Professor Inga Prokopenko


Professor e-One Health and Head of Statistical Multi-Omics

Supervision

Postgraduate research supervision

Publications

Jared G Maina, Zhanna Balkhiyarova, Arie Nouwen, Igor Pupko, Anna Ulrich, Mathilde Boissel, Amélie Bonnefond, Philippe Froguel, Amna Khamis, Inga Prokopenko, Marika Kaakinen (2023)Bidirectional Mendelian Randomization and Multiphenotype GWAS Show Causality and Shared Pathophysiology Between Depression and Type 2 Diabetes, In: Diabetes care46(9)pp. 1707-1714

Depression is a common comorbidity of type 2 diabetes. We assessed the causal relationships and shared genetics between them. We applied two-sample, bidirectional Mendelian randomization (MR) to assess causality between type 2 diabetes and depression. We investigated potential mediation using two-step MR. To identify shared genetics, we performed 1) genome-wide association studies (GWAS) separately and 2) multiphenotype GWAS (MP-GWAS) of type 2 diabetes (19,344 case subjects, 463,641 control subjects) and depression using major depressive disorder (MDD) (5,262 case subjects, 86,275 control subjects) and self-reported depressive symptoms (n = 153,079) in the UK Biobank. We analyzed expression quantitative trait loci (eQTL) data from public databases to identify target genes in relevant tissues. MR demonstrated a significant causal effect of depression on type 2 diabetes (odds ratio 1.26 [95% CI 1.11-1.44], P = 5.46 × 10-4) but not in the reverse direction. Mediation analysis indicated that 36.5% (12.4-57.6%, P = 0.0499) of the effect from depression on type 2 diabetes was mediated by BMI. GWAS of type 2 diabetes and depressive symptoms did not identify shared loci. MP-GWAS identified seven shared loci mapped to TCF7L2, CDKAL1, IGF2BP2, SPRY2, CCND2-AS1, IRS1, CDKN2B-AS1. MDD has not brought any significant association in either GWAS or MP-GWAS. Most MP-GWAS loci had an eQTL, including single nucleotide polymorphisms implicating the cell cycle gene CCND2 in pancreatic islets and brain and the insulin signaling gene IRS1 in adipose tissue, suggesting a multitissue and pleiotropic underlying mechanism. Our results highlight the importance to prevent type 2 diabetes at the onset of depressive symptoms and the need to maintain a healthy weight in the context of its effect on depression and type 2 diabetes comorbidity.

James E D Thaventhiran, Hana Lango Allen, Oliver S Burren, William Rae, Daniel Greene, Emily Staples, Zinan Zhang, James H R Farmery, Ilenia Simeoni, Elizabeth Rivers, Jesmeen Maimaris, Christopher J Penkett, Jonathan Stephens, Sri V V Deevi, Alba Sanchis-Juan, Nicholas S Gleadall, Moira J Thomas, Ravishankar B Sargur, Pavels Gordins, Helen E Baxendale, Matthew Brown, Paul Tuijnenburg, Austen Worth, Steven Hanson, Rachel J Linger, Matthew S Buckland, Paula J Rayner-Matthews, Kimberly C Gilmour, Crina Samarghitean, Suranjith L Seneviratne, David M Sansom, Andy G Lynch, Karyn Megy, Eva Ellinghaus, David Ellinghaus, Silje F Jorgensen, Tom H Karlsen, Kathleen E Stirrups, Antony J Cutler, Dinakantha S Kumararatne, Anita Chandra, J David M Edgar, Archana Herwadkar, Nichola Cooper, Sofia Grigoriadou, Aarnoud P Huissoon, Sarah Goddard, Stephen Jolles, Catharina Schuetz, Felix Boschann, Paul A Lyons, Matthew E Hurles, Sinisa Savic, Siobhan O Burns, Taco W Kuijpers, Ernest Turro, Willem H Ouwehand, Adrian J Thrasher, Kenneth G C Smith, Inga Prokopenko (2020)Whole-genome sequencing of a sporadic primary immunodeficiency cohort, In: Nature (London)583(7814)pp. 90-95

Primary immunodeficiency (PID) is characterized by recurrent and often life-threatening infections, autoimmunity and cancer, and it poses major diagnostic and therapeutic challenges. Although the most severe forms of PID are identified in early childhood, most patients present in adulthood, typically with no apparent family history and a variable clinical phenotype of widespread immune dysregulation: about 25% of patients have autoimmune disease, allergy is prevalent and up to 10% develop lymphoid malignancies . Consequently, in sporadic (or non-familial) PID genetic diagnosis is difficult and the role of genetics is not well defined. Here we address these challenges by performing whole-genome sequencing in a large PID cohort of 1,318 participants. An analysis of the coding regions of the genome in 886 index cases of PID found that disease-causing mutations in known genes that are implicated in monogenic PID occurred in 10.3% of these patients, and a Bayesian approach (BeviMed ) identified multiple new candidate PID-associated genes, including IVNS1ABP. We also examined the noncoding genome, and found deletions in regulatory regions that contribute to disease causation. In addition, we used a genome-wide association study to identify loci that are associated with PID, and found evidence for the colocalization of-and interplay between-novel high-penetrance monogenic variants and common variants (at the PTPN2 and SOCS1 loci). This begins to explain the contribution of common variants to the variable penetrance and phenotypic complexity that are observed in PID. Thus, using a cohort-based whole-genome-sequencing approach in the diagnosis of PID can increase diagnostic yield and further our understanding of the key pathways that influence immune responsiveness in humans.

Vasiliki Lagou, Longda Jiang, Anna Ulrich, Liudmila Zudina, Ayse Demirkan, Karla Sofia Gutiérrez González, Marika Kaakinen, Zhanna Balkhiiarova, Inga Prokopenko, Alessia Faggian, Jared G. Maina, Shiqian Chen, Petar V. Todorov, Sodbo Sharapov, Alessia David, Letizia Marullo, Reedik Magi, Gudmar Thorleifsson, He Gao, Roxana-Maria Rujan, Emma Ahlqvist, Evangelos Evangelou, Beben Benyamin, Robert A Scott, Aaron Isaacs, Jing Hua Zhao, Sara M. Willems, Toby Johnson, Christian Gieger, Harald Grallert, Christa Meisinger, Martina Mueller-Nurasyid, Rona J Strawbridge, Anuj Goel, Denis Rybin, Eva Albrecht, Anne U Jackson, Heather M Stringham, Ivan R., Jr Correa, Eric Farber-Eger, Valgerdur Steinthorsdottir, Andre G. Uitterlinden, Patricia B. Munroe, Morris J. Brown, Julian Schmidberger, Oddgeir Holmen, Barbara Thorand, Kristian Hveem, Tom Wilsgaard, Karen L Mohlke, Zhe Wang, Aleksey Shmeliov, Marcel den Hoed, Ruth J F Loos, Wolfgang Kratzer, Mark Haenle, Wolfgang Koenig, Bernhard O. Boehm, Tricia M. Tan, Alejandra Tomas, Victoria Salem, Inês Barroso, Jaakko Tuomilehto, Michael Boehnke, Jose C. Florez, Anders Hamsten, Hugh Watkins, Inger Njolstad, H-Erich Wichmann, Mark J Caulfield, Kay-Tee Khaw, Cornelia van Duijn, Albert Hofman, Nicholas J. Wareham, Claudia Langenberg, John B. Whitfield, Nicholas G. Martin, Grant Montgomery, Chiara Scapoli, Ioanna Tzoulaki, Paul Elliott, Unnur Thorsteinsdottir, Kari Stefansson, Evan L. Brittain, MI McCarthy, Philippe Froguel, Patrick M. Sexton, Denise Wootten, Leif Groop, Josée Dupuis, James B Meigs, Giuseppe Deganutti, Tune H. Pers, Christopher A. Reynolds, Yurii S. Aulchenko, Ben Jones (2023)GWAS of random glucose in 476,326 individuals provide insights into diabetes pathophysiology, complications and treatment stratification, In: Nature Genetics55(9)pp. 1448-1461 Nature Research

Conventional measurements of fasting and postprandial blood glucose levels investigated in genome-wide association studies (GWAS) cannot capture the effects of DNA variability on 'around the clock' glucoregulatory processes. Here we show that GWAS meta-analysis of glucose measurements under nonstandardized conditions (random glucose (RG)) in 476,326 individuals of diverse ancestries and without diabetes enables locus discovery and innovative pathophysiological observations. We discovered 120 RG loci represented by 150 distinct signals, including 13 with sex-dimorphic effects, two cross-ancestry and seven rare frequency signals. Of these, 44 loci are new for glycemic traits. Regulatory, glycosylation and metagenomic annotations highlight ileum and colon tissues, indicating an underappreciated role of the gastrointestinal tract in controlling blood glucose. Functional follow-up and molecular dynamics simulations of lower frequency coding variants in glucagon-like peptide-1 receptor (GLP1R), a type 2 diabetes treatment target, reveal that optimal selection of GLP-1R agonist therapy will benefit from tailored genetic stratification. We also provide evidence from Mendelian randomization that lung function is modulated by blood glucose and that pulmonary dysfunction is a diabetes complication. Our investigation yields new insights into the biology of glucose regulation, diabetes complications and pathways for treatment stratification. Genome-wide association analyses of blood glucose measurements under nonstandardized conditions provide insights into the biology of glucose regulation, diabetes complications and pathways for treatment stratification.

C.M Middeldorp, I Prokopenko, A Mahajan, M Horikoshi, N.R Robertson, R.N Beaumont, J.P Bradfield, M Bustamante, D.L Cousminer, F.R Day, N.M. de Silva, M Guxens, D.O Mook-Kanamori, B St Pourcain, N.M Warrington, L.S Adair, E Ahlqvist, T.S Ahluwalia, P Almgren, W Ang, M Atalay, J Auvinen, M Bartels, J.S Beckmann, J.R Bilbao, T Bond, J.B Borja, A Cavadino, P Charoen, Z.H Chen, L Coin, C Cooper, J.A Curtin, A Custovic, G.E Davies, G.V Dedoussis, L Duijts, P.R Eastwood, A.U Eliasen, P Elliott, J.G Eriksson, X Estivill, J Fadista, I.O Fedko, T.M Frayling, R Gaillard, W.J Gauderman, F Geller, F Gilliland, V Gilsanz, R Granell, N Grarup, L Groop, D Hadley, H Hakonarson, T Hansen, C.A Hartman, A.T Hattersley, M.G Hayes, J Hebebrand, J Heinrich, O Helgeland, A.K Henders, J Henderson, T.B Henriksen, J.N Hirschhorn, M.F Hivert, B Hocher, J.W Holloway, P Holt, J.J Hottenga, E Hypponen, C Iniguez, S Johansson, A Jugessur, M Kahonen, H.J Kalkwarf, J Kaprio, V Karhunen, J.P Kemp, M Kerkhof, G.H Koppelman, A Korner, S Kotecha, E Kreiner-Moller, B Kulohoma, A Kumar, Z Kutalik, J Lahti, J.M Lappe, H Larsson, T Lehtimaki, A.M Lewin, J Li, P Lichtenstein, C.M Lindgren, V Lindi, A Linneberg, X.P Liu, J Liu, W.L Lowe, S Lundstrom, L.P Lyytikainen, R.C.W Ma, A Mace, R Magi, P Magnus, A.A Mamun, M Mannikko, N.G Martin, H Mbarek, N.S McCarthy, S.E Medland, M Melbye, E Melen, K.L Mohlke, C Monnereau, C.S Morgen, A.P Morris, J.C Murray, R Myhre, J.M Najman, M.G Nivard, E.A Nohr, I.M Nolte, I Ntalla, P O'Reilly, S.E Oberfield, E Oken, A.J Oldehinkel, K Pahkala, T Palviainen, K Panoutsopoulou, O Pedersen, C.E Pennell, G Pershagen, N Pitkanen, R Plomin, C Power, R.B Prasad, L Pulkkinen, K Raikkonen, O.T Raitakari, R.M Reynolds, R.C Richmond, F Rivadeneira, A Roiguez, R.J Rose, R Salem, L Santa-Marina, S.M Saw, T.M Schnurr, J.G Scott, S Selzam, J.A Shepherd, A Simpson, L Skotte, P.M.M Sleiman, H Snieder, T.I.A Sorensen, M Standl, E.A.P Steegers, D.P Strachan, L Straker, T Strandberg, M Taylor, Y.Y Teo, E Thiering, M Torrent, J Tyrrell, A.G Uitterlinden, T. van Beijsterveldt, P.J. van der Most, C.M. van Duijn, J Viikari, N Vilor-Tejedor, S Vogelezang, J.M Vonk, T.G.M Vrijkotte, E Vuoksimaa, C.A Wang, W.J Watkins, H.E Wichmann, G Willemsen, G.M Williams, J.F Wilson, N.R Wray, S.J Xu, C.J Xu, H Yaghootkar, L Yi, M.H Zafarmand, E Zeggini, B.S Zemel, A Hinney, T.A Lakka, A.J.O Whitehouse, J Sunyer, E.E Widen, B Feenstra, S Sebert, B Jacobsson, P.R Njolstad, C Stoltenberg, G.D Smith, D.A Lawlor, L Paternoster, N.J Timpson, K.K Ong, H Bisgaard, K Bonnelykke, V.W.V Jaddoe, H Tiemeier, M.R Jarvelin, D.M Evans, J.R.B Perry, S.F.A Grant, D.I Boomsma, R.M Freathy, M.I McCarthy, J.F Felix, EArly Genetics Lifecourse, EGG Consortium, EGG Membership, EAGLE Membership (2019)The Early Growth Genetics (EGG) and EArly Genetics and Lifecourse Epidemiology (EAGLE) consortia: design, results and future prospects, In: European Journal of Epidemiology34(3)pp. 279-300 Springer

The impact of many unfavorable childhood traits or diseases, such as low birth weight and mental disorders, is not limited to childhood and adolescence, as they are also associated with poor outcomes in adulthood, such as cardiovascular disease. Insight into the genetic etiology of childhood and adolescent traits and disorders may therefore provide new perspectives, not only on how to improve wellbeing during childhood, but also how to prevent later adverse outcomes. To achieve the sample sizes required for genetic research, the Early Growth Genetics (EGG) and EArly Genetics and Lifecourse Epidemiology (EAGLE) consortia were established. The majority of the participating cohorts are longitudinal population-based samples, but other cohorts with data on early childhood phenotypes are also involved. Cohorts often have a broad focus and collect(ed) data on various somatic and psychiatric traits as well as environmental factors. Genetic variants have been successfully identified for multiple traits, for example, birth weight, atopic dermatitis, childhood BMI, allergic sensitization, and pubertal growth. Furthermore, the results have shown that genetic factors also partly underlie the association with adult traits. As sample sizes are still increasing, it is expected that future analyses will identify additional variants. This, in combination with the development of innovative statistical methods, will provide detailed insight on the mechanisms underlying the transition from childhood to adult disorders. Both consortia welcome new collaborations. Policies and contact details are available from the corresponding authors of this manuscript and/or the consortium websites.

Alberto Romagnoni, Inga Prokopenko, Simon Jegou, Kristel Van Steen, Gilles Wainrib, Jean-Pierre Hugot, Laurent Peyrin-Biroulet, Mathias Chamaillard, Jean-Frederick Colombel, Mario Cottone, Mauro D'Amato, Renata D'Inca, Jonas Halfvarson, Paul Henderson, Amir Karban, Nicholas A Kennedy, Mohammed Azam Khan, Marc Lemann, Arie Levine, Dunecan Massey, Monica Milla, Sok Meng Evelyn Ng, Ioannis Oikonomou, Harald Peeters, Deborah D Proctor, Jean-Francois Rahier, Paul Rutgeerts, Frank Seibold, Laura Stronati, Kirstin M Taylor, Leif Torkvist, Kullak Ublick, Johan Van Limbergen, Andre Van Gossum, Morten H Vatn, Hu Zhang, Wei Zhang, Jane M Andrews, Peter A Bampton, Murray Barclay, Timothy H Florin, Richard Gearry, Krupa Krishnaprasad, Ian C Lawrance, Gillian Mahy, Grant W Montgomery, Graham Radford-Smith, Rebecca L Roberts, Lisa A Simms, Katherine Hanigan, Anthony Croft, Leila Amininijad, Isabelle Cleynen, Olivier Dewit, Denis Franchimont, Michel Georges, Debby Laukens, Emilie Theatre, Severine Vermeire, Guy Aumais, Leonard Baidoo, Arthur M Barrie, Karen Beck, Edmond-Jean Bernard, David G Binion, Alain Bitton, Steve R Brant, Judy H Cho, Albert Cohen, Kenneth Croitoru, Mark J Daly, Lisa W Datta, Colette Deslandres, Richard H Duerr, Debra Dutridge, John Ferguson, Joann Fultz, Philippe Goyette, Gordon R Greenberg, Talin Haritunians, Gilles Jobin, Seymour Katz, Raymond G Lahaie, Dermot P McGovern, Linda Nelson, Sok Meng Ng, Kaida Ning, Pierre Pare, Miguel D Regueiro, John D Rioux, Elizabeth Ruggiero, L Philip Schumm, Marc Schwartz, Regan Scott, Yashoda Sharma, Mark S Silverberg, Denise Spears, A Hillary Steinhart, Joanne M Stempak, Jason M Swoger, Constantina Tsagarelis, Clarence Zhang, Hongyu Zhao, Jan Aerts, Tariq Ahmad, Hazel Arbury, Anthony Attwood, Adam Auton, Stephen G Ball, Anthony J Balmforth, Chris Barnes, Jeffrey C Barrett, Ines Barroso, Anne Barton, Amanda J Bennett, Sanjeev Bhaskar, Katarzyna Blaszczyk, John Bowes, Oliver J Brand, Peter S Braund, Francesca Bredin, Gerome Breen, Morris J Brown, Ian N Bruce, Jaswinder Bull, Oliver S Burren, John Burton, Jake Byrnes, Sian Caesar, Niall Cardin, Chris M Clee, Alison J Coffey, John Mc Connell, Donald F Conrad, Jason D Cooper, Anna F Dominiczak, Kate Downes, Hazel E Drummond, Darshna Dudakia, Andrew Dunham, Bernadette Ebbs, Diana Eccles, Sarah Edkins, Cathryn Edwards, Anna Elliot, Paul Emery, David M Evans, Gareth Evans, Steve Eyre, Anne Farmer, I Nicol Ferrier, Edward Flynn, Alistair Forbes, Liz Forty, Jayne A Franklyn, Timothy M Frayling, Rachel M Freathy, Eleni Giannoulatou, Polly Gibbs, Paul Gilbert, Katherine Gordon-Smith, Emma Gray, Elaine Green, Chris J Groves, Detelina Grozeva, Rhian Gwilliam, Anita Hall, Naomi Hammond, Matt Hardy, Pile Harrison, Neelam Hassanali, Husam Hebaishi, Sarah Hines, Anne Hinks, Graham A Hitman, Lynne Hocking, Chris Holmes, Eleanor Howard, Philip Howard, Joanna MM Howson, Debbie Hughes, Sarah Hunt, John D Isaacs, Mahim Jain, Derek P Jewell, Toby Johnson, Jennifer D Jolley, Ian R Jones, Lisa A Jones, George Kirov, Cordelia F Langford, Hana Lango-Allen, G Mark Lathrop, James Lee, Kate L Lee, Charlie Lees, Kevin Lewis, Cecilia M Lindgren, Meeta Maisuria-Armer, Julian Maller, John Mansfield, Jonathan L Marchini, Paul Martin, Dunecan CO Massey, Wendy L McArdle, Peter McGuffin, Kirsten E McLay, Gil McVean, Alex Mentzer, Michael L Mimmack, Ann E Morgan, Andrew P Morris, Craig Mowat, Patricia B Munroe, Simon Myers, William Newman, Elaine R Nimmo, Michael C O'Donovan, Abiodun Onipinla, Nigel R Ovington, Michael J Owen, Kimmo Palin, Aarno Palotie, Kirstie Parnell, Richard Pearson, David Pernet, John RB Perry, Anne Phillips, Vincent Plagnol, Natalie J Prescott, Michael A Quail, Suzanne Rafelt, Nigel W Rayner, David M Reid, Anthony Renwick, Susan M Ring, Neil Robertson, Samuel Robson, Ellie Russell, David St Clair, Jennifer G Sambrook, Jeremy D Sanderson, Stephen J Sawcer, Helen Schuilenburg, Carol E Scott, Richard Scott, Sheila Seal, Sue Shaw-Hawkins, Beverley M Shields, Matthew J Simmonds, Debbie J Smyth, Elilan Somaskantharajah, Katarina Spanova, Sophia Steer, Jonathan Stephens, Helen E Stevens, Kathy Stirrups, Millicent A Stone, David P Strachan, Zhan Su, Deborah PM Symmons, John R Thompson, Wendy Thomson, Martin D Tobin, Mary E Travers, Clare Turnbull, Damjan Vukcevic, Louise Wain, Mark Walker, Neil M Walker, Chris Wallace, Margaret Warren-Perry, Nicholas A Watkins, John Webster, Michael N Weedon, Anthony G Wilson, Matthew Woodburn, B Paul Wordsworth, Chris Yau, Allan H Young, Eleftheria Zeggini, Matthew A Brown, Paul R Burton, Mark J Caulfield, Alastair Compston, Martin Farrall, Stephen CL Gough, Alistair S Hall, Andrew T Hattersley, Adrian VS Hill, Christopher G Mathew, Marcus Pembrey, Jack Satsangi, Michael R Stratton, Jane Worthington, Matthew E Hurles, Audrey Duncanson, Willem H Ouwehand, Miles Parkes, Nazneen Rahman, John A Todd, Nilesh J Samani, Dominic P Kwiatkowski, Mark McCarthy, Nick Craddock, Panos Deloukas, Peter Donnelly, Jenefer M Blackwell, Elvira Bramon, Juan P Casas, Aiden Corvin, Janusz Jankowski, Hugh S Markus, Colin NA Palmer, Robert Plomin, Anna Rautanen, Richard C Trembath, Ananth C Viswanathan, Nicholas W Wood, Chris CA Spencer, Gavin Band, Celine Bellenguez, Colin Freeman, Garrett Hellenthal, Matti Pirinen, Amy Strange, Hannah Blackburn, Suzannah J Bumpstead, Serge Dronov, Matthew Gillman, Alagurevathi Jayakumar, Owen T McCann, Jennifer Liddle, Simon C Potter, Radhi Ravindrarajah, Michelle Ricketts, Matthew Waller, Paul Weston, Sara Widaa, Pamela Whittaker (2019)Comparative performances of machine learning methods for classifying Crohn Disease patients using genome-wide genotyping data, In: Scientific Reports910351 Nature Research

Crohn Disease (CD) is a complex genetic disorder for which more than 140 genes have been identified using genome wide association studies (GWAS). However, the genetic architecture of the trait remains largely unknown. The recent development of machine learning (ML) approaches incited us to apply them to classify healthy and diseased people according to their genomic information. The Immunochip dataset containing 18,227 CD patients and 34,050 healthy controls enrolled and genotyped by the international Inflammatory Bowel Disease genetic consortium (IIBDGC) has been re-analyzed using a set of ML methods: penalized logistic regression (LR), gradient boosted trees (GBT) and artificial neural networks (NN). The main score used to compare the methods was the Area Under the ROC Curve (AUC) statistics. The impact of quality control (QC), imputing and coding methods on LR results showed that QC methods and imputation of missing genotypes may artificially increase the scores. At the opposite, neither the patient/control ratio nor marker preselection or coding strategies significantly affected the results. LR methods, including Lasso, Ridge and ElasticNet provided similar results with a maximum AUC of 0.80. GBT methods like XGBoost, LightGBM and CatBoost, together with dense NN with one or more hidden layers, provided similar AUC values, suggesting limited epistatic effects in the genetic architecture of the trait. ML methods detected near all the genetic variants previously identified by GWAS among the best predictors plus additional predictors with lower effects. The robustness and complementarity of the different methods are also studied. Compared to LR, non-linear models such as GBT or NN may provide robust complementary approaches to identify and classify genetic markers. status: published

Sylvain Sebert, Inga Prokopenko, Estelle Lowry, Nicole Aumüller, Mercedes G Bermúdez, Lise G Bjerregaard, Susanne R de Rooij, Maneka De Silva, Hanan El Marroun, Nadine Hummel, Teija Juola, Giacomo Mason, Daniela Much, Elena Oliveros, Stavros Poupakis, Nina Rautio, Phillipp Schwarzfischer, Evangelia Tzala, Olaf Uhl, Cornelieke van de Beek, Florianne Vehmeijer, Juan Verdejo-Román, Niko Wasenius, Claire Webster, Leena Ala-Mursula, Karl-Heinz Herzig, Sirkka Keinänen-Kiukaanniemi, Jouko Miettunen, Jennifer L Baker, Cristina Campoy, Gabriella Conti, Johan G Eriksson, Sandra Hummel, Vincent Jaddoe, Berthold Koletzko, Alex Lewin, Maria Rodriguez-Palermo, Tessa Roseboom, Ricardo Rueda, Jayne Evans, Janine F Felix, Thorkild I A Sørensen, Marjo-Riitta Järvelin (2019)Cohort Profile: The DynaHEALTH consortium - a European consortium for a life-course bio-psychosocial model of healthy ageing of glucose homeostasis, In: International journal of epidemiology48(4)dyz056pp. 1051-1051K Oxford University Press
Nicole M. Warrington, Inga Prokopenko, Robin N. Beaumont, Momoko Horikoshi, Felix R. Day, Oyvind Helgeland, Charles Laurin, Jonas Bacelis, Shouneng Peng, Ke Hao, Bjarke Feenstra, Andrew R. Wood, Anubha Mahajan, Jessica Tyrrell, Neil R. Robertson, N. William Rayner, Zhen Qiao, Gunn-Helen Moen, Marc Vaudel, Carmen J. Marsit, Jia Chen, Michael Nodzenski, Theresia M. Schnurr, Mohammad H. Zafarmand, Jonathan P. Bradfield, Niels Grarup, Marjolein N. Kooijman, Ruifang Li-Gao, Frank Geller, Tarunveer S. Ahluwalia, Lavinia Paternoster, Rico Rueedi, Ville Huikari, Jouke-Jan Hottenga, Leo-Pekka Lyytikainen, Alana Cavadino, Sarah Metrustry, Diana L. Cousminer, Ying Wu, Elisabeth Thiering, Carol A. Wang, Christian T. Have, Natalia Vilor-Tejedor, Peter K. Joshi, Jodie N. Painter, Ioanna Ntalla, Ronny Myhre, Niina Pitkanen, Elisabeth M. van Leeuwen, Raimo Joro, Vasiliki Lagou, Rebecca C. Richmond, Ana Espinosa, Sheila J. Barton, Hazel M. Inskip, John W. Holloway, Loreto Santa-Marina, Xavier Estivill, Wei Ang, Julie A. Marsh, Christoph Reichetzeder, Letizia Marullo, Berthold Hocher, Kathryn L. Lunetta, Joanne M. Murabito, Caroline L. Relton, Manolis Kogevinas, Leda Chatzi, Catherine Allard, Luigi Bouchard, Marie-France Hivert, Ge Zhang, Louis J. Muglia, Jani Heikkinen, Camilla S. Morgen, Antoine H. C. van Kampen, Barbera D. C. van Schaik, Frank D. Mentch, Claudia Langenberg, Jian'an Luan, Robert A. Scott, Jing Hua Zhao, Gibran Hemani, Susan M. Ring, Amanda J. Bennett, Kyle J. Gaulton, Juan Fernandez-Tajes, Natalie R. van Zuydam, Carolina Medina-Gomez, Hugoline G. de Haan, Frits R. Rosendaal, Zoltan Kutalik, Pedro Marques-Vidal, Shikta Das, Gonneke Willemsen, Hamdi Mbarek, Martina Mueller-Nurasyid, Marie Standl, Emil V. R. Appel, Cilius E. Fonvig, Caecilie Trier, Catharina E. M. van Beijsterveldt, Mario Murcia, Mariona Bustamante, Silvia Bonas-Guarch, David M. Hougaard, Josep M. Mercader, Allan Linneberg, Katharina E. Schraut, Penelope A. Lind, Sarah E. Medland, Beverley M. Shields, Bridget A. Knight, Jin-Fang Chai, Kalliope Panoutsopoulou, Meike Bartels, Friman Sanchez, Jakob Stokholm, David Torrents, Rebecca K. Vinding, Sara M. Willems, Mustafa Atalay, Bo L. Chawes, Peter Kovacs, Marcus A. Tuke, Hanieh Yaghootkar, Katherine S. Ruth, Samuel E. Jones, Po-Ru Loh, Anna Murray, Michael N. Weedon, Anke Toenjes, Michael Stumvoll, Kim F. Michaelsen, Aino-Maija Eloranta, Timo A. Lakka, Cornelia M. van Duijn, Wieland Kiess, Antje Koerner, Harri Niinikoski, Katja Pahkala, Olli T. Raitakari, Bo Jacobsson, Eleftheria Zeggini, George V. Dedoussis, Yik-Ying Teo, Seang-Mei Saw, Grant W. Montgomery, Harry Campbell, James F. Wilson, Tanja G. M. Vrijkotte, Martine Vrijheid, Eco J. C. N. de Geus, M. Geoffrey Hayes, Haja N. Kadarmideen, Jens-Christian Holm, Lawrence J. Beilin, Craig E. Pennell, Joachim Heinrich, Linda S. Adair, Judith B. Borja, Karen L. Mohlke, Johan G. Eriksson, Elisabeth E. Widen, Andrew T. Hattersley, Tim D. Spector, Mika Kaehoenen, Jorma S. Viikari, Terho Lehtimaeki, Dorret I. Boomsma, Sylvain Sebert, Peter Vollenweider, Thorkild I. A. Sorensen, Hans Bisgaard, Klaus Bonnelykke, Jeffrey C. Murray, Mads Melbye, Ellen A. Nohr, Dennis O. Mook-Kanamori, Fernando Rivadeneira, Albert Hofman, Janine F. Felix, Vincent W. V. Jaddoe, Torben Hansen, Charlotta Pisinger, Allan A. Vaag, Oluf Pedersen, Andre G. Uitterlinden, Marjo-Riitta Jarvelin, Christine Power, Elina Hypponen, Denise M. Scholtens, William L. Lowe, George Davey Smith, Nicholas J. Timpson, Andrew P. Morris, Nicholas J. Wareham, Hakon Hakonarson, Struan F. A. Grant, Timothy M. Frayling, Debbie A. Lawlor, Pal R. Njolstad, Stefan Johansson, Ken K. Ong, Mark I. McCarthy, John R. B. Perry, David M. Evans, Rachel M. Freathy (2019)Maternal and fetal genetic effects on birth weight and their relevance to cardio-metabolic risk factors, In: Nature genetics51(5)pp. 804-814 Nature Research

Birth weight variation is influenced by fetal and maternal genetic and non-genetic factors, and has been reproducibly associated with future cardio-metabolic health outcomes. In expanded genome-wide association analyses of own birth weight (n = 321,223) and offspring birth weight (n = 230,069 mothers), we identified 190 independent association signals (129 of which are novel). We used structural equation modeling to decompose the contributions of direct fetal and indirect maternal genetic effects, then applied Mendelian randomization to illuminate causal pathways. For example, both indirect maternal and direct fetal genetic effects drive the observational relationship between lower birth weight and higher later blood pressure: maternal blood pressure-raising alleles reduce offspring birth weight, but only direct fetal effects of these alleles, once inherited, increase later offspring blood pressure. Using maternal birth weight-lowering genotypes to proxy for an adverse intrauterine environment provided no evidence that it causally raises offspring blood pressure, indicating that the inverse birth weight-blood pressure association is attributable to genetic effects, and not to intrauterine programming.

Christopher Hübel, Héléna A Gaspar, Jonathan R I Coleman, Hilary Finucane, Kirstin L Purves, Ken B Hanscombe, Inga Prokopenko, Mariaelisa Graff, Julius S Ngwa, Tsegaselassie Workalemahu, Paul F O'Reilly, Cynthia M Bulik, Gerome Breen, (2019)Genomics of body fat percentage may contribute to sex bias in anorexia nervosa, In: American Journal of Medical Genetics Part B: Neuropsychiatric Genetics180(6)pp. 428-438 Wiley

Anorexia nervosa (AN) occurs nine times more often in females than in males. Although environmental factors likely play a role, the reasons for this imbalanced sex ratio remain unresolved. AN displays high genetic correlations with anthropometric and metabolic traits. Given sex differences in body composition, we investigated the possible metabolic underpinnings of female propensity for AN. We conducted sex-specific GWAS in a healthy and medication-free subsample of the UK Biobank (n = 155,961), identifying 77 genome-wide significant loci associated with body fat percentage (BF%) and 174 with fat-free mass (FFM). Partitioned heritability analysis showed an enrichment for central nervous tissue-associated genes for BF%, which was more prominent in females than males. Genetic correlations of BF% and FFM with the largest GWAS of AN by the Psychiatric Genomics Consortium were estimated to explore shared genomics. The genetic correlations of BF%male and BF%female with AN differed significantly from each other (p 

Irene Miguel-Escalada, Silvia Bonàs-Guarch, Inês Cebola, Joan Ponsa-Cobas, Julen Mendieta-Esteban, Goutham Atla, Biola M. Javierre, Delphine M.Y. Rolando, Irene Farabella, Claire C. Morgan, Javier García-Hurtado, Anthony Beucher, Ignasi Morán, Lorenzo Pasquali, Mireia Ramos-Rodríguez, Emil V.R. Appel, Allan Linneberg, Anette P. Gjesing, Daniel R. Witte, Oluf Pedersen, Niels Grarup, Philippe Ravassard, David Torrents, Josep M. Mercader, Lorenzo Piemonti, Thierry Berney, Eelco J.P. de Koning, Julie Kerr-Conte, François Pattou, Iryna O. Fedko, Leif Groop, Inga Prokopenko, Torben Hansen, Marc A. Marti-Renom, Peter Fraser, Jorge Ferrer (2019)Human pancreatic islet 3D chromatin architecture provides insights into the genetics of type 2 diabetes, In: Nature Genetics51(7)pp. 1137-1148 Nature Research

Genetic studies promise to provide insight into the molecular mechanisms underlying type 2 diabetes (T2D). Variants associated with T2D are often located in tissue-specific enhancer clusters or super-enhancers. So far, such domains have been defined through clustering of enhancers in linear genome maps rather than in three-dimensional (3D) space. Furthermore, their target genes are often unknown. We have created promoter capture Hi-C maps in human pancreatic islets. This linked diabetes-associated enhancers to their target genes, often located hundreds of kilobases away. It also revealed >1,300 groups of islet enhancers, super-enhancers and active promoters that form 3D hubs, some of which show coordinated glucose-dependent activity. We demonstrate that genetic variation in hubs impacts insulin secretion heritability, and show that hub annotations can be used for polygenic scores that predict T2D risk driven by islet regulatory variants. Human islet 3D chromatin architecture, therefore, provides a framework for interpretation of T2D genome-wide association study (GWAS) signals.

Estelle Lowry, Nina Rautio, Ville Karhunen, Jouko Miettunen, Leena Ala-Mursula, Juha Auvinen, Sirkka Keinänen-Kiukaanniemi, Katri Puukka, Inga Prokopenko, Karl-Heinz Herzig, Alexandra Lewin, Sylvain Sebert, Marjo-Riitta Järvelin (2019)Understanding the complexity of glycaemic health: systematic bio-psychosocial modelling of fasting glucose in middle-age adults; a DynaHEALTH study, In: International journal of obesity (2005)43(6)1181pp. 1181-1192

The prevention of the risk of type 2 diabetes (T2D) is complicated by multidimensional interplays between biological and psychosocial factors acting at the individual level. To address the challenge we took a systematic approach, to explore the bio-psychosocial predictors of blood glucose in mid-age. Based on the 31-year and 46-year follow-ups (5,078 participants, 43% male) of Northern Finland Birth Cohort 1966, we used a systematic strategy to select bio-psychosocial variables at 31 years to enable a data-driven approach. As selection criteria, the variable must be (i) a component of the metabolic syndrome or an indicator of psychosocial health using WHO guidelines, (ii) easily obtainable in general health check-ups and (iii) associated with fasting blood glucose at 46 years (P 

Christopher Huebel, Helena Alexandra Gaspar, Jonathan Coleman, Kirstin Purves, Ken Benjamin Hanscombe, Inga Prokopenko, Paul O'Reilly, Cynthia Bulik, Gerome Breen (2019)ATLAS OF SEX-SPECIFIC GENETIC CORRELATIONS ACROSS PSYCHIATRY, ANTHROPOMETRY, AND METABOLIC TRAITS, In: European neuropsychopharmacology29pp. S1033-S1033 Elsevier B.V
Francesca Forzano, Olga Antonova, Angus Clarke, Guido de Wert, Sabine Hentze, Yalda Jamshidi, Yves Moreau, Markus Perola, Inga Prokopenko, Andrew Read, Alexandre Reymond, Vigdis Stefansdottir, Carla van El, Maurizio Genuardi, European Soc Human Genetics, (2023)Reply to Letter by Tellier et al., 'Scientific refutation of ESHG statement on embryo selection', In: European journal of human genetics : EJHG31(3)pp. 279-281 Springer Nature
Francesca Forzano, Olga Antonova, Angus Clarke, Guido de Wert, Sabine Hentze, Yalda Jamshidi, Yves Moreau, Markus Perola, Inga Prokopenko, Andrew Read, Alexandre Reymond, Vigdis Stefansdottir, Carla van El, Maurizio Genuardi, Genuardi Maurizio, Borut Peterlin, Carla Oliveira, Karin Writzl, Gunnar Douzgos Houge, Christophe Cordier, Guido de Wert, Heidi Howard, Milan Macek, Béla Melegh, Alvaro Mendes, Dragica Radojkovic, Emmanuelle Rial-Sebbag, Vigdis Stefánsdottir, Fiona Ulph, Carla van El (2022)Correction: The use of polygenic risk scores in pre-implantation genetic testing: an unproven, unethical practice (European Journal of Human Genetics, (2022), 30, 5, (493-495), 10.1038/s41431-021-01000-x), In: European journal of human genetics : EJHG30(5)

The article “The use of polygenic risk scores in pre-implantation genetic testing: an unproven, unethical practice”, written by Francesca Forzano et al., was originally published electronically on the publisher’s internet portal on 17 December 2021 without open access. With the authors’ decision to opt for Open Choice, the copyright of the article changed on 11 July 2022 to

Christopher Huebel, Helena Alexandra Gaspar, Jonathan Coleman, Kirstin Purves, Ken Benjamin Hanscombe, Inga Prokopenko, Paul O'Reilly, Cynthia Bulik, Gerome Breen (2019)FEMALE-SPECIFIC GENETIC VARIATION ASSOCIATED WITH BODY FAT PERCENTAGE MAY CONTRIBUTE TO RISK FOR ANOREXIA NERVOSA, In: European neuropsychopharmacology29pp. S1048-S1048 Elsevier B.V
A. Sadlon, P. Takousis, E. Evangelou, I. Prokopenko, P. Alexopoulos, C.-M. Udeh-Momoh, G. Price, L. Middleton, R. Perneczky (2023)Association of Blood MicroRNA Expression and Polymorphisms with Cognitive and Biomarker Changes in Older Adults, In: The Journal Of Prevention of Alzheimer's Disease
Joshua Hodgson, Emilia M Swietlik, Richard M Salmon, Charaka Hadinnapola, Ivana Nikolic, John Wharton, Jingxu Guo, James Liley, Matthias Haimel, Marta Bleda, Laura Southgate, Rajiv D Machado, Jennifer M Martin, Carmen M Treacy, Katherine Yates, Louise C Daugherty, Olga Shamardina, Deborah Whitehorn, Simon Holden, Harm J Bogaard, Colin Church, Gerry Coghlan, Robin Condliffe, Paul A Corris, Cesare Danesino, Mélanie Eyries, Henning Gall, Stefano Ghio, Hossein-Ardeschir Ghofrani, J Simon R Gibbs, Barbara Girerd, Arjan C Houweling, Luke Howard, Marc Humbert, David G Kiely, Gabor Kovacs, Allan Lawrie, Robert V MacKenzie Ross, Shahin Moledina, David Montani, Andrea Olschewski, Horst Olschewski, Willem H Ouwehand, Andrew J Peacock, Joanna Pepke-Zaba, Inga Prokopenko, Christopher J Rhodes, Laura Scelsi, Werner Seeger, Florent Soubrier, Jay Suntharalingam, Mark R Toshner, Richard C Trembath, Anton Vonk Noordegraaf, Stephen J Wort, Martin R Wilkins, Paul B Yu, Wei Li, Stefan Gräf, Paul D Upton, Nicholas W Morrell (2020)Characterization of GDF2 Mutations and Levels of BMP9 and BMP10 in Pulmonary Arterial Hypertension, In: American journal of respiratory and critical care medicine201(5)pp. 575-585

Recently, rare heterozygous mutations in were identified in patients with pulmonary arterial hypertension (PAH). encodes the circulating BMP (bone morphogenetic protein) type 9, which is a ligand for the BMP2 receptor. Here we determined the functional impact of mutations and characterized plasma BMP9 and BMP10 levels in patients with idiopathic PAH. Missense BMP9 mutant proteins were expressed and the impact on BMP9 protein processing and secretion, endothelial signaling, and functional activity was assessed. Plasma BMP9 and BMP10 levels and activity were assayed in patients with PAH with variants and in control subjects. Levels were also measured in a larger cohort of control subjects (  = 120) and patients with idiopathic PAH (  = 260). We identified a novel rare variation at the and loci, including copy number variation. , BMP9 missense proteins demonstrated impaired cellular processing and secretion. Patients with PAH who carried these mutations exhibited reduced plasma levels of BMP9 and reduced BMP activity. Unexpectedly, plasma BMP10 levels were also markedly reduced in these individuals. Although overall BMP9 and BMP10 levels did not differ between patients with PAH and control subjects, BMP10 levels were lower in PAH females. A subset of patients with PAH had markedly reduced plasma levels of BMP9 and BMP10 in the absence of mutations. Our findings demonstrate that mutations result in BMP9 loss of function and are likely causal. These mutations lead to reduced circulating levels of both BMP9 and BMP10. These findings support therapeutic strategies to enhance BMP9 or BMP10 signaling in PAH.

Yanina Timasheva, Zhanna Balkhiyarova, Diana Avzaletdinova, Irina Rassoleeva, Tatiana V. V. Morugova, Gulnaz Korytina, Inga Prokopenko, Olga Kochetova (2023)Integrating Common Risk Factors with Polygenic Scores Improves the Prediction of Type 2 Diabetes, In: International journal of molecular sciences24(2)984 Mdpi

We tested associations between 13 established genetic variants and type 2 diabetes (T2D) in 1371 study participants from the Volga-Ural region of the Eurasian continent, and evaluated the predictive ability of the model containing polygenic scores for the variants associated with T2D in our dataset, alone and in combination with other risk factors such as age and sex. Using logistic regression analysis, we found associations with T2D for the CCL20 rs6749704 (OR = 1.68, P-FDR = 3.40 x 10(-5)), CCR5 rs333 (OR = 1.99, P-FDR = 0.033), ADIPOQ rs17366743 (OR = 3.17, P-FDR = 2.64 x 10(-4)), TCF7L2 rs114758349 (OR = 1.77, P-FDR = 9.37 x 10(-5)), and CCL2 rs1024611 (OR = 1.38, P-FDR = 0.033) polymorphisms. We showed that the most informative prognostic model included weighted polygenic scores for these five loci, and non-genetic factors such as age and sex (AUC 85.8%, 95%CI 83.7-87.8%). Compared to the model containing only non-genetic parameters, adding the polygenic score for the five T2D-associated loci showed improved net reclassification (NRI = 37.62%, 1.39 x 10(-6)). Inclusion of all 13 tested SNPs to the model with age and sex did not improve the predictive ability compared to the model containing five T2D-associated variants (NRI = -17.86, p = 0.093). The five variants associated with T2D in people from the Volga-Ural region are linked to inflammation (CCR5, CCL2, CCL20) and glucose metabolism regulation (TCF7L, ADIPOQ2). Further studies in independent groups of T2D patients should validate the prognostic value of the model and elucidate the molecular mechanisms of the disease development.

Liam McAllan, Damir Baranasic, Sergio Villicana, Scarlett Brown, Weihua Zhang, Benjamin Lehne, Marco Adamo, Andrew Jenkinson, Mohamed Elkalaawy, Borzoueh Mohammadi, Majid Hashemi, Nadia Fernandes, Nathalie Lambie, Richard Williams, Colette Christiansen, Youwen Yang, Liudmila Zudina, Vasiliki Lagou, Sili Tan, Juan Castillo-Fernandez, James W. D. King, Richie Soong, Paul Elliott, James Scott, Inga Prokopenko, Ines Cebola, Marie Loh, Boris Lenhard, Rachel L. Batterham, Jordana T. Bell, John C. Chambers, Jaspal S. Kooner, William R. Scott (2023)Integrative genomic analyses in adipocytes implicate DNA methylation in human obesity and diabetes, In: Nature communications14(1)2784pp. 2784-2784 NATURE PORTFOLIO

DNA methylation variations are prevalent in human obesity but evidence of a causative role in disease pathogenesis is limited. Here, we combine epigenome-wide association and integrative genomics to investigate the impact of adipocyte DNA methylation variations in human obesity. We discover extensive DNA methylation changes that are robustly associated with obesity (N = 190 samples, 691 loci in subcutaneous and 173 loci in visceral adipocytes, P < 1 x 10(-7)). We connect obesity-associated methylation variations to transcriptomic changes at >500 target genes, and identify putative methylation-transcription factor interactions. Through Mendelian Randomisation, we infer causal effects of methylation on obesity and obesity-induced metabolic disturbances at 59 independent loci. Targeted methylation sequencing, CRISPR-activation and gene silencing in adipocytes, further identifies regional methylation variations, underlying regulatory elements and novel cellular metabolic effects. Our results indicate DNA methylation is an important determinant of human obesity and its metabolic complications, and reveal mechanisms through which altered methylation may impact adipocyte functions. DNA methylation variation is associated with human obesity but a whether it plays a causal role in disease pathogenesis is unclear. Here, the authors perfom an integrative genomic study in human adipocytes to show that DNA methylation variations contribute to obesity and type 2 diabetes susceptibility, revealing underlying genomic and molecular mechanisms.

Anna Ulrich, John Wharton, Timothy E. Thayer, Emilia M. Swietlik, Tufik R. Assad, Ankit A. Desai, Stefan Graf, Lars Harbaum, Marc Humbert, Nicholas W. Morrell, William C. Nichols, Florent Soubrier, Laura Southgate, David-Alexandre Tregouet, Richard C. Trembath, Evan L. Brittain, Martin R. Wilkins, Inga Prokopenko, Christopher J. Rhodes, (2020)Mendelian randomisation analysis of red cell distribution width in pulmonary arterial hypertension, In: The European respiratory journal55(2)1901486 European Respiratory Soc Journals Ltd

Pulmonary arterial hypertension (PAH) is a rare disease that leads to premature death from right heart failure. It is strongly associated with elevated red cell distribution width (RDW), a correlate of several iron status biomarkers. High RDW values can signal early-stage iron deficiency or iron deficiency anaemia. This study investigated whether elevated RDW is causally associated with PAH. A two-sample Mendelian randomisation (MR) approach was applied to investigate whether genetic predisposition to higher levels of RDW increases the odds of developing PAH. Primary and secondary MR analyses were performed using all available genome-wide significant RDW variants (n=179) and five genome-wide significant RDW variants that act via systemic iron status, respectively. We confirmed the observed association between RDW and PAH (OR 1.90, 95% CI 1.80-2.01) in a multicentre case-control study (cases n=642, disease controls n=15889). The primary MR analysis was adequately powered to detect a causal effect (odds ratio) between 1.25 and 1.52 or greater based on estimates reported in the RDW genome-wide association study or from our own data. There was no evidence for a causal association between RDW and PAH in either the primary (ORcausal 1.07, 95% CI 0.92-1.24) or the secondary (ORcausal 1.09, 95% CI 0.77-1.54) MR analysis. The results suggest that at least some of the observed association of RDW with PAH is secondary to disease progression. Results of iron therapeutic trials in PAH should be interpreted with caution, as any improvements observed may not be mechanistically linked to the development of PAH.

Edward S. Tobias, Elena Avram, Patricia Calapod, Christophe Cordier, Johan T. den Dunnen, Can Ding, Vita Dolzan, Sofia Douzgou Houge, Sally Ann Lynch, James O’Byrne, Philippos Patsalis, Inga Prokopenko, Celia A. Soares, Adam P. Tobias, William G. Newman (2021)The Role of the European Society of Human Genetics in Delivering Genomic Education, In: Frontiers in genetics12693952pp. 693952-693952 Frontiers Media S.A

The European Society of Human Genetics (ESHG) was founded in 1967 as a professional organisation for members working in genetics in clinical practice, research and education. The Society seeks the integration of scientific research and its implementation into clinical practice and the education of specialists and the public in all areas of medical and human genetics. The Society works to do this through many approaches, including educational sessions at the annual conference; training courses in general and specialist areas of genetics; an online resource of educational materials (EuroGEMS); and a mentorship scheme. The ESHG Education Committee is implementing new approaches to expand the reach of its educational activities and portfolio. With changes in technology, appreciation of the utility of genomics in healthcare and the public’s and patients’ increased awareness of the role of genomics, this review will summarise how the ESHG is adapting to deliver innovative educational activity.

James Dooley, V Lagou, Jermaine Goveia, ANNA ULRICH, Katerina Rohlenova, Nathalie Heirman, Tobias Karakach, Yulia Lampi, Shawez Khan, Jun Wang, Tom Dresselaers, Uwe Himmelreich, Marc J Gunter, INGA PROKOPENKO, P Carmeliet, AJ Liston (2020)Heterogeneous Effects of Calorie Content and Nutritional Components Underlie Dietary Influence on Pancreatic Cancer Susceptibility, In: Cell Reports32(2)107880 Cell Press

Pancreatic cancer is a rare but fatal form of cancer, the fourth highest in absolute mortality. Known risk factors include obesity, diet, and type 2 diabetes; however, the low incidence rate and interconnection of these factors confound the isolation of individual effects. Here, we use epidemiological analysis of prospective human cohorts and parallel tracking of pancreatic cancer in mice to dissect the effects of obesity, diet, and diabetes on pancreatic cancer. Through longitudinal monitoring and multi-omics analysis in mice, we found distinct effects of protein, sugar, and fat dietary components, with dietary sugars increasing Mad2l1 expression and tumor proliferation. Using epidemiological approaches in humans, we find that dietary sugars give a MAD2L1 genotype-dependent increased susceptibility to pancreatic cancer. The translation of these results to a clinical setting could aid in the identification of the at-risk population for screening and potentially harness dietary modification as a therapeutic measure. [Display omitted] •Distinct roles for dietary fat, protein, and sugar on murine pancreatic cancer•Dietary glucose triggers Mad2l1 upregulation and tumor cell proliferation in mice•Gene-diet interaction identifies sugar-MAD2L1 link in human pancreatic cancer•Dietary plant fats were protective in human pancreatic cancer susceptibility Dooley et al. used parallel analysis of a murine pancreatic cancer model and a human prospective cohort to study the interaction of diet and pancreatic cancer. Both systems identify complex effects with different dietary components, converging on a link between dietary sugar and the cell-cycle checkpoint gene MAD2L1.

P Parmar, Estelle Lowry, Florianne Vehmeijer, Hanan El Marroun, Alex Lewin, Mimmi Tolvanen, Evangelia Tzala, Leena Ala-Mursula, Karl-Heinz Herzig, Jouko Miettunen, INGA PROKOPENKO, Nina Rautio, Vincent W.V Jaddoe, Marjo-Riitta Jarvelin, Janine F. Felix, Sylvain Sebert (2020)Understanding the cumulative risk of maternal prenatal biopsychosocial factors on birth weight: A DynaHEALTH study on two birth cohorts, In: Journal of Epidemiology and Community Health74pp. 933-941

Background: There are various maternal prenatal biopsychosocial (BPS) predictors of birth weight, making it difficult to quantify their cumulative relationship. Methods: We studied two birth cohorts: Northern Finland Birth Cohort 1986 (NFBC1986) born in 1985–1986 and the Generation R Study (from the Netherlands) born in 2002–2006. In NFBC1986, we selected variables depicting BPS exposure in association with birth weight and performed factor analysis to derive latent constructs representing the relationship between these variables. In Generation R, the same factors were generated weighted by loadings of NFBC1986. Factor scores from each factor were then allocated into tertiles and added together to calculate a cumulative BPS score. In all cases, we used regression analyses to explore the relationship with birth weight corrected for sex and gestational age and additionally adjusted for other factors. Results: Factor analysis supported a four-factor structure, labelled closely to represent their characteristics as ‘Factor1-BMI’ (body mass index), ‘Factor2-DBP’ (diastolic blood pressure), ‘Factor3-Socioeconomic-Obstetric-Profile’ and ‘Factor4-Parental-Lifestyle’. In both cohorts, ‘Factor1-BMI’ was positively associated with birth weight, whereas other factors showed negative association. ‘Factor3-Socioeconomic-Obstetric-Profile’ and ‘Factor4-Parental-Lifestyle’ had the greatest effect size, explaining 30% of the variation in birth weight. Associations of the factors with birth weight were largely driven by ‘Factor1-BMI’. Graded decrease in birth weight was observed with increasing cumulative BPS score, jointly evaluating four factors in both cohorts. Conclusion: Our study is a proof of concept for maternal prenatal BPS hypothesis, highlighting the components snowball effect on birth weight in two different European birth cohorts.

Justiina Ronkainen, Rozenn Nedelec, Angelica Atehortua, ZHANNA BALKHIIAROVA, Anna Cascarano, Vien Ngoc Dang, Ahmed Elhakeem, Esther van Enckevort, Ana Goncalves Soares, Sido Haakma, Miia Halonen, Katharina F Heil, Anni Heiskala, Eleanor Hyde, B Jacquemin, Elina Keikkala, Jules Kerckhoffs, Anton Klåvus, Joanna A Kopinska, Irina Motoc, Johanna Lepeule, Francesca Marazzi, Mari Näätänen, Anton Ribbenstedt, Amanda Rundblad, Otto Savolainen, Valentina Simonetti, Nina de Toro Eadie, Evangelia Tzala, ANNA ULRICH, Thomas Wright, Iman Zarei, Enrico d’Amico, Federico Belotti, Carl Brunius, Christopher Castleton, Marie-Aline Charles, Romy Gaillard, Kati Hanhineva, Gerard Hoek, Kirsten B Holven, Vincent W.V Jaddoe, MARIKA KAAKINEN, Eero Kajantie, M Kavousi, Timo A. Lakka, Jason Matthews, Andrea Piano Mortari, Marja Vääräsmäki, Trudy Voortman, C Webster, Marie Zins, Vincenzo Atella, Maria Bulgheroni, M Chadeau-Hyam, Gabriella Conti, Jayne Evans, Janine F. Felix, Barbara Heude, Marjo-Riitta Jarvelin, Marjukka Kolehmainen, Rikard Landberg, Karim Lekadir, Stefano Parusso, INGA PROKOPENKO, Susanne R de Rooij, Tessa Roseboom, Morris Swertz, Nicholas J. Timpson, Stine M Ulven, Roel Vermeulen, Teija Juola, Sylvain Sebert (2022)LongITools: Dynamic longitudinal exposome trajectories in cardiovascular and metabolic noncommunicable diseases, In: Environmental epidemiology6(1)e184

The current epidemics of cardiovascular and metabolic noncommunicable diseases have emerged alongside dramatic modifications in lifestyle and living environments. These correspond to changes in our “modern” postwar societies globally characterized by rural-to-urban migration, modernization of agricultural practices, and transportation, climate change, and aging. Evidence suggests that these changes are related to each other, although the social and biological mechanisms as well as their interactions have yet to be uncovered. LongITools, as one of the 9 projects included in the European Human Exposome Network, will tackle this environmental health equation linking multidimensional environmental exposures to the occurrence of cardiovascular and metabolic noncommunicable diseases.

Zhanna Balkhiyarova, Rosa Luciano, Marika Kaakinen, Anna Ulrich, Aleksey Shmeliov, Marzia Bianchi, Laura Chioma, Bruno Dallapiccola, Inga Prokopenko, Melania Manco (2021)Relationship between glucose homeostasis and obesity in early life - A study of Italian children and adolescents, In: Human Molecular Geneticsddab287 Oxford University Press

Epidemic obesity is the most important risk factor for prediabetes and type 2 diabetes (T2D) in youth as it is in adults. Obesity shares pathophysiological mechanisms with T2D and is likely to share part of the genetic background. We aimed to test if weighted genetic risk scores (GRSs) for T2D, fasting glucose (FG) and fasting insulin (FI) predict glycaemic traits and if there is a causal relationship between obesity and impaired glucose metabolism in children and adolescents. Genotyping of 42 SNPs established by genome-wide association studies for T2D, FG and FI was performed in 1660 Italian youths aged between 2 and 19 years. We defined GRS for T2D, FG and FI and tested their effects on glycaemic traits, including FG, FI, indices of insulin resistance/beta cell function and body mass index (BMI). We evaluated causal relationships between obesity and FG/FI using one-sample Mendelian randomization analyses in both directions. GRS-FG was associated with FG (beta = 0.075 mmol/l, SE = 0.011, P = 1.58 × 10 −11) and beta cell function (beta = −0.041, SE = 0.0090 P = 5.13 × 10 −6). GRS-T2D also demonstrated an association with beta cell function (beta = −0.020, SE = 0.021 P = 0.030). We detected a causal effect of increased BMI on levels of FI in Italian youths (beta = 0.31 ln (pmol/l), 95%CI [0.078, 0.54], P = 0.0085), while there was no effect of FG/FI levels on BMI. Our results demonstrate that the glycaemic and T2D risk genetic variants contribute to higher FG and FI levels and decreased beta cell function in children and adolescents. The causal effects of adiposity on increased insulin resistance are detectable from childhood age.

Eleni M Loizidou, Anastasia Kucherenko, Pavlo Tatarskyy, Sergey Chernushyn, Ganna Livshyts, Roman Gulkovskyi, Iryna Vorobiova, Yurii Antipkin, Oleksandra Gorodna, MARIKA KAAKINEN, INGA PROKOPENKO, Ludmila Livshits (2021)Risk of recurrent pregnancy loss in the ukrainian population using a combined effect of genetic variants: A case-control study, In: Genes12(1)64 MDPI

We assessed the predictive ability of a combined genetic variant panel for the risk of recurrent pregnancy loss (RPL) through a case-control study. Our study sample was from Ukraine and included 114 cases with idiopathic RPL and 106 controls without any pregnancy losses/complications and with at least one healthy child. We genotyped variants within 12 genetic loci reflecting the main biological pathways involved in pregnancy maintenance: blood coagulation (F2, F5, F7, GP1A), hormonal regulation (ESR1, ADRB2), endometrium and placental function (ENOS, ACE), folate metabolism (MTHFR) and inflammatory response (IL6, IL8, IL10). We showed that a genetic risk score (GRS) calculated from the 12 variants was associated with an increased risk of RPL (odds ratio 1.56, 95% CI: 1.21, 2.04, p = 8.7 × 10−4). The receiver operator characteristic (ROC) analysis resulted in an area under the curve (AUC) of 0.64 (95% CI: 0.57, 0.72), indicating an improved ability of the GRS to classify women with and without RPL. Ιmplementation of the GRS approach can help define women at higher risk of complex multifactorial conditions such as RPL. Future well-powered genome-wide association studies will help in dissecting biological pathways previously unknown for RPL and further improve the identification of women with RPL susceptibility.

C. J. Rhodes, P. Otero-Nunez, J. Wharton, E. M. Swietlik, S. Kariotis, L. Harbaum, M. J. Dunning, J. M. Elinoff, N. Errington, A. A. R. Thomson, J. Iremonger, J. G. Coghlan, P. A. Corris, L. S. Howard, D. G. Kiely, C. Church, J. Pepke-Zaba, M. Toshner, S. J. Wort, A. A. Desai, M. Humbert, W. C. Nichols, L. Southgate, David-Alexandre Tregouet, R. C. Trembath, I. Prokopenko, S. Graf, N. W. Morrell, D. Wang, A. Lawrie, M. R. Wilkins (2020)Whole-blood RNA profiles associated with pulmonary arterial hypertension and clinical outcome, In: American journal of respiratory and critical care medicine202(4)pp. 586-594 American Thoracic Society

Rationale: Idiopathic and heritable pulmonary arterial hypertension (PAH) are rare but comprise a genetically heterogeneous patient group. RNA sequencing linked to the underlying genetic architecture can be used to better understand the underlying pathology by identifying key signaling pathways and stratify patients more robustly according to clinical risk.Objectives: To use a three-stage design of RNA discovery, RNA validation and model construction, and model validation to define a set of PAH-associated RNAs and a single summarizing RNA model score. To define genes most likely to be involved in disease development, we performed Mendelian randomization (MR) analysis.Methods: RNA sequencing was performed on whole-blood samples from 359 patients with idiopathic, heritable, and drug-induced PAH and 72 age- and sex-matched healthy volunteers. The score was evaluated against disease severity markers including survival analysis using all-cause mortality from diagnosis. MR used known expression quantitative trait loci and summary statistics from a PAH genome-wide association study.Measurements and Main Results: We identified 507 genes with differential RNA expression in patients with PAH compared with control subjects. A model of 25 RNAs distinguished PAH with 87% accuracy (area under the curve 95% confidence interval: 0.791–0.945) in model validation. The RNA model score was associated with disease severity and long-term survival (P = 4.66 × 10−6) in PAH. MR detected an association between SMAD5 levels and PAH disease susceptibility (odds ratio, 0.317; 95% confidence interval, 0.129–0.776; P = 0.012).Conclusions: A whole-blood RNA signature of PAH, which includes RNAs relevant to disease pathogenesis, associates with disease severity and identifies patients with poor clinical outcomes. Genetic variants associated with lower SMAD5 expression may increase susceptibility to PAH.

V Lagou, Reedik Magi, JJ Hottenga, Harald Grallert, John R. Perry, Nabila Bouatia-Naji, Letizia Marullo, Denis Rybin, R Jansen, JL Min, AS Dimas, ANNA ULRICH, LIUDMILA ZUDINA, Jesper R Gådin, Longda Jiang, Alessia Faggian, Amélie Bonnefond, Joao Fadista, Maria G Stathopoulou, Aaron Isaacs, SM Willems, Pau Navarro, T Tanaka, Anne U Jackson, May E Montasser, Jeff R O'Connell, Lawrence F Bielak, R. Webster, Richa Saxena, Jeanette M Stafford, Beate St Pourcain, Nicholas J. Timpson, Perttu Salo, SY Shin, Najaf Amin, Albert V Smith, Guo Li, Niek Verweij, Anuj Goel, Ian Ford, Paul C D Johnson, T Johnson, Karen Kapur, G Thorleifsson, RJ Strawbridge, Laura J Rasmussen-Torvik, Tõnu Esko, Evelin Mihailov, T Fall, Ross M Fraser, A Mahajan, Stavroula Kanoni, Vilmantas Giedraitis, ME Kleber, Günther Silbernagel, Julia Meyer, Martina Müller-Nurasyid, Andrea Ganna, Antti-Pekka Sarin, Loic Yengo, Dmitry Shungin, J Luan, Momoko Horikoshi, Ping An, S Sanna, Yvonne Boettcher, NW Rayner, Ilja M Nolte, Tatijana Zemunik, Erik van Iperen, Peter Kovacs, Nicholas D Hastie, SH Wild, Stela McLachlan, SS Campbell, Ozren Polasek, Olga Carlson, Josephine Egan, Wieland Kiess, G Willemsen, Johanna Kuusisto, Markku Laakso, Maria Dimitriou, A Hicks, Rainer Rauramaa, S Bandinelli, B Thorand, Yongmei Liu, Iva Miljkovic, L Lind, Alex Doney, M Perola, AD Hingorani, M Kivimäki, Meena Kumari, Amanda J Bennett, C Groves, C Herder, Heikki A Koistinen, Leena Kinnunen, Ulf de Faire, Stephan J L Bakker, Matti Uusitupa, Colin N. A Palmer, J Wouter Jukema, N Sattar, A Pouta, H Snieder, E Boerwinkle, James S Pankow, PK Magnusson, Ulrika Krus, Chiara Scapoli, Eco J C N de Geus, Matthias Blüher, Bruce H R Wolffenbuttel, Michael A Province, G Abecasis, James B Meigs, G Kees Hovingh, Jaana Lindström, James F Wilson, Alan F Wright, GV Dedoussis, Stefan R Bornstein, Peter E H Schwarz, Anke Tönjes, BR Winkelmann, B Boehm, W März, Andres Metspalu, Jackie F Price, P Deloukas, Antje Körner, Timo A. Lakka, Sirkka M Keinanen-Kiukaanniemi, Timo E Saaristo, Richard N Bergman, J Tuomilehto, N Wareham, Claudia Langenberg, S Männistö, Paul Franks, C Hayward, Veronique Vitart, J Kaprio, Sophie Visvikis-Siest, Beverley Balkau, D Altshuler, Igor Rudan, Michael Stumvoll, Harry Campbell, Cornelia van Duijn, C Gieger, T Illig, L Ferrucci, NL Pedersen, Peter P Pramstaller, Michael Boehnke, Timothy M. Frayling, AR Shuldiner, Patricia A Peyser, Sharon L R Kardia, Lyle J. Palmer, BW Penninx, Pierre Meneton, T Harris, G Navis, Pim van der Harst, George Davey Smith, NG Forouhi, Ruth J F Loos, V Salomaa, N Soranzo, D Boomsma, Leif Groop, Tiinamaija Tuomi, Albert Hofman, Patricia B. Munroe, V Gudnason, DS Siscovick, H Watkins, Cecile Lecoeur, P Vollenweider, A Franco-Cereceda, P Eriksson, Marjo-Riitta Jarvelin, K Stefansson, A Hamsten, G Nicholson, Fredrik Karpe, ET Dermitzakis, C Lindgren, MI McCarthy, P Froguel, MARIKA KAAKINEN, VG Lyssenko, R Watanabe, E Ingelsson, Jose C Florez, J Dupuis, I Barroso, AP Morris, INGA PROKOPENKO (2021)Sex-dimorphic genetic effects and novel loci for fasting glucose and insulin variability, In: Publisher Correction: Sex-dimorphic genetic effects and novel loci for fasting glucose and insulin variability (Nature Communications, (2021), 12, 1, (24), 10.1038/s41467-020-19366-9) Nature Research

Differences between sexes contribute to variation in the levels of fasting glucose and insulin. Epidemiological studies established a higher prevalence of impaired fasting glucose in men and impaired glucose tolerance in women, however, the genetic component underlying this phenomenon is not established. We assess sex-dimorphic (73,089/50,404 women and 67,506/47,806 men) and sex-combined (151,188/105,056 individuals) fasting glucose/fasting insulin genetic effects via genome-wide association study meta-analyses in individuals of European descent without diabetes. Here we report sex dimorphism in allelic effects on fasting insulin at IRS1 and ZNF12 loci, the latter showing higher RNA expression in whole blood in women compared to men. We also observe sex-homogeneous effects on fasting glucose at seven novel loci. Fasting insulin in women shows stronger genetic correlations than in men with waist-to-hip ratio and anorexia nervosa. Furthermore, waist-to-hip ratio is causally related to insulin resistance in women, but not in men. These results position dissection of metabolic and glycemic health sex dimorphism as a steppingstone for understanding differences in genetic effects between women and men in related phenotypes.

Zhanna Balkhiiarova, Saqib Hassan, Marika Kaakinen, Harmen Draisma, Liudmila Zudina, Mohd A Ganie, Aafia Rashid, Zhanna Balkhiyarova, George S Kiran, Paris Vogazianos, Christos Shammas, Joseph Selvin, Athos Antoniades, Ayse Demirkan, Inga Prokopenko (2022)Bifidobacterium Is Enriched in Gut Microbiome of Kashmiri Women with Polycystic Ovary Syndrome, In: Genes13(2)

Polycystic ovary syndrome (PCOS) is a very common endocrine condition in women in India. Gut microbiome alterations were shown to be involved in PCOS, yet it is remarkably understudied in Indian women who have a higher incidence of PCOS as compared to other ethnic populations. During the regional PCOS screening program among young women, we recruited 19 drug naive women with PCOS and 20 control women at the Sher-i-Kashmir Institute of Medical Sciences, Kashmir, North India. We profiled the gut microbiome in faecal samples by 16S rRNA sequencing and included 40/58 operational taxonomic units (OTUs) detected in at least 1/3 of the subjects with relative abundance (RA) ≥ 0.1%. We compared the RAs at a family/genus level in PCOS/non-PCOS groups and their correlation with 33 metabolic and hormonal factors, and corrected for multiple testing, while taking the variation in day of menstrual cycle at sample collection, age and BMI into account. Five genera were significantly enriched in PCOS cases: , , and previously reported for PCOS , and confirmed by different statistical models. At the family level, the relative abundance of was enriched, whereas was decreased among cases. We observed increased relative abundance of and with higher fasting blood glucose levels, and and with larger hip, waist circumference, weight, and with lower prolactin levels. We also detected a novel association between and follicle-stimulating hormone levels and between and alkaline phosphatase, independently of the BMI of the participants. Our report supports that there is a relationship between gut microbiome composition and PCOS with links to specific reproductive health metabolic and hormonal predictors in Indian women.

ZHANNA BALKHIIAROVA, Arie Nouwen, Sonya S. Deschênes, Zhanna Balkhiyarova, Juan R Albertorio-Díaz, INGA PROKOPENKO, Norbert Schmitz (2021)Measurement invariance testing of the patient health questionnaire-9 (PHQ-9) across people with and without diabetes mellitus from the NHANES, EMHS and UK Biobank datasets, In: Journal of Affective Disorders292pp. 311-318 Elsevier B.V

Background The prevalence of depression is higher among those with diabetes than in the general population. The Patient Health Questionnaire (PHQ-9) is commonly used to assess depression in people with diabetes, but measurement invariance of the PHQ-9 across groups of people with and without diabetes has not yet been investigated. Methods Data from three independent cohorts from the USA (n=1,886 with diabetes, n=4,153 without diabetes), Quebec, Canada (n= 800 with diabetes, n= 2,411 without diabetes), and the UK (n=4,981 with diabetes, n=145,570 without diabetes), were used to examine measurement invariance between adults with and without diabetes. A series of multiple group confirmatory factor analyses were performed, with increasingly stringent model constraints applied to assess configural, equal thresholds, and equal thresholds and loadings invariance, respectively. One-factor and two-factor (somatic and cognitive-affective items) models were examined. Results Results demonstrated that the most stringent models, testing equal loadings and thresholds, had satisfactory model fit in the three cohorts for one-factor models (RMSEA = .063 or below and CFI = .978 or above) and two-factor models (RMSEA = .042 or below and CFI = .989 or above). Limitations Data were from Western countries only and we could not distinguish between type of diabetes. Conclusions Results provide support for measurement invariance between groups of people with and without diabetes, using either a one-factor or a two-factor model. While the two-factor solution has a slightly better fit, the one-factor solution is more parsimonious. Depending on research or clinical needs, both factor structures can be used.

Jared G. Maina, Vincent Pascat, Liudmila Zudina, Anna Ulrich, Igor Pupko, Amelie Bonnefond, Zhanna Balkhiyarova, Marika Kaakinen, Philippe Froguel, Inga Prokopenko (2023)Abdominal obesity is a more important causal risk factor for pancreatic cancer than overall obesity, In: European journal of human genetics : EJHG31(8)pp. 962-966 Springer Nature

Obesity and type 2 diabetes (T2D) are associated with increased risk of pancreatic cancer. Here we assessed the relationship between pancreatic cancer and two distinct measures of obesity, namely total adiposity, using BMI, versus abdominal adiposity, using BMI adjusted waist-to-hip ratio (WHRadjBMI) by utilising polygenic scores (PGS) and Mendelian randomisation (MR) analyses. We constructed z-score weighted PGS for BMI and WHRadjBMI using publicly available data and tested for their association with pancreatic cancer defined in UK biobank (UKBB). Using publicly available summary statistics, we then performed bi-directional MR analyses between the two obesity traits and pancreatic cancer. PGS(BMI) was significantly (multiple testing-corrected) associated with pancreatic cancer (OR[95%CI] = 1.0804[1.025-1.14], P = 0.0037). The significance of association declined after T2D adjustment (OR[95%CI] = 1.073[1.018-1.13], P = 0.00904). PGS(WHRadjBMI) association with pancreatic cancer was at the margin of statistical significance (OR[95%CI] = 1.047[0.99-1.104], P = 0.086). T2D adjustment effectively lost any suggestive association of PGS(WHRadjBMI) with pancreatic cancer (OR[95%CI] = 1.039[0.99-1.097], P = 0.14). MR analyses showed a nominally significant causal effect of WHRadjBMI on pancreatic cancer (OR[95%CI] = 1.00095[1.00011-1.0018], P = 0.027) but not for BMI on pancreatic cancer. Overall, we show that abdominal adiposity measured using WHRadjBMI, may be a more important causal risk factor for pancreatic cancer compared to total adiposity, with T2D being a potential driver of this relationship.

Ching-Ti Liu, Jordi Merino, Denis Rybin, Daniel DiCorpo, Kelly S Benke, Jennifer L Bragg-Gresham, Mickaël Canouil, Tanguy Corre, Harald Grallert, Aaron Isaacs, Zoltan Kutalik, Jari Lahti, Letizia Marullo, Carola Marzi, Laura J Rasmussen-Torvik, Ghislain Rocheleau, Rico Rueedi, Chiara Scapoli, Niek Verweij, Nicole Vogelzangs, Sara M Willems, Loïc Yengo, Stephan J L Bakker, John Beilby, Jennie Hui, Eero Kajantie, Martina Müller-Nurasyid, Wolfgang Rathmann, Beverley Balkau, Sven Bergmann, Johan G Eriksson, Jose C Florez, Philippe Froguel, Tamara Harris, Joseph Hung, Alan L James, Maryam Kavousi, Iva Miljkovic, Arthur W Musk, Lyle J Palmer, Annette Peters, Ronan Roussel, Pim van der Harst, Cornelia M van Duijn, Peter Vollenweider, Inês Barroso, Inga Prokopenko, Josée Dupuis, James B Meigs, Nabila Bouatia-Naji (2019)Genome-wide Association Study of Change in Fasting Glucose over time in 13,807 non-diabetic European Ancestry Individuals, In: Scientific reports9(1)9439pp. 9439-8

Type 2 diabetes (T2D) affects the health of millions of people worldwide. The identification of genetic determinants associated with changes in glycemia over time might illuminate biological features that precede the development of T2D. Here we conducted a genome-wide association study of longitudinal fasting glucose changes in up to 13,807 non-diabetic individuals of European descent from nine cohorts. Fasting glucose change over time was defined as the slope of the line defined by multiple fasting glucose measurements obtained over up to 14 years of observation. We tested for associations of genetic variants with inverse-normal transformed fasting glucose change over time adjusting for age at baseline, sex, and principal components of genetic variation. We found no genome-wide significant association (P 

James E D Thaventhiran, Hana Lango Allen, Oliver S Burren, William Rae, Daniel Greene, Emily Staples, Zinan Zhang, James H R Farmery, Ilenia Simeoni, Elizabeth Rivers, Jesmeen Maimaris, Christopher J Penkett, Jonathan Stephens, Sri V V Deevi, Alba Sanchis-Juan, Nicholas S Gleadall, Moira J Thomas, Ravishankar B Sargur, Pavels Gordins, Helen E Baxendale, Matthew Brown, Paul Tuijnenburg, Austen Worth, Steven Hanson, Rachel J Linger, Matthew S Buckland, Paula J Rayner-Matthews, Kimberly C Gilmour, Crina Samarghitean, Suranjith L Seneviratne, David M Sansom, Andy G Lynch, Karyn Megy, Eva Ellinghaus, David Ellinghaus, Silje F Jorgensen, Tom H Karlsen, Kathleen E Stirrups, Antony J Cutler, Dinakantha S Kumararatne, Anita Chandra, J David M Edgar, Archana Herwadkar, Nichola Cooper, Sofia Grigoriadou, Aarnoud P Huissoon, Sarah Goddard, Stephen Jolles, Catharina Schuetz, Felix Boschann, Paul A Lyons, Matthew E Hurles, Sinisa Savic, Siobhan O Burns, Taco W Kuijpers, Ernest Turro, Willem H Ouwehand, Adrian J Thrasher, Kenneth G C Smith, Inga Prokopenko (2020)Publisher Correction: Whole-genome sequencing of a sporadic primary immunodeficiency cohort, In: Nature (London)584(7819)pp. E2-E2

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Tom A. Bond, Ville Karhunen, Matthias Wielscher, Juha Auvinen, Minna Mannikko, Sirkka Keinanen-Kiukaanniemi, Marc J. Gunter, Janine F. Felix, Inga Prokopenko, Jian Yang, Peter M. Visscher, David M. Evans, Sylvain Sebert, Alex Lewin, Paul F. O'Reilly, Debbie A. Lawlor, Marjo-Riitta Jarvelin (2020)Exploring the role of genetic confounding in the association between maternal and offspring body mass index: evidence from three birth cohorts, In: International journal of epidemiology49(1)pp. 233-243 Oxford Univ Press

Background: Maternal pre-pregnancy body mass index (BMI) is positively associated with offspring birth weight (BW) and BMI in childhood and adulthood. Each of these associations could be due to causal intrauterine effects, or confounding (genetic or environmental), or some combination of these. Here we estimate the extent to which the association between maternal BMI and offspring body size is explained by offspring genotype, as a first step towards establishing the importance of genetic confounding. Methods: We examined the associations of maternal pre-pregnancy BMI with offspring BW and BMI at 1, 5, 10 and 15 years, in three European birth cohorts (n

Gabriel Cuellar-Partida, Joyce Y. Tung, Nicholas Eriksson, Eva Albrecht, Fazil Aliev, Ole A. Andreassen, Ines Barroso, Jacques S. Beckmann, Marco P. Boks, Dorret I. Boomsma, Heather A. Boyd, Monique M. B. Breteler, Harry Campbell, Daniel I. Chasman, Lynn F. Cherkas, Gail Davies, Eco J. C. de Geus, Ian J. Deary, Panos Deloukas, Danielle M. Dick, David L. Duffy, Johan G. Eriksson, Tonu Esko, Bjarke Feenstra, Frank Geller, Christian Gieger, Ina Giegling, Scott D. Gordon, Jiali Han, Thomas F. Hansen, Annette M. Hartmann, Caroline Hayward, Kauko Heikkila, Andrew A. Hicks, Joel N. Hirschhorn, Jouke-Jan Hottenga, Jennifer E. Huffman, Liang-Dar Hwang, M. Arfan Ikram, Jaakko Kaprio, John P. Kemp, Kay-Tee Khaw, Norman Klopp, Bettina Konte, Zoltan Kutalik, Jari Lahti, Xin Li, Ruth J. F. Loos, Michelle Luciano, Sigurdur H. Magnusson, Massimo Mangino, Pedro Marques-Vidal, Nicholas G. Martin, Wendy L. McArdle, Mark I. McCarthy, Carolina Medina-Gomez, Mads Melbye, Scott A. Melville, Andres Metspalu, Lili Milani, Vincent Mooser, Mari Nelis, Dale R. Nyholt, Kevin S. O'Connell, Roel A. Ophoff, Cameron Palmer, Aarno Palotie, Teemu Palviainen, Guillaume Pare, Lavinia Paternoster, Leena Peltonen, Brenda W. J. H. Penninx, Ozren Polasek, Peter P. Pramstaller, Inga Prokopenko, Katri Raikkonen, Samuli Ripatti, Fernando Rivadeneira, Igor Rudan, Dan Rujescu, Johannes H. Smit, George Davey Smith, Jordan W. Smoller, Nicole Soranzo, Tim D. Spector, Beate St Pourcain, John M. Starr, Hreinn Stefansson, Stacy Steinberg, Maris Teder-Laving, Gudmar Thorleifsson, Kari Stefansson, Nicholas J. Timpson, Andre G. Uitterlinden, Cornelia M. van Duijn, Frank J. A. van Rooij, Jaqueline M. Vink, Peter Vollenweider, Eero Vuoksimaa, Gerard Waeber, Nicholas J. Wareham, Nicole Warrington, Dawn Waterworth, Thomas Werge, H. -Erich Wichmann, Elisabeth Widen, Gonneke Willemsen, Alan F. Wright, Margaret J. Wright, Mousheng Xu, Jing Hua Zhao, Peter Kraft, David A. Hinds, Cecilia M. Lindgren, Reedik Magi, Benjamin M. Neale, David M. Evans, Sarah E. Medland (2021)Genome-wide association study identifies 48 common genetic variants associated with handedness, In: Nature human behaviour5(1)pp. 59-70 NATURE PORTFOLIO

Handedness has been extensively studied because of its relationship with language and the over-representation of left-handers in some neurodevelopmental disorders. Using data from the UK Biobank, 23andMe and the International Handedness Consortium, we conducted a genome-wide association meta-analysis of handedness (N = 1,766,671). We found 41 loci associated (P < 5 x 10(-8)) with left-handedness and 7 associated with ambidexterity. Tissue-enrichment analysis implicated the CNS in the aetiology of handedness. Pathways including regulation of microtubules and brain morphology were also highlighted. We found suggestive positive genetic correlations between left-handedness and neuropsychiatric traits, including schizophrenia and bipolar disorder. Furthermore, the genetic correlation between left-handedness and ambidexterity is low (r(G) = 0.26), which implies that these traits are largely influenced by different genetic mechanisms. Our findings suggest that handedness is highly polygenic and that the genetic variants that predispose to left-handedness may underlie part of the association with some psychiatric disorders. A genome-wide association study of 1.7 million individuals identified 41 genetic variants associated with left-handedness and 7 associated with ambidexterity. The genetic correlation between the traits was low, thereby implying different aetiologies.

Alexessander Da Silva Couto Alves, N. Maneka G. De Silva, Ville Karhunen, Ulla Sovio, Shikta Das, H. Rob Taal, Nicole M. Warrington, Alexandra M. Lewin, Marika Kaakinen, Diana L. Cousminer, Elisabeth Thiering, Nicholas J. Timpson, Tom A. Bond, Estelle Lowry, Christopher D. Brown, Xavier Estivill, Virpi Lindi, Jonathan P. Bradfield, Frank Geller, Doug Speed, Lachlan J. M. Coin, Marie Loh, Sheila J. Barton, Lawrence J. Beilin, Hans Bisgaard, Klaus Bonnelykke, Rohia Alili, Ida J. Hatoum, Katharina Schramm, Rufus Cartwright, Marie-Aline Charles, Vincenzo Salerno, Karine Clement, Annique A.J Claringbould, BIOS Consortium, Cornelia M. van Duijin, Elena Moltchanova, Johan G. Eriksson, Cathy Elks, Bjarke Feenstra, Claudia Flexeder, Stephen Franks, Timothy M. Frayling, Rachel M. Freathy, Paul Elliot, Elisabeth Widen, Hakon Hakonarson, Andrew T. Hattersley, Alina Rodriguez, Marco Banterle, Joachim Heinrich, Barbara Heude, John W. Holloway, Albert Hofman, Elina Hypponen, Hazel Inskip, Lee M. Kaplan, Asa K. Hedman, Esa Laara, Holger Prokisch, Harald Grallert, Timo A. Lakka, Debbie A. Lawlor, Mads Melbye, Tarunveer S. Ahluwalia, Marcella Marinelli, Iona Y. Millwood, Lyle J. Palmer, Craig E. Pennell, John R. Perry, Susan M. Ring, Markku J. Savolainen, Fernando Rivadeneira, Marie Standl, Jordi Sunyer, Carla M.T Tiesler, Andre G. Uitterlinden, William Schierding, Justin M. O'Sullivan, Inga Prokopenko, Karl-Heinz Herzig, George Davey Smith, Paul O'Reilly, Janine F. Felix, Jessica L. Buxton, Alexandra L. F Blakemore, Ken K. Ong, Vincent W.V Jaddoe, Struan F.A Grant, Sylvain Sebert, Mark L. McCarthy, Marjo-Riitta Jarvelin (2019)GWAS on longitudinal growth traits reveals different genetic factors influencing infant, child, and adult BMI, In: Science Advances5(9) American Association for the Advancement of Science

Early childhood growth patterns are associated with adult health, yet the genetic factors and the developmental stages involved are not fully understood. Here, we combine genome-wide association studies with modeling of longitudinal growth traits to study the genetics of infant and child growth, followed by functional, pathway, genetic correlation, risk score, and colocalization analyses to determine how developmental timings, molecular pathways, and genetic determinants of these traits overlap with those of adult health. We found a robust overlap between the genetics of child and adult body mass index (BMI), with variants associated with adult BMI acting as early as 4 to 6 years old. However, we demonstrated a completely distinct genetic makeup for peak BMI during infancy, influenced by variation at the LEPR/LEPROT locus. These findings suggest that different genetic factors control infant and child BMI. In light of the obesity epidemic, these findings are important to inform the timing and targets of prevention strategies.

Francesca Forzano, Olga Antonova, Angus Clarke, Guido de Wert, Sabine Hentze, Yalda Jamshidi, Yves Moreau, M Perola, Inga Prokopenko, Andrew Read, A Reymond, Vigdis Stefansdottir, Carla van El, Maurizio Genuardi (2021)The use of polygenic risk scores in pre-implantation genetic testing: an unproven, unethical practice, In: European Journal of Human Genetics Springer Nature

Polygenic risk score analyses on embryos (PGT-P) are being marketed by some private testing companies to parents using in vitro fertilisation as being useful in selecting the embryos that carry the least risk of disease in later life. It appears that at least one child has been born after such a procedure. But the utility of a PRS in this respect is severely limited, and to date, no clinical research has been performed to assess its diagnostic effectiveness in embryos. Patients need to be properly informed on the limitations of this use of PRSs, and a societal debate, focused on what would be considered acceptable with regard to the selection of individual traits, should take place before any further implementation of the technique in this population.

INGA PROKOPENKO, Gentaro Miyakawa, Bang Zheng, Jani Heikkinen, Daniela Petrova Quayle, Chinedu Udeh-Momoh, Annique Claringbould, Juliane Neumann, Hazal Haytural, MARIKA KAAKINEN, Elena Loizidou, EM Meissner, Lars Bertram, Djordje O Gveric, Steve M Gentleman, Johannes Attems, Robert Perneczky, Thomas Arzberger, Pierandrea Muglia, Christina M Lill, Laura Parkkinen, Lefkos T Middleton (2019)Alzheimer's disease pathology explains association between dementia with Lewy bodies and APOE-ε4/TOMM40 long poly-T repeat allele variants, In: Alzheimer's and Dementia: Translational Research and Clinical Interventions5(1)pp. 814-824 Wiley Open Access

Introduction The role of TOMM40-APOE 19q13.3 region variants is well documented in Alzheimer's disease (AD) but remains contentious in dementia with Lewy bodies (DLB) and Parkinson's disease dementia (PDD). Methods We dissected genetic profiles within the TOMM40-APOE region in 451 individuals from four European brain banks, including DLB and PDD cases with/without neuropathological evidence of AD-related pathology and healthy controls. Results TOMM40-L/APOE-ε4 alleles were associated with DLB (ORTOMM40-L = 3.61; P value = 3.23 × 10−9; ORAPOE-ε4 = 3.75; P value = 4.90 × 10−10) and earlier age at onset of DLB (HRTOMM40-L = 1.33, P value = .031; HRAPOE-ε4 = 1.46, P value = .004), but not with PDD. The TOMM40-L/APOE-ε4 effect was most pronounced in DLB individuals with concomitant AD pathology (ORTOMM40-L = 4.40, P value = 1.15 × 10−6; ORAPOE-ε4 = 5.65, P value = 2.97 × 10−8) but was not significant in DLB without AD. Meta-analyses combining all APOE-ε4 data in DLB confirmed our findings (ORDLB = 2.93, P value = 3.78 × 10−99; ORDLB+AD = 5.36, P value = 1.56 × 10−47). Discussion APOE-ε4/TOMM40-L alleles increase susceptibility and risk of earlier DLB onset, an effect explained by concomitant AD-related pathology. These findings have important implications in future drug discovery and development efforts in DLB.

Alexey Rayevsky, Dmytro Sirokha, Dariia Samofalova, Dmytro Lozhko, Olexandra Gorodna, INGA PROKOPENKO, Liudmyla Livshits (2021)Functional Effects In Silico Prediction for Androgen Receptor Ligand-Binding Domain Novel I836S Mutation, In: Life (Basel)11(7) MDPI

Over 1000 mutations are described in the androgen receptor (AR) gene. Of those, about 600 were found in androgen insensitivity syndrome (AIS) patients, among which 400 mutations affect the ligand-binding domain (LBD) of the AR protein. Recently, we reported a novel missense mutation c.2507T>G I836S (ClinVarID: 974911) in a patient with complete AIS (CAIS) phenotype. In the present study, we applied a set of computational approaches for the structural analysis of the ligand-binding domains in a wild-type and mutant AR to evaluate the functional impact of the novel I836S mutation. We revealed that the novel I836S substitution leads to a shorter existence time of the ligand’s gating tunnel and internal cavity, occurring only in the presence of S836 phosphorylation. Additionally, the analysis of phosphorylation of the 836 mutant residues explained the negative impact on AR homodimerization, since monomer surface changes indirectly impacted the binding site. Our analyses provide evidence that I836S causes disruptions of AR protein functionality and development of CAIS clinical features in patients.

Christopher Hübel, Héléna A Gaspar, Jonathan R I Coleman, Ken B Hanscombe, Kirstin Purves, INGA PROKOPENKO, Mariaelisa Graff, Julius S Ngwa, Tsegaselassie Workalemahu, Paul O'Reilly, Cynthia M Bulik, Gerome Breen (2019)Genetic correlations of psychiatric traits with body composition and glycemic traits are sex- and age-dependent, In: Nature communications105765 Nature Research

Body composition is often altered in psychiatric disorders. Using genome-wide common genetic variation data, we calculate sex-specific genetic correlations amongst body fat %, fat mass, fat-free mass, physical activity, glycemic traits and 17 psychiatric traits (up to N = 217,568). Two patterns emerge: (1) anorexia nervosa, schizophrenia, obsessive-compulsive disorder, and education years are negatively genetically correlated with body fat % and fat-free mass, whereas (2) attention-deficit/hyperactivity disorder (ADHD), alcohol dependence, insomnia, and heavy smoking are positively correlated. Anorexia nervosa shows a stronger genetic correlation with body fat % in females, whereas education years is more strongly correlated with fat mass in males. Education years and ADHD show genetic overlap with childhood obesity. Mendelian randomization identifies schizophrenia, anorexia nervosa, and higher education as causal for decreased fat mass, with higher body fat % possibly being a causal risk factor for ADHD and heavy smoking. These results suggest new possibilities for targeted preventive strategies.

ANNA ULRICH, Pablo Otero-Núñez, John Wharton, Emilia M Swietlik, Stefan Gräf, N Morrell, D Wang, Allan Lawrie, Martin R Wilkins, INGA PROKOPENKO, Christopher J Rhodes (2020)Expression Quantitative Trait Locus Mapping in Pulmonary Arterial Hypertension, In: Genes11(11)1247 MDPI

Expression quantitative trait loci (eQTL) can provide a link between disease susceptibility variants discovered by genetic association studies and biology. To date, eQTL mapping studies have been primarily conducted in healthy individuals from population-based cohorts. Genetic effects have been known to be context-specific and vary with changing environmental stimuli. We conducted a transcriptome- and genome-wide eQTL mapping study in a cohort of patients with idiopathic or heritable pulmonary arterial hypertension (PAH) using RNA sequencing (RNAseq) data from whole blood. We sought confirmation from three published population-based eQTL studies, including the GTEx Project, and followed up potentially novel eQTL not observed in the general population. In total, we identified 2314 eQTL of which 90% were cis-acting and 75% were confirmed by at least one of the published studies. While we observed a higher GWAS trait colocalization rate among confirmed eQTL, colocalisation rate of novel eQTL reported for lung-related phenotypes was twice as high as that of confirmed eQTL. Functional enrichment analysis of genes with novel eQTL in PAH highlighted immune-related processes, a suspected contributor to PAH. These potentially novel eQTL specific to or active in PAH could be useful in understanding genetic risk factors for other diseases that share common mechanisms with PAH.

Angélique Sadlon, Petros Takousis, Panagiotis Alexopoulos, Evangelos Evangelou, Inga Prokopenko, Robert Perneczky (2019)miRNAs Identify Shared Pathways in Alzheimer’s and Parkinson’s Diseases, In: Trends in Molecular Medicine25(8)pp. 662-672 Elsevier

Despite the identification of several dozens of common genetic variants associated with Alzheimer’s disease (AD) and Parkinson’s disease (PD), most of the genetic risk remains uncharacterised. Therefore, it is important to understand the role of regulatory elements, such as miRNAs. Dysregulated miRNAs are implicated in AD and PD, with potential value in dissecting the shared pathophysiology between the two disorders. miRNAs relevant to both neurodegenerative diseases are related to axonal guidance, apoptosis, and inflammation, therefore, AD and PD likely arise from similar underlying biological pathway defects. Furthermore, pathways regulated by APP, L1CAM, and genes of the caspase family may represent promising therapeutic miRNA targets in AD and PD since they are targeted by dysregulated miRNAs in both disorders. Systematic reviews and meta-analyses clearly identify sets of miRNAs that are dysregulated in AD and postmortem brain samples from patients with PD.Given the central role of miRNAs in neuronal function and the close link between select miRNAs and key pathological processes in AD and PD, it was proposed that this information could be used to better understand the shared pathobiology of the two disorders.It was suggested that miRNA changes are cell type specific and the shifting balance between different cell populations as neurodegeneration advances may be important when miRNAs are considered as diagnostic or therapeutic targets.Similar evidence in other disease areas, such as cancer, has successfully been applied to develop more effective strategies for early detection and disease-modifying interventions.

ZHANNA BALKHIIAROVA, Yanina R Timasheva, Zhanna Balkhiyarova, Timur R Nasibullin, Diana Sh Avzaletdinova, Tatiana V Morugova, Olga E Mustafina, INGA PROKOPENKO (2019)Multilocus associations of inflammatory genes with the risk of type 1 diabetes, In: Gene707pp. 1-8 Elsevier B.V

Background Genome-wide association studies have captured a large proportion of genetic variation related to type 1 diabetes mellitus (T1D). However, most of these studies are performed in populations of European ancestry and therefore the disease risk estimations can be inaccurate when extrapolated to other world populations. Methods We conducted a case-control study in 1866 individuals from the three major populations of the Republic of Bashkortostan (Russians, Tatars, and Bashkirs) in Russian Federation, using single-locus and multilocus approach to identify genetic predictors of T1D. Results We found that LTA rs909253 and TNF rs1800629 polymorphisms were associated with T1D in the group of Tatars. Meta-analysis of the association study results in the three ethnic groups has confirmed the association between the T1D risk and LTA rs909253 genetic variant. LTA rs909253 and TNF rs1800629 loci were also featured in combinations most significantly associated with T1D. Conclusion Our findings suggest that LTA rs909253 and TNF rs1800629 polymorphisms are associated with the risk of T1D both independently and in combination with polymorphic markers in other inflammatory genes, and the analysis of multi-allelic combinations provides valuable insight in the study of polygenic traits.