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1. Urban environment in pregnancy and postpartum depression: An individual participant data meta-analysis of 12 European birth cohorts

Author

Tim Cadman, Katrine Strandberg-Larsen, Lucinda Calas, Malina Christiansen, Iryna Culpin, Payam Dadvand, Montserrat de Castro, Maria Foraster, Serena Fossati, Mònica Guxens, Jennifer R. Harris, Manon Hillegers, Vincent Jaddoe, Yunsung Lee, Johanna Lepeule, Hanan el Marroun, Milena Maule, Rosie McEachen, Chiara Moccia, Johanna Nader, Mark Nieuwenhuijsen, Anne-Marie Nybo Andersen, Rebecca Pearson, Morris Swertz, Marina Vafeiadi, Martine Vrijheid, John Wright, Deborah A Lawlor, and Marie Pedersen

Subjects
Postpartum depression, Ambient air pollution, Natural spaces, Traffic noise, Urban, Built environment, Environmental sciences, GE1-350
Abstract

Background: Urban environmental exposures associate with adult depression, but it is unclear whether they are associated to postpartum depression (PPD). Objectives: We investigated associations between urban environment exposures during pregnancy and PPD. Methods: We included women with singleton deliveries to liveborn children from 12 European birth cohorts (N with minimum one exposure = 30,772, analysis N range 17,686–30,716 depending on exposure; representing 26–46 % of the 66,825 eligible women). We estimated maternal exposure during pregnancy to ambient air pollution with nitrogen dioxide (NO2) and particulate matter (PM2.5 and PM10), road traffic noise (Lden), natural spaces (Normalised Difference Vegetation Index; NDVI, proximity to major green or blue spaces) and built environment (population density, facility richness and walkability). Maternal PPD was assessed 3–18 months after birth using self-completed questionnaires. We used adjusted logistic regression models to estimate cohort-specific associations between each exposure and PPD and combined results via meta-analysis using DataSHIELD. Results: Of the 30,772 women included, 3,078 (10 %) reported having PPD. Exposure to PM10 was associated with slightly increased odds of PPD (adjusted odd ratios (OR) of 1.08 [95 % Confidence Intervals (CI): 0.99, 1.17] per inter quartile range increment of PM10) whilst associations for exposure to NO2 and PM2.5 were close to null. Exposure to high levels of road traffic noise (≥65 dB vs.

Published
2024
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2. Comprehensive evaluation of smoking exposures and their interactions on DNA methylationResearch in context

Author

Thanh T. Hoang, Yunsung Lee, Daniel L. McCartney, Elin T.G. Kersten, Christian M. Page, Paige M. Hulls, Mikyeong Lee, Rosie M. Walker, Charles E. Breeze, Brian D. Bennett, Adam B. Burkholder, James Ward, Anne Lise Brantsæter, Ida H. Caspersen, Alison A. Motsinger-Reif, Marie Richards, Julie D. White, Shanshan Zhao, Rebecca C. Richmond, Maria C. Magnus, Gerard H. Koppelman, Kathryn L. Evans, Riccardo E. Marioni, Siri E. Håberg, Stephanie J. London, Bastiaan Heijmans, Peter ’t Hoen, Joyce van Meurs, Rick Jansen, Lude Franke, Dorret Boomsma, René Pool, Jenny van Dongen, Jouke Hottenga, Marleen van Greevenbroek, Coen Stehouwer, Carla van der Kallen, Casper Schalkwijk, Cisca Wijmenga, Sasha Zhernakova, Ettje Tigchelaar, P. Eline Slagboom, Marian Beekman, Joris Deelen, Diana Van Heemst, Jan Veldink, Leonard van den Berg, Cornelia van Duijn, Bert Hofman, Aaron Isaacs, André Uitterlinden, P. Mila Jhamai, Michael Verbiest, H. Eka Suchiman, Marijn Verkerk, Ruud van der Breggen, Jeroen van Rooij, Nico Lakenberg, Hailiang Mei, Maarten van Iterson, Michiel van Galen, Jan Bot, Dasha Zhernakova, Peter van ‘t Hof, Patrick Deelen, Irene Nooren, Matthijs Moed, Martijn Vermaat, René Luijk, Marc Bonder, Freerk van Dijk, Wibowo Arindrarto, Szymon Kielbasa, Morris Swertz, and Erik van Zwet

Subjects
Illumina EPIC array, Epigenomics, Secondhand smoke exposure, Dietary intake, Sex difference, Smoking cessation, Medicine, Medicine (General), R5-920
Abstract

Summary: Background: Smoking impacts DNA methylation, but data are lacking on smoking-related differential methylation by sex or dietary intake, recent smoking cessation (

Published
2024
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3. Curation and expansion of the Human Phenotype Ontology for systemic autoinflammatory diseases improves phenotype-driven disease-matching

Author

Willem Maassen, Geertje Legger, Ovgu Kul Cinar, Paul van Daele, Marco Gattorno, Brigitte Bader-Meunier, Carine Wouters, Tracy Briggs, Lennart Johansson, Joeri van der Velde, Morris Swertz, Ebun Omoyinmi, Esther Hoppenreijs, Alexandre Belot, Despina Eleftheriou, Roberta Caorsi, Florence Aeschlimann, Guilaine Boursier, Paul Brogan, Matthias Haimel, and Marielle van Gijn

Subjects
Human Phenotype Ontology (HPO), systemic autoinflammatory disorders (SAIDs), genome diagnostics, variant interpretation, whole exome sequencing (WES), LIRICAL, Immunologic diseases. Allergy, RC581-607
Abstract

IntroductionAccurate and standardized phenotypic descriptions are essential in diagnosing rare diseases and discovering new diseases, and the Human Phenotype Ontology (HPO) system was developed to provide a rich collection of hierarchical phenotypic descriptions. However, although the HPO terms for inborn errors of immunity have been improved and curated, it has not been investigated whether this curation improves the diagnosis of systemic autoinflammatory disease (SAID) patients. Here, we aimed to study if improved HPO annotation for SAIDs enhanced SAID identification and to demonstrate the potential of phenotype-driven genome diagnostics using curated HPO terms for SAIDs.MethodsWe collected HPO terms from 98 genetically confirmed SAID patients across eight different European SAID expertise centers and used the LIRICAL (Likelihood Ratio Interpretation of Clinical Abnormalities) computational algorithm to estimate the effect of HPO curation on the prioritization of the correct SAID for each patient.ResultsOur results show that the percentage of correct diagnoses increased from 66% to 86% and that the number of diagnoses with the highest ranking increased from 38 to 45. In a further pilot study, curation also improved HPO-based whole-exome sequencing (WES) analysis, diagnosing 10/12 patients before and 12/12 after curation. In addition, the average number of candidate diseases that needed to be interpreted decreased from 35 to 2.DiscussionThis study demonstrates that curation of HPO terms can increase identification of the correct diagnosis, emphasizing the high potential of HPO-based genome diagnostics for SAIDs.

Published
2023
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4. Deconvolution of bulk blood eQTL effects into immune cell subpopulations

Author

Raúl Aguirre-Gamboa, Niek de Klein, Jennifer di Tommaso, Annique Claringbould, Monique GP van der Wijst, Dylan de Vries, Harm Brugge, Roy Oelen, Urmo Võsa, Maria M. Zorro, Xiaojin Chu, Olivier B. Bakker, Zuzanna Borek, Isis Ricaño-Ponce, Patrick Deelen, Cheng-Jiang Xu, Morris Swertz, Iris Jonkers, Sebo Withoff, Irma Joosten, Serena Sanna, Vinod Kumar, Hans J. P. M. Koenen, Leo A. B. Joosten, Mihai G. Netea, Cisca Wijmenga, BIOS Consortium, Lude Franke, and Yang Li

Subjects
eQTL, Deconvolution, Cell types, Immune cells, Computer applications to medicine. Medical informatics, R858-859.7, Biology (General), QH301-705.5
Abstract

Abstract Background Expression quantitative trait loci (eQTL) studies are used to interpret the function of disease-associated genetic risk factors. To date, most eQTL analyses have been conducted in bulk tissues, such as whole blood and tissue biopsies, which are likely to mask the cell type-context of the eQTL regulatory effects. Although this context can be investigated by generating transcriptional profiles from purified cell subpopulations, current methods to do this are labor-intensive and expensive. We introduce a new method, Decon2, as a framework for estimating cell proportions using expression profiles from bulk blood samples (Decon-cell) followed by deconvolution of cell type eQTLs (Decon-eQTL). Results The estimated cell proportions from Decon-cell agree with experimental measurements across cohorts (R ≥ 0.77). Using Decon-cell, we could predict the proportions of 34 circulating cell types for 3194 samples from a population-based cohort. Next, we identified 16,362 whole-blood eQTLs and deconvoluted cell type interaction (CTi) eQTLs using the predicted cell proportions from Decon-cell. CTi eQTLs show excellent allelic directional concordance with eQTL (≥ 96–100%) and chromatin mark QTL (≥87–92%) studies that used either purified cell subpopulations or single-cell RNA-seq, outperforming the conventional interaction effect. Conclusions Decon2 provides a method to detect cell type interaction effects from bulk blood eQTLs that is useful for pinpointing the most relevant cell type for a given complex disease. Decon2 is available as an R package and Java application ( https://github.com/molgenis/systemsgenetics/tree/master/Decon2 ) and as a web tool ( www.molgenis.org/deconvolution ).

Published
2020
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5. Lack of Association Between Genetic Variants at ACE2 and TMPRSS2 Genes Involved in SARS-CoV-2 Infection and Human Quantitative Phenotypes

Author

Esteban A. Lopera Maya, Adriaan van der Graaf, Pauline Lanting, Marije van der Geest, Jingyuan Fu, Morris Swertz, Lude Franke, Cisca Wijmenga, Patrick Deelen, Alexandra Zhernakova, Serena Sanna, and Lifelines Cohort Study

Subjects
PheWAS, ACE2, TMPRSS2, NSAIDs (non-steroidal anti-inflammatory drugs), ARBs (angiotensin II receptor blockers), COVID-19, Genetics, QH426-470
Abstract

Coronavirus disease 2019 (COVID-19) shows a wide variation in expression and severity of symptoms, from very mild or no symptoms, to flu-like symptoms, and in more severe cases, to pneumonia, acute respiratory distress syndrome, and even death. Large differences in outcome have also been observed between males and females. The causes for this variability are likely to be multifactorial, and to include genetics. The SARS-CoV-2 virus responsible for the infection depends on two human genes: the human receptor angiotensin converting enzyme 2 (ACE2) for cell invasion, and the serine protease TMPRSS2 for S protein priming. Genetic variation in these two genes may thus modulate an individual's genetic predisposition to infection and virus clearance. While genetic data on COVID-19 patients is being gathered, we carried out a phenome-wide association scan (PheWAS) to investigate the role of these genes in other human phenotypes in the general population. We examined 178 quantitative phenotypes including cytokines and cardio-metabolic biomarkers, as well as usage of 58 medications in 36,339 volunteers from the Lifelines population cohort, in relation to 1,273 genetic variants located in or near ACE2 and TMPRSS2. While none reached our threshold for significance, we observed several interesting suggestive associations. For example, single nucleotide polymorphisms (SNPs) near the TMPRSS2 genes were associated with thrombocytes count (p = 1.8 × 10−5). SNPs within the ACE2 gene were associated with (1) the use of angiotensin II receptor blockers (ARBs) combination therapies (p = 5.7 × 10−4), an association that is significantly stronger in females (pdiff = 0.01), and (2) with the use of non-steroid anti-inflammatory and antirheumatic products (p = 5.5 × 10−4). While these associations need to be confirmed in larger sample sizes, they suggest that these variants could play a role in diseases such as thrombocytopenia, hypertension, and chronic inflammation that are often observed in the more severe COVID-19 cases. Further investigation of these genetic variants in the context of COVID-19 is thus promising for better understanding of disease variability. Full results are available at https://covid19research.nl.

Published
2020
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6. Impact of common genetic determinants of Hemoglobin A1c on type 2 diabetes risk and diagnosis in ancestrally diverse populations: A transethnic genome-wide meta-analysis.

Author

Eleanor Wheeler, Aaron Leong, Ching-Ti Liu, Marie-France Hivert, Rona J Strawbridge, Clara Podmore, Man Li, Jie Yao, Xueling Sim, Jaeyoung Hong, Audrey Y Chu, Weihua Zhang, Xu Wang, Peng Chen, Nisa M Maruthur, Bianca C Porneala, Stephen J Sharp, Yucheng Jia, Edmond K Kabagambe, Li-Ching Chang, Wei-Min Chen, Cathy E Elks, Daniel S Evans, Qiao Fan, Franco Giulianini, Min Jin Go, Jouke-Jan Hottenga, Yao Hu, Anne U Jackson, Stavroula Kanoni, Young Jin Kim, Marcus E Kleber, Claes Ladenvall, Cecile Lecoeur, Sing-Hui Lim, Yingchang Lu, Anubha Mahajan, Carola Marzi, Mike A Nalls, Pau Navarro, Ilja M Nolte, Lynda M Rose, Denis V Rybin, Serena Sanna, Yuan Shi, Daniel O Stram, Fumihiko Takeuchi, Shu Pei Tan, Peter J van der Most, Jana V Van Vliet-Ostaptchouk, Andrew Wong, Loic Yengo, Wanting Zhao, Anuj Goel, Maria Teresa Martinez Larrad, Dörte Radke, Perttu Salo, Toshiko Tanaka, Erik P A van Iperen, Goncalo Abecasis, Saima Afaq, Behrooz Z Alizadeh, Alain G Bertoni, Amelie Bonnefond, Yvonne Böttcher, Erwin P Bottinger, Harry Campbell, Olga D Carlson, Chien-Hsiun Chen, Yoon Shin Cho, W Timothy Garvey, Christian Gieger, Mark O Goodarzi, Harald Grallert, Anders Hamsten, Catharina A Hartman, Christian Herder, Chao Agnes Hsiung, Jie Huang, Michiya Igase, Masato Isono, Tomohiro Katsuya, Chiea-Chuen Khor, Wieland Kiess, Katsuhiko Kohara, Peter Kovacs, Juyoung Lee, Wen-Jane Lee, Benjamin Lehne, Huaixing Li, Jianjun Liu, Stephane Lobbens, Jian'an Luan, Valeriya Lyssenko, Thomas Meitinger, Tetsuro Miki, Iva Miljkovic, Sanghoon Moon, Antonella Mulas, Gabriele Müller, Martina Müller-Nurasyid, Ramaiah Nagaraja, Matthias Nauck, James S Pankow, Ozren Polasek, Inga Prokopenko, Paula S Ramos, Laura Rasmussen-Torvik, Wolfgang Rathmann, Stephen S Rich, Neil R Robertson, Michael Roden, Ronan Roussel, Igor Rudan, Robert A Scott, William R Scott, Bengt Sennblad, David S Siscovick, Konstantin Strauch, Liang Sun, Morris Swertz, Salman M Tajuddin, Kent D Taylor, Yik-Ying Teo, Yih Chung Tham, Anke Tönjes, Nicholas J Wareham, Gonneke Willemsen, Tom Wilsgaard, Aroon D Hingorani, EPIC-CVD Consortium, EPIC-InterAct Consortium, Lifelines Cohort Study, Josephine Egan, Luigi Ferrucci, G Kees Hovingh, Antti Jula, Mika Kivimaki, Meena Kumari, Inger Njølstad, Colin N A Palmer, Manuel Serrano Ríos, Michael Stumvoll, Hugh Watkins, Tin Aung, Matthias Blüher, Michael Boehnke, Dorret I Boomsma, Stefan R Bornstein, John C Chambers, Daniel I Chasman, Yii-Der Ida Chen, Yduan-Tsong Chen, Ching-Yu Cheng, Francesco Cucca, Eco J C de Geus, Panos Deloukas, Michele K Evans, Myriam Fornage, Yechiel Friedlander, Philippe Froguel, Leif Groop, Myron D Gross, Tamara B Harris, Caroline Hayward, Chew-Kiat Heng, Erik Ingelsson, Norihiro Kato, Bong-Jo Kim, Woon-Puay Koh, Jaspal S Kooner, Antje Körner, Diana Kuh, Johanna Kuusisto, Markku Laakso, Xu Lin, Yongmei Liu, Ruth J F Loos, Patrik K E Magnusson, Winfried März, Mark I McCarthy, Albertine J Oldehinkel, Ken K Ong, Nancy L Pedersen, Mark A Pereira, Annette Peters, Paul M Ridker, Charumathi Sabanayagam, Michele Sale, Danish Saleheen, Juha Saltevo, Peter Eh Schwarz, Wayne H H Sheu, Harold Snieder, Timothy D Spector, Yasuharu Tabara, Jaakko Tuomilehto, Rob M van Dam, James G Wilson, James F Wilson, Bruce H R Wolffenbuttel, Tien Yin Wong, Jer-Yuarn Wu, Jian-Min Yuan, Alan B Zonderman, Nicole Soranzo, Xiuqing Guo, David J Roberts, Jose C Florez, Robert Sladek, Josée Dupuis, Andrew P Morris, E-Shyong Tai, Elizabeth Selvin, Jerome I Rotter, Claudia Langenberg, Inês Barroso, and James B Meigs

Subjects
Medicine
Abstract

BackgroundGlycated hemoglobin (HbA1c) is used to diagnose type 2 diabetes (T2D) and assess glycemic control in patients with diabetes. Previous genome-wide association studies (GWAS) have identified 18 HbA1c-associated genetic variants. These variants proved to be classifiable by their likely biological action as erythrocytic (also associated with erythrocyte traits) or glycemic (associated with other glucose-related traits). In this study, we tested the hypotheses that, in a very large scale GWAS, we would identify more genetic variants associated with HbA1c and that HbA1c variants implicated in erythrocytic biology would affect the diagnostic accuracy of HbA1c. We therefore expanded the number of HbA1c-associated loci and tested the effect of genetic risk-scores comprised of erythrocytic or glycemic variants on incident diabetes prediction and on prevalent diabetes screening performance. Throughout this multiancestry study, we kept a focus on interancestry differences in HbA1c genetics performance that might influence race-ancestry differences in health outcomes.Methods & findingsUsing genome-wide association meta-analyses in up to 159,940 individuals from 82 cohorts of European, African, East Asian, and South Asian ancestry, we identified 60 common genetic variants associated with HbA1c. We classified variants as implicated in glycemic, erythrocytic, or unclassified biology and tested whether additive genetic scores of erythrocytic variants (GS-E) or glycemic variants (GS-G) were associated with higher T2D incidence in multiethnic longitudinal cohorts (N = 33,241). Nineteen glycemic and 22 erythrocytic variants were associated with HbA1c at genome-wide significance. GS-G was associated with higher T2D risk (incidence OR = 1.05, 95% CI 1.04-1.06, per HbA1c-raising allele, p = 3 × 10-29); whereas GS-E was not (OR = 1.00, 95% CI 0.99-1.01, p = 0.60). In Europeans and Asians, erythrocytic variants in aggregate had only modest effects on the diagnostic accuracy of HbA1c. Yet, in African Americans, the X-linked G6PD G202A variant (T-allele frequency 11%) was associated with an absolute decrease in HbA1c of 0.81%-units (95% CI 0.66-0.96) per allele in hemizygous men, and 0.68%-units (95% CI 0.38-0.97) in homozygous women. The G6PD variant may cause approximately 2% (N = 0.65 million, 95% CI 0.55-0.74) of African American adults with T2D to remain undiagnosed when screened with HbA1c. Limitations include the smaller sample sizes for non-European ancestries and the inability to classify approximately one-third of the variants. Further studies in large multiethnic cohorts with HbA1c, glycemic, and erythrocytic traits are required to better determine the biological action of the unclassified variants.ConclusionsAs G6PD deficiency can be clinically silent until illness strikes, we recommend investigation of the possible benefits of screening for the G6PD genotype along with using HbA1c to diagnose T2D in populations of African ancestry or groups where G6PD deficiency is common. Screening with direct glucose measurements, or genetically-informed HbA1c diagnostic thresholds in people with G6PD deficiency, may be required to avoid missed or delayed diagnoses.

Published
2017
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7. Deleterious alleles in the human genome are on average younger than neutral alleles of the same frequency.

Author

Adam Kiezun, Sara L Pulit, Laurent C Francioli, Freerk van Dijk, Morris Swertz, Dorret I Boomsma, Cornelia M van Duijn, P Eline Slagboom, G J B van Ommen, Cisca Wijmenga, Genome of the Netherlands Consortium, Paul I W de Bakker, and Shamil R Sunyaev

Subjects
Genetics, QH426-470
Abstract

Large-scale population sequencing studies provide a complete picture of human genetic variation within the studied populations. A key challenge is to identify, among the myriad alleles, those variants that have an effect on molecular function, phenotypes, and reproductive fitness. Most non-neutral variation consists of deleterious alleles segregating at low population frequency due to incessant mutation. To date, studies characterizing selection against deleterious alleles have been based on allele frequency (testing for a relative excess of rare alleles) or ratio of polymorphism to divergence (testing for a relative increase in the number of polymorphic alleles). Here, starting from Maruyama's theoretical prediction (Maruyama T (1974), Am J Hum Genet USA 6:669-673) that a (slightly) deleterious allele is, on average, younger than a neutral allele segregating at the same frequency, we devised an approach to characterize selection based on allelic age. Unlike existing methods, it compares sets of neutral and deleterious sequence variants at the same allele frequency. When applied to human sequence data from the Genome of the Netherlands Project, our approach distinguishes low-frequency coding non-synonymous variants from synonymous and non-coding variants at the same allele frequency and discriminates between sets of variants independently predicted to be benign or damaging for protein structure and function. The results confirm the abundance of slightly deleterious coding variation in humans.

Published
2013
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8. The impact of dedicated FAIRification stewardship guiding European Reference Networks towards making rare disease resources FAIR

Author

Bruna dos Santos Vieira, Inês Henriques, César Henriques Bernabé, Shuxin Zhang, Alberto Cámara Ballesteros, Jose Antonio Ramírez García, Joeri van der Velde, Nirupama Benis, Peter 't Hoen, Marco Roos, Annika Jacobsen, Ronald Cornet, Mark Wilkinson, Franz Schaefer, and Morris Swertz

Subjects
European Reference Networks, Patient Registries, FAIR
Abstract

The EJP RD stewards' team was established in July 2020 to support European Reference Networks (ERNs) in creating Findable, Accessible, Interoperable and Reusable (FAIR) patient registries. To track the evolving registry FAIR implementations, the steward's team collected the ERNs' reported updates in an implementation status inventory. We here analyze the progress registered to understand the impact of the team's approach on supporting ERNs. The team conducted two rounds of online interviews in 2020 and 2021 to collect the ERNs implementation status. Prior to the interview, they sent ERNs an inventory structured into five phases: a) data modelling; b) data collection; c) registering the registry; d) data accessibility, e) Data querying; and instructed ERNs to fill it using the terminology "Implemented", "Implementing assisted by expert", "Plans to Implement", "Needs Expert help" and "Not applicable". From a total of 24 ERNs, 20 completed the inventory. The results indicate an increase in the number of FAIR tools implemented from 2020 (32.6%) to 2021 (56.0%). Additionally, the percentage of tools that shifted from "Plans to implement" or "Needs expert help" to "Implemented" in 2021 were, respectively, 35.8% and 18.8%. In both years, the most significant increases in implemented tools are related to the modelling phase - 17.3% in 2020 and 29.2% in 2021 - and "making data accessible for querying" - 5.2% in 2020 to 13.2% in 2021. Out of all five stages, the tools more frequently marked as "Plans to Implement" in 2020 concerned the modelling phase (9.8%), which in 2021 decreased to 4.6%. Changes in staff and different people completing the inventory are limitations of this analysis, as they could result in different interpretations of categorizing the tools and, occasionally, the loss of reported evolution. Regardless, the joint approach between ERNs and Stewards appears to have resulted in more implemented tools, mainly in the modelling stage. It also allows prioritizing future efforts on accessibility and discoverability for querying, and data reuse. We expect the number of implemented tools to plateau and the tools planned for implementation or needing expert help to decrease as a result of the ERNs learning more about the options for FAIR data.&nbsp

Published
2023
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9. Critical steps towards large-scale implementation of the FAIR data principles

Author

Bruna dos Santos Vieira, César Henrique Bernabé, Ines Henriques, Shuxin Zhang, Alberto Ballasteros Camara, Jose Antonio Ramírez García, Joeri van der Velde, Philip van Damme, Pablo Alarcón Moreno, Nirupama Benis, Jolanda Strubel, Fieke Schoots, Pauline L'Henaff, P.A.C. 't Hoen, Marco Roos, Annika Jacobsen, Ronald Cornet, Mark D. Wilkinson, Franz Schaefer, Morris Swertz, and Mijke Jetten

Subjects
FAIRification stewards, FAIRification workflow, Generic FAIRirification workflow, FAIRopoly, FAIR data stewardship, De Novo FAIRification, FAIR data principles, FAIRification
Abstract

The process of making data Findable, Accessible, Interoperable and Reusable (FAIR - FAIRification) varies across projects, depending on their objectives and domain needs. However, such variation can complicate identifying the best workflow for an efficient large-scale national implementation. It is therefore necessary to align the different FAIRification processes and workflows. With this aim in mind, we mapped a set of FAIRification workflows to understand the divergence among them and identify critical common FAIRification and domain-specific steps. This work was executed in the context of the DutchHealth-RIand theEuropean Joint Programme on Rare Diseases (EJP RD), which both rely on the FAIR principles to enable sustainable data reuse in the healthcare domain. First, we gathered a group of FAIR experts amongst the collaborators in the two initiatives. Next, we identified a set of relevant workflows used within the rare disease domain and the Dutch health research infrastructure context. A total of seven workflows were selected, including the EJP RDFAIRopoly, given its compilation of theDe NovoandGenericworkflows. Through several hands-on meetings, we discussed the interpretation and best mapping of the workflows’ steps. Finally, we considered any steps that were mapped in more than four workflows (>50%) as critical. Preliminary results show three critical steps: a) identification of FAIRification objectives and expertise, b) (meta)data assessment, definition and semantic modelling, and c) defining data licensing (or consent), access and use conditions. The first can impact the success of the FAIRification of projects, whereas (meta)data assessment and modelling are intrinsically related to the core of the FAIR principles: semantic interoperability and machine actionability of (meta)data. Finally, licensing (consenting), accessing and reusing conditions are equally crucial for healthcare data reuse as they protect sensitive information. Future work includes identifying and analysing domain-specific steps and detailing each critical step into recommended resources, checklists and needed expertise. Any training needs regarding the FAIR expertise capacity can then be identified from such descriptions. We expect that embedding critical steps in the national research infrastructure can improve FAIR data availability.

Published
2023
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10. Exposure to urban environmental stressors in pregnancy and postpartum depression: A meta-analysis of 11 European birth cohorts

Author

Tim Cadman, Katrine Strandberg-Larsen, Lucinda Calas, Malina Christiansen, Iryna Culpin, Payam Dadvand, Montserrat de Castro, Maria Foraster, Serena Fossati, Mònica Guxens, Jennifer Harris, Manon Hillegers, Vincent Jaddoe, Yunsung Lee, Johanna Lepeule, Hanan el Marroun, Milena Maule, Rosie McEachen, Chiara Moccia, Johanna Nader, Mark Nieuwenhuijsen, Anne-Marie Nybo-Andersen, Rebecca Pearson, Morris Swertz, Marina Vafaidi, Martine Vrijheid, John Wright, Deborah Lawlor, and Marie Pedersen

Subjects
General Earth and Planetary Sciences, General Environmental Science
Published
2022

11. Position paper on management of personal data in environment and health research in Europe

Author

Eva, Govarts, Liese, Gilles, Stephanie, Bopp, Petr, Holub, Leslie, Matalonga, Roel, Vermeulen, Martine, Vrijheid, Sergi, Beltran, Mette, Hartlev, Sarah, Jones, Laura, Rodriguez Martin, Arnout, Standaert, Morris, Swertz A., Jan, Theunis, Xenia, Trier, Nina, Vogel, Koert, Van Espen, Sylvie, Remy, Greet, Schoeters, Eva, Govarts, Liese, Gilles, Stephanie, Bopp, Petr, Holub, Leslie, Matalonga, Roel, Vermeulen, Martine, Vrijheid, Sergi, Beltran, Mette, Hartlev, Sarah, Jones, Laura, Rodriguez Martin, Arnout, Standaert, Morris, Swertz A., Jan, Theunis, Xenia, Trier, Nina, Vogel, Koert, Van Espen, Sylvie, Remy, and Greet, Schoeters

Abstract

Management of datasets that include health information and other sensitive personal information of European study participants has to be compliant with the General Data Protection Regulation (GDPR, Regulation (EU) 2016/679). Within scientific research, the widely subscribed'FAIR' data principles should apply, meaning that research data should be findable, accessible, interoperable and re-usable. Balancing the aim of open science driven FAIR data management with GDPR compliant personal data protection safeguards is now a common challenge for many research projects dealing with (sensitive) personal data.In December 2020 a workshop was held with representatives of several large EU research consortia and of the European Commission to reflect on how to apply the FAIR data principles for environment and health research (E&H). Several recent data intensive EU funded E&H research projects face this challenge and work intensively towards developing solutions to access, exchange, store, handle, share, process and use such sensitive personal data, with the aim to support European and transnational collaborations. As a result, several recommendations, opportunities and current limitations were formulated.New technical developments such as federated data management and analysis systems, machine learning together with advanced search software, harmonized ontologies and data quality standards should in principle facilitate the FAIRification of data. To address ethical, legal, political and financial obstacles to the wider re-use of data for research purposes, both specific expertise and underpinning infrastructure are needed. There is a need for the E&H research data to find their place in the European Open Science Cloud. Communities using health and population data, environmental data and other publicly available data have to interconnect and synergize. To maximize the use and re-use of environment and health data, a dedicated supporting European infr

Published
2022

12. Towards an Interoperable Ecosystem of Research Cohort andReal-world Data Catalogues Enabling Multi-center Studies

Author

Morris Swertz, Esther van Enckevort, José Luis Oliveira, Isabel Fortier, Julie Bergeron, Nicolas H. Thurin, Eleanor Hyde, Alexander Kellmann, Romin Pahoueshnja, Miriam Sturkenboom, Marianne Cunnington, Anne-Marie Nybo Andersen, Yannick Marcon, Gonçalo Gonçalves, Rosa Gini, and Groningen Institute for Gastro Intestinal Genetics and Immunology (3GI)

Subjects
Cohort Studies, Common Data Elements, Information Dissemination, Humans, General Medicine, Ecosystem
Abstract

Objectives: Existing individual-level human data cover large populations on many dimensions such as lifestyle, demography, laboratory measures, clinical parameters, etc. Recent years have seen large investments in data catalogues to FAIRify data descriptions to capitalise on this great promise, i.e. make catalogue contents more Findable, Accessible, Interoperable and Reusable. However, their valuable diversity also created heterogeneity, which poses challenges to optimally exploit their richness.Methods: In this opinion review, we analyse catalogues for human subject research ranging from cohort studies to surveillance, administrative and healthcare records.Results: We observe that while these catalogues are heterogeneous, have various scopes, and use different terminologies, still the underlying concepts seem potentially harmonizable. We propose a unified framework to enable catalogue data sharing, with catalogues of multi-center cohorts nested as a special case in catalogues of real-world data sources. Moreover, we list recommendations to create an integrated community of metadata catalogues and an open catalogue ecosystem to sustain these efforts and maximise impact.Conclusions: We propose to embrace the autonomy of motivated catalogue teams and invest in their collaboration via minimal standardisation efforts such as clear data licensing, persistent identifiers for linking same records between catalogues, minimal metadata ‘common data elements’ using shared ontologies, symmetric architectures for data sharing (push/pull) with clear provenance tracks to process updates and acknowledge original contributors. And most importantly, we encourage the creation of environments for collaboration and resource sharing between catalogue developers, building on international networks such as OpenAIRE and research data alliance, as well as domain specific ESFRIs such as BBMRI and ELIXIR. OBJECTIVES: Existing individual-level human data cover large populations on many dimensions such as lifestyle, demography, laboratory measures, clinical parameters, etc. Recent years have seen large investments in data catalogues to FAIRify data descriptions to capitalise on this great promise, i.e. make catalogue contents more Findable, Accessible, Interoperable and Reusable. However, their valuable diversity also created heterogeneity, which poses challenges to optimally exploit their richness. METHODS: In this opinion review, we analyse catalogues for human subject research ranging from cohort studies to surveillance, administrative and healthcare records. RESULTS: We observe that while these catalogues are heterogeneous, have various scopes, and use different terminologies, still the underlying concepts seem potentially harmonizable. We propose a unified framework to enable catalogue data sharing, with catalogues of multi-center cohorts nested as a special case in catalogues of real-world data sources. Moreover, we list recommendations to create an integrated community of metadata catalogues and an open catalogue ecosystem to sustain these efforts and maximise impact. CONCLUSIONS: We propose to embrace the autonomy of motivated catalogue teams and invest in their collaboration via minimal standardisation efforts such as clear data licensing, persistent identifiers for linking same records between catalogues, minimal metadata 'common data elements' using shared ontologies, symmetric architectures for data sharing (push/pull) with clear provenance tracks to process updates and acknowledge original contributors. And most importantly, we encourage the creation of environments for collaboration and resource sharing between catalogue developers, building on international networks such as OpenAIRE and research data alliance, as well as domain specific ESFRIs such as BBMRI and ELIXIR.

Published
2022
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13. Large-scale cis- and trans-eQTL analyses identify thousands of genetic loci and polygenic scores that regulate blood gene expression

Author

Mahmoud Elansary, Knut Krohn, Eleonora Porcu, Julia Dmitrieva, Michel Georges, Harm-Jan Westra, Isabel Alves, Matthias Nauck, Jan H. Veldink, Joost Verlouw, Anette Kalnapenkis, Silva Kasela, Alex W. Hewitt, Roy Oelen, Willem H. Ouwehand, Frank Beutner, Ilkka Seppälä, Yukihide Momozawa, Samuli Ripatti, Brenda W.J.H. Penninx, Patrick Deelen, Michael Stumvoll, Jenny van Dongen, Jonathan K. Pritchard, Roman Kreuzhuber, Marie-Julie Favé, Bernett Lee, Hailang Mei, Biao Zeng, Philip Awadalla, Shuang Li, Kate Downes, Gibran Hemani, Urko M. Marigorta, Anke Tönjes, Morris Swertz, Robert Warmerdam, Joseph E. Powell, Mika Kähönen, Urmo Võsa, Brandon L. Pierce, Benjamin P. Fairfax, Anand Kumar Andiappan, Bastiaan T. Heijmans, Martina Müller-Nurasyid, Sven Bergmann, Katharina Schramm, Hanieh Yaghootkar, Sina Rüeger, Monique G. P. van der Wijst, Lude Franke, Ting Qi, Rick Jansen, Greg Gibson, Cisca Wijmenga, Marc Jan Bonder, Yungil Kim, Viktorija Kukushkina, Johannes Kettunen, Joachim Thiery, Peter A C 't Hoen, Zoltán Kutalik, Jian Yang, Dylan H. de Vries, Olaf Rötzschke, Maarten van Iterson, Peter Kovacs, Peter M. Visscher, Wibowo Arindrarto, Oliver Stegle, Natalia Pervjakova, Julian C. Knight, Tõnu Esko, Annique Claringbould, Lili Milani, Patrick F. Sullivan, Habibul Ahsan, Timothy M. Frayling, Lin Tong, Uwe Völker, Reyhan Sönmez Flitman, Eline Slagboom, Dorret I. Boomsma, Holger Prokisch, Michel G. Nivard, Mawusse Agbessi, Joyce B. J. van Meurs, Alexis Battle, Futao Zhang, Emmanouil T. Dermitzakis, Morris A. Swertz, Grant W. Montgomery, Terho Lehtimäki, Coen D.A. Stehouwer, Jaanika Kronberg, Holger Kirsten, Olli T. Raitakari, Sina A. Gharib, Bruce M. Psaty, Seyhan Yazar, Markus Loeffler, Harm Brugge, Jose Alquicira Hernandez, Mark W. Christiansen, Andrew A. Brown, Markus Perola, Markus Scholz, Ashis Saha, Alexander Teumer, Psychiatry, APH - Mental Health, Amsterdam Neuroscience - Complex Trait Genetics, Amsterdam Neuroscience - Mood, Anxiety, Psychosis, Stress & Sleep, APH - Digital Health, Groningen Institute for Gastro Intestinal Genetics and Immunology (3GI), Stem Cell Aging Leukemia and Lymphoma (SALL), BIOS Consortium, i2QTL Consortium, 't Hoen, PAC, van Meurs, J., van Dongen, J., van Iterson, M., Swertz, M.A., Jan Bonder, M., Biological Psychology, APH - Personalized Medicine, APH - Methodology, Internal Medicine, Interne Geneeskunde, MUMC+: HVC Pieken Maastricht Studie (9), MUMC+: MA Interne Geneeskunde (3), MUMC+: MA Med Staf Artsass Interne Geneeskunde (9), and RS: Carim - V01 Vascular complications of diabetes and metabolic syndrome

Subjects
DISORDER, Multifactorial Inheritance, Quantitative Trait Loci, Genome-wide association study, Quantitative trait locus, Biology, Polymorphism, Single Nucleotide, Gene Expression Regulation/genetics, DISEASE, LINKS, Transcriptome, 03 medical and health sciences, 0302 clinical medicine, All institutes and research themes of the Radboud University Medical Center, RELEVANCE, Blood Proteins/genetics, Gene expression, Genetics, Humans, GENOME-WIDE ASSOCIATION, Polymorphism, Gene, Multifactorial Inheritance/genetics, 030304 developmental biology, Regulation of gene expression, RISK, 0303 health sciences, ARCHITECTURE, Blood Proteins, Transcriptome/genetics, Polymorphism, Single Nucleotide/genetics, Phenotype, SERINE BIOSYNTHESIS, HUMAN TRANSCRIPTOME, DEFICIENCY, Gene Expression Regulation, Expression quantitative trait loci, genome-wide association studies, gene expression, gene regulation, Quantitative Trait Loci/genetics, Nanomedicine Radboud Institute for Molecular Life Sciences [Radboudumc 19], Single Nucleotide/genetics, 030217 neurology & neurosurgery, Genome-Wide Association Study
Abstract

Trait-associated genetic variants affect complex phenotypes primarily via regulatory mechanisms on the transcriptome. To investigate the genetics of gene expression, we performed cis- and trans-expression quantitative trait locus (eQTL) analyses using blood-derived expression from 31,684 individuals through the eQTLGen Consortium. We detected cis-eQTL for 88% of genes, and these were replicable in numerous tissues. Distal trans-eQTL (detected for 37% of 10,317 trait-associated variants tested) showed lower replication rates, partially due to low replication power and confounding by cell type composition. However, replication analyses in single-cell RNA-seq data prioritized intracellular trans-eQTL. Trans-eQTL exerted their effects via several mechanisms, primarily through regulation by transcription factors. Expression of 13% of the genes correlated with polygenic scores for 1,263 phenotypes, pinpointing potential drivers for those traits. In summary, this work represents a large eQTL resource, and its results serve as a starting point for in-depth interpretation of complex phenotypes.Analyses of expression profiles from whole blood of 31,684 individuals identify cis-expression quantitative trait loci (eQTL) effects for 88% of genes and trans-eQTL effects for 37% of trait-associated variants.

Published
2021

14. FAIRification of data: Great but how?

Author

Morris Swertz, Zdenka Dudová, Aleš Křenek, Eleanor Hyde, and Members Ehen Metadata Working Group

Subjects
General Earth and Planetary Sciences, General Environmental Science
Published
2021

15. EOSC-Life: Building a digital space for the life sciences - D1.2 EOSC repository deployment for project demonstrators

Author

Helen Parkinson (EMBL-EBI, ELIXIR), Ugis Sarkans (EMBL-EBI, ELIXIR, Euro BioImaging), Phil Gribbon, Gesa Witt, Andrea Zaliani, Manfred Kohler (Fraunhofer, EU OPENSCREEN), Jason Swedlow, Jean-Marie Burel (UNIVDUN, EUBI), Morris Swertz, Esther van Enckevort (UMCG, BBMRI), Petr Holub (BBMRI ERIC), Marzia Massimi, Rafaele Matteoni (CNR, INFRAFRONTIER), Holger Maier(HMGU, Reetta Hinttala, Anne Heikkinen (UOULU, Philipp Gormanns (INFRAFRONTIER GMBH, Laura del Cano, Laurent Vasseur, Sophie Leblanc, Yann Herault (CERBM-GIE, Dimitris Kontoyiannis, Christina Chandras, Dimitra Panou (FLEMING, José Miguel López Coronado, Rosa Aznar Novella (UVEG, MIRRI), Vincent Robert, Ammar Ben Hadj Amor (KNAW, Serge Casaregola, Jean-Luc Legras, Michel-Yves Mistou (INRA, Paolo Romano (USMI, Isabelle Perseil (INSERM, ERINHA), Romain David (ERINHA), Roland Pieruschka (FZJ, EMPHASIS), Katrina Exter, Marc Portier, Cedric Decruw (VLIZ, EMBRC), S. Canham, C. Ohmann, S. Goryanin (ECRIN-ERIC), Laura Del Cano (CSIC, Instruct), Maddalena Fratelli (IRFMN, EATRIS), Carole Goble, Stuart Owen, Stian Soiland-Reyes, Nick Juty (UNIMAN, ISBE), WP6: Susanna Sansone, Peter McQuilton (UOXF), Marco Roos (LUMC), Luiz Bonino (LUMC) WP2: Carole Goble, and Nick Juty (UNIMAN)

Subjects
ComputingMilieux_LEGALASPECTSOFCOMPUTING, FAIR dataset, European Open Science Cloud
Abstract

This deliverable addresses EOSC-Life WP1's objectives related to publication of data and data resources in cloud repositories by making available resources in EOSC-Life's registries; the implementation of FAIR services and standards, by development of FAIR registries in collaboration with WP6; and evolution of repository infrastructure by making available registry entries deriving from WP3 demonstrators. Use cases for EOSC-Life registries have been defined for general and clinical research data use and the 'EOSC-Life' collection in FAIRsharing has been populated and released comprising more than 100 data resources and standards. A clinical MetaData Repository has also been developed to address challenges of clinical data sharing in Europe. We have engaged with EOSC, sister projects such as FAIRsFAIR and ENVRI to consider the features of registries, cross registry interoperability and use cases which link EOSC projects. We will continue to update the registries as the project progresses and as new dataset and resources are made available and will engage with pan-EOSC registry planning based on our work to date.

Published
2021

16. Meta-analysis uncovers genome-wide significant variants for rapid kidney function decline

Author

Lukas Habegger, Charumathi Sabanayagam, Michael Preuss, Laura M. Raffield, Mary F. Feitosa, Bamidele O. Tayo, Kevin Ho, Leo-Pekka Lyytikäinen, Florian Kronenberg, Valencia Hui Xian Foo, Adrienne Tin, Michael Cantor, Nisha Bansal, Tarunveer S. Ahluwalia, Melanie Waldenberger, Sarah A. Pendergrass, Behrooz Z. Alizadeh, Wolfgang Koenig, Qiong Yang, Xiaodong Bai, Christoph Wanner, Ben Schöttker, Giovanni Coppola, A. R. Shuldiner, Leslie A. Lange, Piyush Gampawar, Markus Scholz, Tien Yin Wong, Mary L. Biggs, Morris Swertz, Alicia Hawes, Girish N. Nadkarni, Christina-Alexandra Schulz, Chiea Chuen Khor, Ricardo H. Ulloa, Jeffrey C. Staples, Miao-Li Chee, Laura M. Yerges-Armstrong, Andrew Blumenfeld, Karlhans Endlich, Bernhard Banas, Bruce H.R. Wolffenbuttel, Kai-Uwe Eckardt, Pavel Hamet, Carsten A. Böger, Harold Snieder, Marcus B. Jones, Judy Wang, Shih-Jen Hwang, Mathias Gorski, Anselm Hoppmann, Josyf C. Mychaleckyj, Bernd Holleczek, Pamela R. Matias-Garcia, Rainer Rettig, Karsten B. Sieber, Manasi Pradhan, Pashupati P. Mishra, Peter Rossing, Matthias Wuttke, Miao-Ling Chee, H. Marike Boezen, Yong Li, M. Arfan Ikram, Jeffrey G. Reid, Teresa Nutile, Maria Sotiropoulos Padilla, Lude Franke, Robert J. Carroll, Luca A. Lotta, Bernhard K. Krämer, Kjell Nikus, Jerome I. Rotter, Thomas Meitinger, Lars Wallentin, Cisca Wijmenga, Kent D. Taylor, Holly Kramer, Louis Widom, Olli T. Raitakari, Marcus E. Kleber, Man Li, Nina Hutri-Kähönen, Massimiliano Cocca, Reinhold Schmidt, John D. Overton, Cristian Pattaro, Michael Lattari, Sarah E. Wolf, Jin-Fang Chai, Karina Toledo, Brigitte Kühnel, Zhenhua Gu, Peter Almgren, Caitlin Forsythe, Yuri Milaneschi, Stephan J. L. Bakker, Layal Chaker, Dawn M. Waterworth, Silke Szymczak, James G. Wilson, Peter J. van der Most, Michelle L. O'Donoghue, William Salerno, Masayuki Yasuda, Sahar Ghasemi, Eric Boerwinkle, Josef Coresh, Ilja M. Nolte, Kia Manoochehri, Konstantin Strauch, Thomas D. Schleicher, Myriam Rheinberger, Audrey Y. Chu, Sanaz Sedaghat, Sandra Freitag-Wolf, Boting Ning, Matthias Nauck, Christina Beechert, Helena Schmidt, Harvey D. White, Nina Mononen, Johanne Tremblay, Navya Shilpa Josyula, Mika Kähönen, Katrin Horn, Andre Franke, Marianne Rots, Bettina Jung, Alexander R. Rosenkranz, Christian M. Shaffer, Mary Ann Lukas, Gerjan Navis, Christian Gieger, John Chalmers, Shareef Khalid, Uwe Völker, Marju Orho-Melander, Iris M. Heid, Brenda W.J.H. Penninx, A. Baras, Alexander Lopez, Evan Maxwell, Ruth J. F. Loos, Erin D. Fuller, Christa Meisinger, Gonçalo R. Abecasis, Suganthi Balasubramanian, Chris H. L. Thio, Martin H. de Borst, Stefan Coassin, Ching-Yu Cheng, Wolfgang Lieb, Kenneth Rice, Alexander Teumer, Mark Woodward, Gisu Eom, Hermann Brenner, Thomas W. Winkler, Anna Köttgen, Edith Hofer, Aris Economides, Ron T. Gansevoort, Pim van der Harst, Lyndon J. Mitnaul, Bruce M. Psaty, Erwin P. Bottinger, Olle Melander, Niek Verweij, Frauke Degenhardt, Yan Zhang, Mohsen Ghanbari, Veronika Wanner, Terho Lehtimäki, Leland Barnard, Tampere University, Primary Health Care, Department of Paediatrics, Clinical Medicine, Department of Clinical Physiology and Nuclear Medicine, Department of Clinical Chemistry, TAYS Heart Centre, Groningen Institute for Organ Transplantation (GIOT), Groningen Kidney Center (GKC), Cardiovascular Centre (CVC), Life Course Epidemiology (LCE), Department of Marketing Management, Epidemiology, Internal Medicine, Psychiatry, Amsterdam Neuroscience - Complex Trait Genetics, Amsterdam Neuroscience - Mood, Anxiety, Psychosis, Stress & Sleep, APH - Mental Health, and APH - Digital Health

Subjects
0301 basic medicine, medicine.medical_specialty, Genome-wide association study, 030232 urology & nephrology, Protein Disulfide-Isomerases, Hasso-Plattner-Institut für Digital Engineering GmbH, Renal function, Locus (genetics), Biology, AMP-Activated Protein Kinases, Kidney, 3121 Internal medicine, 03 medical and health sciences, chemistry.chemical_compound, 0302 clinical medicine, end-stage kidney disease, rapid eGFRcrea decline, Urologi och njurmedicin, medicine, Humans, Urology and Nephrology, ddc:610, Allele, Genetic association, Genetics, Creatinine, genome-wide association study, Acute kidney injury, acute kidney injury, medicine.disease, United Kingdom, ddc, 030104 developmental biology, chemistry, Nephrology, Medical genetics, 3111 Biomedicine, 610 Medizin und Gesundheit, Glomerular Filtration Rate
Abstract

Rapid decline of glomerular filtration rate estimated from creatinine (eGFRcrea) is associated with severe clinical endpoints. In contrast to cross-sectionally assessed eGFRcrea, the genetic basis for rapid eGFRcrea decline is largely unknown. To help define this, we meta-analyzed 42 genome-wide association studies from the Chronic Kidney Diseases Genetics Consortium and United Kingdom Biobank to identify genetic loci for rapid eGFRcrea decline. Two definitions of eGFRcrea decline were used: 3 mL/min/1.73m(2)/year or more ("Rapid3"; encompassing 34,874 cases, 107,090 controls) and eGFRcrea decline 25% or more and eGFRcrea under 60 mL/min/1.73m(2) at follow-up among those with eGFRcrea 60 mL/min/1.73m(2) or more at baseline ("CKDi25"; encompassing 19,901 cases, 175,244 controls). Seven independent variants were identified across six loci for Rapid3 and/or CKDi25: consisting of five variants at four loci with genome-wide significance (near UMOD-PDILT (2), PRKAG2, WDR72, OR2S2) and two variants among 265 known eGFRcrea variants (near GATM, LARP4B). All these loci were novel for Rapid3 and/or CKDi25 and our bioinformatic follow-up prioritized variants and genes underneath these loci. The OR2S2 locus is novel for any eGFRcrea trait including interesting candidates. For the five genome-wide significant lead variants, we found supporting effects for annual change in blood urea nitrogen or cystatin-based eGFR, but not for GATM or (LARP4B). Individuals at high compared to those at low genetic risk (8-14 vs. 0-5 adverse alleles) had a 1.20-fold increased risk of acute kidney injury (95% confidence interval 1.08-1.33). Thus, our identified loci for rapid kidney function decline may help prioritize therapeutic targets and identify mechanisms and individuals at risk for sustained deterioration of kidney function., Zweitveröffentlichungen der Universität Potsdam : Reihe der Digital Engineering Fakultät; 19

Published
2021

17. Advancing tools for human early lifecourse exposome research and translation (ATHLETE): Project overview

Author

Pavel Piler, Serena Fossati, Josep Perelló, Rodney Ortiz, Jana Klanova, Mark J. Nieuwenhuijsen, Marie Pedersen, Hector C. Keun, Kristine B. Gutzkow, Laurent Le Brusquet, Morris Swertz, Joane Quentin, Sandrine Mathy, Tim S. Nawrot, Arthur Tenenhaus, Nerea Lertxundi, Ivonne Leenen, Adrian Rodriguez, Ana Esplugues, Claire Philippat, Lesley Hoyles, Esther van Enckevort, José Manuel Sabin Capote, Rosemary R. C. McEachan, Valérie Siroux, Jacob van Klaveren, María Dolores Gómez Roig, Jordi Sunyer, Sandra Andrušaitytė, Juan R. González, Regina Grazuleviciene, Mariona Bustamante, Natacha Cingotti, Cécile Chevrier, Genon Jensen, Christos Lionis, Ellen Hessel, Míriam Pérez-Cruz, Rémy Slama, Ronan Garlantezec, Susana Santos, Mònica Guxens, Maria-Jose Lopez-Espinosa, Eleanor Hyde, Costanza Pizzi, Sido Haakma, Sarah Lyon-Caen, Tiffany Yang, Martine Vrijheid, Sabrina Llop, Lorenzo Richiardi, Vincent W. V. Jaddoe, Alexandros P. Siskos, Dan Mason, Xavier Basagaña, John Wright, Paul Burton, Joana Porcel, Léa Maitre, Katrine Strandberg-Larsen, Leonardo Santiago, Maribel Casas, Nikos Stratakis, Marina Vafeiadi, David V. Conti, Payam Dadvand, Theano Roumeliotaki, Karine Angeli, Edurne Mazarico, Demetris Avraam, Gunn Marit Aasvang, Liesbeth Duijts, Rebecca Wilson, Cathrine Thomsen, Amélie Crépet, Andreas Kortenkamp, Leda Chatzi, Aitana Lertxundi, Ferran Ballester, and Commission of the European Communities

Subjects
Child health, Global and Planetary Change, Exposome, Epidemiology, Health, Toxicology and Mutagenesis, Public Health, Environmental and Occupational Health, Adolescent health, Review Article, 010501 environmental sciences, 01 natural sciences, Pollution, Early life, 03 medical and health sciences, 0302 clinical medicine, Exposure assessment, Engineering ethics, 030212 general & internal medicine, Sociology, 0105 earth and related environmental sciences
Abstract

Early life stages are vulnerable to environmental hazards and present important windows of opportunity for lifelong disease prevention. This makes early life a relevant starting point for exposome studies. The Advancing Tools for Human Early Lifecourse Exposome Research and Translation (ATHLETE) project aims to develop a toolbox of exposome tools and a Europe-wide exposome cohort that will be used to systematically quantify the effects of a wide range of community- and individual-level environmental risk factors on mental, cardiometabolic, and respiratory health outcomes and associated biological pathways, longitudinally from early pregnancy through to adolescence. Exposome tool and data development include as follows: (1) a findable, accessible, interoperable, reusable (FAIR) data infrastructure for early life exposome cohort data, including 16 prospective birth cohorts in 11 European countries; (2) targeted and nontargeted approaches to measure a wide range of environmental exposures (urban, chemical, physical, behavioral, social); (3) advanced statistical and toxicological strategies to analyze complex multidimensional exposome data; (4) estimation of associations between the exposome and early organ development, health trajectories, and biological (metagenomic, metabolomic, epigenetic, aging, and stress) pathways; (5) intervention strategies to improve early life urban and chemical exposomes, co-produced with local communities; and (6) child health impacts and associated costs related to the exposome. Data, tools, and results will be assembled in an openly accessible toolbox, which will provide great opportunities for researchers, policymakers, and other stakeholders, beyond the duration of the project. ATHLETE's results will help to better understand and prevent health damage from environmental exposures and their mixtures from the earliest parts of the life course onward. ISGlobal acknowledges support from the Spanish Ministry of Science, Innovation and Universities through the “Centro de Excelencia Severo Ochoa 2019–2023” Program (CEX2018-000806-S) and support from the Generalitat de Catalunya through the Centres de Recerca de Catalunya Program. We acknowledge collaboration with European projects, specifically: Human Early Life Exposome (HELIX) (FP7 grant agreement number 308333), LifeCycle (H2020 grant agreement number 733206), and Connecting Europe and Canada in personalized health (EUCAN-Connect) (H2020 Grant Agreement number 824989). The Born in Bradford (BiB) cohort is only possible because of the enthusiasm and commitment of the Children and Parents in BiB. We are grateful to all the participants, health professionals, and researchers who have made BiB happen. The BiB cohort is only possible because of the enthusiasm and commitment of the children and parents in BiB. We are grateful to all the participants, health professionals, schools, and researchers who have made BiB happen. BiB has received funding from the Wellcome Trust (101597), a joint grant from the UK Medical Research Council and UK Economic and Social Science Research Council (MR/N024391/1), a British Heart Foundation Clinical Study grant (CS/16/4/32482). The Norwegian Mother, Father and Child Cohort Study is supported by the Norwegian Ministry of Health and Care Services and the Ministry of Education and Research. We are grateful to all the participating families in Norway who take part in this ongoing cohort study. The Danish National Birth Cohort was established with a significant grant from the Danish National Research Foundation. Additional support was obtained from the Danish Regional Committees, the Pharmacy Foundation, the Egmont Foundation, the March of Dimes Birth Defects Foundation, the Health Foundation, and other minor grants. The Danish National Birth Cohort Biobank has been supported by the Novo Nordisk Foundation and the Lundbeck Foundation. Follow-up of mothers and children have been supported by the Danish Medical Research Council (SSVF 0646, 271-08-0839/06-066023, O602-01042B, 0602-02738B); the Lundbeck Foundation (195/04, R100-A9193); The Innovation Fund Denmark 0603-00294B (09-067124); the Nordea Foundation (02-2013-2014); Aarhus Ideas (AU R9-A959-13-S804); University of Copenhagen Strategic Grant (IFSV 2012); and the Danish Council for Independent Research (DFF—4183-00594 and DFF—4183-00152). The general design of the Generation R Study is made possible by financial support from the Erasmus MC, University Medical Center, Rotterdam, Erasmus University Rotterdam, Netherlands Organization for Health Research and Development (ZonMw), Netherlands Organisation for Scientific Research (NWO), Ministry of Health, Welfare and Sport, and Ministry of Youth and Families. This project received funding from the European Union’s Horizon 2020 research and innovation programme (LIFECYCLE, grant agreement number 733206, 2016; EUCAN-Connect grant agreement number 824989; ATHLETE, grant agreement number 874583). We gratefully acknowledge the contribution of participants, research collaborators, general practitioners, hospitals, midwives, and pharmacies in Rotterdam. The INfancia y Medio Ambiente cohort (INMA) Sababell study was funded by grants from Instituto de Salud Carlos III (Red INMA G03/176; CB06/02/0041; PI041436; PI081151 incl. Fondo Europeo de Desarollo Regional (FEDER) funds; PI12/01890 incl. FEDER funds; CP13/00054 incl. FEDER funds; PI15/00118 incl. FEDER funds; CP16/00128 incl. FEDER funds; PI16/00118 incl. FEDER funds; PI16/00261 incl. FEDER funds; PI17/01340 incl. FEDER funds, PI18/00547 incl. FEDER funds, PI20/01695 incl. FEDER funds), Centro de Investigación Biomédica en Red - Epidemiología y Salud Pública (CIBERESP), Generalitat de Catalunya-Comissió Interdepartamental de Recerca i Innovació Tecnològia 1999SGR 00241, Generalitat de Catalunya-Agencia de Gestión de Ayudas Universitarias y de Investigación (2009 SGR 501, 2014 SGR 822), Fundació La Marató de TV3 (090430), Spanish Ministry of Economy and Competitiveness (SAF2012-32991 incl. FEDER funds), Agence Nationale de Securite Sanitaire de l’Alimentation de l’Environnement et du Travail (1262C0010; EST-2016 RF-21, EST-19 RF-04), and the European Commission (261357, 308333, 603794 and 634453). The INMA Valencia study was supported by grants from Instituto de Salud Carlos III (FIS-FEDER: 13/2032, 13/1944, 14/00891, 16/1288, 17/00663, and 19/1338; Miguel Servet-FSE: CP15/0025 and MSII16/00051, 00051, and MSII20/0006), Alicia Koplowitz Foundation 2017, Generalitat Valenciana (AICO/2020/285), and Spanish Association Against Cancer (AECC) “Seed Ideas” 2019 (IDEAS19098LOPE). INMA Gipuzkoa was funded by grants from Instituto de Salud Carlos III (FIS-PI06/0867, FIS-PI09/00090, FIS-PI13/02187, and FIS-PI18/01142 incl. FEDER funds), CIBERESP, Department of Health of the Basque Government (2005111093, 2009111069, 2013111089, and 2015111065), and the Provincial Government of Gipuzkoa (DFG06/002, DFG08/001, and DFG15/221) and annual agreements with the municipalities of the study area (Zumarraga, Urretxu, Legazpi, Azkoitia y Azpeitia y Beasain). The Sepages cohort would like to thank the Grenoble University Hospital (CHU-GA) biobank (bb-0033-00069). We thank the Sepages Study group (E. Eyriey, P. Hoffmann, E. Hullo, J. Lepeule, C. Llerena, S. Lyon-Caen, X. Morin, A. Morlot, C. Philippat, I. Pin, J. Quentin, V. Siroux, R. Slama) and the participants of the Suivi de l’Exposition à la Pollution Atmosphérique durant la Grossesse et Effets sur la Santé (SEPAGES) study. We acknowledge support from Auvergne-Rhône-Alpes Région, Soutien aux coopérations universitaires et scientifiques internationales fund to support collaborations between Catalunya and Auvergne-Rhône-Alpes. SEPAGES cohort was supported by the European Research Council (consolidator grant N 311765-E-DOHaD, Principal Investigator [PI], R. Slama), by French National Research Agency (ANR), the ANR (Pregnancy, Air Pollution, Epigenetics and Respiratory health project ANR-12-PDOC-0029-01, PI, J. Lepeule; A Longitudinal Analysis of Effects of Early Life Exposure to Phenols on Health in Humans project, 14-CE21-0007-01, PI, R. Slama; Gut Microbiota in early childhood and Maternal Environmental exposures project, PI, R. Slama; Prenatal Exposure to Tobacco smoking and Air Pollution and Effects on offspring respiratory and neurodevelopmental outcomes ANR 18-CE36-005, PI, J. Lepeule). The Central European Longitudinal Study of Pregnacy and Childhood: The Next Generation (TNG) cohort is supported by the RECETOX research infrastructure (the Ministry of Education, Youth and Sports of the Czech Republic: LM2018121) and the CETOCOEN EXCELLENCE Teaming 2 project of European Union (EU) Horizon 2020 (857560) and the MEYS of the Czech Republic (02.1.01/0.0/0.0/18_ 046/0015975). The Barcelona Life Study Cohort has received funding from European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme under grant agreement number (785994) (Prenatal exposure to urban air pollution and pre and post-natal brain development project) and from the Health Effects Institute (HEI) under Agreement number 4959-RFPA15-1/18-1 (FRONTIER project). Genotyping in the HELIX study was supported by project PI17/01225 (Instituto de Salud Carlos III, co-funded by European Union [European Regional Development Fund], “A way to make Europe”) and the Centro Nacional de Genotipado-CEGEN (PRB2-ISCIII). The Nascita e Infanzia: gli Effetti dell’Ambiente cohort was partially funded by the Compagnia SanPaolo Foundation and the Piedmont Region. The Piccolipiù project was funded by the Italian National Center for Disease Prevention and Control (National Centre for Disease Prevention and Control grants years 2010 and 2014) and by the Italian Ministry of Health (art 12 and 12 bis D.lgs 502/92). The Perturbateurs Endocriniens: Étude Longitudinale sur les Anomalies de la Grossesse, l’Infertilité et l’Enfance study is supported by National Institute of Health and Medical Research and has received multiple funds from the ANR, the French Agency for Food, Environmental and Occupational Health and Safety (ANSES), the Fondation de France, the National Institute for Public Health Surveillance (InVS), the French, Ministry of Labor, the French Ministry of Health, and the French Ministry of Ecology. DataSHIELD is funded under a group of projects that underpin a program of development and application of secure methods for co-analysis, data sharing, and visualization in the Population Health Sciences Institute at Newcastle University (United Kingdom). These include: the “Connected Health Cities project” (North East and North Cumbria) funded by the UK Department of Health (RES/0150/7943/202); the “EUCanConnect project” (European Commission H2020 Flagship Collaboration with Canada); the “58FORWARDS project” (Fostering new Opportunities for Researchers via Wider Access to Research Data and Samples) funded jointly by the Wellcome Trust and the Medical Research Council (108439/Z/15/Z); and the “METADAC project” (Managing Ethico-social, Technical and Administrative issues in Data ACcess) funded jointly by the Medical Research Council, the Wellcome Trust, and the Economic and Social Research Council (MR/N01104X/1 and MR/N01104X/2). We acknowledge the Molecular Genetics Information System team, including Fleur Kelpin, Tommy de Boer, Mariska Slofstra, Connor Stroomberg, Jelmer Veen, Jeroen van Veen, Fernanda de Andrade, Marije van der Geest, Dieuwke Roelofs-Prins, Dennis Hendriksen, Bart Charbon, Joeri van der Velde, Max Postema, Erik Schaberg, Christiaan Hilbrands, Alexander Kellmann, and Luuk Dijkhuis.

Published
2021

18. Feasibility of predicting allele specific expression from genetic variants using machine learning

Author

Zhenhua Zhang, Freerk van Dijk, Niek de Klein, Mariëlle van Gijn, Lude Franke, BIOS consortium, Morris Swertz, and K Joeri van der Velde

Subjects
animal structures
Abstract

Background: Allele-specific expression (ASE) refers to divergent abundances of allelic copies of a transcript and is quantified by RNA sequencing. Multiple studies have shown that ASE likely plays a role in many diseases by modulating the pathogenesis or phenotypes. However, routine genome diagnostics is based on DNA sequencing and therefore neglects the regulation of gene expression such as ASE. To take advantage of ASE information in absence of RNA sequencing, ASE must be predicted using only DNA variation. Results: We have constructed ASE models from BIOS and GTEx that predict local ASE using DNA features. These models are highly stable as shown by performance metrics, cross-validation, and feature importance. Many different types of features are involved in these predictions, highlighting the complex regulation that underlies ASE. We applied the BIOS-trained model to population variants in three genes in which ASE plays a role in disease penetrance or modulation: BRCA2, RET, and NF1. This resulted in predicted ASE effects for 27 out of 8,957 variants. Ten of these were known pathogenic variants, while the rest are interesting candidates for further elucidation of disease etiology. Conclusions: We demonstrated that ASE can be stably and reliably predicted from DNA features using machine-learning models. Future efforts may further improve sensitivity and translate these models into a new class of genome diagnostic in silico prediction tools to prioritize candidate pathogenic variants or regulators thereof for follow-up validation by RNA sequencing.

Published
2020
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19. Genome Analyses of >200,000 Individuals Identify 58 Loci for Chronic Inflammation and Highlight Pathways that Link Inflammation and Complex Disorders

Author

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

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

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

Published
2018

20. Analysis of requirements on biobank and study workflows

Author

Morris Swertz, Pieter Neerincx, Ondřej Vojtíšek, and Petr Holub

Abstract

Human biobanks, which are the core of BBMRI-ERIC medical research infrastructure, are repositories of biological material and data associated with the research participants (donors or patients willing to participate in the research). The associated data covers a broad range of data types: from data collected directly from the research participants and medical processes related to them, to data generated from the biological material. This document focuses on describing biobank data processing workflows that were selected for piloting in EGI-Engage the biobanks by the BBMRI.nl and BBMRI.cz (national nodes of BBMRI-ERIC) together with their associated biobanks. The main focus is on proteomics and genomics workflows, which cover both extremes of privacy-sensitive data processing spectrum: from relatively non-sensitive applications to very sensitive ones.

Published
2016
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21. Tobacco smoking is associated with DNA methylation of diabetes susceptibility genes

Author

Joyce Van Meurs, Marc Jan Bonder, Oscar Franco, Eric Sijbrands, Morris Swertz, René Pool, H. Eka D. Suchiman, Cornelia Van Duijn, Jenny Van Dongen, Pieternella Slagboom, Marian Beekman, Szymon Kiełbasa, Lude Franke, Abbas Dehghan, Patrick Deelen, Epidemiology, Internal Medicine, Biological Psychology, and Pediatric surgery

Subjects
0301 basic medicine, Male, Endocrinology, Diabetes and Metabolism, LOCI, BIOS consortium, Genome-wide association study, Disease, Type 2 diabetes, DISEASE, 0302 clinical medicine, 1114 Paediatrics And Reproductive Medicine, Genetics, DNA methylation, Smoking, Middle Aged, Tobacco smoking, GENOME, ADIPOSE-TISSUE, 1117 Public Health And Health Services, CpG site, 030220 oncology & carcinogenesis, CPG SITES, Female, Life Sciences & Biomedicine, VALIDATION, Article, Endocrinology & Metabolism, 03 medical and health sciences, SDG 3 - Good Health and Well-being, Diabetes mellitus, Internal Medicine, medicine, Humans, Risk factor, Gene, METAANALYSIS, Aged, Science & Technology, business.industry, 1103 Clinical Sciences, medicine.disease, 030104 developmental biology, Diabetes Mellitus, Type 2, REPLICATION, CIGARETTE-SMOKING, Gene expression, WIDE ANALYSIS, business, Genome-Wide Association Study
Abstract

Aims/hypothesis Tobacco smoking, a risk factor for diabetes, is an established modifier of DNA methylation. We hypothesised that tobacco smoking modifies DNA methylation of genes previously identified for diabetes. Methods We annotated CpG sites available on the Illumina Human Methylation 450K array to diabetes genes previously identified by genome-wide association studies (GWAS), and investigated them for an association with smoking by comparing current to never smokers. The discovery study consisted of 630 individuals (Bonferroni-corrected p = 1.4 × 10−5), and we sought replication in an independent sample of 674 individuals. The replicated sites were tested for association with nearby genetic variants and gene expression and fasting glucose and insulin levels. Results We annotated 3,620 CpG sites to the genes identified in the GWAS on type 2 diabetes. Comparing current smokers to never smokers, we found 12 differentially methylated CpG sites, of which five replicated: cg23161492 within ANPEP (p = 1.3 × 10−12); cg26963277 (p = 1.2 × 10−9), cg01744331 (p = 8.0 × 10−6) and cg16556677 (p = 1.2 × 10−5) within KCNQ1 and cg03450842 (p = 3.1 × 10−8) within ZMIZ1. The effect of smoking on DNA methylation at the replicated CpG sites attenuated after smoking cessation. Increased DNA methylation at cg23161492 was associated with decreased gene expression levels of ANPEP (p = 8.9 × 10−5). rs231356-T, which was associated with hypomethylation of cg26963277 (KCNQ1), was associated with a higher odds of diabetes (OR 1.06, p = 1.3 × 10−5). Additionally, hypomethylation of cg26963277 was associated with lower fasting insulin levels (p = 0.04). Conclusions/interpretation Tobacco smoking is associated with differential DNA methylation of the diabetes risk genes ANPEP, KCNQ1 and ZMIZ1. Our study highlights potential biological mechanisms connecting tobacco smoking to excess risk of type 2 diabetes. Electronic supplementary material The online version of this article (doi:10.1007/s00125-016-3872-0) contains peer-reviewed but unedited supplementary material, which is available to authorised users.

Published
2016

22. Genetic and environmental influences interact with age and sex in shaping the human methylome

Author

Joyce Van Meurs, Marc Jan Bonder, Marleen Van Greevenbroek, Michel Nivard, Morris Swertz, René Pool, H. Eka D. Suchiman, Coen Stehouwer, Marijn Verkerk, Cornelia Van Duijn, Jenny Van Dongen, Pieternella Slagboom, Marian Beekman, Casper G Schalkwijk, Szymon Kiełbasa, Lude Franke, Rick Jansen, Gonneke Willemsen, Carla Van der Kallen, Patrick Deelen, Interne Geneeskunde, RS: CARIM - R3.01 - Vascular complications of diabetes and the metabolic syndrome, MUMC+: HVC Pieken Maastricht Studie (9), MUMC+: MA Interne Geneeskunde (3), Psychiatry, Amsterdam Neuroscience - Complex Trait Genetics, Biological Psychology, and Internal Medicine

Subjects
0301 basic medicine, Netherlands Twin Register (NTR), Adult, Male, Aging, Adolescent, Science, Inheritance Patterns, General Physics and Astronomy, Single-nucleotide polymorphism, Biology, Genome, Polymorphism, Single Nucleotide, General Biochemistry, Genetics and Molecular Biology, Article, 03 medical and health sciences, Sex Factors, SDG 3 - Good Health and Well-being, Genetic variation, Twins, Dizygotic, Humans, Gene–environment interaction, Genetics, Multidisciplinary, Genome, Human, Smoking, Age Factors, General Chemistry, Twins, Monozygotic, Heritability, DNA Methylation, Explained variation, 030104 developmental biology, Phenotype, Child, Preschool, DNA methylation, CpG Islands, Female, Gene-Environment Interaction
Abstract

The methylome is subject to genetic and environmental effects. Their impact may depend on sex and age, resulting in sex- and age-related physiological variation and disease susceptibility. Here we estimate the total heritability of DNA methylation levels in whole blood and estimate the variance explained by common single nucleotide polymorphisms at 411,169 sites in 2,603 individuals from twin families, to establish a catalogue of between-individual variation in DNA methylation. Heritability estimates vary across the genome (mean=19%) and interaction analyses reveal thousands of sites with sex-specific heritability as well as sites where the environmental variance increases with age. Integration with previously published data illustrates the impact of genome and environment across the lifespan at methylation sites associated with metabolic traits, smoking and ageing. These findings demonstrate that our catalogue holds valuable information on locations in the genome where methylation variation between people may reflect disease-relevant environmental exposures or genetic variation., Differential impact of genetic and environmental influences on DNA methylation may result in sex- and age-related physiological variation and disease susceptibility. By analysing DNA methylome of 2,603 individuals from twin families, here, the authors establish a catalogue of between-individual variation in DNA methylation.

Published
2016

24. Population-specific genotype imputations using minimac or IMPUTE2

Author

Alexandros Kanterakis, Bruce H.R. Wolffenbuttel, Morris Swertz, Sara Pulit, H. Eka D. Suchiman, Cornelia Van Duijn, Pieternella Slagboom, Marian Beekman, Barbera Van Schaik, Lennart C. Karssen, Esther Van Enckevort, Alexander Schönhuth, Patrick Deelen, Nanomedicine & Drug Targeting, Groningen Institute for Gastro Intestinal Genetics and Immunology (3GI), Biological Psychology, Neuroscience Campus Amsterdam - Neurobiology of Mental Health, Evolutionary Intelligence, and Epidemiology

Subjects
Netherlands Twin Register (NTR), NETHERLANDS, Genome-wide association study, Single-nucleotide polymorphism, FORMAT, Biology, VARIANTS, Polymorphism, Single Nucleotide, SEQUENCE, General Biochemistry, Genetics and Molecular Biology, 03 medical and health sciences, 0302 clinical medicine, Meta-Analysis as Topic, QUALITY-CONTROL, Statistics, GENOME-WIDE ASSOCIATION, COMMON, 030304 developmental biology, Genetic association, Genetics, 0303 health sciences, SETS, Haplotype, GENETIC-VARIATION, Biobank, Haplotypes, Sample size determination, Cohort, LOW-FREQUENCY, Software, 030217 neurology & neurosurgery, Imputation (genetics), Genome-Wide Association Study
Abstract

In order to meaningfully analyze common and rare genetic variants, results from genome-wide association studies (GWASASs) of multiple cohorts need to be combined in a meta-analysis in order to obtain enough power. This requires all cohorts to have the same single-nucleotide polymorphisms (SNPSNPSNPs) in their GWASASs. To this end, genotypes that have not been measured in a given cohort can be imputed on the basis of a set of reference haplotypes. This protocol provides guidelines for performing imputations with two widely used tools: minimac and IMPUTEPUTEPUTEPUTE2. These guidelines were developed and used by the Genome of the Netherlands (GoNL) consortium, which has created a population-specific reference panel for genetic imputations and used this reference to impute various Dutch biobanks. We also describe several factors that might influence the final imputation quality. This protocol, which has been used by the largest Dutch biobanks, should take approximately several days, depending on the sample size of the biobank and the computer resources available.

Published
2015

27. SYSGENET: a meeting report from a new European network for systems genetics

Author

David Threadgill, Rudi Balling, Paul Denny, Wim Crusio, Paul Franken, Joan Campbell-Tofte, Klaus Schughart, Morris Swertz, Danny Arends, Juan M Falcon-Perez, Ewelina Knapska, Andreas Beyer, Ana Maria Aransay, Steffen Möller, and Department of Infection Genetics, Helmholtz Centre for Infection Research, 38124, Braunschweig, Germany, klaus.schughart@helmholtz-hzi.de.

Subjects
0303 health sciences, West Nile virus, EPS-2, Library science, Biology, Bioinformatics, medicine.disease_cause, Article, Human genetics, 03 medical and health sciences, 0302 clinical medicine, medicine, Information system, Genetics, Life Science, Cooperative behavior, Systems genetics, Analysis tools, Laboratory of Nematology, Laboratorium voor Nematologie, 030217 neurology & neurosurgery, 030304 developmental biology
Abstract

The first scientific meeting of the newly established European SYSGENET network took place at the Helmholtz Centre for Infection Research (HZI) in Braunschweig, April 7-9, 2010. About 50 researchers working in the field of systems genetics using mouse genetic reference populations (GRP) participated in the meeting and exchanged their results, phenotyping approaches, and data analysis tools for studying systems genetics. In addition, the future of GRP resources and phenotyping in Europe was discussed.

Published
2010

28. Novel genetic associations for blood pressure identified via gene-alcohol interaction in up to 570K individuals across multiple ancestries

Author

Rico Rueedi, Yuri Milaneschi, Brenda W.J.H. Penninx, Neil Poulter, Karen Schwander, Marco Brumat, Kenneth Rice, Yize Li, Veronique Vitart, Ioanna Ntalla, Michele K. Evans, Jeffrey R. O'Connell, Nilesh J. Samani, Colleen M. Sitlani, W. James Gauderman, Xuan Deng, Paul M. Ridker, Yun J. Sung, Yukihide Momozawa, Archie Campbell, Tin Louie, Nona Sotoodehnia, Yii-Der Ida Chen, Cornelia M. van Duijn, Tanika N. Kelly, Peter S. Sever, André G. Uitterlinden, Brigitte Kühnel, John M. Starr, Lawrence F. Bielak, Christopher P. Nelson, Wanqing Wen, Stephan B. Felix, Stefan Weiss, Daniel Levy, Nicholette D. Palmer, Alisa K. Manning, Salman M. Tajuddin, Jill M. Norris, Marie Loh, M. Abdullah Said, Alena Stančáková, Anuradhani Kasturiratne, John M. C. Connell, Jian'an Luan, Tuomas O. Kilpeläinen, Amy R. Bentley, Stephen Sidney, Alan B. Zonderman, Karin Leander, David J. Porteous, Jianjun Liu, Tin Aung, Charles B. Eaton, Sharon L.R. Kardia, Rajkumar Dorajoo, Stephen Turner, Michael Boehnke, Diane M. Becker, Cora E. Lewis, Ozren Polasek, Mickaël Canouil, Kurt Lohman, Georg Ehret, Sarah E. Harris, Robert A. Scott, Claude Bouchard, Lynne E. Wagenknecht, Mohsen Ghanbari, Stephen B. Kritchevsky, Jin-Fang Chai, Gregory L. Burke, Jiang He, Federica Laguzzi, Michael R. Brown, Walter Palmas, Lili Milani, Thomas T. Perls, Tibor V. Varga, José Eduardo Krieger, Erin B. Ware, Tamara B. Harris, Tomohiro Katsuya, Nicole Schupf, Mika Kähönen, Nana Matoba, Hugues Aschard, Ilaria Gandin, Jennifer A. Smith, Traci M. Bartz, James Scott, Tuomo Rankinen, Yuan Shi, Meian He, Timo A. Lakka, Helen R. Warren, Mike A. Nalls, Kent D. Taylor, Woon-Puay Koh, Ya Xing Wang, Muhammad Riaz, Sandosh Padmanabhan, Mary F. Feitosa, Jost B. Jonas, Paul Elliott, Christian Gieger, Terho Lehtimäki, Kaare Christensen, Maris Alver, Pirjo Komulainen, Pamela J. Schreiner, M. Arfan Ikram, David R. Weir, Charles Kooperberg, Oscar H. Franco, Yongmei Liu, Lisa de las Fuentes, Nancy L. Pedersen, Thomas W. Winkler, Bruna Gigante, Göran Hallmans, Ingrid B. Borecki, Shiow Lin, Ian J. Deary, Wei Zheng, Yajuan Wang, Bernardo L. Horta, Heather M. Stringham, Bruce M. Psaty, Paul W. Franks, Weihua Zhang, Nora Franceschini, Adolfo Correa, Nita G. Forouhi, Xiuqing Guo, Fumihiko Takeuchi, L. Adrienne Cupples, William R. Scott, Zoltán Kutalik, He Gao, Nicholas J. Wareham, E. Shyong Tai, Aravinda Chakravarti, C. Charles Gu, Paolo Gasparini, Albertine J. Oldehinkel, Xueling Sim, Norihiro Kato, Evangelos Evangelou, Philippe Froguel, Colin A. McKenzie, Qing Duan, Aldi T. Kraja, Carsten Oliver Schmidt, Bamidele O. Tayo, Xiaofeng Zhu, Thomas Meitinger, Mary K. Wojczynski, Markku Laakso, Mark J. Caulfield, Carl D. Langefeld, Jingzhong Ding, Yechiel Friedlander, Tien Yin Wong, Virginia Fisher, Raymond Noordam, Caizheng Yu, Pim van der Harst, Yik Ying Teo, Ervin R. Fox, Sabanayagam Charumathi, Jonathan Marten, Nicholas Y.Q. Tan, Jerome I. Rotter, Harold Snieder, Karen L. Mohlke, Christine Williams, Olli T. Raitakari, Renée de Mutsert, Lihua Wang, Kathryn Roll, Jingmin Liu, Dongfeng Gu, Wei Zhao, Lynda M. Rose, Michael A. Province, Fernando Pires Hartwig, Rob M. van Dam, Barry I. Freedman, Andres Metspalu, Donald W. Bowden, Andrea R. V. R. Horimoto, Martin Farrall, Frits R. Rosendaal, Rainer Rauramaa, Konstantin Strauch, Albert V. Smith, Yanick Hagemeijer, Michiaki Kubo, Ilja M. Nolte, Tõnu Esko, Yih Chung Tham, Cathy C. Laurie, Antonietta Robino, Anne U. Jackson, Chuan Gao, Dabeeru C. Rao, Xiao-Ou Shu, H. Janaka de Silva, Morris J. Brown, Alanna C. Morrison, Peter J. van der Most, Jian-Min Yuan, Melanie Waldenberger, Leslie J. Raffel, Ulrich John, Fang-Chi Hsu, Reedik Mägi, Solomon K. Musani, Chiea Chuen Khor, Mario Sims, Ruben N. Eppinga, Melissa A. Richard, Yoichiro Kamatani, Changwei Li, Qiuyin Cai, Daniel I. Chasman, Mathilde Boissel, Claudia Langenberg, Sami Heikkinen, Jasmin Divers, Saima Afaq, Wen Bin Wei, Jaspal S. Kooner, Terrence Forrester, Hua Tang, Charles N. Rotimi, Anuj Goel, Annette Peters, Tangchun Wu, Dennis O. Mook-Kanamori, Caroline Hayward, Ching-Yu Cheng, Lisa R. Yanek, Ananda R. Wickremasinghe, Chew-Kiat Heng, Myriam Fornage, Dina Vojinovic, Najaf Amin, Lenore J. Launer, Hugh Watkins, Johanna Kuusisto, Jing Hua Zhao, Barbara V. Howard, Vilmundur Gudnason, Ulrich Broeckel, Eric Boerwinkle, Saskia P. Hagenaars, Dan E. Arking, Peter Vollenweider, Alexandre C. Pereira, Jie Yao, Makoto Hirata, Patricia B. Munroe, Patricia A. Peyser, Jessica D. Faul, Xu Chen, Patrik K. E. Magnusson, John C. Chambers, Tamar Sofer, Marzyeh Amini, Benjamin Lehne, Epidemiology, Erasmus MC other, Neurology, Radiology & Nuclear Medicine, Internal Medicine, Læknadeild (HÍ), Faculty of Medicine (UI), School of Health Sciences (UI), Heilbrigðisvísindasvið (HÍ), Háskóli Íslands (HÍ), University of Iceland (UI), Life Course Epidemiology (LCE), Interdisciplinary Centre Psychopathology and Emotion regulation (ICPE), Cardiovascular Centre (CVC), Washington University School of Medicine in St. Louis, Washington University in Saint Louis (WUSTL), Brigham and Women's Hospital [Boston], Harvard Medical School [Boston] (HMS), University of Regensburg, Queen Mary University of London (QMUL), Harbor UCLA Medical Center [Torrance, Ca.], Department of Epidemiology, University of North Carolina [Chapel Hill] (UNC), University of North Carolina System (UNC)-University of North Carolina System (UNC)-UNC Gillings School of Global Public Health-Carolina Center for Genome Sciences, Northwestern Polytechnical University [Xi'an] (NPU), Centre for Molecular Epidemiology, National University of Singapore (NUS), Harvard School of Public Health, Centre de Bioinformatique, Biostatistique et Biologie Intégrative (C3BI), Institut Pasteur [Paris]-Centre National de la Recherche Scientifique (CNRS), European Genomic Institute for Diabetes - FR 3508 (EGID), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Lille-Centre National de la Recherche Scientifique (CNRS), Institut Pasteur de Lille, Réseau International des Instituts Pasteur (RIIP), National Institutes of Health [Bethesda] (NIH), The following authors declare commercial private and/or governmental affiliations: Bruce M. Psaty (BMP) serves on the DSMB of a clinical trial funded by Zoll Lifecor and on the Steering Committee of the Yale Open Data Access Project funded by Johnson & Johnson. Barbara V. Howard (BVH) has a contract from National Heart, Lung, and Blood Institute (NHLBI). Brenda W.J.H. Penninx (BWJHP) has received research funding (non-related to the work reported here) from Jansen Research and Boehringer Ingelheim. Mike A. Nalls (MAN) is supported by a consulting contract between Data Tecnica International LLC and the National Institute on Aging (NIA), National Institutes of Health (NIH), Bethesda, MD, USA. MAN also consults for Illumina Inc., the Michael J. Fox Foundation, and the University of California Healthcare. MAN also has commercial affiliation with Data Tecnica International, Glen Echo, MD, USA. Mark J. Caulfield (MJC) has commercial affiliation and is Chief Scientist for Genomics England, a UK government company. Oscar H Franco (OHF) is supported by grants from Metagenics (on women's health and epigenetics) and from Nestlé (on child health). Peter S. Sever (PSS) is financial supported from several pharmaceutical companies which manufacture either blood pressure lowering or lipid lowering agents, or both, and consultancy fees. Paul W. Franks (PWF) has been a paid consultant in the design of a personalized nutrition trial (PREDICT) as part of a private-public partnership at Kings College London, UK, and has received research support from several pharmaceutical companies as part of European Union Innovative Medicines Initiative (IMI) projects. Fimlab LTD provided support in the form of salaries for author Terho Lehtimäki (TL) but did not have any additional role in the study design to publish, or preparation of the manuscript. Gen‐info Ltd provided support in the form of salaries for author Ozren Polašek (OP) but did not have any additional role in the study design to publish, or preparation of the manuscript. The specific roles of these authors are articulated in the ‘author contributions’ section. There are no patents, products in development, or marked products to declare. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript., AGES (Age Gene/Environment Susceptibility Reykjavik Study) is approved by the Icelandic National Bioethics Committee, VSN: 00–063. The researchers are indebted to the participants for their willingness to participate in the study. ARIC (Atherosclerosis Risk in Communities): The authors thank the staff and participants of the ARIC study for their important contributions. CARDIA (Coronary Artery Risk Development in Young Adults): This manuscript has been reviewed and approved by CARDIA for scientific content. CHS (Cardiovascular Health Study): A full list of principal CHS investigators and institutions can be found at CHS-NHLBI.org. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. IGMM (Institute of Genetics and Molecular Medicine): CROATIA-Korcula: We would like to acknowledge the staff of several institutions in Croatia that supported the field work, including but not limited to The University of Split and Zagreb Medical Schools and the Croatian Institute for Public Health. We would like to acknowledge the invaluable contributions of the recruitment team in Korcula, the administrative teams in Croatia and Edinburgh and the participants. The SNP genotyping for the CROATIA-Korcula cohort was performed in Helmholtz Zentrum München, Neuherberg, Germany. CROATIA-Vis: We would like to acknowledge the staff of several institutions in Croatia that supported the field work, including but not limited to The University of Split and Zagreb Medical Schools, the Institute for Anthropological Research in Zagreb and Croatian Institute for Public Health. The SNP genotyping for the CROATIA-Vis cohort was performed in the core genotyping laboratory of the Wellcome Trust Clinical Research Facility at the Western General Hospital, Edinburgh, Scotland. GS:SFHS: Generation Scotland received core support from the Chief Scientist Office of the Scottish Government Health Directorates [CZD/16/6] and the Scottish Funding Council [HR03006]. Genotyping of the GS:SFHS samples was carried out by the Genetics Core Laboratory at the Wellcome Trust Clinical Research Facility, Edinburgh, Scotland. ERF (Erasmus Rucphen Family study): We are grateful to all study participants and their relatives, general practitioners and neurologists for their contributions and to P. Veraart for her help in genealogy, J. Vergeer for the supervision of the laboratory work, P. Snijders for his help in data collection and E.M. van Leeuwen for genetic imputation. GENOA (Genetic Epidemiology Network of Arteriopathy): Genotyping was performed at the Mayo Clinic (Stephen T. Turner, MD, Mariza de Andrade PhD, Julie Cunningham, PhD). We thank Eric Boerwinkle, PhD and Megan L. Grove from the Human Genetics Center and Institute of Molecular Medicine and Division of Epidemiology, University of Texas Health Science Center, Houston, Texas, USA for their help with genotyping. We would also like to thank the families that participated in the GENOA study. HANDLS (Healthy Aging in Neighborhoods of Diversity across the Life Span): Data analyses for the HANDLS study utilized the high-performance computational resources of the Biowulf Linux cluster at the National Institutes of Health, Bethesda, MD. http://hpc.nih.gov HUFS (Howard University Family Study): We thank the participants of the study. The contents of this publication are solely the responsibility of the authors and do not necessarily represent the official view of the National Institutes of Health. HyperGEN (Hypertension Genetic Epidemiology Network): The study involves: University of Utah: (Network Coordinating Center, Field Center, and Molecular Genetics Lab), Univ. of Alabama at Birmingham: (Field Center and Echo Coordinating and Analysis Center), Medical College of Wisconsin: (Echo Genotyping Lab), Boston University: (Field Center), University of Minnesota: (Field Center and Biochemistry Lab), University of North Carolina: (Field Center), Washington University: (Data Coordinating Center), Weil Cornell Medical College: (Echo Reading Center), National Heart, Lung, & Blood Institute. For a complete list of HyperGEN Investigators: http://www.biostat.wustl.edu/hypergen/Acknowledge.html JHS (Jackson Heart Study): The authors wish to thank the staffs and participants of the JHS. MESA (Multi-Ethnic Study of Atherosclerosis): MESA and the MESA SHARe project are conducted in collaboration with MESA investigators. Genotyping was performed at Affymetrix (Santa Clara, California, USA) and the Broad Institute of Harvard and MIT (Boston, Massachusetts, USA) using the Affymetrix Genome-Wide Human SNP Array 6.0. NEO (The Netherlands Epidemiology of Obesity study): The authors of the NEO study thank all individuals who participated in the Netherlands Epidemiology in Obesity study, all participating general practitioners for inviting eligible participants and all research nurses for collection of the data. We thank the NEO study group, Petra Noordijk, Pat van Beelen and Ingeborg de Jonge for the coordination, lab and data management of the NEO study. RS (Rotterdam Study) was funded by Erasmus Medical Center and Erasmus University, Rotterdam, Netherlands Organization for the Health Research and Development (ZonMw), the Research Institute for Diseases in the Elderly (RIDE), the Ministry of Education, Culture and Science, the Ministry for Health, Welfare and Sports, the European Commission (DG XII), and the Municipality of Rotterdam. The authors are grateful to the study participants, the staff from the Rotterdam Study and the participating general practitioners and pharmacists. The generation and management of GWAS genotype data for the Rotterdam Study was executed by the Human Genotyping Facility of the Genetic Laboratory of the Department of Internal Medicine, Erasmus MC, Rotterdam, The Netherlands. We thank Pascal Arp, Mila Jhamai, Marijn Verkerk, Lizbeth Herrera, Marjolein Peters and Carolina Medina-Gomez for their help in creating the GWAS database, and Karol Estrada, Yurii Aulchenko and Carolina Medina-Gomez for the creation and analysis of imputed data. WHI (Women’s Health Initiative): The authors thank the WHI investigators and staff for their dedication, and the study participants for making the program possible. A full listing of WHI investigators can be found at: http://www.whi.org/researchers/Documents%20%20Write%20a%20Paper/WHI%20Investigator%20Short%20List.pdf Replication: AA-DHS (African American Diabetes Heart Study): The investigators acknowledge the cooperation of our Diabetes Heart Study (DHS) and AA-DHS participants. ASCOT (Anglo-Scandinavian Cardiac Outcomes Trial): We thank all ASCOT trial participants, physicians, nurses, and practices in the participating countries for their important contribution to the study. In particular, we thank Clare Muckian and David Toomey for their help in DNA extraction, storage, and handling. We would also like to acknowledge the Barts and The London Genome Centre staff for genotyping the Exome chip array. P.B.M, M.J.C and H.R.W wish to acknowledge the support of the NIHR Cardiovascular Biomedical Research Centre at Barts and Queen Mary University of London, UK. BBJ (Biobank Japan Project): We thank all the participants, medical coordinators of the cooperating hospitals for collecting samples and clinical information in the project. BRIGHT (British Genetics of Hypertension): The BRIGHT study is extremely grateful to all the patients who participated in the study and the BRIGHT nursing team. P.B.M, M.J.C and H.R.W wish to acknowledge the support of the NIHR Cardiovascular Biomedical Research Centre at Barts and Queen Mary University of London, UK. CoLaus (Cohorte Lausannoise Study): The authors would like to thank all the people who participated in the recruitment of the participants, data collection and validation, particularly Nicole Bonvin, Yolande Barreau, Mathieu Firmann, François Bastardot, Julien Vaucher, Panagiotis Antiochos and Cédric Gubelmann. DESIR (Data from an Epidemiological Study on the Insulin Resistance): The DESIR Study Group is composed of Inserm-U1018 (Paris: B. Balkau, P. Ducimetière, E. Eschwège), Inserm-U367 (Paris: F. Alhenc-Gelas), CHU d’Angers (A. Girault), Bichat Hospital (Paris: F. Fumeron, M. Marre, R. Roussel), CHU de Rennes (F. Bonnet), CNRS UMR-8199 (Lille: A. Bonnefond, P. Froguel), Medical Examination Services (Alençon, Angers, Blois, Caen, Chartres, Chateauroux, Cholet, LeMans, Orléans and Tours), Research Institute for General Medicine (J. Cogneau), the general practitioners of the region and the Cross- Regional Institute for Health (C. Born, E. Caces, M. Cailleau, N. Copin, J.G. Moreau, F. Rakotozafy, J. Tichet, S. Vol). DHS (Diabetes Heart Study): The authors thank the investigators, staff, and participants of the DHS for their valuable contributions. EGCUT Estonian Genome Center—University of Tartu (Estonian Biobank): Data analyzes were carried out in part in the High Performance Computing Center of University of Tartu. EPIC (European Prospective Investigation into Cancer and Nutrition)-Norfolk: We thank all EPIC participants and staff for their contribution to the study. FENLAND (The Fenland Study): We are grateful to all the volunteers for their time and help, and to the General Practitioners and practice staff for assistance with recruitment. We thank the Fenland Study Investigators, Fenland Study Co-ordination team and the Epidemiology Field, Data and Laboratory teams. We further acknowledge support from the Medical research council (MC_UU_12015/1). GeneSTAR (Genetic Studies of Atherosclerosis Risk): We are very grateful to all of our participants for their long-term involvement. GLACIER (Gene x Lifestyle Interactions and Complex Traits Involved in Elevated Disease Risk): We thank the participants, health professionals and data managers involved in the Västerbottens Intervention Project. We are also grateful to the staff of the Northern Sweden Biobank for preparing materials and to K Enqvist and T Johansson (Västerbottens County Council, Umeå, Sweden) for DNA preparation. HCHS/SOL (Hispanic Community Health Study/Study of Latinos): We thank the participants and staff of the HCHS/SOL study for their contributions to this study. HRS (Health & Retirement Study): Our genotyping was conducted by the NIH Center for Inherited Disease Research (CIDR) at Johns Hopkins University. Genotyping quality control and final preparation of the data were performed by the Genetics Coordinating Center at the University of Washington. HyperGEN-AXIOM (Hypertension Genetic Epidemiology Network—Axiom Chip GWAS): We thank the study investigators, staff and participants for their value contributions. INGI (Italian Network Genetic Isolate): We thank all the inhabitants who participated to the projects. InterAct (The EPIC-InterAct Case-Cohort Study): We thank all EPIC participants and staff for their contribution to the study. IRAS (Insulin Resistance Atherosclerosis Study): The authors thank study investigators, staff, and participants for their valuable contributions. KORA (Cooperative Health Research in the Augsburg Region): We thank all KORA participants and staff for their contribution to the study. LBC1921 (Lothian Birth Cohort 1921): We thank the LBC1921 cohort participants and team members who contributed to these studies. Funding from the Biological Sciences Research Council (BBSRC) and Medical Research Council (MRC) is gratefully acknowledged. LBC1936 (Lothian Birth Cohort 1936): We thank the LBC1936 cohort participants and team members who contributed to these studies. Funding from the Biological Sciences Research Council (BBSRC) and Medical Research Council (MRC) is gratefully acknowledged. LifeLines (Lifelines Cohort Study): The authors wish to acknowledge the services of the Lifelines, the contributing research centers delivering data to Lifelines, and all the study participants. The authors wish to acknowledge the services of the Lifelines, the contributing research centers delivering data to Lifelines, and all the study participants. Also, Lifelines acknowledges the contributions from Behrooz Z Alizadeh (Department of Epidemiology, University of Groningen, University Medical Center Groningen, The Netherlands), H Marike Boezen (Department of Epidemiology, University of Groningen, University Medical Center Groningen, The Netherlands), Lude Franke (Department of Genetics, University of Groningen, University Medical Center Groningen, The Netherlands), Pim van der Harst (Department of Cardiology, University of Groningen, University Medical Center Groningen, The Netherlands), Gerjan Navis (Department of Internal Medicine, Division of Nephrology, University of Groningen, University Medical Center Groningen, The Netherlands), Marianne Rots (Department of Medical Biology, University of Groningen, University Medical Center Groningen, The Netherlands), Harold Snieder (Department of Epidemiology, University of Groningen, University Medical Center Groningen, The Netherlands), Morris Swertz (Department of Genetics, University of Groningen, University Medical Center Groningen, The Netherlands), Bruce HR Wolffenbuttel (Department of Endocrinology, University of Groningen, University Medical Center Groningen, The Netherlands), Cisca Wijmenga (Department of Genetics, University of Groningen, University Medical Center Groningen, The Netherlands). LLFS (Long Life Family Study): The LLFS would like to thank the participants and research staff who make the study possible. LOLIPOP (London Life Sciences Prospective Population Study): We acknowledge support of the MRC-PHE Centre for Environment and Health, and the NIHR Health Protection Research Unit on Health Impact of Environmental Hazards. The work was carried out in part at the NIHR/Wellcome Trust Imperial Clinical Research Facility. The views expressed are those of the author(s) and not necessarily those of the Imperial College Healthcare NHS Trust, the NHS, the NIHR or the Department of Health. We thank the participants and research staff who made the study possible. PROCARDIS (Precocious Coronary Artery Disease): The PROCARDIS researchers thank the patients for their selfless participation in this project. RHS (Ragama Health Study): The RHS was supported by the Grant of National Center for Global Health and Medicine (NCGM), Japan. SWHS/SMHS (Shanghai Women's Health Study/ Shanghai Men's Health Study): We thank all the individuals who took part in these studies and all the researchers who have enabled this work to be carried out. TRAILS (TRacking Adolescents’ Individual Lives Survey): TRAILS is a collaborative project involving various departments of the University Medical Center and University of Groningen, the Erasmus University Medical Center Rotterdam, the University of Utrecht, the Radboud Medical Center Nijmegen, and the Parnassia Bavo group, all in the Netherlands. We are grateful to all adolescents who participated in this research and to everyone who worked on this project and made it possible. UKB (United Kingdom Biobank, www.ukbiobank.ac.uk): This research has been conducted using the UK Biobank Resource. The UK Biobank data were analyzed from the data set corresponding to UK Biobank access application no. 236, application title 'Genome-wide association study of blood pressure', with Paul Elliott as the PI/applicant. This work was supported by the UK-CMC and the BP working group., InterAct Consortium, Marten, Jonathan [0000-0001-6916-2014], Luan, Jian'an [0000-0003-3137-6337], Zhao, Jing Hua [0000-0003-4930-3582], Forouhi, Nita [0000-0002-5041-248X], Langenberg, Claudia [0000-0002-5017-7344], Wareham, Nicholas [0000-0003-1422-2993], Apollo - University of Cambridge Repository, Lee Kong Chian School of Medicine (LKCMedicine), Institut Pasteur [Paris] (IP)-Centre National de la Recherche Scientifique (CNRS), Institut Européen de Génomique du Diabète - European Genomic Institute for Diabetes - FR 3508 (EGID), Réseau International des Instituts Pasteur (RIIP)-Réseau International des Instituts Pasteur (RIIP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Lille-Centre National de la Recherche Scientifique (CNRS), Feitosa, Mary F., Kraja, Aldi T., Chasman, Daniel I., Sung, Yun J., Winkler, Thomas W., Ntalla, Ioanna, Guo, Xiuqing, Franceschini, Nora, Cheng, Ching-Yu, Sim, Xueling, Vojinovic, Dina, Marten, Jonathan, Musani, Solomon K., Li, Changwei, Bentley, Amy R., Brown, Michael R., Schwander, Karen, Richard, Melissa A., Noordam, Raymond, Aschard, Hugue, Bartz, Traci M., Bielak, Lawrence F., Dorajoo, Rajkumar, Fisher, Virginia, Hartwig, Fernando P., Horimoto, Andrea R. V. R., Lohman, Kurt K., Manning, Alisa K., Rankinen, Tuomo, Smith, Albert V., Tajuddin, Salman M., Wojczynski, Mary K., Alver, Mari, Boissel, Mathilde, Cai, Qiuyin, Campbell, Archie, Chai, Jin Fang, Chen, Xu, Divers, Jasmin, Gao, Chuan, Goel, Anuj, Hagemeijer, Yanick, Harris, Sarah E., He, Meian, Hsu, Fang-Chi, Jackson, Anne U., Kähönen, Mika, Kasturiratne, Anuradhani, Komulainen, Pirjo, Kühnel, Brigitte, Laguzzi, Federica, Luan, Jian'An, Matoba, Nana, Nolte, Ilja M., Padmanabhan, Sandosh, Riaz, Muhammad, Rueedi, Rico, Robino, Antonietta, Said, M. Abdullah, Scott, Robert A., Sofer, Tamar, Stančáková, Alena, Takeuchi, Fumihiko, Tayo, Bamidele O., Van Der Most, Peter J., Varga, Tibor V., Vitart, Veronique, Wang, Yajuan, Ware, Erin B., Warren, Helen R., Weiss, Stefan, Wen, Wanqing, Yanek, Lisa R., Zhang, Weihua, Zhao, Jing Hua, Afaq, Saima, Amin, Najaf, Amini, Marzyeh, Arking, Dan E., Aung, Tin, Boerwinkle, Eric, Borecki, Ingrid, Broeckel, Ulrich, Brown, Morri, Brumat, Marco, Burke, Gregory L., Canouil, Mickaël, Chakravarti, Aravinda, Charumathi, Sabanayagam, Chen, Yii-Der Ida, Connell, John M., Correa, Adolfo, De Las Fuentes, Lisa, De Mutsert, Renée, De Silva, H. Janaka, Deng, Xuan, Ding, Jingzhong, Duan, Qing, Eaton, Charles B., Ehret, Georg, Eppinga, Ruben N., Evangelou, Evangelo, Faul, Jessica D., Felix, Stephan B., Forouhi, Nita G., Forrester, Terrence, Franco, Oscar H., Friedlander, Yechiel, Gandin, Ilaria, Gao, He, Ghanbari, Mohsen, Gigante, Bruna, Gu, C. Charle, Gu, Dongfeng, Hagenaars, Saskia P., Hallmans, Göran, Harris, Tamara B., He, Jiang, Heikkinen, Sami, Heng, Chew-Kiat, Hirata, Makoto, Howard, Barbara V., Ikram, M. Arfan, John, Ulrich, Katsuya, Tomohiro, Khor, Chiea Chuen, Kilpeläinen, Tuomas O., Koh, Woon-Puay, Krieger, José E., Kritchevsky, Stephen B., Kubo, Michiaki, Kuusisto, Johanna, Lakka, Timo A., Langefeld, Carl D., Langenberg, Claudia, Launer, Lenore J., Lehne, Benjamin, Lewis, Cora E., Li, Yize, Lin, Shiow, Liu, Jianjun, Liu, Jingmin, Loh, Marie, Louie, Tin, Mägi, Reedik, Mckenzie, Colin A., Meitinger, Thoma, Metspalu, Andre, Milaneschi, Yuri, Milani, Lili, Mohlke, Karen L., Momozawa, Yukihide, Nalls, Mike A., Nelson, Christopher P., Sotoodehnia, Nona, Norris, Jill M., O'Connell, Jeff R., Palmer, Nicholette D., Perls, Thoma, Pedersen, Nancy L., Peters, Annette, Peyser, Patricia A., Poulter, Neil, Raffel, Leslie J., Raitakari, Olli T., Roll, Kathryn, Rose, Lynda M., Rosendaal, Frits R., Rotter, Jerome I., Schmidt, Carsten O., Schreiner, Pamela J., Schupf, Nicole, Scott, William R., Sever, Peter S., Shi, Yuan, Sidney, Stephen, Sims, Mario, Sitlani, Colleen M., Smith, Jennifer A., Snieder, Harold, Starr, John M., Strauch, Konstantin, Stringham, Heather M., Tan, Nicholas Y. Q., Tang, Hua, Taylor, Kent D., Teo, Yik Ying, Tham, Yih Chung, Turner, Stephen T., Uitterlinden, André G., Vollenweider, Peter, Waldenberger, Melanie, Wang, Lihua, Wang, Ya Xing, Wei, Wen Bin, Williams, Christine, Yao, Jie, Yu, Caizheng, Yuan, Jian-Min, Zhao, Wei, Zonderman, Alan B., Becker, Diane M., Boehnke, Michael, Bowden, Donald W., Chambers, John C., Deary, Ian J., Esko, Tõnu, Farrall, Martin, Franks, Paul W., Freedman, Barry I., Froguel, Philippe, Gasparini, Paolo, Gieger, Christian, Jonas, Jost Bruno, Kamatani, Yoichiro, Kato, Norihiro, Kooner, Jaspal S., Kutalik, Zoltán, Laakso, Markku, Laurie, Cathy C., Leander, Karin, Lehtimäki, Terho, Magnusson, Patrik K. E., Oldehinkel, Albertine J., Penninx, Brenda W. J. H., Polasek, Ozren, Porteous, David J., Rauramaa, Rainer, Samani, Nilesh J., Scott, Jame, Shu, Xiao-Ou, Van Der Harst, Pim, Wagenknecht, Lynne E., Wareham, Nicholas J., Watkins, Hugh, Weir, David R., Wickremasinghe, Ananda R., Wu, Tangchun, Zheng, Wei, Bouchard, Claude, Christensen, Kaare, Evans, Michele K., Gudnason, Vilmundur, Horta, Bernardo L., Kardia, Sharon L. R., Liu, Yongmei, Pereira, Alexandre C., Psaty, Bruce M., Ridker, Paul M., Van Dam, Rob M., Gauderman, W. Jame, Zhu, Xiaofeng, Mook-Kanamori, Dennis O., Fornage, Myriam, Rotimi, Charles N., Cupples, L. Adrienne, Kelly, Tanika N., Fox, Ervin R., Hayward, Caroline, Van Duijn, Cornelia M., Tai, E. Shyong, Wong, Tien Yin, Kooperberg, Charle, Palmas, Walter, Rice, Kenneth, Morrison, Alanna C., Elliott, Paul, Caulfield, Mark J., Munroe, Patricia B., Rao, Dabeeru C., Province, Michael A., Levy, Daniel, Psychiatry, Amsterdam Neuroscience - Complex Trait Genetics, Surgery, APH - Mental Health, Amsterdam Neuroscience - Mood, Anxiety, Psychosis, Stress & Sleep, APH - Digital Health, and Ehret, Georg Benedikt

Subjects
Genetics and Molecular Biology (all), Male, Erfðagreining, Áfengissýki, LOCI, Social Sciences, Blood Pressure, Genome-wide association study, Biochemistry, Vascular Medicine, TRANSCRIPTION FACTOR GATA4, Biochemistry, Genetics and Molecular Biology (all), Agricultural and Biological Sciences (all), DEPENDENCE, HEPATOCELLULAR-CARCINOMA, 80 and over, Psychology, Public and Occupational Health, Alcohol consumption, Cardiac and Cardiovascular Systems, Gene–environment interaction, ddc:616, Aged, 80 and over, [STAT.AP]Statistics [stat]/Applications [stat.AP], MESH: Middle Aged, Kardiologi, MESH: Polymorphism, Single Nucleotide, Áfengisneysla, MESH: Gene-Environment Interaction, COMMON VARIANTS, Genomics, MESH: Blood Pressure, Pedigree, 3. Good health, Näringslära, MESH: Young Adult, Physical Sciences, Medicine, Medical genetics, Erfðarannsóknir, Statistics (Mathematics), medicine.medical_specialty, Blood Pressure/genetics, Alcohol Drinking, MESH: Pedigree, Science, Genetic loci, ta3111, Genome Complexity, 03 medical and health sciences, Gene mapping, Genetics, Humans, Polymorphism, Statistical Methods, GENOME-WIDE ASSOCIATION, Molecular Biology Techniques, Molecular Biology, Alleles, Aged, MESH: Adolescent, MESH: Humans, Adolescent, Adult, Alcohol Drinking/epidemiology, Alcohol Drinking/genetics, Cohort Studies, Continental Population Groups/genetics, Continental Population Groups/statistics & numerical data, Female, Gene-Environment Interaction, Genetic Predisposition to Disease/epidemiology, Genetic Predisposition to Disease/genetics, Genome-Wide Association Study, Hypertension/epidemiology, Hypertension/genetics, Middle Aged, Polymorphism, Single Nucleotide, Young Adult, Gene Mapping, Racial Groups, ta1182, Biology and Life Sciences, Computational Biology, MESH: Adult, Meta-analysis, 030104 developmental biology, Genetic Loci, MESH: Genome-Wide Association Study, [INFO.INFO-BI]Computer Science [cs]/Bioinformatics [q-bio.QM], MESH: Female, Mathematics, MESH: Alcohol Drinking, Meta-Analysis, 0301 basic medicine, MESH: Continental Population Groups, MESH: Hypertension, Mathematical and Statistical Techniques, MESH: Aged, 80 and over, Polymorphism (computer science), Medicine and Health Sciences, FUNCTIONAL VARIATION, MESH: Cohort Studies, MESH: Aged, Alcohol Consumption, Multidisciplinary, Nutrition and Dietetics, MESH: Genetic Predisposition to Disease, Genetic Predisposition to Disease/epidemiology/genetics, Single Nucleotide, Blóðþrýstingur, ENVIRONMENT INTERACTION, PTP4A1-PHF3-EYS VARIANTS, Alcoholism, ANCESTRAIS, Háþrýstingur, Hypertension, Blood pressure, [STAT.ME]Statistics [stat]/Methodology [stat.ME], Medical Genetics, Research Article, Substance-Related Disorders, Addiction, RISK, METAANALYSIS, Research and Analysis Methods, Mental Health and Psychiatry, medicine, Medicine [Science], Genetic Predisposition to Disease, Allele, Hypertension/epidemiology/genetics, Nutrition, Medicinsk genetik, Continental Population Groups/genetics/statistics & numerical data, business.industry, Alcohol Drinking/epidemiology/genetics, Genetic architecture, MESH: Male, Introns, Diet, BODY-MASS INDEX, [SDV.GEN.GH]Life Sciences [q-bio]/Genetics/Human genetics, [SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie, business
Abstract

Publisher's version (útgefin grein)., Heavy alcohol consumption is an established risk factor for hypertension; the mechanism by which alcohol consumption impact blood pressure (BP) regulation remains unknown. We hypothesized that a genome-wide association study accounting for gene-alcohol consumption interaction for BP might identify additional BP loci and contribute to the understanding of alcohol-related BP regulation. We conducted a large two-stage investigation incorporating joint testing of main genetic effects and single nucleotide variant (SNV)-alcohol consumption interactions. In Stage 1, genome-wide discovery meta-analyses in ≈131K individuals across several ancestry groups yielded 3,514 SNVs (245 loci) with suggestive evidence of association (P < 1.0 x 10−5). In Stage 2, these SNVs were tested for independent external replication in ≈440K individuals across multiple ancestries. We identified and replicated (at Bonferroni correction threshold) five novel BP loci (380 SNVs in 21 genes) and 49 previously reported BP loci (2,159 SNVs in 109 genes) in European ancestry, and in multi-ancestry meta-analyses (P < 5.0 x 10−8). For African ancestry samples, we detected 18 potentially novel BP loci (P < 5.0 x 10−8) in Stage 1 that warrant further replication. Additionally, correlated meta-analysis identified eight novel BP loci (11 genes). Several genes in these loci (e.g., PINX1, GATA4, BLK, FTO and GABBR2) have been previously reported to be associated with alcohol consumption. These findings provide insights into the role of alcohol consumption in the genetic architecture of hypertension., The following authors declare commercial private and/or governmental affiliations: Bruce M. Psaty (BMP) serves on the DSMB of a clinical trial funded by Zoll Lifecor and on the Steering Committee of the Yale Open Data Access Project funded by Johnson & Johnson. Barbara V. Howard (BVH) has a contract from National Heart, Lung, and Blood Institute (NHLBI). Brenda W.J.H. Penninx (BWJHP) has received research funding (non-related to the work reported here) from Jansen Research and Boehringer Ingelheim. Mike A. Nalls (MAN) is supported by a consulting contract between Data Tecnica International LLC and the National Institute on Aging (NIA), National Institutes of Health (NIH), Bethesda, MD, USA. MAN also consults for Illumina Inc., the Michael J. Fox Foundation, and the University of California Healthcare. MAN also has commercial affiliation with Data Tecnica International, Glen Echo, MD, USA. Mark J. Caulfield (MJC) has commercial affiliation and is Chief Scientist for Genomics England, a UK government company. Oscar H Franco (OHF) is supported by grants from Metagenics (on women's health and epigenetics) and from Nestlé (on child health). Peter S. Sever (PSS) is financial supported from several pharmaceutical companies which manufacture either blood pressure lowering or lipid lowering agents, or both, and consultancy fees. Paul W. Franks (PWF) has been a paid consultant in the design of a personalized nutrition trial (PREDICT) as part of a private-public partnership at Kings College London, UK, and has received research support from several pharmaceutical companies as part of European Union Innovative Medicines Initiative (IMI) projects. Fimlab LTD provided support in the form of salaries for author Terho Lehtimäki (TL) but did not have any additional role in the study design to publish, or preparation of the manuscript. Gen‐info Ltd provided support in the form of salaries for author Ozren Polašek (OP) but did not have any additional role in the study design to publish, or preparation of the manuscript. The specific roles of these authors are articulated in the ‘author contributions’ section. There are no patents, products in development, or marked products to declare. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Published
2018

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