 1 (PAI-1) plays an essential role in the fibrinolysis system and thrombosis. Population studies have reported that blood PAI-1 levels are associated with increased risk of coronary heart disease (CHD). However, it is unclear whether the association reflects a causal influence of PAI-1 on CHD risk. To evaluate the association between PAI-1 and CHD, we applied a 3-step strategy. First, we investigated the observational association between PAI-1 and CHD incidence using a systematic review based on a literature search for PAI-1 and CHD studies. Second, we explored the causal association between PAI-1 and CHD using a Mendelian randomization approach using summary statistics from large genome-wide association studies. Finally, we explored the causal effect of PAI-1 on cardiovascular risk factors including metabolic and subclinical atherosclerosis measures. In the systematic meta-analysis, the highest quantile of blood PAI-1 level was associated with higher CHD risk comparing with the lowest quantile (odds ratio=2.17; 95% CI: 1.53, 3.07) in an age- and sex-adjusted model. The effect size was reduced in studies using a multivariable-adjusted model (odds ratio=1.46; 95% CI: 1.13, 1.88). The Mendelian randomization analyses suggested a causal effect of increased PAI-1 level on CHD risk (odds ratio=1.22 per unit increase of log-transformed PAI-1; 95% CI: 1.01, 1.47). In addition, we also detected a causal effect of PAI-1 on elevating blood glucose and high-density lipoprotein cholesterol. Our study indicates a causal effect of elevated PAI-1 level on CHD risk, which may be mediated by glucose dysfunction.

Published
2017

50. Comparison of HapMap and 1000 Genomes Reference Panels in a Large-Scale Genome-Wide Association Study

Author

de Vries, Paul S, Sabater-Lleal, Maria, Chasman, Daniel I, Trompet, Stella, Ahluwalia, Tarunveer S, Teumer, Alexander, Kleber, Marcus E, Chen, Ming-Huei, Wang, Jie Jin, Attia, John R, Marioni, Riccardo E, Steri, Maristella, Weng, Lu-Chen, Pool, Rene, Grossmann, Vera, Brody, Jennifer A, Venturini, Cristina, Tanaka, Toshiko, Rose, Lynda M, Oldmeadow, Christopher, Mazur, Johanna, Basu, Saonli, Frånberg, Mattias, Yang, Qiong, Ligthart, Symen, Hottenga, Jouke J, Rumley, Ann, Mulas, Antonella, de Craen, Anton JM, Grotevendt, Anne, Taylor, Kent D, Delgado, Graciela E, Kifley, Annette, Lopez, Lorna M, Berentzen, Tina L, Mangino, Massimo, Bandinelli, Stefania, Morrison, Alanna C, Hamsten, Anders, Tofler, Geoffrey, de Maat, Moniek PM, Draisma, Harmen HM, Lowe, Gordon D, Zoledziewska, Magdalena, Sattar, Naveed, Lackner, Karl J, Völker, Uwe, McKnight, Barbara, Huang, Jie, Holliday, Elizabeth G, McEvoy, Mark A, Starr, John M, Hysi, Pirro G, Hernandez, Dena G, Guan, Weihua, Rivadeneira, Fernando, McArdle, Wendy L, Slagboom, P Eline, Zeller, Tanja, Psaty, Bruce M, Uitterlinden, André G, de Geus, Eco JC, Stott, David J, Binder, Harald, Hofman, Albert, Franco, Oscar H, Rotter, Jerome I, Ferrucci, Luigi, Spector, Tim D, Deary, Ian J, März, Winfried, Greinacher, Andreas, Wild, Philipp S, Cucca, Francesco, Boomsma, Dorret I, Watkins, Hugh, Tang, Weihong, Ridker, Paul M, Jukema, Jan W, Scott, Rodney J, Mitchell, Paul, Hansen, Torben, O'Donnell, Christopher J, Smith, Nicholas L, Strachan, David P, and Dehghan, Abbas

Subjects
Epidemiology, Biological Sciences, Health Sciences, Genetics, Human Genome, Genome-Wide Association Study, HapMap Project, Humans, General Science & Technology
Abstract

An increasing number of genome-wide association (GWA) studies are now using the higher resolution 1000 Genomes Project reference panel (1000G) for imputation, with the expectation that 1000G imputation will lead to the discovery of additional associated loci when compared to HapMap imputation. In order to assess the improvement of 1000G over HapMap imputation in identifying associated loci, we compared the results of GWA studies of circulating fibrinogen based on the two reference panels. Using both HapMap and 1000G imputation we performed a meta-analysis of 22 studies comprising the same 91,953 individuals. We identified six additional signals using 1000G imputation, while 29 loci were associated using both HapMap and 1000G imputation. One locus identified using HapMap imputation was not significant using 1000G imputation. The genome-wide significance threshold of 5×10-8 is based on the number of independent statistical tests using HapMap imputation, and 1000G imputation may lead to further independent tests that should be corrected for. When using a stricter Bonferroni correction for the 1000G GWA study (P-value < 2.5×10-8), the number of loci significant only using HapMap imputation increased to 4 while the number of loci significant only using 1000G decreased to 5. In conclusion, 1000G imputation enabled the identification of 20% more loci than HapMap imputation, although the advantage of 1000G imputation became less clear when a stricter Bonferroni correction was used. More generally, our results provide insights that are applicable to the implementation of other dense reference panels that are under development.

Published
2017

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