|Partner Organization||Partner Country|
|2.Forschergruppe Diabetes e.V. am Helmholtz Zentrum München||Germany|
|3.University of Granada||Spain|
|4.Universite de Lille||France|
|5.Erasmus Medical Center||The Netherlands|
|6.University of Melbourne||Australia|
PREcisE’s goal is to use longitudinal data from the pre-conceptional period up until adulthood to explore the life-course and molecular pathways pertaining the mother to offspring transmissibility of impaired glycaemic health. The project harnesses very large data from cohorts/biobanks from Spain, Germany, Finland, France and the Netherlands. It also joins hands with related projects (e.g., ALPHABET & NutriPROGRAM) and other consortia (e.g, PACE: Pregnancy And Childhood Epigenetics, EGG: Early Growth Genetics, MethQTL: Global Methylation Collaboration) to study the mother-to-offspring transmission of glycaemic health through epigenetic factors.
PREcisE’s main objectives are:
1.To identify robust epigenetic markers in the offspring demarking an exposure to adverse maternal glucose metabolism during pregnancy.
2.To characterize the underpinning molecular pathways and the tissue specificity of such epigenetic markers through gene expression analysis in human tissues.
3.To explore the role of pre- and postnatal nutrition in modifying impaired maternal glucose programming.
4.To exemplify the lasting impact of adopting healthy dietary behaviours from pregnancy onwards on lifelong health.
5.To use state of the art statistical methodology (Bayesian Structural Equation Models) to examine the interplays between maternal glycaemic health indicators, epigenetics, and offspring impaired glycaemic health.
6.Causal analyses of maternal glucose response related epigenetic marker - outcome association using Mendelian Randomisation (MR).
Key results of the project are:
1.Association of maternal glucose area under the curve with child DNA methylation (DNAm) at two adjacent CpGs in the well-known Thioredoxin Interacting (TXNIP) gene.
2. Maternal T1D associated with childhood DNAm at TXNIP. DNAm at TXNIP was also associated with multiple metabolic phenotypes in childhood, adulthood and with some early growth factors in infancy (BMI at Adiposity(A)Peak, Age at ARebound).
3.The two methylation markers were associated with TXNIP expression in the liver.
4. Harmonisation of the dietary indices; glycaemic index (GI) and glycaemic load (GL) as well as the dietary inflammatory index. In addition, GI has been revised to improve its application as pre- and postnatal exposure variable, in ongoing meta-analysis on DNAm during childhood and adolescence.
5. Maternal GI and GL (mostly in mothers with overweight/obesity), adherence to the Mediterranean diet (excluding alcohol) during pregnancy were associated with cord blood DNAm.
6. Maternal early-pregnancy glucose concentrations, but not insulin concentrations, were associated with DNAm in all weight groups, and maternal plasma fatty acid pattern characterized by higher concentrations of n-3 polyunsaturated fatty acids may be associated with accelerated epigenetic gestational ageing.
7. Dietary GL in children and adolescents was positively associated with the methylation of cg20274553 (WDR27). Stratification in children by weight identified several DNAm sites related to GI or GL. Among all identified DNAm sites (N = 537), 76 in blood and 89 in adipose tissue were related to the expression of genes that modulate metabolic processes.
8. Higher sugar-containing beverage intake in infancy was associated with NAFLD in school-aged children, independent of sugar-containing beverage intake and BMI at school age.
9. DNAm at three CpGs (cg05937453, cg25212453, and cg10040131), each in a different age range, was associated with BMI at Bonferroni significance, P < 1.06 × 10−7. DNA methylation at the 187 CpGs previously identified to be associated with adult BMI, increased with advancing age across childhood and adolescence in our analyses. In addition, correlation coefficients between effect estimates for those CpGs in adults and in children and adolescents also increased. Among the top findings for each age range, we observed increasing enrichment for the CpGs that were previously identified in adults (birth Penrichment = 1; childhood Penrichment = 2.00 × 10−4; adolescence Penrichment = 2.10 × 10−7).
10. Development of a life-course model using data from 7 life stages: pre-natal, birth, infancy, childhood, adolescence, early adulthood at 31 years and late adulthood at 46 years, to explore the dynamic determinants of metabolic heath.
11. Testing and application of the above life course model in NFBC1966 data showed that early life up to age of 11y and early adulthood are critical periods to tackle later BMI development.
12. Proxies for the two identified methylation markers were not yet available for MR analyses but MR analyses were carried out using another methylation marker at TXNIP (from published literature) that was associated with T2D in EWAS meta-analyses as a proof of principle. This, however, showed a null causal association between TXNIP and T2D.
We advanced our knowledge on mechanisms of how environment may impact on people’s health and identified elements for preventative measures.
Evidence is emerging to support that a range of pre- and postnatal life-style exposures (e.g. gestational diabetes mellitus (GDM) of the mother, maternal smoking, nutrition) may have an impact on the epigenome and can induce epigenetic marks (e.g. DNAm marks) that predict risk of metabolic disease later in life.
Here we will summarise the key highlights by work package. During the first year of the project, we completed the work on prenatal smoke exposure within PREcisE (Wiklund et al, 2019) showing a dose-response relationship between maternal smoking and blood DNAm in the offspring, replicated permanency of several of these methylation markers until middle age and associations with some causal evidence with adult disorders. These observations have clear public health importance. Public policy actions and guidelines may be improved to better guide strategies for prevention. Still in some countries prevalence of maternal smoking is high.
Within WP1 we have undertaken and completed multiple EWAS meta-analyses to investigate the associations of maternal glycaemic health and metabolism during pregnancy with offspring DNAm, discovering one of the best studied epigenetic marks to date. In particular, we have investigated DNAm profiles in new-born blood and blood collected in later childhood in relation to maternal fasting glucose levels (plasma or whole blood values), maternal glucose response to oral glucose tolerance test (OGTT) and maternal fasted serum insulin levels during pregnancy. The projects were led by PREcisE researchers and in collaboration with Pregnancy and Childhood Epigenetics, PACE, consortium. The analyses showed the association of maternal glucose (area under the curve from OGTT) with child DNAm and identified two adjacent CpGs in the well-known TXNIP gene. TXNIP methylation has been previously found to be associated with metabolic phenotypes and future T2D risk. Both CpGs in TXNIP in our analyses are novel, not yet been described in the literature. Follow up in PREcisE cohorts and datasets showed that DNAm in liver was associated with TXNIP expression and that maternal T1D was also associated with childhood DNAm at TXNIP. In addition, DNAm at TXNIP was associated with multiple metabolic phenotypes in childhood and adulthood. A scientific paper detailing the meta-EWAS was published.
Within WP2 we have completed the harmonisation of dietary indices between cohorts, to be included as pre- and postnatal exposure variables in ongoing meta-analysis on DNAm during childhood and adolescence. The harmonised dietary indices include the glycaemic index and glycaemic load as well as the dietary inflammatory index which has been revised to improve its application in multi-cohort collaborations. A manuscript on the revised calculation of the dietary inflammatory index has been published (PMID: 34748580). The harmonized dietary variables from WP2.1 were taken forward to EWAS meta-analyses on the impact of prenatal and postnatal diet on the epigenome at birth, adolescence, and later ages. We found associations between dietary glycaemic index / glycaemic load during pregnancy and early childhood with DNAm in new-born blood and during later childhood/adolescence. While only few associations between GI/GL and DNAm were observed when analysing the total cohort, stratification into subjects with overweight/obesity and normal weight, revealed that dietary GI/GL was associated with different methylation of numerous CpGs, mostly in the overweight/obese stratum. As this was consistently observed in both meta-analyses, the maternal GI/GL and childhood GI/GL analysis, we suggest that pathways, that are affected by dietary GI/GL, are different between mothers and children with overweight/obesity and with normal weight. This was further strengthened by the finding that associations between maternal early blood glucose concentrations and DNAm in new-borns differed between mothers with overweight/obesity and normal weight mothers.
Within WP3 development of a life course model using seven life stages: pre-natal, birth, infancy, childhood, adolescence, early adulthood at 31 years and late adulthood at 46 years, to explore the dynamic determinants of glycaemic and metabolic heath and its application in NFBC66 data showed that early life up to age of 11y and early adulthood are critical periods for designing appropriate interventions to tackle later BMI development. We discovered that many prenatal and very early factors' associations on distal outcomes are mediated through adiposity rebound measures and that CpGs discovered in TXNIP gene associate with age at adiposity rebound. Work demonstrated the necessity of further structural equation model (SEM) development, update and testing because the earlier packages available could not easily handle complex, multiple type of data. Substantive amount of work was spent on this developmental work and the software is now available for future analyses (under review). We have also worked together with DataSHIELD (https://www.datashield.org/) that offers a platform for analyses of multiple datasets at the same time. Our software is implemented in DataSHIELD, tested and ready for use. The SEMs allow, with triangulation, some inferences of causal associations.
|Authors||Title||Year, Issue, PP||Partners Number||Doi|
|Heil SG, Herzog EM, Griffioen PH, van Zelst B, Willemsen SP, de Rijke YB, Steegers-Theunissen* RPM, Steegers EAP. [ERASMUS]||Lower S-adenosylmethionine levels and DNA hypomethylation of placental growth factor (PlGF) in placental tissue of early-onset preeclampsia-complicated pregnancies.||10.1371/journal.pone.0226969|
|Liu J, Carnero-Montoro E, van Dongen J, Lent S, Nedeljkovic I, Ligthart S, et al||An integrative cross-omics analysis of DNA methylation sites of glucose and insulin homeostasis||10.1038/s41467-019-10487-4|
|Ott R*, Pawlow X*, Weiß A*, Hofelich A, Herbst M, Hummel N, Prehn C, Adamski J, Römisch-Margl W, Kastenmüller G, Ziegler AG, Hummel S*. [FDeV]||Intergenerational Metabolomic Analysis of Mothers with a History of Gestational Diabetes Mellitus and Their Offspring||10.3390/ijms21249647|
|Geurtsen ML, Jaddoe VWV, Gaillard R, Felix JF* [ERASMUS]||Associations of maternal early-pregnancy blood glucose and insulin concentrations with DNA methylation in newborns.||10.1186/s13148-020-00924-3.|
|Yeung EH, Guan W, Zeng X, Salas LA, Mumford SL, de Prado Bert P, van Meel ER, Malmberg A, Sunyer J, Duijts L, Felix JF*, Czamara D, Hämäläinen E, Binder EB, Räikkönen K, Lahti J, London SJ, Silver RM, Schisterman EF [ERASMUS]||Cord blood DNA methylation reflects cord blood C-reactive protein levels but not maternal levels: a longitudinal study and meta-analysis.||10.1186/s13148-020-00852-2|
|Monasso GS, Jaddoe VWV, de Jongste JC, Duijts L, Felix JF* [ERASMUS]||Timing- and Dose-Specific Associations of Prenatal Smoke Exposure With Newborn DNA Methylation.||10.1093/ntr/ntaa069.|
|Sharp GC, Alfano R, Ghantous A, Urquiza J, Rifas-Shiman SL, Page CM, Jin J, Fernández-Barrés S, Santorelli G, Tindula G; 36 other members of the Pregnancy and Childhood Epigenetics (PACE) consortium||Paternal body mass index and offspring DNA methylation: findings from the PACE consortium||10.1093/ije/dyaa267|
|Mulder RH, Neumann A, Cecil CAM, Walton E, Houtepen LC, Simpkin AJ, Rijlaarsdam J, Heijmans BT, Gaunt TR, Felix JF*, Jaddoe VWV, Bakermans-Kranenburg MJ, Tiemeier H, Relton CL, van IJzendoorn MH, Suderman M||Epigenome-wide change and variation in DNA methylation in childhood: Trajectories from birth to late adolescence||10.1093/hmg/ddaa280|
|Vehmeijer FOL, Küpers LK, Sharp GC, Salas LA, Lent S, Jima DD, Tindula G, Reese S, Qi C, Gruzieva O, Page C, Rezwan FI, Melton PE, Nohr E, Escaramís G, Rzehak P, Heiskala A, Gong T, Tuominen ST, Gao L, Ross JP, Starling AP, Holloway JW, Yousefi P, Aasvang GM, Beilin LJ, Bergström A, Binder E, Chatzi L, Corpeleijn E, Czamara D, Eskenazi B, Ewart S, Ferre N, Grote V, Gruszfeld D, Håberg SE, Hoyo C, Huen K, Karlsson R, Kull I, Langhendries JP, Lepeule J, Magnus MC, Maguire RL, Molloy PL, Monnereau C, Mori TA, Oken E, Räikkönen K, Rifas-Shiman S, Ruiz-Arenas C, Sebert S*, Ullemar V, Verduci E, Vonk JM, Xu CJ, Yang IV, Zhang H, Zhang W, Karmaus W, Dabelea D, Muhlhausler BS, Breton CV, Lahti J, Almqvist C, Jarvelin MR*, Koletzko B, Vrijheid M, Sørensen TIA, Huang RC, Arshad SH, Nystad W, Melén E, Koppelman GH, London SJ, Holland N, Bustamante M, Murphy SK, Hivert MF, Baccarelli A, Relton CL, Snieder H, Jaddoe VWV, Felix JF*||DNA methylation and body mass index from birth to adolescence: meta-analyses of epigenome-wide association studies||10.1186/s13073-020-00810-w|
|Van den Berg CB, Herzog EM, Duvekot JJ, Van der Spek PJ, Steegers EAP, Stoop MP, Willemsen SP, Steegers-Theunissen RPM*||Differences in DNA methylation of insulin-like growth factor 2 and cadherin 13 in patients with preeclampsia.||https://doi.org/10.1016/j.preghy.2020.01.010|
|Elmar W. Tobi*, Catarina Almqvist, Anna Hedman, Ellika Andolf, Jan Holte, Jan I. Olofsson, Håkan Wramsby, Margaretha Wramsby, Göran Pershagen, Bastiaan T. Heijmans, Anastasia N. Iliadou||DNA methylation differences at birth after conception through ART.||https://doi.org/10.1093/humrep/deaa253|
|Herzog EM, Eggink AJ, Willemsen SP, Slieker RC, Felix JF, Stubbs AP, Van der Spek PJ, Van Meurs JBJ, Heijmans BT, Steegers-Theunissen RPM*||The tissue-specific aspect of genome-wide DNA methylation in newborn and placental tissues: implications for epigenetic epidemiologic studies||10.1017/S2040174420000136|
|Oliver Robinson, Alice R Carter, Mika Ala-Korpela, Juan P Casas, Nishi Chaturvedi, Jorgen Engmann, Laura D Howe, Alun D. Hughes , Marjo-Riitta Jarvelin*, Mika Ka¨ho¨ nen, Ville Karhunen*, Diana Kuh, Tina Shah, Yoav Ben-Shlomo, Reecha Sofat, Chung-Ho E Lau, Terho Lehtima¨ ki, Usha Menon, Olli Raitakari, Andy Ryan, Rui Providencia, Stephanie Smith, Julie Taylor, Therese Tillin, Jorma Viikari, Andrew Wong, Aroon D Hingorani, Mika Kivima¨ki and Paolo Vineis.||Metabolic profiles of socio-economic position: a multi-cohort analysis||doi: 10.1093/ije/dyaa188|
|Canouil M*, Khamis A, Keikkala E, Hummel S*, Lobbens S, Bonnefond A*, Delahaye F, Tzala E*, Mustaniemi S, Vääräsmäki M, Jarvelin MR*, Sebert S*, Kajantie E, Froguel P, Andrew T||Epigenome-Wide Association Study Reveals Methylation Loci Associated With Offspring Gestational Diabetes Mellitus Exposure and Maternal Methylome||10.2337/dc20-2960|
|Robinson O, Chadeau Hyam M, Karaman I, Climaco Pinto R, Ala-Korpela M, Handakas E, Fiorito G, Gao H, Heard A, Jarvelin MR*, Lewis M, Pazoki R, Polidoro S, Tzoulaki I, Wielscher M, Elliott P, Vineis P.||Determinants of Accelerated Metabolomic and Epigenetic Aging in a UK Cohort.||10.1111/acel.13149|
|Geurtsen ML, Santos S, Gaillard R, Felix JF*, Jaddoe VWV||Associations Between Intake of Sugar-Containing Beverages in Infancy With Liver Fat Accumulation at School Age.||10.1002/hep.31611|
|Geurtsen ML, Wahab RJ, Felix JF*, Gaillard R, Jaddoe VWV||Maternal Early-Pregnancy Glucose Concentrations and Liver Fat Among School-Age Children||10.1002/hep.31910|
|Pawlow X, Ott R*, Winkler C, Ziegler AG, Hummel S*||A new mathematical approach to improve the original dietary inflammatory index (DII) calculation||10.1371/journal.pone.0259629|
|Monasso GS, Jaddoe VWV, Kupers LK, Felix JF*||Epigenetic age acceleration and cardiovascular outcomes in school-age children: The Generation R Study||10.1186/s13148-021-01193-4|
|Tobi EW*, Almqvist C, Hedman A, Andolf E, Holte J, Olofsson JI, et al||DNA methylation differences at birth after conception through ART||10.1093/humrep/deaa253.|
|Monasso GS, Voortman T, Felix JF*||Maternal plasma fatty acid patterns in mid-pregnancy and offspring epigenetic gestational age at birth.||10.1080/15592294.2022.2076051|
|Kupers LK, Fernandez-Barres S, Nounu A, Friedman C, Fore R, Mancano G et al||Maternal Mediterranean diet in pregnancy and newborn DNA methylation: a meta-analysis in the PACE Consortium||10.1080/15592294.2022.2038412|
|Küpers LK, Fernández-Barrés S, Mancano G, Johnson L, Ott R, Vioque J, Colombo M, Landgraf K, Tobi EW*, Körner A, Gaillard R, de Vries JHM, Jaddoe VWV, Vrijheid M, Sharp GC, Felix JF*||Maternal Dietary Glycemic Index and Glycemic Load in Pregnancy and Offspring Cord Blood DNA Methylation||10.2337/dc21-2662|
|Tobi EW*, Juvinao-Quintero DL, Ronkainen J, Ott R*, Alfano R, Canouil M et al||Maternal Glycemic Dysregulation During Pregnancy and Neonatal Blood DNA Methylation:Meta-analyses of Epigenome-Wide Association Studies||10.2337/dc21-1701|
|Monasso GS, Silva CCV, Santos S, Goncalvez R, Gaillard R, Felix JF*, et al.||Infant weight growth patterns, childhood BMI, and arterial health at age 10 years||10.1002/oby.23376|
|Emmanouil Bouras,Ville Karhunen,Dipender Gill,Jian Huang, Philip C. Haycock,Marc J. Gunter,Mattias Johansson,Paul Brennan,Tim Key,Sarah J. Lewis,Richard M. Martin,Neil Murphy, Elizabeth A. Platz,Ruth Travis,James Yarmolinsky,Verena Zuber,Paul Martin,Michail Katsoulis,Heinz Freisling,Therese Haugdahl Nøst,Matthias B. Schulze,Laure Dossus,Rayjean J. Hung,Christopher I. Amos,Ari Ahola-Olli,Saranya Palaniswamy,Minna Männikkö,Juha Auvinen,Karl-Heinz Herzig,Sirkka Keinänen-Kiukaanniemi,Terho Lehtimäki,Veikko Salomaa,Olli Raitakari,Marko Salmi,Sirpa Jalkanen,The PRACTICAL consortium, Marjo-Riitta Jarvelin*Abbas Dehghan,and Konstantinos K. Tsilidis||Circulating inflammatory cytokines and risk of five cancers: a Mendelian randomization analysis||10.1186/s12916-021-02193-0|
|Wielscher M, Mandaviya PR, Kuehnel B, Joehanes R, Mustafa R, Robinson O, Zhang Y, Bodinier B, Walton E, Mishra PP, Schlosser P, Wilson R, Tsai PC, Palaniswamy S, Marioni RE, Fiorito G, Cugliari G, Karhunen V, Ghanbari M, Psaty BM, Loh M, Bis JC, Lehne B, Sotoodehnia N, Deary IJ, Chadeau-Hyam M, Brody JA, Cardona A, Selvin E, Smith AK, Miller AH, Torres MA, Marouli E, Gào X, van Meurs JBJ, Graf-Schindler J, Rathmann W, Koenig W, Peters A, Weninger W, Farlik M, Zhang T, Chen W, Xia Y, Teumer A, Nauck M, Grabe HJ, Doerr M, Lehtimäki T, Guan W, Milani L, Tanaka T, Fisher K, Waite LL, Kasela S, Vineis P, Verweij N, van der Harst P, Iacoviello L, Sacerdote C, Panico S, Krogh V, Tumino R, Tzala E*, Matullo G, Hurme MA, Raitakari OT, Colicino E, Baccarelli AA, Kähönen M, Herzig KH, Li S; BIOS consortium, Conneely KN, Kooner JS, Köttgen A, Heijmans BT, Deloukas P, Relton C, Ong KK, Bell JT, Boerwinkle E, Elliott P, Brenner H, Beekman M, Levy D, Waldenberger M, Chambers JC, Dehghan A, Järvelin MR*||DNA methylation signature of chronic low-grade inflammation and its role in cardio-respiratory diseases.||10.1038/s41467-022-29792-6|
|Pervjakova N, Moen GH, Borges MC, Ferreira T, Cook JP, Allard C, Beaumont RN, Canouil M, Hatem G, Heiskala A, Joensuu A, Karhunen V, Kwak SH, Lin FTJ, Liu J, Rifas-Shiman S, Tam CH, Tam WH, Thorleifsson G, Andrew T, Auvinen J, Bhowmik B, Bonnefond A, Delahaye F, Demirkan A, Froguel P, Haller-Kikkatalo K, Hardardottir H, Hummel S, Hussain A, Kajantie E, Keikkala E, Khamis A, Lahti J, Lekva T, Mustaniemi S, Sommer C, Tagoma A, Tzala E, Uibo R, Vääräsmäki M, Villa PM, Birkeland KI, Bouchard L, Duijn CM, Finer S, Groop L, Hämäläinen E, Hayes GM, Hitman GA, Jang HC, Järvelin MR*, Jenum AK, Laivuori H, Ma RC, Melander O, Oken E, Park KS, Perron P, Prasad RB, Qvigstad E, Sebert S, Stefansson K, Steinthorsdottir V, Tuomi T, Hivert MF, Franks PW, McCarthy MI, Lindgren CM, Freathy RM, Lawlor DA, Morris AP, Mägi R.||Multi-ancestry genome-wide association study of gestational diabetes mellitus highlights genetic links with type 2 diabetes.||10.1093/hmg/ddac050|
|Bond TA, Richmond RC, Karhunen V, Cuellar-Partida G, Borges MC, Zuber V, Couto Alves A, Mason D, Yang TC, Gunter MJ, Dehghan A, Tzoulaki I, Sebert S, Evans DM, Lewin AM, O'Reilly PF, Lawlor DA, Järvelin MR*||Exploring the causal effect of maternal pregnancy adiposity on offspring adiposity: Mendelian randomisation using polygenic risk scores||10.1186/s12916-021-02216-w|
|Freni-Sterrantino A, Fiorito G, D'Errico A, Robinson O, Virtanen M, Ala-Mursula L, Järvelin MR*, Ronkainen J, Vineis P||Work-related stress and well-being in association with epigenetic age acceleration: A Northern Finland Birth Cohort 1966 Study.||10.18632/aging.203872|
|Evangelia Tzala*, Sylvain Sebert*, Raffael Ott *, Leanne K Küpers*, Mercedes G Bermudez *, Mickaël Canouil*, Inga Prokopenko*, Richard Saffery*, Marja Vääräsmäki, Eero Kajantie*, Cristina Campoy*, Régine Steegers-Theunissen*, Vincent W. Jaddoe *, Phillippe Froguel*, Priyanka Parmar, Amelie Bonnefond*, Janine F. Felix *, Sandra Hummel*, Elmar W.Tobi*, Marjo-Riitta Järvelin *||HARMONISING AND COMBINING COHORTS IN DEVELOPMENTAL ORIGINS OF HEALTH AND DISEASE RESEARCH. The PREcisE project.||2021, 18, 164-171||Download|
|Robinson O, Carter AR, Ala-Korpela M, Casas JP, Chaturvedi N, Engmann J, Howe LD, Hughes AD, Järvelin MR*, Kähönen M, Karhunen V, Kuh D, Shah T, Ben-Shlomo Y, Sofat R, Lau CE, Lehtimäki T, Menon U, Raitakari O, Ryan A, Providencia R, Smith S, Taylor J, Tillin T, Viikari J, Wong A, Hingorani AD, Kivimäki M, Vineis P||Metabolic profiles of socio-economic position: a multi-cohort analysis.||10.1093/ije/dyaa188|
|Wielscher M, Amaral AFS, van der Plaat D, Wain LV, Sebert S, Mosen-Ansorena D, Auvinen J, Herzig KH, Dehghan A, Jarvis DL, Jarvelin MR*||Genetic correlation and causal relationships between cardio-metabolic traits and lung function impairment.||doi: 10.1186/s13073-021-00914-x|
|Karhunen V, Bond TA, Zuber V, Hurtig T, Moilanen I, Järvelin MR*, Evangelou M, Rodriguez A||The link between attention deficit hyperactivity disorder (ADHD) symptoms and obesity-related traits: genetic and prenatal explanations.||10.1038/s41398-021-01584-4|
|Bottolo L, Banterle M, Richardson S, Ala-Korpela M, Järvelin MR*, Lewin A||A computationally efficient Bayesian seemingly unrelated regressions model for high-dimensional quantitative trait loci discovery.||10.1111/rssc.12490|
|Nedelec R, Miettunen J, Männikkö M, Järvelin MR*, Sebert S*||Maternal and infant prediction of the child BMI trajectories; studies across two generations of Northern Finland birth cohorts.||10.1038/s41366-020-00695|
|Target group||Authors||Means of communication||Hyperlink|
|Scientist||Dr. Elmar Tobi (ERASMUS) - What is epigenetics – how Evolutionary Biology and Embryology helps us understand the nature of epigenetics. Departments of neonatology and obstetrics, Erasmus MC, November 7th, 2018||Oral presentation|
|MSc students||Dr. Elmar Tobi (ERASMUS), “The origin of the Developmental origins hypothesis and why it matters for metabolic disease”, course for interdisciplinary Master education track, November 14th 2018||Lecture|
|MSc students||Dr. Tobi (ERASMUS), Analyzing DNA methylation micro-array data, Computer practical,October 18th 2018||Teaching an demonstration|
|Master students and teachers||Prof. Marjo-Riitta Jarvelin (IC): Northern Finland Birth Cohort Studies – data and some results including early life epigenetics. MSc Health Data Analytics and Machine Learning, London, UK, Jan 2019.||Lecture|
|MSc students, clinicians, nutritionists||Prof. Marjo-Riitta Jarvelin (IC): Introduction – Genes and Environment short course, Understanding genetic influence on growth and development, London, UK, Feb 2019.||Lecture|
|Professional Practitioners||Prof. Marjo-Riitta Jarvelin (Imperial Colelge London),Lessons from the DynaHEALTH consortium: bio-psychosocial model of glycaemic health”. 55th EASD (European Association for the Study of Diabetes) Annual Meeting Symposium, Barcelona, Spain, Sept 2019||A formal working group, expert panel or dialogue|
|Scientists||Associate Prof. Janine Felix (ERASMUS); Early-life programming of life course health. Helmholtz Zentrum für Umweltforschung UFZ, Leipzig, Germany, Feb 2019.||Lecture|
|Scientists||Associate Prof. Janine Felix (ERASMUS); "Maternal factors and epigenetics" during the 45th Annual meeting of the German Society for Neonatology and Pediatric intensive care, Leipzig (Germany), May 2019 May 2019.||Oral Presentation|
|Scientists||Dr. Evangelia Tzala (IC); Bayesian Life-Course Path Analysis Model: Application NFBC (national Finnish Birth Cohort) 1966. PREcisE kick-off meeting, Lille, France, Jun 2019.||Short talk|
|Scientists||Prof. Steegers-Theunissen RPM (ERASMUS). Periconception one carbon metabolism and embryonic and placental health, 12th International conference on One Carbon Metabolism, B Vitamins and Homocysteine, Reus, Jun 2019 (invited speaker).||Lecture|
|Public Outreach||Associate Prof. Janine Felix (ERASMUS); Biosamples panel session during the “Born in Bradford” Science Festival 2019, Bradford, UK, Oct 2019 (participated in the panel).||Panel session|
|PhD students||Prof. Marjo-Riitta Jarvelin (IC): Research Design for Social Sciences and Medicine. Three-hour interactive session including aspects of genetic/epigenetic studies. Imperial College Graduate School, London, UK, Feb 2019.||Lecture|
|Master students and teachers||Prof. Marjo-Riitta Jarvelin (IC): Lifecourse models – data – on metabolic traits addressing early life epigenetics. MSc Health Data Analytics and Machine Learning, London, UK, Nov 2019.||Lecture|
|Clinicians, scientists||Dr. Elmar Tobi (Erasmus): A precise meta-analysis on maternal glycemic traits and cord blood DNA methylation. - Erasmus MC department talk Nov 2020||Lecture|
|Public (for the lower income parts of Rotterdam)||Prof. Steegers-Theunissen RPM [ERASMUS}. Een gezonde baby: wat kun je zelf doen? For You Magazine editie Rotterdam 2019, 2: 30. Title in English: A healthy baby; what can you do?||Magazine interview|
|Postgraduate students||Prof. Jarvelin (IC), Interactive introductory session (1.5 hours) for new PhD students in the pathway of Life Course, Psychology and Health (n ~40 ) of the London Interdisciplinary Social Science Programme (LISS), between Imperial College Graduate School, King’s College London and Queen Mary University London) Oct 2020.||Oral Presentation|
|Scientists. policy makers, general public||Prof. Marjo-Riitta Jarvelin (IC); Protective and preventive healthcare. Highlights of the importance of lifestyle factors and early years intervention 2020||Interview paper (profile):|
|Students and Scientists||Associate Prof. Janine Felix (ERASMUS), Pregnancy exposures and offspring DNA methylation” in FASEB “The Epigenome in Human Health and Diseases Conference,October 2021||Lecture|
|Policymakers/politicians,Professional Practitioners,Industry/Business||Associate Prof. Janine Felix (ERASMUS ) & Prof Marjo-Riitta Jarvelin (IC), Early-life nutrition, epigenetics and life course health; Where science has taken us, Lecture during the 6th JPI-HDHL conference, April-20-21-2021||Oral Presentation|
|Scientist, Postgraduates||Prof. Sylvain Sebert (IC), Life-Course Modelling on Adult BMI,Presentation to the annual meeting of the EUCAN Connect project,2021||Oral Presentation|
|Clinician and Nurses||Dr. Sandra Hummel (FDeV): Overweight and Diabetes during childhood, Annual meeting of the German Diabetes Association, May 2021||Oral Presentation|
|Public Outreach||Dr. Sandra Hummel (FDeV): Gestational Diabetes||Podcast|
|Teachers||Dr. Sandra Hummel (FDeV), Teachers training, Helmholtz Zentrum München, Diabetes-information portal; Munich, Germany: Prediction and Prevention of diabetes, May 2021||Seminar|
|Public||Prof. Marjo-Riitta Jarvelin (IC), Lifelong health – what Birth Cohort Studies May tell you? Tales from the Northern Finland Birth Cohorts, 16.06.2022||Public lecture (recorded), followed by a newspaper interview and article.|
|Scientists||Prof. Jarvelin (IC), Conference on Epidemiological Birth Cohort and Longitudinal Studies- the 4th Paula Rantakallio symposium, 15-17th June 2022||Presentation|
|Clinicians, Nurses||Dr. Sandra Hummel (FDeV); Training meeting CJD Diabetes Center Berchtesgaden, Germany: Diabetes and adolescence – Prevention of type 2 diabetes, October 2021||Oral Presentation/Seminar|
|Professional Practitioners||Dr. Sandra Hummel (FeDV), Teenagers with diabetes, FORSCHERGRUPPE DIABETES e.V-Germany, 2021||Oral Presentation|
|Physicians, Nurses||Dr. Sandra Hummel (FDeV): Breastfeeding and Diabetes – health benefits for mothers and their offspring. Webinar organised by the Institute for the Advancement of Breastfeeding & Lactation Education (IABLE), 20.10.2021||Lecture|
|Teachers||Dr. Sandra Hummel (FeDV), Health promotion – Prevention – Diet,Workshop for teachers, FORSCHERGRUPPE DIABETES e.V-Germany||Workshop|
|Public Outreach||Dr. Sandra Hummel (FDeV): Diabetes during pregnancy – Article in UGB Forum 03/2021||Article in lay journal|
|Scientific community||Dr. Raffael Ott (FDeV): Epigenome-wide associations with dietary glycemic index and glycemic load in children and adolescents vary by weight status. 31.08.2022||Abstract|
|MSc students – Epidemiology||Dr. Sandra Hummel (FDeV); Lecture MSc Epidemiology, Ludwig-Maximilians University, Munich, Germany: Prediction and Prevention of Diabetes, April 2021 and April 2022||Lecture|
|Medical students||University Munich, Germany: Type 1 Diabetes, Gestational Diabetes, 2021 and 2022||Lecture|
|Patent licence||Partners involved||Year||International eu or national patent||Comment|
|Book chapter||Hoek J, Steegers-Theunissen RPM* [ERASMUS], Sinclair K., Schoenmakers S. The science of preconception. In: Shawe J, Steegers EAP, Verbiest S (eds) Preconception health and care: A life course approach. (2020) ISBN 978-3-030-31752-2. https://doi.org/10.1007/978-3-030-31753-9_3||2020|
|Textbook chapter||Akhter Z, Van der Windt M, Van der Kleij R, Heslehurst N, Steegers-Theunissen RPM* [ERASMUS]. (2019) Preconception health and care: a life-course approach. Textbook, chapter 5.||2019|
|Handbook||Van der Kleij R, Van der Windt M, Steegers-Theunissen RPM*[ERASMUS]. Handboek Leeftstijlgeneeskunde – De eerste 1000 dagen en de 100 ervoor | rond de zwangerschap. (2019) ISBN 9789036823234||2019||Aimed at Dutch general practitioners and mid-wifes.|
|Textbook chapter||Ganzevoort W, Painter RC, Van Wassemaer-Leemhuis AG, De Bakker BS, Steegers-Theunissen RPM*, Faas MM [ERASMUS]. Textbook of obstetrics and gynaecology. A life course approach. Part II Conception and foetal health. Embryonic, placental and foetal growth and development. 121-138. (2019) ISBN 978 90 368 2130 8||2019||For a textbook used for Medical training (used at the Erasmus Medical Centre among others)|
|Textbook chapter||Schoenmakers S, Koster MPH, Steegers-Theunissen RPM* [ERASMUS]. Textbook of obstetrics and gynaecology. A life course approach. Part II Conception and foetal health. Preconception health and care. 107-120. (2019) ISBN 978 90 368 2130 8||2019||For a textbook used for Medical training (used at the Erasmus Medical Centre among others)|
|PhD thesis||Ville Karhunen [IC]; Statistical modelling strategies in molecular epidemiology, with an application to attention-deficit hyperactivity disorder,||2020 (year completed)||Supervisor: Marjo-Riitta Jarvelin [IC]|