Author: "David J. Porteous" - Searchworks@Jio Institute Digital Library Search Results

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1. X-chromosome and kidney function: evidence from a multi-trait genetic analysis of 908,697 individuals reveals sex-specific and sex-differential findings in genes regulated by androgen response elements

Author: Markus Scholz, Katrin Horn, Janne Pott, Matthias Wuttke, Andreas Kühnapfel, M. Kamal Nasr, Holger Kirsten, Yong Li, Anselm Hoppmann, Mathias Gorski, Sahar Ghasemi, Man Li, Adrienne Tin, Jin-Fang Chai, Massimiliano Cocca, Judy Wang, Teresa Nutile, Masato Akiyama, Bjørn Olav Åsvold, Nisha Bansal, Mary L. Biggs, Thibaud Boutin, Hermann Brenner, Ben Brumpton, Ralph Burkhardt, Jianwen Cai, Archie Campbell, Harry Campbell, John Chalmers, Daniel I. Chasman, Miao Ling Chee, Miao Li Chee, Xu Chen, Ching-Yu Cheng, Renata Cifkova, Martha Daviglus, Graciela Delgado, Katalin Dittrich, Todd L. Edwards, Karlhans Endlich, J. Michael Gaziano, Ayush Giri, Franco Giulianini, Scott D. Gordon, Daniel F. Gudbjartsson, Stein Hallan, Pavel Hamet, Catharina A. Hartman, Caroline Hayward, Iris M. Heid, Jacklyn N. Hellwege, Bernd Holleczek, Hilma Holm, Nina Hutri-Kähönen, Kristian Hveem, Berend Isermann, Jost B. Jonas, Peter K. Joshi, Yoichiro Kamatani, Masahiro Kanai, Mika Kastarinen, Chiea Chuen Khor, Wieland Kiess, Marcus E. Kleber, Antje Körner, Peter Kovacs, Alena Krajcoviechova, Holly Kramer, Bernhard K. Krämer, Mikko Kuokkanen, Mika Kähönen, Leslie A. Lange, James P. Lash, Terho Lehtimäki, Hengtong Li, Bridget M. Lin, Jianjun Liu, Markus Loeffler, Leo-Pekka Lyytikäinen, Patrik K. E. Magnusson, Nicholas G. Martin, Koichi Matsuda, Yuri Milaneschi, Pashupati P. Mishra, Nina Mononen, Grant W. Montgomery, Dennis O. Mook-Kanamori, Josyf C. Mychaleckyj, Winfried März, Matthias Nauck, Kjell Nikus, Ilja M. Nolte, Raymond Noordam, Yukinori Okada, Isleifur Olafsson, Albertine J. Oldehinkel, Brenda W. J. H. Penninx, Markus Perola, Nicola Pirastu, Ozren Polasek, David J. Porteous, Tanja Poulain, Bruce M. Psaty, Ton J. Rabelink, Laura M. Raffield, Olli T. Raitakari, Humaira Rasheed, Dermot F. Reilly, Kenneth M. Rice, Anne Richmond, Paul M. Ridker, Jerome I. Rotter, Igor Rudan, Charumathi Sabanayagam, Veikko Salomaa, Neil Schneiderman, Ben Schöttker, Mario Sims, Harold Snieder, Klaus J. Stark, Kari Stefansson, Hannah Stocker, Michael Stumvoll, Patrick Sulem, Gardar Sveinbjornsson, Per O. Svensson, E-Shyong Tai, Kent D. Taylor, Bamidele O. Tayo, Andrej Teren, Yih-Chung Tham, Joachim Thiery, Chris H. L. Thio, Laurent F. Thomas, Johanne Tremblay, Anke Tönjes, Peter J. van der Most, Veronique Vitart, Uwe Völker, Ya Xing Wang, Chaolong Wang, Wen Bin Wei, John B. Whitfield, Sarah H. Wild, James F. Wilson, Thomas W. Winkler, Tien-Yin Wong, Mark Woodward, Xueling Sim, Audrey Y. Chu, Mary F. Feitosa, Unnur Thorsteinsdottir, Adriana M. Hung, Alexander Teumer, Nora Franceschini, Afshin Parsa, Anna Köttgen, Pascal Schlosser, and Cristian Pattaro
Subjects: Science
Abstract: Abstract X-chromosomal genetic variants are understudied but can yield valuable insights into sexually dimorphic human traits and diseases. We performed a sex-stratified cross-ancestry X-chromosome-wide association meta-analysis of seven kidney-related traits (n = 908,697), identifying 23 loci genome-wide significantly associated with two of the traits: 7 for uric acid and 16 for estimated glomerular filtration rate (eGFR), including four novel eGFR loci containing the functionally plausible prioritized genes ACSL4, CLDN2, TSPAN6 and the female-specific DRP2. Further, we identified five novel sex-interactions, comprising male-specific effects at FAM9B and AR/EDA2R, and three sex-differential findings with larger genetic effect sizes in males at DCAF12L1 and MST4 and larger effect sizes in females at HPRT1. All prioritized genes in loci showing significant sex-interactions were located next to androgen response elements (ARE). Five ARE genes showed sex-differential expressions. This study contributes new insights into sex-dimorphisms of kidney traits along with new prioritized gene targets for further molecular research.
Published: 2024
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2. Genetic insights into resting heart rate and its role in cardiovascular disease

Author: Yordi J. van de Vegte, Ruben N. Eppinga, M. Yldau van der Ende, Yanick P. Hagemeijer, Yuvaraj Mahendran, Elias Salfati, Albert V. Smith, Vanessa Y. Tan, Dan E. Arking, Ioanna Ntalla, Emil V. Appel, Claudia Schurmann, Jennifer A. Brody, Rico Rueedi, Ozren Polasek, Gardar Sveinbjornsson, Cecile Lecoeur, Claes Ladenvall, Jing Hua Zhao, Aaron Isaacs, Lihua Wang, Jian’an Luan, Shih-Jen Hwang, Nina Mononen, Kirsi Auro, Anne U. Jackson, Lawrence F. Bielak, Linyao Zeng, Nabi Shah, Maria Nethander, Archie Campbell, Tuomo Rankinen, Sonali Pechlivanis, Lu Qi, Wei Zhao, Federica Rizzi, Toshiko Tanaka, Antonietta Robino, Massimiliano Cocca, Leslie Lange, Martina Müller-Nurasyid, Carolina Roselli, Weihua Zhang, Marcus E. Kleber, Xiuqing Guo, Henry J. Lin, Francesca Pavani, Tessel E. Galesloot, Raymond Noordam, Yuri Milaneschi, Katharina E. Schraut, Marcel den Hoed, Frauke Degenhardt, Stella Trompet, Marten E. van den Berg, Giorgio Pistis, Yih-Chung Tham, Stefan Weiss, Xueling S. Sim, Hengtong L. Li, Peter J. van der Most, Ilja M. Nolte, Leo-Pekka Lyytikäinen, M. Abdullah Said, Daniel R. Witte, Carlos Iribarren, Lenore Launer, Susan M. Ring, Paul S. de Vries, Peter Sever, Allan Linneberg, Erwin P. Bottinger, Sandosh Padmanabhan, Bruce M. Psaty, Nona Sotoodehnia, Ivana Kolcic, The DCCT/EDIC Research Group, David O. Arnar, Daniel F. Gudbjartsson, Hilma Holm, Beverley Balkau, Claudia T. Silva, Christopher H. Newton-Cheh, Kjell Nikus, Perttu Salo, Karen L. Mohlke, Patricia A. Peyser, Heribert Schunkert, Mattias Lorentzon, Jari Lahti, Dabeeru C. Rao, Marilyn C. Cornelis, Jessica D. Faul, Jennifer A. Smith, Katarzyna Stolarz-Skrzypek, Stefania Bandinelli, Maria Pina Concas, Gianfranco Sinagra, Thomas Meitinger, Melanie Waldenberger, Moritz F. Sinner, Konstantin Strauch, Graciela E. Delgado, Kent D. Taylor, Jie Yao, Luisa Foco, Olle Melander, Jacqueline de Graaf, Renée de Mutsert, Eco J. C. de Geus, Åsa Johansson, Peter K. Joshi, Lars Lind, Andre Franke, Peter W. Macfarlane, Kirill V. Tarasov, Nicholas Tan, Stephan B. Felix, E-Shyong Tai, Debra Q. Quek, Harold Snieder, Johan Ormel, Martin Ingelsson, Cecilia Lindgren, Andrew P. Morris, Olli T. Raitakari, Torben Hansen, Themistocles Assimes, Vilmundur Gudnason, Nicholas J. Timpson, Alanna C. Morrison, Patricia B. Munroe, David P. Strachan, Niels Grarup, Ruth J. F. Loos, Susan R. Heckbert, Peter Vollenweider, Caroline Hayward, Kari Stefansson, Philippe Froguel, Leif Groop, Nicholas J. Wareham, Cornelia M. van Duijn, Mary F. Feitosa, Christopher J. O’Donnell, Mika Kähönen, Markus Perola, Michael Boehnke, Sharon L. R. Kardia, Jeanette Erdmann, Colin N. A. Palmer, Claes Ohlsson, David J. Porteous, Johan G. Eriksson, Claude Bouchard, Susanne Moebus, Peter Kraft, David R. Weir, Daniele Cusi, Luigi Ferrucci, Sheila Ulivi, Giorgia Girotto, Adolfo Correa, Stefan Kääb, Annette Peters, John C. Chambers, Jaspal S. Kooner, Winfried März, Jerome I. Rotter, Andrew A. Hicks, J. Gustav Smith, Lambertus A. L. M. Kiemeney, Dennis O. Mook-Kanamori, Brenda W. J. H. Penninx, Ulf Gyllensten, James F. Wilson, Stephen Burgess, Johan Sundström, Wolfgang Lieb, J. Wouter Jukema, Mark Eijgelsheim, Edward L. M. Lakatta, Ching-Yu Cheng, Marcus Dörr, Tien-Yin Wong, Charumathi Sabanayagam, Albertine J. Oldehinkel, Harriette Riese, Terho Lehtimäki, Niek Verweij, and Pim van der Harst
Subjects: Science
Abstract: Abstract Resting heart rate is associated with cardiovascular diseases and mortality in observational and Mendelian randomization studies. The aims of this study are to extend the number of resting heart rate associated genetic variants and to obtain further insights in resting heart rate biology and its clinical consequences. A genome-wide meta-analysis of 100 studies in up to 835,465 individuals reveals 493 independent genetic variants in 352 loci, including 68 genetic variants outside previously identified resting heart rate associated loci. We prioritize 670 genes and in silico annotations point to their enrichment in cardiomyocytes and provide insights in their ECG signature. Two-sample Mendelian randomization analyses indicate that higher genetically predicted resting heart rate increases risk of dilated cardiomyopathy, but decreases risk of developing atrial fibrillation, ischemic stroke, and cardio-embolic stroke. We do not find evidence for a linear or non-linear genetic association between resting heart rate and all-cause mortality in contrast to our previous Mendelian randomization study. Systematic alteration of key differences between the current and previous Mendelian randomization study indicates that the most likely cause of the discrepancy between these studies arises from false positive findings in previous one-sample MR analyses caused by weak-instrument bias at lower P-value thresholds. The results extend our understanding of resting heart rate biology and give additional insights in its role in cardiovascular disease development.
Published: 2023
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3. Phenome-wide analyses identify an association between the parent-of-origin effects dependent methylome and the rate of aging in humans

Author: Chenhao Gao, Carmen Amador, Rosie M. Walker, Archie Campbell, Rebecca A. Madden, Mark J. Adams, Xiaomeng Bai, Ying Liu, Miaoxin Li, Caroline Hayward, David J. Porteous, Xueyi Shen, Kathryn L. Evans, Chris S. Haley, Andrew M. McIntosh, Pau Navarro, and Yanni Zeng
Subjects: Atypical parent-of-origin effect, Aging, DNAmTL acceleration, Maternal smoking exposure, Lifestyle, Intelligence, Biology (General), QH301-705.5, Genetics, QH426-470
Abstract: Abstract Background The variation in the rate at which humans age may be rooted in early events acting through the genomic regions that are influenced by such events and subsequently are related to health phenotypes in later life. The parent-of-origin-effect (POE)-regulated methylome includes regions enriched for genetically controlled imprinting effects (the typical type of POE) and regions influenced by environmental effects associated with parents (the atypical POE). This part of the methylome is heavily influenced by early events, making it a potential route connecting early exposures, the epigenome, and aging. We aim to test the association of POE-CpGs with early and later exposures and subsequently with health-related phenotypes and adult aging. Results We perform a phenome-wide association analysis for the POE-influenced methylome using GS:SFHS (N discovery = 5087, N replication = 4450). We identify and replicate 92 POE-CpG-phenotype associations. Most of the associations are contributed by the POE-CpGs belonging to the atypical class where the most strongly enriched associations are with aging (DNAmTL acceleration), intelligence, and parental (maternal) smoking exposure phenotypes. A proportion of the atypical POE-CpGs form co-methylation networks (modules) which are associated with these phenotypes, with one of the aging-associated modules displaying increased within-module methylation connectivity with age. The atypical POE-CpGs also display high levels of methylation heterogeneity, fast information loss with age, and a strong correlation with CpGs contained within epigenetic clocks. Conclusions These results identify the association between the atypical POE-influenced methylome and aging and provide new evidence for the “early development of origin” hypothesis for aging in humans.
Published: 2023
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4. Genetic architecture of spatial electrical biomarkers for cardiac arrhythmia and relationship with cardiovascular disease

Author: William J. Young, Jeffrey Haessler, Jan-Walter Benjamins, Linda Repetto, Jie Yao, Aaron Isaacs, Andrew R. Harper, Julia Ramirez, Sophie Garnier, Stefan van Duijvenboden, Antoine R. Baldassari, Maria Pina Concas, ThuyVy Duong, Luisa Foco, Jonas L. Isaksen, Hao Mei, Raymond Noordam, Casia Nursyifa, Anne Richmond, Meddly L. Santolalla, Colleen M. Sitlani, Negin Soroush, Sébastien Thériault, Stella Trompet, Stefanie Aeschbacher, Fariba Ahmadizar, Alvaro Alonso, Jennifer A. Brody, Archie Campbell, Adolfo Correa, Dawood Darbar, Antonio De Luca, Jean-François Deleuze, Christina Ellervik, Christian Fuchsberger, Anuj Goel, Christopher Grace, Xiuqing Guo, Torben Hansen, Susan R. Heckbert, Rebecca D. Jackson, Jan A. Kors, Maria Fernanda Lima-Costa, Allan Linneberg, Peter W. Macfarlane, Alanna C. Morrison, Pau Navarro, David J. Porteous, Peter P. Pramstaller, Alexander P. Reiner, Lorenz Risch, Ulrich Schotten, Xia Shen, Gianfranco Sinagra, Elsayed Z. Soliman, Monika Stoll, Eduardo Tarazona-Santos, Andrew Tinker, Katerina Trajanoska, Eric Villard, Helen R. Warren, Eric A. Whitsel, Kerri L. Wiggins, Dan E. Arking, Christy L. Avery, David Conen, Giorgia Girotto, Niels Grarup, Caroline Hayward, J.Wouter Jukema, Dennis O. Mook-Kanamori, Morten Salling Olesen, Sandosh Padmanabhan, Bruce M. Psaty, Cristian Pattaro, Antonio Luiz P. Ribeiro, Jerome I. Rotter, Bruno H. Stricker, Pim van der Harst, Cornelia M. van Duijn, Niek Verweij, James G. Wilson, Michele Orini, Philippe Charron, Hugh Watkins, Charles Kooperberg, Henry J. Lin, James F. Wilson, Jørgen K. Kanters, Nona Sotoodehnia, Borbala Mifsud, Pier D. Lambiase, Larisa G. Tereshchenko, and Patricia B. Munroe
Subjects: Science
Abstract: The spatial and frontal QRS-T angles are electrocardiographic (ECG) predictors for arrhythmia. This work used genetic analyses to identify associated loci and pathways, and explore their relationships with other ECG traits and cardiovascular disease.
Published: 2023
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5. Genome-wide association study of susceptibility to hospitalised respiratory infections [version 2; peer review: 1 approved, 2 approved with reservations]

Author: Sina A. Gharib, Louise V. Wain, Tõnu Esko, Gail P. Jarvik, Scott Hebbring, Eric B. Larson, Sarah H. Landis, Ruth J.F. Loos, Jiangyuan Liu, Caroline Hayward, Arden Moscati, Yuan Luo, Bahram Namjou, Hana Mullerova, Marjo-Riitta Järvelin, Jennifer K. Quint, Eeva Sliz, Marylyn D. Ritchie, Laurent Thomas, Ian B. Stanaway, Kristian Hveem, David Michalovich, Ian P. Hall, James F. Wilson, Jing Chen, Alexander T. Williams, Martin D. Tobin, Joanna C. Betts, Hardeep Naghra-van Gijzel, Richard Packer, Edith M. Hessel, Astrid J. Yeo, Nicola F. Reeve, Bjørn Olav Åsvold, Erik Abner, Archie Campbell, Traci M. Bartz, Juha Auvinen, Catherine John, Ben Brumpton, Yuki Bradford, Su Chu, David J. Porteous, Nick Shrine, Michael H. Cho, QiPing Feng, and David R. Crosslin
Subjects: Respiratory infections, GWAS, UK Biobank, electronic medical records, eng, Medicine, Science
Abstract: Background: Globally, respiratory infections contribute to significant morbidity and mortality. However, genetic determinants of respiratory infections are understudied and remain poorly understood. Methods: We conducted a genome-wide association study in 19,459 hospitalised respiratory infection cases and 101,438 controls from UK Biobank (Stage 1). We followed-up well-imputed top signals from our Stage 1 analysis in 50,912 respiratory infection cases and 150,442 controls from 11 cohorts (Stage 2). We aggregated effect estimates across studies using inverse variance-weighted meta-analyses. Additionally, we investigated the function of the top signals in order to gain understanding of the underlying biological mechanisms. Results: From our Stage 1 analysis, we report 56 signals at P
Published: 2023
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6. Feasibility and ethics of using data from the Scottish newborn blood spot archive for research

Author: Sarah Cunningham-Burley, Daniel L. McCartney, Archie Campbell, Robin Flaig, Clare E. L. Orange, Carol Porteous, Mhairi Aitken, Ciaran Mulholland, Sara Davidson, Selena M. McCafferty, Lee Murphy, Nicola Wrobel, Sarah McCafferty, Karen Wallace, David StClair, Shona Kerr, Caroline Hayward, Andrew M. McIntosh, Cathie Sudlow, Riccardo E. Marioni, Jill Pell, Zosia Miedzybrodzka, and David J. Porteous
Subjects: Medicine
Abstract: Cunningham-Burley, McCartney, Campbell, Flaig, Orange et al. assess the ethics and potential benefit of secondary data use from newborn blood spot archives for research in a Citizen’s jury that agreed this was in the public interest. They also investigate and demonstrate the feasibility of using the archives for research purposes.
Published: 2022
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7. Genetic analyses of the electrocardiographic QT interval and its components identify additional loci and pathways

Author: William J. Young, Najim Lahrouchi, Aaron Isaacs, ThuyVy Duong, Luisa Foco, Farah Ahmed, Jennifer A. Brody, Reem Salman, Raymond Noordam, Jan-Walter Benjamins, Jeffrey Haessler, Leo-Pekka Lyytikäinen, Linda Repetto, Maria Pina Concas, Marten E. van den Berg, Stefan Weiss, Antoine R. Baldassari, Traci M. Bartz, James P. Cook, Daniel S. Evans, Rebecca Freudling, Oliver Hines, Jonas L. Isaksen, Honghuang Lin, Hao Mei, Arden Moscati, Martina Müller-Nurasyid, Casia Nursyifa, Yong Qian, Anne Richmond, Carolina Roselli, Kathleen A. Ryan, Eduardo Tarazona-Santos, Sébastien Thériault, Stefan van Duijvenboden, Helen R. Warren, Jie Yao, Dania Raza, Stefanie Aeschbacher, Gustav Ahlberg, Alvaro Alonso, Laura Andreasen, Joshua C. Bis, Eric Boerwinkle, Archie Campbell, Eulalia Catamo, Massimiliano Cocca, Michael J. Cutler, Dawood Darbar, Alessandro De Grandi, Antonio De Luca, Jun Ding, Christina Ellervik, Patrick T. Ellinor, Stephan B. Felix, Philippe Froguel, Christian Fuchsberger, Martin Gögele, Claus Graff, Mariaelisa Graff, Xiuqing Guo, Torben Hansen, Susan R. Heckbert, Paul L. Huang, Heikki V. Huikuri, Nina Hutri-Kähönen, M. Arfan Ikram, Rebecca D. Jackson, Juhani Junttila, Maryam Kavousi, Jan A. Kors, Thiago P. Leal, Rozenn N. Lemaitre, Henry J. Lin, Lars Lind, Allan Linneberg, Simin Liu, Peter W. MacFarlane, Massimo Mangino, Thomas Meitinger, Massimo Mezzavilla, Pashupati P. Mishra, Rebecca N. Mitchell, Nina Mononen, May E. Montasser, Alanna C. Morrison, Matthias Nauck, Victor Nauffal, Pau Navarro, Kjell Nikus, Guillaume Pare, Kristen K. Patton, Giulia Pelliccione, Alan Pittman, David J. Porteous, Peter P. Pramstaller, Michael H. Preuss, Olli T. Raitakari, Alexander P. Reiner, Antonio Luiz P. Ribeiro, Kenneth M. Rice, Lorenz Risch, David Schlessinger, Ulrich Schotten, Claudia Schurmann, Xia Shen, M. Benjamin Shoemaker, Gianfranco Sinagra, Moritz F. Sinner, Elsayed Z. Soliman, Monika Stoll, Konstantin Strauch, Kirill Tarasov, Kent D. Taylor, Andrew Tinker, Stella Trompet, André Uitterlinden, Uwe Völker, Henry Völzke, Melanie Waldenberger, Lu-Chen Weng, Eric A. Whitsel, James G. Wilson, Christy L. Avery, David Conen, Adolfo Correa, Francesco Cucca, Marcus Dörr, Sina A. Gharib, Giorgia Girotto, Niels Grarup, Caroline Hayward, Yalda Jamshidi, Marjo-Riitta Järvelin, J. Wouter Jukema, Stefan Kääb, Mika Kähönen, Jørgen K. Kanters, Charles Kooperberg, Terho Lehtimäki, Maria Fernanda Lima-Costa, Yongmei Liu, Ruth J. F. Loos, Steven A. Lubitz, Dennis O. Mook-Kanamori, Andrew P. Morris, Jeffrey R. O’Connell, Morten Salling Olesen, Michele Orini, Sandosh Padmanabhan, Cristian Pattaro, Annette Peters, Bruce M. Psaty, Jerome I. Rotter, Bruno Stricker, Pim van der Harst, Cornelia M. van Duijn, Niek Verweij, James F. Wilson, Dan E. Arking, Julia Ramirez, Pier D. Lambiase, Nona Sotoodehnia, Borbala Mifsud, Christopher Newton-Cheh, and Patricia B. Munroe
Subjects: Science
Abstract: The QT interval is a heritable electrocardiographic measure associated with arrhythmia risk when prolonged. Here, the authors used a series of genetic analyses to identify genetic loci, pathways, therapeutic targets, and relationships with cardiovascular disease.
Published: 2022
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8. Integrated methylome and phenome study of the circulating proteome reveals markers pertinent to brain health

Author: Danni A. Gadd, Robert F. Hillary, Daniel L. McCartney, Liu Shi, Aleks Stolicyn, Neil A. Robertson, Rosie M. Walker, Robert I. McGeachan, Archie Campbell, Shen Xueyi, Miruna C. Barbu, Claire Green, Stewart W. Morris, Mathew A. Harris, Ellen V. Backhouse, Joanna M. Wardlaw, J. Douglas Steele, Diego A. Oyarzún, Graciela Muniz-Terrera, Craig Ritchie, Alejo Nevado-Holgado, Tamir Chandra, Caroline Hayward, Kathryn L. Evans, David J. Porteous, Simon R. Cox, Heather C. Whalley, Andrew M. McIntosh, and Riccardo E. Marioni
Subjects: Science
Abstract: Characterising associations between the methylome, proteome and phenome may provide insight into biological pathways governing brain health. Here, blood protein markers of brain health are integrated with omics data to reveal DNA methylation differences that associate with these protein markers.
Published: 2022
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9. Long COVID burden and risk factors in 10 UK longitudinal studies and electronic health records

Author: Ellen J. Thompson, Dylan M. Williams, Alex J. Walker, Ruth E. Mitchell, Claire L. Niedzwiedz, Tiffany C. Yang, Charlotte F. Huggins, Alex S. F. Kwong, Richard J. Silverwood, Giorgio Di Gessa, Ruth C. E. Bowyer, Kate Northstone, Bo Hou, Michael J. Green, Brian Dodgeon, Katie J. Doores, Emma L. Duncan, Frances M. K. Williams, OpenSAFELY Collaborative, Andrew Steptoe, David J. Porteous, Rosemary R. C. McEachan, Laurie Tomlinson, Ben Goldacre, Praveetha Patalay, George B. Ploubidis, Srinivasa Vittal Katikireddi, Kate Tilling, Christopher T. Rentsch, Nicholas J. Timpson, Nishi Chaturvedi, and Claire J. Steves
Subjects: Science
Abstract: Current understanding of Long COVID is limited, in part, due to lack of evidence from population-representative studies. Here, the authors analyse data from ten UK population-based studies and electronic health records, and find wide variation in the frequency of Long COVID between studies but some consistent risk factors.
Published: 2022
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10. Differential and shared genetic effects on kidney function between diabetic and non-diabetic individuals

Author: Thomas W. Winkler, Humaira Rasheed, Alexander Teumer, Mathias Gorski, Bryce X. Rowan, Kira J. Stanzick, Laurent F. Thomas, Adrienne Tin, Anselm Hoppmann, Audrey Y. Chu, Bamidele Tayo, Chris H. L. Thio, Daniele Cusi, Jin-Fang Chai, Karsten B. Sieber, Katrin Horn, Man Li, Markus Scholz, Massimiliano Cocca, Matthias Wuttke, Peter J. van der Most, Qiong Yang, Sahar Ghasemi, Teresa Nutile, Yong Li, Giulia Pontali, Felix Günther, Abbas Dehghan, Adolfo Correa, Afshin Parsa, Agnese Feresin, Aiko P. J. de Vries, Alan B. Zonderman, Albert V. Smith, Albertine J. Oldehinkel, Alessandro De Grandi, Alexander R. Rosenkranz, Andre Franke, Andrej Teren, Andres Metspalu, Andrew A. Hicks, Andrew P. Morris, Anke Tönjes, Anna Morgan, Anna I. Podgornaia, Annette Peters, Antje Körner, Anubha Mahajan, Archie Campbell, Barry I. Freedman, Beatrice Spedicati, Belen Ponte, Ben Schöttker, Ben Brumpton, Bernhard Banas, Bernhard K. Krämer, Bettina Jung, Bjørn Olav Åsvold, Blair H. Smith, Boting Ning, Brenda W. J. H. Penninx, Brett R. Vanderwerff, Bruce M. Psaty, Candace M. Kammerer, Carl D. Langefeld, Caroline Hayward, Cassandra N. Spracklen, Cassianne Robinson-Cohen, Catharina A. Hartman, Cecilia M. Lindgren, Chaolong Wang, Charumathi Sabanayagam, Chew-Kiat Heng, Chiara Lanzani, Chiea-Chuen Khor, Ching-Yu Cheng, Christian Fuchsberger, Christian Gieger, Christian M. Shaffer, Christina-Alexandra Schulz, Cristen J. Willer, Daniel I. Chasman, Daniel F. Gudbjartsson, Daniela Ruggiero, Daniela Toniolo, Darina Czamara, David J. Porteous, Dawn M. Waterworth, Deborah Mascalzoni, Dennis O. Mook-Kanamori, Dermot F. Reilly, E. Warwick Daw, Edith Hofer, Eric Boerwinkle, Erika Salvi, Erwin P. Bottinger, E-Shyong Tai, Eulalia Catamo, Federica Rizzi, Feng Guo, Fernando Rivadeneira, Franco Guilianini, Gardar Sveinbjornsson, Georg Ehret, Gerard Waeber, Ginevra Biino, Giorgia Girotto, Giorgio Pistis, Girish N. Nadkarni, Graciela E. Delgado, Grant W. Montgomery, Harold Snieder, Harry Campbell, Harvey D. White, He Gao, Heather M. Stringham, Helena Schmidt, Hengtong Li, Hermann Brenner, Hilma Holm, Holgen Kirsten, Holly Kramer, Igor Rudan, Ilja M. Nolte, Ioanna Tzoulaki, Isleifur Olafsson, Jade Martins, James P. Cook, James F. Wilson, Jan Halbritter, Janine F. Felix, Jasmin Divers, Jaspal S. Kooner, Jeannette Jen-Mai Lee, Jeffrey O’Connell, Jerome I. Rotter, Jianjun Liu, Jie Xu, Joachim Thiery, Johan Ärnlöv, Johanna Kuusisto, Johanna Jakobsdottir, Johanne Tremblay, John C. Chambers, John B. Whitfield, John M. Gaziano, Jonathan Marten, Josef Coresh, Jost B. Jonas, Josyf C. Mychaleckyj, Kaare Christensen, Kai-Uwe Eckardt, Karen L. Mohlke, Karlhans Endlich, Katalin Dittrich, Kathleen A. Ryan, Kenneth M. Rice, Kent D. Taylor, Kevin Ho, Kjell Nikus, Koichi Matsuda, Konstantin Strauch, Kozeta Miliku, Kristian Hveem, Lars Lind, Lars Wallentin, Laura M. Yerges-Armstrong, Laura M. Raffield, Lawrence S. Phillips, Lenore J. Launer, Leo-Pekka Lyytikäinen, Leslie A. Lange, Lorena Citterio, Lucija Klaric, M. Arfan Ikram, Marcus Ising, Marcus E. Kleber, Margherita Francescatto, Maria Pina Concas, Marina Ciullo, Mario Piratsu, Marju Orho-Melander, Markku Laakso, Markus Loeffler, Markus Perola, Martin H. de Borst, Martin Gögele, Martina La Bianca, Mary Ann Lukas, Mary F. Feitosa, Mary L. Biggs, Mary K. Wojczynski, Maryam Kavousi, Masahiro Kanai, Masato Akiyama, Masayuki Yasuda, Matthias Nauck, Melanie Waldenberger, Miao-Li Chee, Miao-Ling Chee, Michael Boehnke, Michael H. Preuss, Michael Stumvoll, Michael A. Province, Michele K. Evans, Michelle L. O’Donoghue, Michiaki Kubo, Mika Kähönen, Mika Kastarinen, Mike A. Nalls, Mikko Kuokkanen, Mohsen Ghanbari, Murielle Bochud, Navya Shilpa Josyula, Nicholas G. Martin, Nicholas Y. Q. Tan, Nicholette D. Palmer, Nicola Pirastu, Nicole Schupf, Niek Verweij, Nina Hutri-Kähönen, Nina Mononen, Nisha Bansal, Olivier Devuyst, Olle Melander, Olli T. Raitakari, Ozren Polasek, Paolo Manunta, Paolo Gasparini, Pashupati P. Mishra, Patrick Sulem, Patrik K. E. Magnusson, Paul Elliott, Paul M. Ridker, Pavel Hamet, Per O. Svensson, Peter K. Joshi, Peter Kovacs, Peter P. Pramstaller, Peter Rossing, Peter Vollenweider, Pim van der Harst, Rajkumar Dorajoo, Ralene Z. H. Sim, Ralph Burkhardt, Ran Tao, Raymond Noordam, Reedik Mägi, Reinhold Schmidt, Renée de Mutsert, Rico Rueedi, Rob M. van Dam, Robert J. Carroll, Ron T. Gansevoort, Ruth J. F. Loos, Sala Cinzia Felicita, Sanaz Sedaghat, Sandosh Padmanabhan, Sandra Freitag-Wolf, Sarah A. Pendergrass, Sarah E. Graham, Scott D. Gordon, Shih-Jen Hwang, Shona M. Kerr, Simona Vaccargiu, Snehal B. Patil, Stein Hallan, Stephan J. L. Bakker, Su-Chi Lim, Susanne Lucae, Suzanne Vogelezang, Sven Bergmann, Tanguy Corre, Tarunveer S. Ahluwalia, Terho Lehtimäki, Thibaud S. Boutin, Thomas Meitinger, Tien-Yin Wong, Tobias Bergler, Ton J. Rabelink, Tõnu Esko, Toomas Haller, Unnur Thorsteinsdottir, Uwe Völker, Valencia Hui Xian Foo, Veikko Salomaa, Veronique Vitart, Vilmantas Giedraitis, Vilmundur Gudnason, Vincent W. V. Jaddoe, Wei Huang, Weihua Zhang, Wen Bin Wei, Wieland Kiess, Winfried März, Wolfgang Koenig, Wolfgang Lieb, Xin Gao, Xueling Sim, Ya Xing Wang, Yechiel Friedlander, Yih-Chung Tham, Yoichiro Kamatani, Yukinori Okada, Yuri Milaneschi, Zhi Yu, Lifelines cohort study, DiscovEHR/MyCode study, VA Million Veteran Program, Klaus J. Stark, Kari Stefansson, Carsten A. Böger, Adriana M. Hung, Florian Kronenberg, Anna Köttgen, Cristian Pattaro, and Iris M. Heid
Subjects: Biology (General), QH301-705.5
Abstract: A large-scale GWAS provides insight on diabetes-dependent genetic effects on the glomerular filtration rate, a common metric to monitor kidney health in disease.
Published: 2022
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11. Home working and social and mental wellbeing at different stages of the COVID-19 pandemic in the UK: Evidence from 7 longitudinal population surveys

Author: Jacques Wels, Bożena Wielgoszewska, Bettina Moltrecht, Charlotte Booth, Michael J. Green, Olivia KL Hamilton, Evangelia Demou, Giorgio Di Gessa, Charlotte Huggins, Jingmin Zhu, Gillian Santorelli, Richard J. Silverwood, Daniel Kopasker, Richard J. Shaw, Alun Hughes, Praveetha Patalay, Claire Steves, Nishi Chaturvedi, David J. Porteous, Rebecca Rhead, Srinivasa Vittal Katikireddi, and George B. Ploubidis
Subjects: Medicine
Abstract: Background Home working has increased since the Coronavirus Disease 2019 (COVID-19) pandemic’s onset with concerns that it may have adverse health implications. We assessed the association between home working and social and mental wellbeing among the employed population aged 16 to 66 through harmonised analyses of 7 UK longitudinal studies. Methods and findings We estimated associations between home working and measures of psychological distress, low life satisfaction, poor self-rated health, low social contact, and loneliness across 3 different stages of the pandemic (T1 = April to June 2020 –first lockdown, T2 = July to October 2020 –eased restrictions, T3 = November 2020 to March 2021 –second lockdown) using modified Poisson regression and meta-analyses to pool results across studies. We successively adjusted the model for sociodemographic characteristics (e.g., age, sex), job characteristics (e.g., sector of activity, pre-pandemic home working propensities), and pre-pandemic health. Among respectively 10,367, 11,585, and 12,179 participants at T1, T2, and T3, we found higher rates of home working at T1 and T3 compared with T2, reflecting lockdown periods. Home working was not associated with psychological distress at T1 (RR = 0.92, 95% CI = 0.79 to 1.08) or T2 (RR = 0.99, 95% CI = 0.88 to 1.11), but a detrimental association was found with psychological distress at T3 (RR = 1.17, 95% CI = 1.05 to 1.30). Study limitations include the fact that pre-pandemic home working propensities were derived from external sources, no information was collected on home working dosage and possible reverse association between change in wellbeing and home working likelihood. Conclusions No clear evidence of an association between home working and mental wellbeing was found, apart from greater risk of psychological distress during the second lockdown, but differences across subgroups (e.g., by sex or level of education) may exist. Longer term shifts to home working might not have adverse impacts on population wellbeing in the absence of pandemic restrictions but further monitoring of health inequalities is required. Jacques Wels and colleagues investigate the relationship between working from home and different indicators of mental and social wellbeing in the UK. Author summary Why was this study done? ➢ The number of workers working from home drastically increased during the Coronavirus Disease 2019 (COVID-19) pandemic. ➢ Little is known about the relationship between home working and mental and social wellbeing before and during the pandemic. ➢ As some home working schemes are likely to remain post-pandemic, understanding this association is important. What did the researchers do and find? ➢ We analysed data from 7 UK-based population surveys to better understand the relationship between working from home (partially or fully) and different indicators of mental and social wellbeing. ➢ We analysed these relationships over 3 time points—i.e., April to June 2020 (T1), July to October 2020 (T2), and November 2020 to March 2021 (T3)—and controlled for sociodemographic (e.g., age, sex, and ethnicity) and job characteristics (e.g., sector of activity, key worker status). ➢ We found that home working was not associated with psychological distress at T1 or T2, but at T3 it was associated with increased psychological distress (relative risk = 1.17, 95% CI = 1.05 to 1.30). No other meaningful associations were found. ➢ We stratified these associations by sex, education level, age, and full-time versus part-time employment and found that home working was associated with greater psychological distress in those with lower than degree level education. What do these findings mean? ➢ We found no clear evidence of a lasting association between home working, mental health, and social wellbeing which may indicate that, during the pandemic, home working was not detrimental nor beneficial for workers’ wellbeing. ➢ Differences across subgroups may exist and specific impacts by sex, age, and education level need to be investigated further.
Published: 2023

12. Identifying the Common Genetic Basis of Antidepressant Response

Author: Oliver Pain, Karen Hodgson, Vassily Trubetskoy, Stephan Ripke, Victoria S. Marshe, Mark J. Adams, Enda M. Byrne, Adrian I. Campos, Tania Carrillo-Roa, Annamaria Cattaneo, Thomas D. Als, Daniel Souery, Mojca Z. Dernovsek, Chiara Fabbri, Caroline Hayward, Neven Henigsberg, Joanna Hauser, James L. Kennedy, Eric J. Lenze, Glyn Lewis, Daniel J. Müller, Nicholas G. Martin, Benoit H. Mulsant, Ole Mors, Nader Perroud, David J. Porteous, Miguel E. Rentería, Charles F. Reynolds, III, Marcella Rietschel, Rudolf Uher, Eleanor M. Wigmore, Wolfgang Maier, Naomi R. Wray, Katherine J. Aitchison, Volker Arolt, Bernhard T. Baune, Joanna M. Biernacka, Guido Bondolfi, Katharina Domschke, Masaki Kato, Qingqin S. Li, Yu-Li Liu, Alessandro Serretti, Shih-Jen Tsai, Gustavo Turecki, Richard Weinshilboum, Andrew M. McIntosh, Cathryn M. Lewis, Siegfried Kasper, Joseph Zohar, Stuart Montgomery, Diego Albani, Gianluigi Forloni, Panagiotis Ferentinos, Dan Rujescu, Julien Mendlewicz, Manuel Mattheisen, Maciej Trzaskowski, Abdel Abdellaoui, Esben Agerbo, Tracy M. Air, Till F.M. Andlauer, Silviu-Alin Bacanu, Marie Bækvad-Hansen, Aartjan T.F. Beekman, Tim B. Bigdeli, Elisabeth B. Binder, Julien Bryois, Henriette N. Buttenschøn, Jonas Bybjerg-Grauholm, Na Cai, Enrique Castelao, Jane Hvarregaard Christensen, Toni-Kim Clarke, Jonathan R.I. Coleman, Lucía Colodro-Conde, Baptiste Couvy-Duchesne, Nick Craddock, Gregory E. Crawford, Gail Davies, Ian J. Deary, Franziska Degenhardt, Eske M. Derks, Nese Direk, Conor V. Dolan, Erin C. Dunn, Thalia C. Eley, Valentina Escott-Price, Farnush Farhadi Hassan Kiadeh, Hilary K. Finucane, Jerome C. Foo, Andreas J. Forstner, Josef Frank, Héléna A. Gaspar, Michael Gill, Fernando S. Goes, Scott D. Gordon, Jakob Grove, Lynsey S. Hall, Christine Søholm Hansen, Thomas F. Hansen, Stefan Herms, Ian B. Hickie, Per Hoffmann, Georg Homuth, Carsten Horn, Jouke-Jan Hottenga, David M. Hougaard, David M. Howard, Marcus Ising, Rick Jansen, Ian Jones, Lisa A. Jones, Eric Jorgenson, James A. Knowles, Isaac S. Kohane, Julia Kraft, Warren W. Kretzschmar, Zoltán Kutalik, Yihan Li, Penelope A. Lind, Donald J. MacIntyre, Dean F. MacKinnon, Robert M. Maier, Jonathan Marchini, Hamdi Mbarek, Patrick McGrath, Peter McGuffin, Sarah E. Medland, Divya Mehta, Christel M. Middeldorp, Evelin Mihailov, Yuri Milaneschi, Lili Milani, Francis M. Mondimore, Grant W. Montgomery, Sara Mostafavi, Niamh Mullins, Matthias Nauck, Bernard Ng, Michel G. Nivard, Dale R. Nyholt, Paul F. O’Reilly, Hogni Oskarsson, Michael J. Owen, Jodie N. Painter, Carsten Bøcker Pedersen, Marianne Giørtz Pedersen, Roseann E. Peterson, Wouter J. Peyrot, Giorgio Pistis, Danielle Posthuma, Jorge A. Quiroz, Per Qvist, John P. Rice, Brien P. Riley, Margarita Rivera, Saira Saeed Mirza, Robert Schoevers, Eva C. Schulte, Ling Shen, Jianxin Shi, Stanley I. Shyn, Engilbert Sigurdsson, Grant C.B. Sinnamon, Johannes H. Smit, Daniel J. Smith, Hreinn Stefansson, Stacy Steinberg, Fabian Streit, Jana Strohmaier, Katherine E. Tansey, Henning Teismann, Alexander Teumer, Wesley Thompson, Pippa A. Thomson, Thorgeir E. Thorgeirsson, Matthew Traylor, Jens Treutlein, André G. Uitterlinden, Daniel Umbricht, Sandra Van der Auwera, Albert M. van Hemert, Alexander Viktorin, Peter M. Visscher, Yunpeng Wang, Bradley T. Webb, Shantel Marie Weinsheimer, Jürgen Wellmann, Gonneke Willemsen, Stephanie H. Witt, Yang Wu, Hualin S. Xi, Jian Yang, Futao Zhang, Klaus Berger, Dorret I. Boomsma, Sven Cichon, Udo Dannlowski, E.J.C. de Geus, J. Raymond DePaulo, Enrico Domenici, Tõnu Esko, Hans J. Grabe, Steven P. Hamilton, Andrew C. Heath, Kenneth S. Kendler, Stefan Kloiber, Susanne Lucae, Pamela A.F. Madden, Patrik K. Magnusson, Andres Metspalu, Preben Bo Mortensen, Bertram Müller-Myhsok, Merete Nordentoft, Markus M. Nöthen, Michael C. O’Donovan, Sara A. Paciga, Nancy L. Pedersen, Brenda W.J.H. Penninx, Roy H. Perlis, James B. Potash, Martin Preisig, Catherine Schaefer, Thomas G. Schulze, Jordan W. Smoller, Kari Stefansson, Henning Tiemeier, Henry Völzke, Myrna M. Weissman, Thomas Werge, Douglas F. Levinson, Gerome Breen, Anders D. Børglum, and Patrick F. Sullivan
Subjects: Antidepressant response, Depression, Genetics, GWAS, MDD, Polygenic score, Psychiatry, RC435-571
Abstract: Background: Antidepressants are a first-line treatment for depression. However, only a third of individuals experience remission after the first treatment. Common genetic variation, in part, likely regulates antidepressant response, yet the success of previous genome-wide association studies has been limited by sample size. This study performs the largest genetic analysis of prospectively assessed antidepressant response in major depressive disorder to gain insight into the underlying biology and enable out-of-sample prediction. Methods: Genome-wide analysis of remission (nremit = 1852, nnonremit = 3299) and percentage improvement (n = 5218) was performed. Single nucleotide polymorphism–based heritability was estimated using genome-wide complex trait analysis. Genetic covariance with eight mental health phenotypes was estimated using polygenic scores/AVENGEME. Out-of-sample prediction of antidepressant response polygenic scores was assessed. Gene-level association analysis was performed using MAGMA and transcriptome-wide association study. Tissue, pathway, and drug binding enrichment were estimated using MAGMA. Results: Neither genome-wide association study identified genome-wide significant associations. Single nucleotide polymorphism–based heritability was significantly different from zero for remission (h2 = 0.132, SE = 0.056) but not for percentage improvement (h2 = −0.018, SE = 0.032). Better antidepressant response was negatively associated with genetic risk for schizophrenia and positively associated with genetic propensity for educational attainment. Leave-one-out validation of antidepressant response polygenic scores demonstrated significant evidence of out-of-sample prediction, though results varied in external cohorts. Gene-based analyses identified ETV4 and DHX8 as significantly associated with antidepressant response. Conclusions: This study demonstrates that antidepressant response is influenced by common genetic variation, has a genetic overlap schizophrenia and educational attainment, and provides a useful resource for future research. Larger sample sizes are required to attain the potential of genetics for understanding and predicting antidepressant response.
Published: 2022
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13. Genome‐Wide Association Study of NAFLD Using Electronic Health Records

Author: Cameron J. Fairfield, Thomas M. Drake, Riinu Pius, Andrew D. Bretherick, Archie Campbell, David W. Clark, Jonathan A. Fallowfield, Caroline Hayward, Neil C. Henderson, Peter K. Joshi, Nicholas L. Mills, David J. Porteous, Prakash Ramachandran, Robert K. Semple, Catherine A. Shaw, Cathie L.M. Sudlow, Paul R.H.J. Timmers, James F. Wilson, Stephen J. Wigmore, Ewen M. Harrison, and Athina Spiliopoulou
Subjects: Diseases of the digestive system. Gastroenterology, RC799-869
Abstract: Genome‐wide association studies (GWAS) have identified several risk loci for nonalcoholic fatty liver disease (NAFLD). Previous studies have largely relied on small sample sizes and have assessed quantitative traits. We performed a case‐control GWAS in the UK Biobank using recorded diagnosis of NAFLD based on diagnostic codes recommended in recent consensus guidelines. We performed a GWAS of 4,761 cases of NAFLD and 373,227 healthy controls without evidence of NAFLD. Sensitivity analyses were performed excluding other co‐existing hepatic pathology, adjusting for body mass index (BMI) and adjusting for alcohol intake. A total of 9,723,654 variants were assessed by logistic regression adjusted for age, sex, genetic principal components, and genotyping batch. We performed a GWAS meta‐analysis using available summary association statistics. Six risk loci were identified (P
Published: 2022
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14. Blood-based epigenome-wide analyses of cognitive abilities

Author: Daniel L. McCartney, Robert F. Hillary, Eleanor L. S. Conole, Daniel Trejo Banos, Danni A. Gadd, Rosie M. Walker, Cliff Nangle, Robin Flaig, Archie Campbell, Alison D. Murray, Susana Muñoz Maniega, María del C. Valdés-Hernández, Mathew A. Harris, Mark E. Bastin, Joanna M. Wardlaw, Sarah E. Harris, David J. Porteous, Elliot M. Tucker-Drob, Andrew M. McIntosh, Kathryn L. Evans, Ian J. Deary, Simon R. Cox, Matthew R. Robinson, and Riccardo E. Marioni
Subjects: DNA methylation, EWAS, Cognitive ability, Prediction, Epidemiology, Biology (General), QH301-705.5, Genetics, QH426-470
Abstract: Abstract Background Blood-based markers of cognitive functioning might provide an accessible way to track neurodegeneration years prior to clinical manifestation of cognitive impairment and dementia. Results Using blood-based epigenome-wide analyses of general cognitive function, we show that individual differences in DNA methylation (DNAm) explain 35.0% of the variance in general cognitive function (g). A DNAm predictor explains ~4% of the variance, independently of a polygenic score, in two external cohorts. It also associates with circulating levels of neurology- and inflammation-related proteins, global brain imaging metrics, and regional cortical volumes. Conclusions As sample sizes increase, the ability to assess cognitive function from DNAm data may be informative in settings where cognitive testing is unreliable or unavailable.
Published: 2022
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15. Global Biobank analyses provide lessons for developing polygenic risk scores across diverse cohorts

Author: Ying Wang, Shinichi Namba, Esteban Lopera, Sini Kerminen, Kristin Tsuo, Kristi Läll, Masahiro Kanai, Wei Zhou, Kuan-Han Wu, Marie-Julie Favé, Laxmi Bhatta, Philip Awadalla, Ben Brumpton, Patrick Deelen, Kristian Hveem, Valeria Lo Faro, Reedik Mägi, Yoshinori Murakami, Serena Sanna, Jordan W. Smoller, Jasmina Uzunovic, Brooke N. Wolford, Cristen Willer, Eric R. Gamazon, Nancy J. Cox, Ida Surakka, Yukinori Okada, Alicia R. Martin, Jibril Hirbo, Kuan-Han H. Wu, Humaira Rasheed, Jibril B. Hirbo, Arjun Bhattacharya, Huiling Zhao, Esteban A. Lopera-Maya, Sinéad B. Chapman, Juha Karjalainen, Mitja Kurki, Maasha Mutaamba, Juulia J. Partanen, Ben M. Brumpton, Sameer Chavan, Tzu-Ting Chen, Michelle Daya, Yi Ding, Yen-Chen A. Feng, Christopher R. Gignoux, Sarah E. Graham, Whitney E. Hornsby, Nathan Ingold, Ruth Johnson, Triin Laisk, Kuang Lin, Jun Lv, Iona Y. Millwood, Priit Palta, Anita Pandit, Michael H. Preuss, Unnur Thorsteinsdottir, Matthew Zawistowski, Xue Zhong, Archie Campbell, Kristy Crooks, Geertruida H. de Bock, Nicholas J. Douville, Sarah Finer, Lars G. Fritsche, Christopher J. Griffiths, Yu Guo, Karen A. Hunt, Takahiro Konuma, Riccardo E. Marioni, Jansonius Nomdo, Snehal Patil, Nicholas Rafaels, Anne Richmond, Jonathan A. Shortt, Peter Straub, Ran Tao, Brett Vanderwerff, Kathleen C. Barnes, Marike Boezen, Zhengming Chen, Chia-Yen Chen, Judy Cho, George Davey Smith, Hilary K. Finucane, Lude Franke, Andrea Ganna, Tom R. Gaunt, Tian Ge, Hailiang Huang, Jennifer Huffman, Jukka T. Koskela, Clara Lajonchere, Matthew H. Law, Liming Li, Cecilia M. Lindgren, Ruth J.F. Loos, Stuart MacGregor, Koichi Matsuda, Catherine M. Olsen, David J. Porteous, Jordan A. Shavit, Harold Snieder, Richard C. Trembath, Judith M. Vonk, David Whiteman, Stephen J. Wicks, Cisca Wijmenga, John Wright, Jie Zheng, Xiang Zhou, Michael Boehnke, Daniel H. Geschwind, Caroline Hayward, Eimear E. Kenny, Yen-Feng Lin, Hilary C. Martin, Sarah E. Medland, Aarno V. Palotie, Bogdan Pasaniuc, Kari Stefansson, David A. van Heel, Robin G. Walters, Sebastian Zöllner, Cristen J. Willer, Mark J. Daly, and Benjamin M. Neale
Subjects: Global-Biobank Meta-analysis Initiative, polygenic risk scores, multi-ancestry genetic prediction, accuracy heterogeneity, Genetics, QH426-470, Internal medicine, RC31-1245
Abstract: Summary: Polygenic risk scores (PRSs) have been widely explored in precision medicine. However, few studies have thoroughly investigated their best practices in global populations across different diseases. We here utilized data from Global Biobank Meta-analysis Initiative (GBMI) to explore methodological considerations and PRS performance in 9 different biobanks for 14 disease endpoints. Specifically, we constructed PRSs using pruning and thresholding (P + T) and PRS-continuous shrinkage (CS). For both methods, using a European-based linkage disequilibrium (LD) reference panel resulted in comparable or higher prediction accuracy compared with several other non-European-based panels. PRS-CS overall outperformed the classic P + T method, especially for endpoints with higher SNP-based heritability. Notably, prediction accuracy is heterogeneous across endpoints, biobanks, and ancestries, especially for asthma, which has known variation in disease prevalence across populations. Overall, we provide lessons for PRS construction, evaluation, and interpretation using GBMI resources and highlight the importance of best practices for PRS in the biobank-scale genomics era.
Published: 2023
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16. Association of low-frequency and rare coding variants with information processing speed

Author: Jan Bressler, Gail Davies, Albert V. Smith, Yasaman Saba, Joshua C. Bis, Xueqiu Jian, Caroline Hayward, Lisa Yanek, Jennifer A. Smith, Saira S. Mirza, Ruiqi Wang, Hieab H. H. Adams, Diane Becker, Eric Boerwinkle, Archie Campbell, Simon R. Cox, Gudny Eiriksdottir, Chloe Fawns-Ritchie, Rebecca F. Gottesman, Megan L. Grove, Xiuqing Guo, Edith Hofer, Sharon L. R. Kardia, Maria J. Knol, Marisa Koini, Oscar L. Lopez, Riccardo E. Marioni, Paul Nyquist, Alison Pattie, Ozren Polasek, David J. Porteous, Igor Rudan, Claudia L. Satizabal, Helena Schmidt, Reinhold Schmidt, Stephen Sidney, Jeannette Simino, Blair H. Smith, Stephen T. Turner, Sven J. van der Lee, Erin B. Ware, Rachel A. Whitmer, Kristine Yaffe, Qiong Yang, Wei Zhao, Vilmundur Gudnason, Lenore J. Launer, Annette L. Fitzpatrick, Bruce M. Psaty, Myriam Fornage, M. Arfan Ikram, Cornelia M. van Duijn, Sudha Seshadri, Thomas H. Mosley, and Ian J. Deary
Subjects: Neurosciences. Biological psychiatry. Neuropsychiatry, RC321-571
Abstract: Abstract Measures of information processing speed vary between individuals and decline with age. Studies of aging twins suggest heritability may be as high as 67%. The Illumina HumanExome Bead Chip genotyping array was used to examine the association of rare coding variants with performance on the Digit-Symbol Substitution Test (DSST) in community-dwelling adults participating in the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium. DSST scores were available for 30,576 individuals of European ancestry from nine cohorts and for 5758 individuals of African ancestry from four cohorts who were older than 45 years and free of dementia and clinical stroke. Linear regression models adjusted for age and gender were used for analysis of single genetic variants, and the T5, T1, and T01 burden tests that aggregate the number of rare alleles by gene were also applied. Secondary analyses included further adjustment for education. Meta-analyses to combine cohort-specific results were carried out separately for each ancestry group. Variants in RNF19A reached the threshold for statistical significance (p = 2.01 × 10−6) using the T01 test in individuals of European descent. RNF19A belongs to the class of E3 ubiquitin ligases that confer substrate specificity when proteins are ubiquitinated and targeted for degradation through the 26S proteasome. Variants in SLC22A7 and OR51A7 were suggestively associated with DSST scores after adjustment for education for African-American participants and in the European cohorts, respectively. Further functional characterization of its substrates will be required to confirm the role of RNF19A in cognitive function.
Published: 2021
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17. Hair glucocorticoids are associated with childhood adversity, depressive symptoms and reduced global and lobar grey matter in Generation Scotland

Author: Claire Green, Aleks Stolicyn, Mathew A. Harris, Xueyi Shen, Liana Romaniuk, Miruna C. Barbu, Emma L. Hawkins, Joanna M. Wardlaw, J. Douglas Steele, Gordon D. Waiter, Anca-Larisa Sandu, Archie Campbell, David J. Porteous, Jonathan R. Seckl, Stephen M. Lawrie, Rebecca M. Reynolds, Jonathan Cavanagh, Andrew M. McIntosh, and Heather C. Whalley
Subjects: Neurosciences. Biological psychiatry. Neuropsychiatry, RC321-571
Abstract: Abstract Hypothalamic–pituitary–adrenal (HPA) axis dysregulation has been commonly reported in major depressive disorder (MDD), but with considerable heterogeneity of results; potentially due to the predominant use of acute measures of an inherently variable/phasic system. Chronic longer-term measures of HPA-axis activity have yet to be systematically examined in MDD, particularly in relation to brain phenotypes, and in the context of early-life/contemporaneous stress. Here, we utilise a temporally stable measure of cumulative HPA-axis function (hair glucocorticoids) to investigate associations between cortisol, cortisone and total glucocorticoids with concurrent measures of (i) lifetime-MDD case/control status and current symptom severity, (ii) early/current-life stress and (iii) structural neuroimaging phenotypes, in N = 993 individuals from Generation Scotland (mean age = 59.1 yrs). Increased levels of hair cortisol were significantly associated with reduced global and lobar brain volumes with reductions in the frontal, temporal and cingulate regions (β range = −0.057 to −0.104, all P FDR
Published: 2021
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18. Birth weight associations with DNA methylation differences in an adult population

Author: Rebecca A. Madden, Daniel L. McCartney, Rosie M. Walker, Robert F. Hillary, Mairead L. Bermingham, Konrad Rawlik, Stewart W. Morris, Archie Campbell, David J. Porteous, Ian J. Deary, Kathryn L. Evans, Jonathan Hafferty, Andrew M. McIntosh, and Riccardo E. Marioni
Subjects: dna methylation, generation scotland, birth weight, depression, ewas, Genetics, QH426-470
Abstract: The Developmental Origins of Health and Disease (DOHaD) theory predicts that prenatal and early life events shape adult health outcomes. Birth weight is a useful indicator of the foetal experience and has been associated with multiple adult health outcomes. DNA methylation (DNAm) is one plausible mechanism behind the relationship of birth weight to adult health. Through data linkage between Generation Scotland and historic Scottish birth cohorts, and birth records held through the NHS Information and Statistics Division, a sample of 1,757 individuals with available birth weight and DNAm data was derived. Epigenome-wide association studies (EWAS) were performed in two independently generated DNAm subgroups (nSet1 = 1,395, nSet2 = 362), relating adult DNAm from whole blood to birth weight. Meta-analysis yielded one genome-wide significant CpG site (p = 5.97x10−9), cg00966482. There was minimal evidence for attenuation of the effect sizes for the lead loci upon adjustment for numerous potential confounder variables (body mass index, educational attainment, and socioeconomic status). Associations between birth weight and epigenetic measures of biological age were also assessed. Associations between lower birth weight and higher Grim Age acceleration (p(FDR) = 3.6x10−3) and shorter DNAm-derived telomere length (p(FDR) = 1.7x10−3) are described, although results for three other epigenetic clocks were null. Our results provide support for an association between birth weight and DNAm both locally at one CpG site, and globally via biological ageing estimates.
Published: 2021
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19. Genome-wide association studies identify 137 genetic loci for DNA methylation biomarkers of aging

Author: Daniel L. McCartney, Josine L. Min, Rebecca C. Richmond, Ake T. Lu, Maria K. Sobczyk, Gail Davies, Linda Broer, Xiuqing Guo, Ayoung Jeong, Jeesun Jung, Silva Kasela, Seyma Katrinli, Pei-Lun Kuo, Pamela R. Matias-Garcia, Pashupati P. Mishra, Marianne Nygaard, Teemu Palviainen, Amit Patki, Laura M. Raffield, Scott M. Ratliff, Tom G. Richardson, Oliver Robinson, Mette Soerensen, Dianjianyi Sun, Pei-Chien Tsai, Matthijs D. van der Zee, Rosie M. Walker, Xiaochuan Wang, Yunzhang Wang, Rui Xia, Zongli Xu, Jie Yao, Wei Zhao, Adolfo Correa, Eric Boerwinkle, Pierre-Antoine Dugué, Peter Durda, Hannah R. Elliott, Christian Gieger, The Genetics of DNA Methylation Consortium, Eco J. C. de Geus, Sarah E. Harris, Gibran Hemani, Medea Imboden, Mika Kähönen, Sharon L. R. Kardia, Jacob K. Kresovich, Shengxu Li, Kathryn L. Lunetta, Massimo Mangino, Dan Mason, Andrew M. McIntosh, Jonas Mengel-From, Ann Zenobia Moore, Joanne M. Murabito, NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium, Miina Ollikainen, James S. Pankow, Nancy L. Pedersen, Annette Peters, Silvia Polidoro, David J. Porteous, Olli Raitakari, Stephen S. Rich, Dale P. Sandler, Elina Sillanpää, Alicia K. Smith, Melissa C. Southey, Konstantin Strauch, Hemant Tiwari, Toshiko Tanaka, Therese Tillin, Andre G. Uitterlinden, David J. Van Den Berg, Jenny van Dongen, James G. Wilson, John Wright, Idil Yet, Donna Arnett, Stefania Bandinelli, Jordana T. Bell, Alexandra M. Binder, Dorret I. Boomsma, Wei Chen, Kaare Christensen, Karen N. Conneely, Paul Elliott, Luigi Ferrucci, Myriam Fornage, Sara Hägg, Caroline Hayward, Marguerite Irvin, Jaakko Kaprio, Deborah A. Lawlor, Terho Lehtimäki, Falk W. Lohoff, Lili Milani, Roger L. Milne, Nicole Probst-Hensch, Alex P. Reiner, Beate Ritz, Jerome I. Rotter, Jennifer A. Smith, Jack A. Taylor, Joyce B. J. van Meurs, Paolo Vineis, Melanie Waldenberger, Ian J. Deary, Caroline L. Relton, Steve Horvath, and Riccardo E. Marioni
Subjects: DNA methylation, GWAS, Epigenetic clock, Biology (General), QH301-705.5, Genetics, QH426-470
Abstract: Abstract Background Biological aging estimators derived from DNA methylation data are heritable and correlate with morbidity and mortality. Consequently, identification of genetic and environmental contributors to the variation in these measures in populations has become a major goal in the field. Results Leveraging DNA methylation and SNP data from more than 40,000 individuals, we identify 137 genome-wide significant loci, of which 113 are novel, from genome-wide association study (GWAS) meta-analyses of four epigenetic clocks and epigenetic surrogate markers for granulocyte proportions and plasminogen activator inhibitor 1 levels, respectively. We find evidence for shared genetic loci associated with the Horvath clock and expression of transcripts encoding genes linked to lipid metabolism and immune function. Notably, these loci are independent of those reported to regulate DNA methylation levels at constituent clock CpGs. A polygenic score for GrimAge acceleration showed strong associations with adiposity-related traits, educational attainment, parental longevity, and C-reactive protein levels. Conclusion This study illuminates the genetic architecture underlying epigenetic aging and its shared genetic contributions with lifestyle factors and longevity.
Published: 2021
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20. Functional brain defects in a mouse model of a chromosomal t(1;11) translocation that disrupts DISC1 and confers increased risk of psychiatric illness

Author: Marion Bonneau, Shane T. O’ Sullivan, Miguel A. Gonzalez-Lozano, Paul Baxter, Phillippe Gautier, Elena Marchisella, Neil R. Hardingham, Robert A. Chesters, Helen Torrance, David M. Howard, Maurits A. Jansen, Melanie McMillan, Yasmin Singh, Michel Didier, Frank Koopmans, Colin A. Semple, Andrew M. McIntosh, Hansjürgen Volkmer, Maarten Loos, Kevin Fox, Giles E. Hardingham, Anthony C. Vernon, David J. Porteous, August B. Smit, David J. Price, and J. Kirsty Millar
Subjects: Neurosciences. Biological psychiatry. Neuropsychiatry, RC321-571
Abstract: Abstract A balanced t(1;11) translocation that directly disrupts DISC1 is linked to schizophrenia and affective disorders. We previously showed that a mutant mouse, named Der1, recapitulates the effect of the translocation upon DISC1 expression. Here, RNAseq analysis of Der1 mouse brain tissue found enrichment for dysregulation of the same genes and molecular pathways as in neuron cultures generated previously from human t(1;11) translocation carriers via the induced pluripotent stem cell route. DISC1 disruption therefore apparently accounts for a substantial proportion of the effects of the t(1;11) translocation. RNAseq and pathway analysis of the mutant mouse predicts multiple Der1-induced alterations converging upon synapse function and plasticity. Synaptosome proteomics confirmed that the Der1 mutation impacts synapse composition, and electrophysiology found reduced AMPA:NMDA ratio in hippocampal neurons, indicating changed excitatory signalling. Moreover, hippocampal parvalbumin-positive interneuron density is increased, suggesting that the Der1 mutation affects inhibitory control of neuronal circuits. These phenotypes predict that neurotransmission is impacted at many levels by DISC1 disruption in human t(1;11) translocation carriers. Notably, genes implicated in schizophrenia, depression and bipolar disorder by large-scale genetic studies are enriched among the Der1-dysregulated genes, just as we previously observed for the t(1;11) translocation carrier-derived neurons. Furthermore, RNAseq analysis predicts that the Der1 mutation primarily targets a subset of cell types, pyramidal neurons and interneurons, previously shown to be vulnerable to the effects of common schizophrenia-associated genetic variants. In conclusion, DISC1 disruption by the t(1;11) translocation may contribute to the psychiatric disorders of translocation carriers through commonly affected pathways and processes in neurotransmission.
Published: 2021
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21. Identification of epigenome-wide DNA methylation differences between carriers of APOE ε4 and APOE ε2 alleles

Author: Rosie M. Walker, Kadi Vaher, Mairead L. Bermingham, Stewart W. Morris, Andrew D. Bretherick, Yanni Zeng, Konrad Rawlik, Carmen Amador, Archie Campbell, Chris S. Haley, Caroline Hayward, David J. Porteous, Andrew M. McIntosh, Riccardo E. Marioni, and Kathryn L. Evans
Subjects: Alzheimer’s disease, APOE, Apolipoprotein E, DNA methylation, Cholesterol, Lipids, Medicine, Genetics, QH426-470
Abstract: Abstract Background The apolipoprotein E (APOE) ε4 allele is the strongest genetic risk factor for late onset Alzheimer’s disease, whilst the ε2 allele confers protection. Previous studies report differential DNA methylation of APOE between ε4 and ε2 carriers, but associations with epigenome-wide methylation have not previously been characterised. Methods Using the EPIC array, we investigated epigenome-wide differences in whole blood DNA methylation patterns between Alzheimer’s disease-free APOE ε4 (n = 2469) and ε2 (n = 1118) carriers from the two largest single-cohort DNA methylation samples profiled to date. Using a discovery, replication and meta-analysis study design, methylation differences were identified using epigenome-wide association analysis and differentially methylated region (DMR) approaches. Results were explored using pathway and methylation quantitative trait loci (meQTL) analyses. Results We obtained replicated evidence for DNA methylation differences in a ~ 169 kb region, which encompasses part of APOE and several upstream genes. Meta-analytic approaches identified DNA methylation differences outside of APOE: differentially methylated positions were identified in DHCR24, LDLR and ABCG1 (2.59 × 10−100 ≤ P ≤ 2.44 × 10−8) and DMRs were identified in SREBF2 and LDLR (1.63 × 10−4 ≤ P ≤ 3.01 × 10−2). Pathway and meQTL analyses implicated lipid-related processes and high-density lipoprotein cholesterol was identified as a partial mediator of the methylation differences in ABCG1 and DHCR24. Conclusions APOE ε4 vs. ε2 carrier status is associated with epigenome-wide methylation differences in the blood. The loci identified are located in trans as well as cis to APOE and implicate genes involved in lipid homeostasis.
Published: 2021
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22. Complex trait methylation scores in the prediction of major depressive disorder

Author: Miruna C. Barbu, Carmen Amador, Alex S.F. Kwong, Xueyi Shen, Mark J. Adams, David M. Howard, Rosie M. Walker, Stewart W. Morris, Josine L. Min, Chunyu Liu, Jenny van Dongen, Mohsen Ghanbari, Caroline Relton, David J. Porteous, Archie Campbell, Kathryn L. Evans, Heather C. Whalley, and Andrew M. McIntosh
Subjects: DNA methylation, Methylation score, Environmental factors, Major depressive disorder, Generation Scotland, Avon longitudinal study of parents and children, Medicine, Medicine (General), R5-920
Abstract: Summary: Background: DNA methylation (DNAm) is associated with time-varying environmental factors that contribute to major depressive disorder (MDD) risk. We sought to test whether DNAm signatures of lifestyle and biochemical factors were associated with MDD to reveal dynamic biomarkers of MDD risk that may be amenable to lifestyle interventions. Methods: Here, we calculated methylation scores (MS) at multiple p-value thresholds for lifestyle (BMI, smoking, alcohol consumption, and educational attainment) and biochemical (high-density lipoprotein (HDL) and total cholesterol) factors in Generation Scotland (GS) (N=9,502) and in a replication cohort (ALSPACadults, N=565), using CpG sites reported in previous well-powered methylome-wide association studies. We also compared their predictive accuracy for MDD to a MDD MS in an independent GS sub-sample (N=4,432). Findings: Each trait MS was significantly associated with its corresponding phenotype in GS (βrange=0.089–1.457) and in ALSPAC (βrange=0.078–2.533). Each MS was also significantly associated with MDD before and after adjustment for its corresponding phenotype in GS (βrange=0.053–0.145). After accounting for relevant lifestyle factors, MS for educational attainment (β=0.094) and alcohol consumption (MSp-value
Published: 2022
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23. Bayesian reassessment of the epigenetic architecture of complex traits

Author: Daniel Trejo Banos, Daniel L. McCartney, Marion Patxot, Lucas Anchieri, Thomas Battram, Colette Christiansen, Ricardo Costeira, Rosie M. Walker, Stewart W. Morris, Archie Campbell, Qian Zhang, David J. Porteous, Allan F. McRae, Naomi R. Wray, Peter M. Visscher, Chris S. Haley, Kathryn L. Evans, Ian J. Deary, Andrew M. McIntosh, Gibran Hemani, Jordana T. Bell, Riccardo E. Marioni, and Matthew R. Robinson
Subjects: Science
Abstract: Linking epigenetic marks to clinical outcomes promises insight into the underlying processes. Here, the authors introduce a statistical approach to estimate associations between a phenotype and all epigenetic probes jointly, and to estimate the proportion of variation captured by epigenetic effects.
Published: 2020
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24. Multi-ancestry GWAS of the electrocardiographic PR interval identifies 202 loci underlying cardiac conduction

Author: Ioanna Ntalla, Lu-Chen Weng, James H. Cartwright, Amelia Weber Hall, Gardar Sveinbjornsson, Nathan R. Tucker, Seung Hoan Choi, Mark D. Chaffin, Carolina Roselli, Michael R. Barnes, Borbala Mifsud, Helen R. Warren, Caroline Hayward, Jonathan Marten, James J. Cranley, Maria Pina Concas, Paolo Gasparini, Thibaud Boutin, Ivana Kolcic, Ozren Polasek, Igor Rudan, Nathalia M. Araujo, Maria Fernanda Lima-Costa, Antonio Luiz P. Ribeiro, Renan P. Souza, Eduardo Tarazona-Santos, Vilmantas Giedraitis, Erik Ingelsson, Anubha Mahajan, Andrew P. Morris, Fabiola Del Greco M, Luisa Foco, Martin Gögele, Andrew A. Hicks, James P. Cook, Lars Lind, Cecilia M. Lindgren, Johan Sundström, Christopher P. Nelson, Muhammad B. Riaz, Nilesh J. Samani, Gianfranco Sinagra, Sheila Ulivi, Mika Kähönen, Pashupati P. Mishra, Nina Mononen, Kjell Nikus, Mark J. Caulfield, Anna Dominiczak, Sandosh Padmanabhan, May E. Montasser, Jeff R. O’Connell, Kathleen Ryan, Alan R. Shuldiner, Stefanie Aeschbacher, David Conen, Lorenz Risch, Sébastien Thériault, Nina Hutri-Kähönen, Terho Lehtimäki, Leo-Pekka Lyytikäinen, Olli T. Raitakari, Catriona L. K. Barnes, Harry Campbell, Peter K. Joshi, James F. Wilson, Aaron Isaacs, Jan A. Kors, Cornelia M. van Duijn, Paul L. Huang, Vilmundur Gudnason, Tamara B. Harris, Lenore J. Launer, Albert V. Smith, Erwin P. Bottinger, Ruth J. F. Loos, Girish N. Nadkarni, Michael H. Preuss, Adolfo Correa, Hao Mei, James Wilson, Thomas Meitinger, Martina Müller-Nurasyid, Annette Peters, Melanie Waldenberger, Massimo Mangino, Timothy D. Spector, Michiel Rienstra, Yordi J. van de Vegte, Pim van der Harst, Niek Verweij, Stefan Kääb, Katharina Schramm, Moritz F. Sinner, Konstantin Strauch, Michael J. Cutler, Diane Fatkin, Barry London, Morten Olesen, Dan M. Roden, M. Benjamin Shoemaker, J. Gustav Smith, Mary L. Biggs, Joshua C. Bis, Jennifer A. Brody, Bruce M. Psaty, Kenneth Rice, Nona Sotoodehnia, Alessandro De Grandi, Christian Fuchsberger, Cristian Pattaro, Peter P. Pramstaller, Ian Ford, J. Wouter Jukema, Peter W. Macfarlane, Stella Trompet, Marcus Dörr, Stephan B. Felix, Uwe Völker, Stefan Weiss, Aki S. Havulinna, Antti Jula, Katri Sääksjärvi, Veikko Salomaa, Xiuqing Guo, Susan R. Heckbert, Henry J. Lin, Jerome I. Rotter, Kent D. Taylor, Jie Yao, Renée de Mutsert, Arie C. Maan, Dennis O. Mook-Kanamori, Raymond Noordam, Francesco Cucca, Jun Ding, Edward G. Lakatta, Yong Qian, Kirill V. Tarasov, Daniel Levy, Honghuang Lin, Christopher H. Newton-Cheh, Kathryn L. Lunetta, Alison D. Murray, David J. Porteous, Blair H. Smith, Bruno H. Stricker, André Uitterlinden, Marten E. van den Berg, Jeffrey Haessler, Rebecca D. Jackson, Charles Kooperberg, Ulrike Peters, Alexander P. Reiner, Eric A. Whitsel, Alvaro Alonso, Dan E. Arking, Eric Boerwinkle, Georg B. Ehret, Elsayed Z. Soliman, Christy L. Avery, Stephanie M. Gogarten, Kathleen F. Kerr, Cathy C. Laurie, Amanda A. Seyerle, Adrienne Stilp, Solmaz Assa, M. Abdullah Said, M. Yldau van der Ende, Pier D. Lambiase, Michele Orini, Julia Ramirez, Stefan Van Duijvenboden, David O. Arnar, Daniel F. Gudbjartsson, Hilma Holm, Patrick Sulem, Gudmar Thorleifsson, Rosa B. Thorolfsdottir, Unnur Thorsteinsdottir, Emelia J. Benjamin, Andrew Tinker, Kari Stefansson, Patrick T. Ellinor, Yalda Jamshidi, Steven A. Lubitz, and Patricia B. Munroe
Subjects: Science
Abstract: On the electrocardiogram, the PR interval reflects conduction from the atria to ventricles and also serves as risk indicator of cardiovascular morbidity and mortality. Here, the authors perform genome-wide meta-analyses for PR interval in multiple ancestries and identify 141 previously unreported genetic loci.
Published: 2020
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25. A proteomic survival predictor for COVID-19 patients in intensive care

Author: Vadim Demichev, Pinkus Tober-Lau, Tatiana Nazarenko, Oliver Lemke, Simran Kaur Aulakh, Harry J. Whitwell, Annika Röhl, Anja Freiwald, Mirja Mittermaier, Lukasz Szyrwiel, Daniela Ludwig, Clara Correia-Melo, Lena J. Lippert, Elisa T. Helbig, Paula Stubbemann, Nadine Olk, Charlotte Thibeault, Nana-Maria Grüning, Oleg Blyuss, Spyros Vernardis, Matthew White, Christoph B. Messner, Michael Joannidis, Thomas Sonnweber, Sebastian J. Klein, Alex Pizzini, Yvonne Wohlfarter, Sabina Sahanic, Richard Hilbe, Benedikt Schaefer, Sonja Wagner, Felix Machleidt, Carmen Garcia, Christoph Ruwwe-Glösenkamp, Tilman Lingscheid, Laure Bosquillon de Jarcy, Miriam S. Stegemann, Moritz Pfeiffer, Linda Jürgens, Sophy Denker, Daniel Zickler, Claudia Spies, Andreas Edel, Nils B. Müller, Philipp Enghard, Aleksej Zelezniak, Rosa Bellmann-Weiler, Günter Weiss, Archie Campbell, Caroline Hayward, David J. Porteous, Riccardo E. Marioni, Alexander Uhrig, Heinz Zoller, Judith Löffler-Ragg, Markus A. Keller, Ivan Tancevski, John F. Timms, Alexey Zaikin, Stefan Hippenstiel, Michael Ramharter, Holger Müller-Redetzky, Martin Witzenrath, Norbert Suttorp, Kathryn Lilley, Michael Mülleder, Leif Erik Sander, Florian Kurth, and Markus Ralser
Subjects: Computer applications to medicine. Medical informatics, R858-859.7
Abstract: Global healthcare systems are challenged by the COVID-19 pandemic. There is a need to optimize allocation of treatment and resources in intensive care, as clinically established risk assessments such as SOFA and APACHE II scores show only limited performance for predicting the survival of severely ill COVID-19 patients. Additional tools are also needed to monitor treatment, including experimental therapies in clinical trials. Comprehensively capturing human physiology, we speculated that proteomics in combination with new data-driven analysis strategies could produce a new generation of prognostic discriminators. We studied two independent cohorts of patients with severe COVID-19 who required intensive care and invasive mechanical ventilation. SOFA score, Charlson comorbidity index, and APACHE II score showed limited performance in predicting the COVID-19 outcome. Instead, the quantification of 321 plasma protein groups at 349 timepoints in 50 critically ill patients receiving invasive mechanical ventilation revealed 14 proteins that showed trajectories different between survivors and non-survivors. A predictor trained on proteomic measurements obtained at the first time point at maximum treatment level (i.e. WHO grade 7), which was weeks before the outcome, achieved accurate classification of survivors (AUROC 0.81). We tested the established predictor on an independent validation cohort (AUROC 1.0). The majority of proteins with high relevance in the prediction model belong to the coagulation system and complement cascade. Our study demonstrates that plasma proteomics can give rise to prognostic predictors substantially outperforming current prognostic markers in intensive care. Author summary Healthcare systems around the world are struggling to accommodate high numbers of the most severely ill patients with COVID-19. Moreover, the pandemic creates a pressing need to accelerate clinical trials investigating potential new therapeutics. While various biomarkers can discriminate and predict the future course of disease for patients of different disease severity, prognosis remains difficult for patient groups with similar disease severity, e.g. patients requiring intensive care. Established risk assessments in intensive care medicine such as the SOFA or APACHE II show only limited reliability in predicting future disease outcomes for COVID-19. In this study we hypothesized that the plasma proteome, which reflects the complete set of proteins that are expressed by an organism and are present in the blood, and which is known to comprehensively capture the host response to COVID-19, can be leveraged to allow for prediction of survival in the most critically ill patients with COVID-19. Here, we found 14 proteins, which over time changed in opposite directions for patients who survive compared to patients who do not survive on intensive care. Using a machine learning model which combines the measurements of multiple proteins, we were able to accurately predict survival in critically ill patients with COVID-19 from single blood samples, weeks before the outcome, substantially outperforming established risk predictors.
Published: 2022

26. An epigenome-wide association study of sex-specific chronological ageing

Author: Daniel L. McCartney, Futao Zhang, Robert F. Hillary, Qian Zhang, Anna J. Stevenson, Rosie M. Walker, Mairead L. Bermingham, Thibaud Boutin, Stewart W. Morris, Archie Campbell, Alison D. Murray, Heather C. Whalley, David J. Porteous, Caroline Hayward, Kathryn L. Evans, Tamir Chandra, Ian J. Deary, Andrew M. McIntosh, Jian Yang, Peter M. Visscher, Allan F. McRae, and Riccardo E. Marioni
Subjects: DNA methylation, Ageing, Sexual dimorphism, X chromosome, Generation Scotland, Medicine, Genetics, QH426-470
Abstract: Abstract Background Advanced age is associated with cognitive and physical decline and is a major risk factor for a multitude of disorders. There is also a gap in life expectancy between males and females. DNA methylation differences have been shown to be associated with both age and sex. Here, we investigate age-by-sex differences in blood-based DNA methylation in an unrelated cohort of 2586 individuals between the ages of 18 and 87 years, with replication in a further 4450 individuals between the ages of 18 and 93 years. Methods Linear regression models were applied, with stringent genome-wide significance thresholds (p
Published: 2019
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27. Genome-wide analysis identifies molecular systems and 149 genetic loci associated with income

Author: W. David Hill, Neil M. Davies, Stuart J. Ritchie, Nathan G. Skene, Julien Bryois, Steven Bell, Emanuele Di Angelantonio, David J. Roberts, Shen Xueyi, Gail Davies, David C. M. Liewald, David J. Porteous, Caroline Hayward, Adam S. Butterworth, Andrew M. McIntosh, Catharine R. Gale, and Ian J. Deary
Subjects: Science
Abstract: Household income is used as a marker of socioeconomic position, a trait that is associated with better physical and mental health. Here, Hill et al. report a genome-wide association study for household income in the UK and explore its relationship with intelligence in post-GWAS analyses including Mendelian randomization.
Published: 2019
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28. Lifestyle and Genetic Factors Modify Parent-of-Origin Effects on the Human Methylome

Author: Yanni Zeng, Carmen Amador, Chenhao Gao, Rosie M. Walker, Stewart W. Morris, Archie Campbell, Azra Frkatović, Rebecca A Madden, Mark J. Adams, Shuai He, Andrew D. Bretherick, Caroline Hayward, David J. Porteous, James F. Wilson, Kathryn L. Evans, Andrew M. McIntosh, Pau Navarro, and Chris S. Haley
Subjects: parent-of-origin effect, DNA methylation, interaction (modification) effect, mQTL, DNA methylation machinery genes, smoking, Medicine, Medicine (General), R5-920
Abstract: Background: parent-of-origin effects (POE) play important roles in complex disease and thus understanding their regulation and associated molecular and phenotypic variation are warranted. Previous studies mainly focused on the detection of genomic regions or phenotypes regulated by POE. Understanding whether POE may be modified by environmental or genetic exposures is important for understanding of the source of POE-associated variation, but only a few case studies addressing modifiable POE exist. Methods: in order to understand this high order of POE regulation, we screened 101 genetic and environmental factors such as ‘predicted mRNA expression levels’ of DNA methylation/imprinting machinery genes and environmental exposures. POE-mQTL-modifier interaction models were proposed to test the potential of these factors to modify POE at DNA methylation using data from Generation Scotland: The Scottish Family Health Study(N=2315). Findings: a set of vulnerable/modifiable POE-CpGs were identified (modifiable-POE-regulated CpGs, N=3). Four factors, ‘lifetime smoking status’ and ‘predicted mRNA expression levels’ of TET2, SIRT1 and KDM1A, were found to significantly modify the POE on the three CpGs in both discovery and replication datasets. We further identified plasma protein and health-related phenotypes associated with the methylation level of one of the identified CpGs. Interpretation: the modifiable POE identified here revealed an important yet indirect path through which genetic background and environmental exposures introduce their effect on DNA methylation, motivating future comprehensive evaluation of the role of these modifiers in complex diseases. Funding: NSFC (81971270),H2020-MSCA-ITN(721815), Wellcome (204979/Z/16/Z,104036/Z/14/Z), MRC (MC_UU_00007/10, MC_PC_U127592696), CSO (CZD/16/6,CZB/4/276, CZB/4/710), SFC (HR03006), EUROSPAN (LSHG-CT-2006-018947), BBSRC (BBS/E/D/30002276), SYSU, Arthritis Research UK, NHLBI, NIH.
Published: 2021
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29. CovidLife: a resource to understand mental health, well-being and behaviour during the COVID-19 pandemic in the UK [version 1; peer review: 2 approved]

Author: David J. Porteous, Riccardo E. Marioni, Caroline Hayward, Andrew M. McIntosh, Ian J. Deary, Chloe Fawns-Ritchie, Clifford Nangle, Louise Hartley, Cathie Sudlow, Christie Levein, Rebecca Dawson, Robin Flaig, Archie Campbell, Elaine Douglas, Charlotte Huggins, Drew M. Altschul, David Bell, Daniel L. McCartney, and Rachel Edwards
Subjects: COVID-19, psychological, mental health, well-being, longitudinal study, observational study, eng, Medicine, Science
Abstract: CovidLife is a longitudinal observational study designed to investigate the impact of the COVID-19 pandemic on mental health, well-being and behaviour in adults living in the UK. In total, 18,518 participants (mean age = 56.43, SD = 14.35) completed the first CovidLife questionnaire (CovidLife1) between April and June 2020. To date, participants have completed two follow-up assessments. CovidLife2 took place between July and August 2020 (n = 11,319), and CovidLife3 took place in February 2021 (n = 10,386). A range of social and psychological measures were administered at each wave including assessments of anxiety, depression, well-being, loneliness and isolation. Information on sociodemographic, health, and economic circumstances was also collected. Questions also assessed information on COVID-19 infections and symptoms, compliance to COVID-19 restrictions, and opinions on the UK and Scottish Governments’ handling of the pandemic. CovidLife includes a subsample of 4,847 participants from the Generation Scotland cohort (N~24,000, collected 2006-2011); a well-characterised cohort of families in Scotland with pre-pandemic data on mental health, physical health, lifestyle, and socioeconomic factors, along with biochemical and genomic data derived from biological samples. These participants also consented to their study data being linked to Scottish health records. CovidLife and Generation Scotland data can be accessed and used by external researchers following approval from the Generation Scotland Access Committee. CovidLife can be used to investigate mental health, well-being and behaviour during COVID-19; how these vary according to sociodemographic, health and economic circumstances; and how these change over time. The Generation Scotland subsample with pre-pandemic data and linkage to health records can be used to investigate the predictors of health and well-being during COVID-19 and the future health consequences of the COVID-19 pandemic.
Published: 2021
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30. Cohort profile for the STratifying Resilience and Depression Longitudinally (STRADL) study: A depression-focused investigation of Generation Scotland, using detailed clinical, cognitive, and neuroimaging assessments [version 2; peer review: 2 approved]

Author: Tina Habota, Anca-Larisa Sandu, Gordon D. Waiter, Christopher J. McNeil, J. Douglas Steele, Jennifer A. Macfarlane, Heather C. Whalley, Ruth Valentine, Dawn Younie, Nichola Crouch, Emma L. Hawkins, Yoriko Hirose, Liana Romaniuk, Keith Milburn, Gordon Buchan, Tessa Coupar, Mairi Stirling, Baljit Jagpal, Beverly MacLennan, Lucasz Priba, Mathew A. Harris, Jonathan D. Hafferty, Mark J. Adams, Archie I. Campbell, Donald J. MacIntyre, Alison Pattie, Lee Murphy, Rebecca M. Reynolds, Rebecca Elliot, Ian S. Penton-Voak, Marcus R. Munafò, Kathryn L. Evans, Jonathan R. Seckl, Joanna M. Wardlaw, Stephen M. Lawrie, Christopher S. Haley, David J. Porteous, Ian J. Deary, Alison D. Murray, and Andrew M. McIntosh
Subjects: Medicine, Science
Abstract: STratifying Resilience and Depression Longitudinally (STRADL) is a population-based study built on the Generation Scotland: Scottish Family Health Study (GS:SFHS) resource. The aim of STRADL is to subtype major depressive disorder (MDD) on the basis of its aetiology, using detailed clinical, cognitive, and brain imaging assessments. The GS:SFHS provides an important opportunity to study complex gene-environment interactions, incorporating linkage to existing datasets and inclusion of early-life variables for two longitudinal birth cohorts. Specifically, data collection in STRADL included: socio-economic and lifestyle variables; physical measures; questionnaire data that assesses resilience, early-life adversity, personality, psychological health, and lifetime history of mood disorder; laboratory samples; cognitive tests; and brain magnetic resonance imaging. Some of the questionnaire and cognitive data were first assessed at the GS:SFHS baseline assessment between 2006-2011, thus providing longitudinal measures relevant to the study of depression, psychological resilience, and cognition. In addition, routinely collected historic NHS data and early-life variables are linked to STRADL data, further providing opportunities for longitudinal analysis. Recruitment has been completed and we consented and tested 1,188 participants.
Published: 2021
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31. Improved precision of epigenetic clock estimates across tissues and its implication for biological ageing

Author: Qian Zhang, Costanza L. Vallerga, Rosie M. Walker, Tian Lin, Anjali K. Henders, Grant W. Montgomery, Ji He, Dongsheng Fan, Javed Fowdar, Martin Kennedy, Toni Pitcher, John Pearson, Glenda Halliday, John B. Kwok, Ian Hickie, Simon Lewis, Tim Anderson, Peter A. Silburn, George D. Mellick, Sarah E. Harris, Paul Redmond, Alison D. Murray, David J. Porteous, Christopher S. Haley, Kathryn L. Evans, Andrew M. McIntosh, Jian Yang, Jacob Gratten, Riccardo E. Marioni, Naomi R. Wray, Ian J. Deary, Allan F. McRae, and Peter M. Visscher
Subjects: DNA methylation, Age prediction, Epigenetic clock, Ageing, Mortality, Medicine, Genetics, QH426-470
Abstract: Abstract Background DNA methylation changes with age. Chronological age predictors built from DNA methylation are termed ‘epigenetic clocks’. The deviation of predicted age from the actual age (‘age acceleration residual’, AAR) has been reported to be associated with death. However, it is currently unclear how a better prediction of chronological age affects such association. Methods In this study, we build multiple predictors based on training DNA methylation samples selected from 13,661 samples (13,402 from blood and 259 from saliva). We use the Lothian Birth Cohorts of 1921 (LBC1921) and 1936 (LBC1936) to examine whether the association between AAR (from these predictors) and death is affected by (1) improving prediction accuracy of an age predictor as its training sample size increases (from 335 to 12,710) and (2) additionally correcting for confounders (i.e., cellular compositions). In addition, we investigated the performance of our predictor in non-blood tissues. Results We found that in principle, a near-perfect age predictor could be developed when the training sample size is sufficiently large. The association between AAR and mortality attenuates as prediction accuracy increases. AAR from our best predictor (based on Elastic Net, https://github.com/qzhang314/DNAm-based-age-predictor) exhibits no association with mortality in both LBC1921 (hazard ratio = 1.08, 95% CI 0.91–1.27) and LBC1936 (hazard ratio = 1.00, 95% CI 0.79–1.28). Predictors based on small sample size are prone to confounding by cellular compositions relative to those from large sample size. We observed comparable performance of our predictor in non-blood tissues with a multi-tissue-based predictor. Conclusions This study indicates that the epigenetic clock can be improved by increasing the training sample size and that its association with mortality attenuates with increased prediction of chronological age.
Published: 2019
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32. Author Correction: Study of 300,486 individuals identifies 148 independent genetic loci influencing general cognitive function

Author: Gail Davies, Max Lam, Sarah E. Harris, Joey W. Trampush, Michelle Luciano, W. David Hill, Saskia P. Hagenaars, Stuart J. Ritchie, Riccardo E. Marioni, Chloe Fawns-Ritchie, David C. M. Liewald, Judith A. Okely, Ari V. Ahola-Olli, Catriona L. K. Barnes, Lars Bertram, Joshua C. Bis, Katherine E. Burdick, Andrea Christoforou, Pamela DeRosse, Srdjan Djurovic, Thomas Espeseth, Stella Giakoumaki, Sudheer Giddaluru, Daniel E. Gustavson, Caroline Hayward, Edith Hofer, M. Arfan Ikram, Robert Karlsson, Emma Knowles, Jari Lahti, Markus Leber, Shuo Li, Karen A. Mather, Ingrid Melle, Derek Morris, Christopher Oldmeadow, Teemu Palviainen, Antony Payton, Raha Pazoki, Katja Petrovic, Chandra A. Reynolds, Muralidharan Sargurupremraj, Markus Scholz, Jennifer A. Smith, Albert V. Smith, Natalie Terzikhan, Anbupalam Thalamuthu, Stella Trompet, Sven J. van der Lee, Erin B. Ware, B. Gwen Windham, Margaret J. Wright, Jingyun Yang, Jin Yu, David Ames, Najaf Amin, Philippe Amouyel, Ole A. Andreassen, Nicola J. Armstrong, Amelia A. Assareh, John R. Attia, Deborah Attix, Dimitrios Avramopoulos, David A. Bennett, Anne C. Böhmer, Patricia A. Boyle, Henry Brodaty, Harry Campbell, Tyrone D. Cannon, Elizabeth T. Cirulli, Eliza Congdon, Emily Drabant Conley, Janie Corley, Simon R. Cox, Anders M. Dale, Abbas Dehghan, Danielle Dick, Dwight Dickinson, Johan G. Eriksson, Evangelos Evangelou, Jessica D. Faul, Ian Ford, Nelson A. Freimer, He Gao, Ina Giegling, Nathan A. Gillespie, Scott D. Gordon, Rebecca F. Gottesman, Michael E. Griswold, Vilmundur Gudnason, Tamara B. Harris, Annette M. Hartmann, Alex Hatzimanolis, Gerardo Heiss, Elizabeth G. Holliday, Peter K. Joshi, Mika Kähönen, Sharon L. R. Kardia, Ida Karlsson, Luca Kleineidam, David S. Knopman, Nicole A. Kochan, Bettina Konte, John B. Kwok, Stephanie Le Hellard, Teresa Lee, Terho Lehtimäki, Shu-Chen Li, Christina M. Lill, Tian Liu, Marisa Koini, Edythe London, Will T. Longstreth, Oscar L. Lopez, Anu Loukola, Tobias Luck, Astri J. Lundervold, Anders Lundquist, Leo-Pekka Lyytikäinen, Nicholas G. Martin, Grant W. Montgomery, Alison D. Murray, Anna C. Need, Raymond Noordam, Lars Nyberg, William Ollier, Goran Papenberg, Alison Pattie, Ozren Polasek, Russell A. Poldrack, Bruce M. Psaty, Simone Reppermund, Steffi G. Riedel-Heller, Richard J. Rose, Jerome I. Rotter, Panos Roussos, Suvi P. Rovio, Yasaman Saba, Fred W. Sabb, Perminder S. Sachdev, Claudia L. Satizabal, Matthias Schmid, Rodney J. Scott, Matthew A. Scult, Jeannette Simino, P. Eline Slagboom, Nikolaos Smyrnis, Aïcha Soumaré, Nikos C. Stefanis, David J. Stott, Richard E. Straub, Kjetil Sundet, Adele M. Taylor, Kent D. Taylor, Ioanna Tzoulaki, Christophe Tzourio, André Uitterlinden, Veronique Vitart, Aristotle N. Voineskos, Jaakko Kaprio, Michael Wagner, Holger Wagner, Leonie Weinhold, K. Hoyan Wen, Elisabeth Widen, Qiong Yang, Wei Zhao, Hieab H. H. Adams, Dan E. Arking, Robert M. Bilder, Panos Bitsios, Eric Boerwinkle, Ornit Chiba-Falek, Aiden Corvin, Philip L. De Jager, Stéphanie Debette, Gary Donohoe, Paul Elliott, Annette L. Fitzpatrick, Michael Gill, David C. Glahn, Sara Hägg, Narelle K. Hansell, Ahmad R. Hariri, M. Kamran Ikram, J. Wouter Jukema, Eero Vuoksimaa, Matthew C. Keller, William S. Kremen, Lenore Launer, Ulman Lindenberger, Aarno Palotie, Nancy L. Pedersen, Neil Pendleton, David J. Porteous, Katri Räikkönen, Olli T. Raitakari, Alfredo Ramirez, Ivar Reinvang, Igor Rudan, Dan Rujescu, Reinhold Schmidt, Helena Schmidt, Peter W. Schofield, Peter R. Schofield, John M. Starr, Vidar M. Steen, Julian N. Trollor, Steven T. Turner, Cornelia M. Van Duijn, Arno Villringer, Daniel R. Weinberger, David R. Weir, James F. Wilson, Anil Malhotra, Andrew M. McIntosh, Catharine R. Gale, Sudha Seshadri, Thomas H. Mosley, Jan Bressler, Todd Lencz, and Ian J. Deary
Subjects: Science
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
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33. Identification of novel differentially methylated sites with potential as clinical predictors of impaired respiratory function and COPDResearch in context

Author: Mairead L. Bermingham, Rosie M. Walker, Riccardo E. Marioni, Stewart W. Morris, Konrad Rawlik, Yanni Zeng, Archie Campbell, Paul Redmond, Heather C. Whalley, Mark J. Adams, Caroline Hayward, Ian J. Deary, David J. Porteous, Andrew M. McIntosh, and Kathryn L. Evans
Subjects: Medicine, Medicine (General), R5-920
Abstract: Background: The causes of poor respiratory function and COPD are incompletely understood, but it is clear that genes and the environment play a role. As DNA methylation is under both genetic and environmental control, we hypothesised that investigation of differential methylation associated with these phenotypes would permit mechanistic insights, and improve prediction of COPD. We investigated genome-wide differential DNA methylation patterns using the recently released 850 K Illumina EPIC array. This is the largest single population, whole-genome epigenetic study to date. Methods: Epigenome-wide association studies (EWASs) of respiratory function and COPD were performed in peripheral blood samples from the Generation Scotland: Scottish Family Health Study (GS:SFHS) cohort (n = 3781; 274 COPD cases and 2919 controls). In independent COPD incidence data (n = 149), significantly differentially methylated sites (DMSs; p
Published: 2019
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34. Parent of origin genetic effects on methylation in humans are common and influence complex trait variation

Author: Yanni Zeng, Carmen Amador, Charley Xia, Riccardo Marioni, Duncan Sproul, Rosie M. Walker, Stewart W. Morris, Andrew Bretherick, Oriol Canela-Xandri, Thibaud S. Boutin, David W. Clark, Archie Campbell, Konrad Rawlik, Caroline Hayward, Reka Nagy, Albert Tenesa, David J. Porteous, James F. Wilson, Ian J. Deary, Kathryn L. Evans, Andrew M. McIntosh, Pau Navarro, and Chris S. Haley
Subjects: Science
Abstract: Parent-of-origin effects (POE) are observed when there are different effects from alleles inherited from the two parents on phenotypic measures. Here, Zeng et al. study POE on DNA methylation in 5,101 individuals and identify genetic variants that associate with methylation variation via POE and their potential phenotypic consequences.
Published: 2019
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35. Multi-ancestry study of blood lipid levels identifies four loci interacting with physical activity

Author: Tuomas O. Kilpeläinen, Amy R. Bentley, Raymond Noordam, Yun Ju Sung, Karen Schwander, Thomas W. Winkler, Hermina Jakupović, Daniel I. Chasman, Alisa Manning, Ioanna Ntalla, Hugues Aschard, Michael R. Brown, Lisa de las Fuentes, Nora Franceschini, Xiuqing Guo, Dina Vojinovic, Stella Aslibekyan, Mary F. Feitosa, Minjung Kho, Solomon K. Musani, Melissa Richard, Heming Wang, Zhe Wang, Traci M. Bartz, Lawrence F. Bielak, Archie Campbell, Rajkumar Dorajoo, Virginia Fisher, Fernando P. Hartwig, Andrea R. V. R. Horimoto, Changwei Li, Kurt K. Lohman, Jonathan Marten, Xueling Sim, Albert V. Smith, Salman M. Tajuddin, Maris Alver, Marzyeh Amini, Mathilde Boissel, Jin Fang Chai, Xu Chen, Jasmin Divers, Evangelos Evangelou, Chuan Gao, Mariaelisa Graff, Sarah E. Harris, Meian He, Fang-Chi Hsu, Anne U. Jackson, Jing Hua Zhao, Aldi T. Kraja, Brigitte Kühnel, Federica Laguzzi, Leo-Pekka Lyytikäinen, Ilja M. Nolte, Rainer Rauramaa, Muhammad Riaz, Antonietta Robino, Rico Rueedi, Heather M. Stringham, Fumihiko Takeuchi, Peter J. van der Most, Tibor V. Varga, Niek Verweij, Erin B. Ware, Wanqing Wen, Xiaoyin Li, Lisa R. Yanek, Najaf Amin, Donna K. Arnett, Eric Boerwinkle, Marco Brumat, Brian Cade, Mickaël Canouil, Yii-Der Ida Chen, Maria Pina Concas, John Connell, Renée de Mutsert, H. Janaka de Silva, Paul S. de Vries, Ayşe Demirkan, Jingzhong Ding, Charles B. Eaton, Jessica D. Faul, Yechiel Friedlander, Kelley P. Gabriel, Mohsen Ghanbari, Franco Giulianini, Chi Charles Gu, Dongfeng Gu, Tamara B. Harris, Jiang He, Sami Heikkinen, Chew-Kiat Heng, Steven C. Hunt, M. Arfan Ikram, Jost B. Jonas, Woon-Puay Koh, Pirjo Komulainen, Jose E. Krieger, Stephen B. Kritchevsky, Zoltán Kutalik, Johanna Kuusisto, Carl D. Langefeld, Claudia Langenberg, Lenore J. Launer, Karin Leander, Rozenn N. Lemaitre, Cora E. Lewis, Jingjing Liang, Lifelines Cohort Study, Jianjun Liu, Reedik Mägi, Ani Manichaikul, Thomas Meitinger, Andres Metspalu, Yuri Milaneschi, Karen L. Mohlke, Thomas H. Mosley, Alison D. Murray, Mike A. Nalls, Ei-Ei Khaing Nang, Christopher P. Nelson, Sotoodehnia Nona, Jill M. Norris, Chiamaka Vivian Nwuba, Jeff O’Connell, Nicholette D. Palmer, George J. Papanicolau, Raha Pazoki, Nancy L. Pedersen, Annette Peters, Patricia A. Peyser, Ozren Polasek, David J. Porteous, Alaitz Poveda, Olli T. Raitakari, Stephen S. Rich, Neil Risch, Jennifer G. Robinson, Lynda M. Rose, Igor Rudan, Pamela J. Schreiner, Robert A. Scott, Stephen S. Sidney, Mario Sims, Jennifer A. Smith, Harold Snieder, Tamar Sofer, John M. Starr, Barbara Sternfeld, Konstantin Strauch, Hua Tang, Kent D. Taylor, Michael Y. Tsai, Jaakko Tuomilehto, André G. Uitterlinden, M. Yldau van der Ende, Diana van Heemst, Trudy Voortman, Melanie Waldenberger, Patrik Wennberg, Gregory Wilson, Yong-Bing Xiang, Jie Yao, Caizheng Yu, Jian-Min Yuan, Wei Zhao, Alan B. Zonderman, Diane M. Becker, Michael Boehnke, Donald W. Bowden, Ulf de Faire, Ian J. Deary, Paul Elliott, Tõnu Esko, Barry I. Freedman, Philippe Froguel, Paolo Gasparini, Christian Gieger, Norihiro Kato, Markku Laakso, Timo A. Lakka, Terho Lehtimäki, Patrik K. E. Magnusson, Albertine J. Oldehinkel, Brenda W. J. H. Penninx, Nilesh J. Samani, Xiao-Ou Shu, Pim van der Harst, Jana V. Van Vliet-Ostaptchouk, Peter Vollenweider, Lynne E. Wagenknecht, Ya X. Wang, Nicholas J. Wareham, David R. Weir, Tangchun Wu, Wei Zheng, Xiaofeng Zhu, Michele K. Evans, Paul W. Franks, Vilmundur Gudnason, Caroline Hayward, Bernardo L. Horta, Tanika N. Kelly, Yongmei Liu, Kari E. North, Alexandre C. Pereira, Paul M. Ridker, E. Shyong Tai, Rob M. van Dam, Ervin R. Fox, Sharon L. R. Kardia, Ching-Ti Liu, Dennis O. Mook-Kanamori, Michael A. Province, Susan Redline, Cornelia M. van Duijn, Jerome I. Rotter, Charles B. Kooperberg, W. James Gauderman, Bruce M. Psaty, Kenneth Rice, Patricia B. Munroe, Myriam Fornage, L. Adrienne Cupples, Charles N. Rotimi, Alanna C. Morrison, Dabeeru C. Rao, and Ruth J. F. Loos
Subjects: Science
Abstract: GWAS have identified more than 500 genetic loci associated with blood lipid levels. Here, the authors report a genome-wide analysis of interactions between genetic markers and physical activity, and find that physical activity modifies the effects of four genetic loci on HDL or LDL cholesterol.
Published: 2019
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36. Correction: Association of low-frequency and rare coding variants with information processing speed

Author: Jan Bressler, Gail Davies, Albert V. Smith, Yasaman Saba, Joshua C. Bis, Xueqiu Jian, Caroline Hayward, Lisa Yanek, Jennifer A. Smith, Saira S. Mirza, Ruiqi Wang, Hieab H. H. Adams, Diane Becker, Eric Boerwinkle, Archie Campbell, Simon R. Cox, Gudny Eiriksdottir, Chloe Fawns-Ritchie, Rebecca F. Gottesman, Megan L. Grove, Xiuqing Guo, Edith Hofer, Sharon L. R. Kardia, Maria J. Knol, Marisa Koini, Oscar L. Lopez, Riccardo E. Marioni, Paul Nyquist, Alison Pattie, Ozren Polasek, David J. Porteous, Igor Rudan, Claudia L. Satizabal, Helena Schmidt, Reinhold Schmidt, Stephen Sidney, Jeannette Simino, Blair H. Smith, Stephen T. Turner, Sven J. van der Lee, Erin B. Ware, Rachel A. Whitmer, Kristine Yaffe, Qiong Yang, Wei Zhao, Vilmundur Gudnason, Lenore J. Launer, Annette L. Fitzpatrick, Bruce M. Psaty, Myriam Fornage, M. Arfan Ikram, Cornelia M. van Duijn, Sudha Seshadri, Thomas H. Mosley, and Ian J. Deary
Subjects: Neurosciences. Biological psychiatry. Neuropsychiatry, RC321-571
Published: 2022
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37. Using a knowledge exchange event to assess study participants’ attitudes to research in a rapidly evolving research context [version 2; peer review: 3 approved]

Author: Iona Beange, Elizabeth J. Kirkham, Sue Fletcher-Watson, Matthew H. Iveson, Stephen M. Lawrie, G. David Batty, James P. Boardman, Ian J. Deary, Corri Black, David J. Porteous, and Andrew M. McIntosh
Subjects: Medicine, Science
Abstract: Background: The UK hosts some of the world’s longest-running longitudinal cohort studies, which make repeated observations of their participants and use these data to explore health outcomes. An alternative method for data collection is record linkage; the linking together of electronic health and administrative records. Applied nationally, this could provide unrivalled opportunities to follow a large number of people in perpetuity. However, public attitudes to the use of data in research are currently unclear. Here we report on an event where we collected attitudes towards recent opportunities and controversies within health data science. Methods: The event was attended by ~250 individuals (cohort members and their guests), who had been invited through the offices of their participating cohort studies. There were a series of presentations describing key research results and the audience participated in 15 multiple-choice questions using interactive voting pads. Results: Our participants showed a high level of trust in researchers (87% scoring them 4/5 or 5/5) and doctors (81%); but less trust in commercial companies (35%). They supported the idea of researchers using information from both neonatal blood spots (Guthrie spots) (97% yes) and from electronic health records (95% yes). Our respondents were willing to wear devices like a ’Fit-bit’ (88% agreed) or take a brain scan that might predict later mental illness (73%). However, they were less willing to take a new drug for research purposes (45%). They were keen to encourage others to take part in research; whether that be offering the opportunity to pregnant mothers (97% agreed) or extending invitations to their own children and grandchildren (98%). Conclusions: Our participants were broadly supportive of research access to data, albeit less supportive when commercial interests were involved. Public engagement events that facilitate two-way interactions can influence and support future research and public engagement efforts.
Published: 2020
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38. Using a knowledge exchange event to assess study participants’ attitudes to research in a rapidly evolving research context [version 1; peer review: 3 approved]

Author: Iona Beange, Elizabeth J. Kirkham, Sue Fletcher-Watson, Matthew H. Iveson, Stephen M. Lawrie, G. David Batty, James P. Boardman, Ian J. Deary, Corri Black, David J. Porteous, and Andrew M. McIntosh
Subjects: Medicine, Science
Abstract: Background: The UK hosts some of the world’s longest-running longitudinal cohort studies, who make repeated observations of their participants and use these data to explore health outcomes. An alternative method for data collection is record linkage; the linking together of electronic health and administrative records. Applied nationally, this could provide unrivalled opportunities to follow a large number of people in perpetuity. However, public attitudes to the use of data in research are currently unclear. Here we report on an event where we collected attitudes towards recent opportunities and controversies within health data science. Methods: The event was attended by ~250 individuals (cohort members and their guests), who had been invited through the offices of their participating cohort studies. There were a series of presentations describing key research results and the audience participated in 15 multiple-choice questions using interactive voting pads. Results: Our participants showed a high level of trust in researchers (87% scoring them 4/5 or 5/5) and doctors (81%); but less trust in commercial companies (35%). They supported the idea of researchers using information from both neonatal blood spots (Guthrie spots) (97% yes) and from electronic health records (95% yes). Our respondents were willing to wear devices like a ’Fit-bit’ (78% agreed) or take a brain scan that might predict later mental illness (73%). However, they were less willing to take a new drug for research purposes (45%). They were keen to encourage others to take part in research; whether that be offering the opportunity to pregnant mothers (97% agreed) or extending invitations to their own children and grandchildren (98%). Conclusions: Our participants were broadly supportive of research access to data, albeit less supportive when commercial interests were involved. Public engagement events that facilitate two-way interactions can influence and support future research and public engagement efforts.
Published: 2020
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39. DNA methylation in APOE: The relationship with Alzheimer's and with cardiovascular health

Author: Jure Mur, Daniel L. McCartney, Rosie M. Walker, Archie Campbell, Mairead L. Bermingham, Stewart W. Morris, David J. Porteous, Andrew M. McIntosh, Ian J. Deary, Kathryn L. Evans, and Riccardo E. Marioni
Subjects: Alzheimer's disease, APOE, biomarker, cardiovascular disease, cholesterol, DNA methylation, Neurology. Diseases of the nervous system, RC346-429, Geriatrics, RC952-954.6
Abstract: Abstract Introduction Genetic variation in the apolipoprotein E (APOE) gene is associated with Alzheimer's disease (AD) and risk factors for cardiovascular disease (CVD). DNA methylationat APOE has been associated with altered cognition and AD. It is unclear if epigenetic marks could be used for predicting future disease. Methods We assessed blood‐based DNA methylation at 13 CpGs in the APOE gene in 5828 participants from the Generation Scotland (GS) cohort. Using linear mixed models regression, we examined the relationships among APOE methylation, cognition, cholesterol, the family history of AD and the risk for CVD. Results DNA methylation at two CpGs was associated with the ratio of total cholesterol and HDL cholesterol, but not with cognition, family history of AD, or the risk of CVD. Discussion APOE methylation is associated with the levels of blood cholesterol, but there is no evidence for the utility of APOE methylation as a biomarker for predicting AD or CVD.
Published: 2020
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40. Epigenome‐wide analyses identify DNA methylation signatures of dementia risk

Author: Rosie M. Walker, Mairead L. Bermingham, Kadi Vaher, Stewart W. Morris, Toni‐Kim Clarke, Andrew D. Bretherick, Yanni Zeng, Carmen Amador, Konrad Rawlik, Kalyani Pandya, Caroline Hayward, Archie Campbell, David J. Porteous, Andrew M. McIntosh, Riccardo E. Marioni, and Kathryn L. Evans
Subjects: alcohol, Alzheimer's disease, dementia, DNA methylation, genetic risk score, risk factors, Neurology. Diseases of the nervous system, RC346-429, Geriatrics, RC952-954.6
Abstract: Abstract Introduction Dementia pathogenesis begins years before clinical symptom onset, necessitating the understanding of premorbid risk mechanisms. Here we investigated potential pathogenic mechanisms by assessing DNA methylation associations with dementia risk factors in Alzheimer's disease (AD)–free participants. Methods Associations between dementia risk measures (family history, AD genetic risk score [GRS], and dementia risk scores [combining lifestyle, demographic, and genetic factors]) and whole‐blood DNA methylation were assessed in discovery and replication samples (n = ~400 to ~5000) from Generation Scotland. Results AD genetic risk and two dementia risk scores were associated with differential methylation. The GRS associated predominantly with methylation differences in cis but also identified a genomic region implicated in Parkinson disease. Loci associated with dementia risk scores were enriched for those previously associated with body mass index and alcohol consumption. Discussion Dementia risk measures show widespread association with blood‐based methylation, generating several hypotheses for assessment by future studies.
Published: 2020
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41. Epigenetic signatures of starting and stopping smokingResearch in context

Author: Daniel L. McCartney, Anna J. Stevenson, Robert F. Hillary, Rosie M. Walker, Mairead L. Bermingham, Stewart W. Morris, Toni-Kim Clarke, Archie Campbell, Alison D. Murray, Heather C. Whalley, David J. Porteous, Peter M. Visscher, Andrew M. McIntosh, Kathryn L. Evans, Ian J. Deary, and Riccardo E. Marioni
Subjects: Medicine, Medicine (General), R5-920
Abstract: Background: Multiple studies have made robust associations between differential DNA methylation and exposure to cigarette smoke. But whether a DNA methylation phenotype is established immediately upon exposure, or only after prolonged exposure is less well–established. Here, we assess DNA methylation patterns from peripheral blood samples in current smokers in response to dose and duration of exposure, along with the effects of smoking cessation on DNA methylation in former smokers. Methods: Dimensionality reduction was applied to DNA methylation data at 90 previously identified smoking–associated CpG sites for over 4900 individuals in the Generation Scotland cohort. K–means clustering was performed to identify clusters associated with current and never smoker status based on these methylation patterns. Cluster assignments were assessed with respect to duration of exposure in current smokers (years as a smoker), time since smoking cessation in former smokers (years), and dose (cigarettes per day). Findings: Two clusters were specified, corresponding to never smokers (97·5% of whom were assigned to Cluster 1) and current smokers (81·1% of whom were assigned to Cluster 2). The exposure time point from which >50% of current smokers were assigned to the smoker–enriched cluster varied between 5 and 9 years in heavier smokers and between 15 and 19 years in lighter smokers. Low–dose former smokers were more likely to be assigned to the never smoker–enriched cluster in the first year following cessation. In contrast, a period of at least two years was required before the majority of former high–dose smokers were assigned to the never smoker–enriched cluster. Interpretation: Our findings suggest that smoking–associated DNA methylation changes are a result of prolonged exposure to cigarette smoke, and can be reversed following cessation. The length of time in which these signatures are established and recovered is dose dependent. Should DNA methylation–based signatures of smoking status be predictive of smoking–related health outcomes, our findings may provide an additional criterion on which to stratify risk. Keywords: DNA methylation, Epigenetics, Smoking, Epidemiology
Published: 2018
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42. Epigenetic prediction of complex traits and death

Author: Daniel L. McCartney, Robert F. Hillary, Anna J. Stevenson, Stuart J. Ritchie, Rosie M. Walker, Qian Zhang, Stewart W. Morris, Mairead L. Bermingham, Archie Campbell, Alison D. Murray, Heather C. Whalley, Catharine R. Gale, David J. Porteous, Chris S. Haley, Allan F. McRae, Naomi R. Wray, Peter M. Visscher, Andrew M. McIntosh, Kathryn L. Evans, Ian J. Deary, and Riccardo E. Marioni
Subjects: DNA methylation, Polygenic scores, Prediction, Ageing, Mortality, Biology (General), QH301-705.5, Genetics, QH426-470
Abstract: Abstract Background Genome-wide DNA methylation (DNAm) profiling has allowed for the development of molecular predictors for a multitude of traits and diseases. Such predictors may be more accurate than the self-reported phenotypes and could have clinical applications. Results Here, penalized regression models are used to develop DNAm predictors for ten modifiable health and lifestyle factors in a cohort of 5087 individuals. Using an independent test cohort comprising 895 individuals, the proportion of phenotypic variance explained in each trait is examined for DNAm-based and genetic predictors. Receiver operator characteristic curves are generated to investigate the predictive performance of DNAm-based predictors, using dichotomized phenotypes. The relationship between DNAm scores and all-cause mortality (n = 212 events) is assessed via Cox proportional hazards models. DNAm predictors for smoking, alcohol, education, and waist-to-hip ratio are shown to predict mortality in multivariate models. The predictors show moderate discrimination of obesity, alcohol consumption, and HDL cholesterol. There is excellent discrimination of current smoking status, poorer discrimination of college-educated individuals and those with high total cholesterol, LDL with remnant cholesterol, and total:HDL cholesterol ratios. Conclusions DNAm predictors correlate with lifestyle factors that are associated with health and mortality. They may supplement DNAm-based predictors of age to identify the lifestyle profiles of individuals and predict disease risk.
Published: 2018
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43. Study of 300,486 individuals identifies 148 independent genetic loci influencing general cognitive function

Author: Gail Davies, Max Lam, Sarah E. Harris, Joey W. Trampush, Michelle Luciano, W. David Hill, Saskia P. Hagenaars, Stuart J. Ritchie, Riccardo E. Marioni, Chloe Fawns-Ritchie, David C. M. Liewald, Judith A. Okely, Ari V. Ahola-Olli, Catriona L. K. Barnes, Lars Bertram, Joshua C. Bis, Katherine E. Burdick, Andrea Christoforou, Pamela DeRosse, Srdjan Djurovic, Thomas Espeseth, Stella Giakoumaki, Sudheer Giddaluru, Daniel E. Gustavson, Caroline Hayward, Edith Hofer, M. Arfan Ikram, Robert Karlsson, Emma Knowles, Jari Lahti, Markus Leber, Shuo Li, Karen A. Mather, Ingrid Melle, Derek Morris, Christopher Oldmeadow, Teemu Palviainen, Antony Payton, Raha Pazoki, Katja Petrovic, Chandra A. Reynolds, Muralidharan Sargurupremraj, Markus Scholz, Jennifer A. Smith, Albert V. Smith, Natalie Terzikhan, Anbupalam Thalamuthu, Stella Trompet, Sven J. van der Lee, Erin B. Ware, B. Gwen Windham, Margaret J. Wright, Jingyun Yang, Jin Yu, David Ames, Najaf Amin, Philippe Amouyel, Ole A. Andreassen, Nicola J. Armstrong, Amelia A. Assareh, John R. Attia, Deborah Attix, Dimitrios Avramopoulos, David A. Bennett, Anne C. Böhmer, Patricia A. Boyle, Henry Brodaty, Harry Campbell, Tyrone D. Cannon, Elizabeth T. Cirulli, Eliza Congdon, Emily Drabant Conley, Janie Corley, Simon R. Cox, Anders M. Dale, Abbas Dehghan, Danielle Dick, Dwight Dickinson, Johan G. Eriksson, Evangelos Evangelou, Jessica D. Faul, Ian Ford, Nelson A. Freimer, He Gao, Ina Giegling, Nathan A. Gillespie, Scott D. Gordon, Rebecca F. Gottesman, Michael E. Griswold, Vilmundur Gudnason, Tamara B. Harris, Annette M. Hartmann, Alex Hatzimanolis, Gerardo Heiss, Elizabeth G. Holliday, Peter K. Joshi, Mika Kähönen, Sharon L. R. Kardia, Ida Karlsson, Luca Kleineidam, David S. Knopman, Nicole A. Kochan, Bettina Konte, John B. Kwok, Stephanie Le Hellard, Teresa Lee, Terho Lehtimäki, Shu-Chen Li, Christina M. Lill, Tian Liu, Marisa Koini, Edythe London, Will T. Longstreth, Oscar L. Lopez, Anu Loukola, Tobias Luck, Astri J. Lundervold, Anders Lundquist, Leo-Pekka Lyytikäinen, Nicholas G. Martin, Grant W. Montgomery, Alison D. Murray, Anna C. Need, Raymond Noordam, Lars Nyberg, William Ollier, Goran Papenberg, Alison Pattie, Ozren Polasek, Russell A. Poldrack, Bruce M. Psaty, Simone Reppermund, Steffi G. Riedel-Heller, Richard J. Rose, Jerome I. Rotter, Panos Roussos, Suvi P. Rovio, Yasaman Saba, Fred W. Sabb, Perminder S. Sachdev, Claudia L. Satizabal, Matthias Schmid, Rodney J. Scott, Matthew A. Scult, Jeannette Simino, P. Eline Slagboom, Nikolaos Smyrnis, Aïcha Soumaré, Nikos C. Stefanis, David J. Stott, Richard E. Straub, Kjetil Sundet, Adele M. Taylor, Kent D. Taylor, Ioanna Tzoulaki, Christophe Tzourio, André Uitterlinden, Veronique Vitart, Aristotle N. Voineskos, Jaakko Kaprio, Michael Wagner, Holger Wagner, Leonie Weinhold, K. Hoyan Wen, Elisabeth Widen, Qiong Yang, Wei Zhao, Hieab H. H. Adams, Dan E. Arking, Robert M. Bilder, Panos Bitsios, Eric Boerwinkle, Ornit Chiba-Falek, Aiden Corvin, Philip L. De Jager, Stéphanie Debette, Gary Donohoe, Paul Elliott, Annette L. Fitzpatrick, Michael Gill, David C. Glahn, Sara Hägg, Narelle K. Hansell, Ahmad R. Hariri, M. Kamran Ikram, J. Wouter Jukema, Eero Vuoksimaa, Matthew C. Keller, William S. Kremen, Lenore Launer, Ulman Lindenberger, Aarno Palotie, Nancy L. Pedersen, Neil Pendleton, David J. Porteous, Katri Räikkönen, Olli T. Raitakari, Alfredo Ramirez, Ivar Reinvang, Igor Rudan, Dan Rujescu, Reinhold Schmidt, Helena Schmidt, Peter W. Schofield, Peter R. Schofield, John M. Starr, Vidar M. Steen, Julian N. Trollor, Steven T. Turner, Cornelia M. Van Duijn, Arno Villringer, Daniel R. Weinberger, David R. Weir, James F. Wilson, Anil Malhotra, Andrew M. McIntosh, Catharine R. Gale, Sudha Seshadri, Thomas H. Mosley, Jan Bressler, Todd Lencz, and Ian J. Deary
Subjects: Science
Abstract: Cognitive function is associated with health and important life outcomes. Here, the authors perform a genome-wide association study for general cognitive function in 300,486 individuals and identify genetic loci that implicate neural and cell developmental pathways in this trait.
Published: 2018
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44. Investigating the relationship between DNA methylation age acceleration and risk factors for Alzheimer's disease

Author: Daniel L. McCartney, Anna J. Stevenson, Rosie M. Walker, Jude Gibson, Stewart W. Morris, Archie Campbell, Alison D. Murray, Heather C. Whalley, David J. Porteous, Andrew M. McIntosh, Kathryn L. Evans, Ian J. Deary, and Riccardo E. Marioni
Subjects: DNA methylation, Epigenetic clock, Alzheimer's disease, Genetics, Generation Scotland, Neurology. Diseases of the nervous system, RC346-429, Geriatrics, RC952-954.6
Abstract: Abstract Introduction The “epigenetic clock” is a DNA methylation–based estimate of biological age and is correlated with chronological age—the greatest risk factor for Alzheimer's disease (AD). Genetic and environmental risk factors exist for AD, several of which are potentially modifiable. In this study, we assess the relationship between the epigenetic clock and AD risk factors. Methods Multilevel models were used to assess the relationship between age acceleration (the residual of biological age regressed onto chronological age) and AD risk factors relating to cognitive reserve, lifestyle, disease, and genetics in the Generation Scotland study (n = 5100). Results We report significant associations between age acceleration and body mass index, total cholesterol to high‐density lipoprotein cholesterol ratios, socioeconomic status, high blood pressure, and smoking behavior (Bonferroni‐adjusted P
Published: 2018
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45. Genome-wide meta-analysis of 241,258 adults accounting for smoking behaviour identifies novel loci for obesity traits

Author: Anne E. Justice, Thomas W. Winkler, Mary F. Feitosa, Misa Graff, Virginia A. Fisher, Kristin Young, Llilda Barata, Xuan Deng, Jacek Czajkowski, David Hadley, Julius S. Ngwa, Tarunveer S. Ahluwalia, Audrey Y. Chu, Nancy L. Heard-Costa, Elise Lim, Jeremiah Perez, John D. Eicher, Zoltán Kutalik, Luting Xue, Anubha Mahajan, Frida Renström, Joseph Wu, Qibin Qi, Shafqat Ahmad, Tamuno Alfred, Najaf Amin, Lawrence F. Bielak, Amelie Bonnefond, Jennifer Bragg, Gemma Cadby, Martina Chittani, Scott Coggeshall, Tanguy Corre, Nese Direk, Joel Eriksson, Krista Fischer, Mathias Gorski, Marie Neergaard Harder, Momoko Horikoshi, Tao Huang, Jennifer E. Huffman, Anne U. Jackson, Johanne Marie Justesen, Stavroula Kanoni, Leena Kinnunen, Marcus E. Kleber, Pirjo Komulainen, Meena Kumari, Unhee Lim, Jian'an Luan, Leo-Pekka Lyytikäinen, Massimo Mangino, Ani Manichaikul, Jonathan Marten, Rita P. S. Middelberg, Martina Müller-Nurasyid, Pau Navarro, Louis Pérusse, Natalia Pervjakova, Cinzia Sarti, Albert Vernon Smith, Jennifer A. Smith, Alena Stančáková, Rona J. Strawbridge, Heather M. Stringham, Yun Ju Sung, Toshiko Tanaka, Alexander Teumer, Stella Trompet, Sander W. van der Laan, Peter J. van der Most, Jana V. Van Vliet-Ostaptchouk, Sailaja L. Vedantam, Niek Verweij, Jacqueline M. Vink, Veronique Vitart, Ying Wu, Loic Yengo, Weihua Zhang, Jing Hua Zhao, Martina E. Zimmermann, Niha Zubair, Gonçalo R. Abecasis, Linda S. Adair, Saima Afaq, Uzma Afzal, Stephan J. L. Bakker, Traci M. Bartz, John Beilby, Richard N. Bergman, Sven Bergmann, Reiner Biffar, John Blangero, Eric Boerwinkle, Lori L. Bonnycastle, Erwin Bottinger, Daniele Braga, Brendan M. Buckley, Steve Buyske, Harry Campbell, John C. Chambers, Francis S. Collins, Joanne E. Curran, Gert J. de Borst, Anton J. M. de Craen, Eco J. C. de Geus, George Dedoussis, Graciela E. Delgado, Hester M. den Ruijter, Gudny Eiriksdottir, Anna L. Eriksson, Tõnu Esko, Jessica D. Faul, Ian Ford, Terrence Forrester, Karl Gertow, Bruna Gigante, Nicola Glorioso, Jian Gong, Harald Grallert, Tanja B. Grammer, Niels Grarup, Saskia Haitjema, Göran Hallmans, Anders Hamsten, Torben Hansen, Tamara B. Harris, Catharina A. Hartman, Maija Hassinen, Nicholas D. Hastie, Andrew C. Heath, Dena Hernandez, Lucia Hindorff, Lynne J. Hocking, Mette Hollensted, Oddgeir L. Holmen, Georg Homuth, Jouke Jan Hottenga, Jie Huang, Joseph Hung, Nina Hutri-Kähönen, Erik Ingelsson, Alan L. James, John-Olov Jansson, Marjo-Riitta Jarvelin, Min A. Jhun, Marit E. Jørgensen, Markus Juonala, Mika Kähönen, Magnus Karlsson, Heikki A. Koistinen, Ivana Kolcic, Genovefa Kolovou, Charles Kooperberg, Bernhard K. Krämer, Johanna Kuusisto, Kirsti Kvaløy, Timo A. Lakka, Claudia Langenberg, Lenore J. Launer, Karin Leander, Nanette R. Lee, Lars Lind, Cecilia M. Lindgren, Allan Linneberg, Stephane Lobbens, Marie Loh, Mattias Lorentzon, Robert Luben, Gitta Lubke, Anja Ludolph-Donislawski, Sara Lupoli, Pamela A. F. Madden, Reija Männikkö, Pedro Marques-Vidal, Nicholas G. Martin, Colin A. McKenzie, Barbara McKnight, Dan Mellström, Cristina Menni, Grant W. Montgomery, AW (Bill) Musk, Narisu Narisu, Matthias Nauck, Ilja M. Nolte, Albertine J. Oldehinkel, Matthias Olden, Ken K. Ong, Sandosh Padmanabhan, Patricia A. Peyser, Charlotta Pisinger, David J. Porteous, Olli T. Raitakari, Tuomo Rankinen, D. C. Rao, Laura J. Rasmussen-Torvik, Rajesh Rawal, Treva Rice, Paul M. Ridker, Lynda M. Rose, Stephanie A. Bien, Igor Rudan, Serena Sanna, Mark A. Sarzynski, Naveed Sattar, Kai Savonen, David Schlessinger, Salome Scholtens, Claudia Schurmann, Robert A. Scott, Bengt Sennblad, Marten A. Siemelink, Günther Silbernagel, P Eline Slagboom, Harold Snieder, Jan A. Staessen, David J. Stott, Morris A. Swertz, Amy J. Swift, Kent D. Taylor, Bamidele O. Tayo, Barbara Thorand, Dorothee Thuillier, Jaakko Tuomilehto, Andre G. Uitterlinden, Liesbeth Vandenput, Marie-Claude Vohl, Henry Völzke, Judith M. Vonk, Gérard Waeber, Melanie Waldenberger, R. G. J. Westendorp, Sarah Wild, Gonneke Willemsen, Bruce H. R. Wolffenbuttel, Andrew Wong, Alan F. Wright, Wei Zhao, M Carola Zillikens, Damiano Baldassarre, Beverley Balkau, Stefania Bandinelli, Carsten A. Böger, Dorret I. Boomsma, Claude Bouchard, Marcel Bruinenberg, Daniel I. Chasman, Yii-DerIda Chen, Peter S. Chines, Richard S. Cooper, Francesco Cucca, Daniele Cusi, Ulf de Faire, Luigi Ferrucci, Paul W. Franks, Philippe Froguel, Penny Gordon-Larsen, Hans- Jörgen Grabe, Vilmundur Gudnason, Christopher A. Haiman, Caroline Hayward, Kristian Hveem, Andrew D. Johnson, J Wouter Jukema, Sharon L. R. Kardia, Mika Kivimaki, Jaspal S. Kooner, Diana Kuh, Markku Laakso, Terho Lehtimäki, Loic Le Marchand, Winfried März, Mark I. McCarthy, Andres Metspalu, Andrew P. Morris, Claes Ohlsson, Lyle J. Palmer, Gerard Pasterkamp, Oluf Pedersen, Annette Peters, Ulrike Peters, Ozren Polasek, Bruce M. Psaty, Lu Qi, Rainer Rauramaa, Blair H. Smith, Thorkild I. A. Sørensen, Konstantin Strauch, Henning Tiemeier, Elena Tremoli, Pim van der Harst, Henrik Vestergaard, Peter Vollenweider, Nicholas J. Wareham, David R. Weir, John B. Whitfield, James F. Wilson, Jessica Tyrrell, Timothy M. Frayling, Inês Barroso, Michael Boehnke, Panagiotis Deloukas, Caroline S. Fox, Joel N. Hirschhorn, David J. Hunter, Tim D. Spector, David P. Strachan, Cornelia M. van Duijn, Iris M. Heid, Karen L. Mohlke, Jonathan Marchini, Ruth J. F. Loos, Tuomas O. Kilpeläinen, Ching-Ti Liu, Ingrid B. Borecki, Kari E. North, and L Adrienne Cupples
Subjects: Science
Abstract: Genome-wide association studies (GWAS) have become a key tool to discover genetic markers for complex traits; however, environmental factors that interact with genes are rarely considered. Here, the authors conduct a GWAS of obesity traits, and find that smoking may alter genetic susceptibilities.
Published: 2017
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46. Assessment of dried blood spots for DNA methylation profiling [version 1; peer review: 2 approved]

Author: Rosie M. Walker, Louise MacGillivray, Sarah McCafferty, Nicola Wrobel, Lee Murphy, Shona M. Kerr, Stewart W. Morris, Archie Campbell, Andrew M. McIntosh, David J. Porteous, and Kathryn L. Evans
Subjects: Medicine, Science
Abstract: Background: DNA methylation reflects health-related environmental exposures and genetic risk, providing insights into aetiological mechanisms and potentially predicting disease onset, progression and treatment response. An increasingly recognised need for large-scale, longitudinally-profiled samples collected world-wide has made the development of efficient and straightforward sample collection and storage procedures a pressing issue. An alternative to the low-temperature storage of EDTA tubes of venous blood samples, which are frequently the source of the DNA used in such studies, is to collect and store at room temperature blood samples using purpose built filter paper, such as Whatman FTA® cards. Our goal was to determine whether DNA stored in this manner can be used to generate DNA methylation profiles comparable to those generated using blood samples frozen in EDTA tubes. Methods: DNA methylation profiles were obtained from matched EDTA tube and Whatman FTA® card whole-blood samples from 62 Generation Scotland: Scottish Family Health Study participants using the Infinium HumanMethylation450 BeadChip. Multiple quality control procedures were implemented, the relationship between the two sample types assessed, and epigenome-wide association studies (EWASs) performed for smoking status, age and the interaction between these variables and sample storage method. Results: Dried blood spot (DBS) DNA methylation profiles were of good quality and DNA methylation profiles from matched DBS and EDTA tube samples were highly correlated (mean r = 0.991) and could distinguish between participants. EWASs replicated established associations for smoking and age, with no evidence for moderation by storage method. Conclusions: Our results support the use of Whatman FTA® cards for collecting and storing blood samples for DNA methylation profiling. This approach is likely to be particularly beneficial for large-scale studies and those carried out in areas where freezer access is limited. Furthermore, our results will inform consideration of the use of newborn heel prick DBSs for research use.
Published: 2019
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47. Genetic and environmental determinants of stressful life events and their overlap with depression and neuroticism [version 2; referees: 1 approved, 2 approved with reservations]

Author: Toni-Kim Clarke, Yanni Zeng, Lauren Navrady, Charley Xia, Chris Haley, Archie Campbell, Pau Navarro, Carmen Amador, Mark J. Adams, David M. Howard, Aleix Soler, Caroline Hayward, Pippa A. Thomson, Blair H. Smith, Sandosh Padmanabhan, Lynne J. Hocking, Lynsey S. Hall, David J. Porteous, Major Depressive Disorder Working Group of the Psychiatric Genomics Consortium, Ian J. Deary, and Andrew M. McIntosh
Subjects: Medicine, Science
Abstract: Background: Stressful life events (SLEs) and neuroticism are risk factors for major depressive disorder (MDD). However, SLEs and neuroticism are heritable and genetic risk for SLEs is associated with risk for MDD. We sought to investigate the genetic and environmental contributions to SLEs in a family-based sample, and quantify genetic overlap with MDD and neuroticism. Methods: A subset of Generation Scotland: the Scottish Family Health Study (GS), consisting of 9618 individuals with information on MDD, past 6 month SLEs, neuroticism and genome-wide genotype data was used in the present study. We estimated the heritability of SLEs using GCTA software. The environmental contribution to SLEs was assessed by modelling familial, couple and sibling components. Using polygenic risk scores (PRS) and LD score regression (LDSC) we analysed the genetic overlap between MDD, neuroticism and SLEs. Results: Past 6-month life events were positively associated with lifetime MDD status (β=0.21, r2=1.1%, p=2.5 x 10-25) and neuroticism (β =0.13, r2=1.9%, p=1.04 x 10-37) at the phenotypic level. Common SNPs explained 8% of the phenotypic variance in personal life events (those directly affecting the individual) (S.E.=0.03, p= 9 x 10-4). A significant effect of couple environment was detected accounting for 13% (S.E.=0.03, p=0.016) of the phenotypic variation in SLEs. PRS analyses found that reporting more SLEs was associated with a higher polygenic risk for MDD (β =0.05, r2=0.3%, p=3 x 10-5), but not a higher polygenic risk for neuroticism. LDSC showed a significant genetic correlation between SLEs and both MDD (rG=0.33, S.E.=0.08 ) and neuroticism (rG=0.15, S.E.=0.07). Conclusions: These findings suggest that SLEs should not be regarded solely as environmental risk factors for MDD as they are partially heritable and this heritability is shared with risk for MDD and neuroticism. Further work is needed to determine the causal direction and source of these associations.
Published: 2019
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48. Author Correction: Bayesian reassessment of the epigenetic architecture of complex traits

Author: Daniel Trejo Banos, Daniel L. McCartney, Marion Patxot, Lucas Anchieri, Thomas Battram, Colette Christiansen, Ricardo Costeira, Rosie M. Walker, Stewart W. Morris, Archie Campbell, Qian Zhang, David J. Porteous, Allan F. McRae, Naomi R. Wray, Peter M. Visscher, Chris S. Haley, Kathryn L. Evans, Ian J. Deary, Andrew M. McIntosh, Gibran Hemani, Jordana T. Bell, Riccardo E. Marioni, and Matthew R. Robinson
Subjects: Science
Abstract: An amendment to this paper has been published and can be accessed via a link at the top of the paper.
Published: 2020
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49. Meta-analysis of exome array data identifies six novel genetic loci for lung function [version 3; referees: 2 approved]

Author: Victoria E. Jackson, Jeanne C. Latourelle, Louise V. Wain, Albert V. Smith, Megan L. Grove, Traci M. Bartz, Ma'en Obeidat, Michael A. Province, Wei Gao, Beenish Qaiser, David J. Porteous, Patricia A. Cassano, Tarunveer S. Ahluwalia, Niels Grarup, Jin Li, Elisabeth Altmaier, Jonathan Marten, Sarah E. Harris, Ani Manichaikul, Tess D. Pottinger, Ruifang Li-Gao, Allan Lind-Thomsen, Anubha Mahajan, Lies Lahousse, Medea Imboden, Alexander Teumer, Bram Prins, Leo-Pekka Lyytikäinen, Gudny Eiriksdottir, Nora Franceschini, Colleen M. Sitlani, Jennifer A. Brody, Yohan Bossé, Wim Timens, Aldi Kraja, Anu Loukola, Wenbo Tang, Yongmei Liu, Jette Bork-Jensen, Johanne M. Justesen, Allan Linneberg, Leslie A. Lange, Rajesh Rawal, Stefan Karrasch, Jennifer E. Huffman, Blair H. Smith, Gail Davies, Kristin M. Burkart, Josyf C. Mychaleckyj, Tobias N. Bonten, Stefan Enroth, Lars Lind, Guy G. Brusselle, Ashish Kumar, Beate Stubbe, Understanding Society Scientific Group, Mika Kähönen, Annah B. Wyss, Bruce M. Psaty, Susan R. Heckbert, Ke Hao, Taina Rantanen, Stephen B. Kritchevsky, Kurt Lohman, Tea Skaaby, Charlotta Pisinger, Torben Hansen, Holger Schulz, Ozren Polasek, Archie Campbell, John M. Starr, Stephen S. Rich, Dennis O. Mook-Kanamori, Åsa Johansson, Erik Ingelsson, André G. Uitterlinden, Stefan Weiss, Olli T. Raitakari, Vilmundur Gudnason, Kari E. North, Sina A. Gharib, Don D. Sin, Kent D. Taylor, George T. O'Connor, Jaakko Kaprio, Tamara B. Harris, Oluf Pederson, Henrik Vestergaard, James G. Wilson, Konstantin Strauch, Caroline Hayward, Shona Kerr, Ian J. Deary, R. Graham Barr, Renée de Mutsert, Ulf Gyllensten, Andrew P. Morris, M. Arfan Ikram, Nicole Probst-Hensch, Sven Gläser, Eleftheria Zeggini, Terho Lehtimäki, David P. Strachan, Josée Dupuis, Alanna C. Morrison, Ian P. Hall, Martin D. Tobin, and Stephanie J. London
Subjects: Genomics, Medicine, Science
Abstract: Background: Over 90 regions of the genome have been associated with lung function to date, many of which have also been implicated in chronic obstructive pulmonary disease. Methods: We carried out meta-analyses of exome array data and three lung function measures: forced expiratory volume in one second (FEV1), forced vital capacity (FVC) and the ratio of FEV1 to FVC (FEV1/FVC). These analyses by the SpiroMeta and CHARGE consortia included 60,749 individuals of European ancestry from 23 studies, and 7,721 individuals of African Ancestry from 5 studies in the discovery stage, with follow-up in up to 111,556 independent individuals. Results: We identified significant (P
Published: 2018
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50. Meta-analysis of exome array data identifies six novel genetic loci for lung function [version 2; referees: 2 approved]

Author: Victoria E. Jackson, Jeanne C. Latourelle, Louise V. Wain, Albert V. Smith, Megan L. Grove, Traci M. Bartz, Ma'en Obeidat, Michael A. Province, Wei Gao, Beenish Qaiser, David J. Porteous, Patricia A. Cassano, Tarunveer S. Ahluwalia, Niels Grarup, Jin Li, Elisabeth Altmaier, Jonathan Marten, Sarah E. Harris, Ani Manichaikul, Tess D. Pottinger, Ruifang Li-Gao, Allan Lind-Thomsen, Anubha Mahajan, Lies Lahousse, Medea Imboden, Alexander Teumer, Bram Prins, Leo-Pekka Lyytikäinen, Gudny Eiriksdottir, Nora Franceschini, Colleen M. Sitlani, Jennifer A. Brody, Yohan Bossé, Wim Timens, Aldi Kraja, Anu Loukola, Wenbo Tang, Yongmei Liu, Jette Bork-Jensen, Johanne M. Justesen, Allan Linneberg, Leslie A. Lange, Rajesh Rawal, Stefan Karrasch, Jennifer E. Huffman, Blair H. Smith, Gail Davies, Kristin M. Burkart, Josyf C. Mychaleckyj, Tobias N. Bonten, Stefan Enroth, Lars Lind, Guy G. Brusselle, Ashish Kumar, Beate Stubbe, Understanding Society Scientific Group, Mika Kähönen, Annah B. Wyss, Bruce M. Psaty, Susan R. Heckbert, Ke Hao, Taina Rantanen, Stephen B. Kritchevsky, Kurt Lohman, Tea Skaaby, Charlotta Pisinger, Torben Hansen, Holger Schulz, Ozren Polasek, Archie Campbell, John M. Starr, Stephen S. Rich, Dennis O. Mook-Kanamori, Åsa Johansson, Erik Ingelsson, André G. Uitterlinden, Stefan Weiss, Olli T. Raitakari, Vilmundur Gudnason, Kari E. North, Sina A. Gharib, Don D. Sin, Kent D. Taylor, George T. O'Connor, Jaakko Kaprio, Tamara B. Harris, Oluf Pederson, Henrik Vestergaard, James G. Wilson, Konstantin Strauch, Caroline Hayward, Shona Kerr, Ian J. Deary, R. Graham Barr, Renée de Mutsert, Ulf Gyllensten, Andrew P. Morris, M. Arfan Ikram, Nicole Probst-Hensch, Sven Gläser, Eleftheria Zeggini, Terho Lehtimäki, David P. Strachan, Josée Dupuis, Alanna C. Morrison, Ian P. Hall, Martin D. Tobin, and Stephanie J. London
Subjects: Genomics, Medicine, Science
Abstract: Background: Over 90 regions of the genome have been associated with lung function to date, many of which have also been implicated in chronic obstructive pulmonary disease. Methods: We carried out meta-analyses of exome array data and three lung function measures: forced expiratory volume in one second (FEV1), forced vital capacity (FVC) and the ratio of FEV1 to FVC (FEV1/FVC). These analyses by the SpiroMeta and CHARGE consortia included 60,749 individuals of European ancestry from 23 studies, and 7,721 individuals of African Ancestry from 5 studies in the discovery stage, with follow-up in up to 111,556 independent individuals. Results: We identified significant (P
Published: 2018
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