Maximizing human developmental


Here, you can view the most recent findings and publications of the LifeCycle research team. Just click on the respective title to read or download the original article.

Number of LifeCyle publications to date: 181


  1. Pinot de Moira A et al. (2022). Associations of early-life pet ownership with asthma and allergic sensitization: A meta-analysis of more than 77,000 children from the EU Child Cohort Network. J Allergy Clin Immunol


  1. Ardura-Garcia C et al. (2021). ERS International Congress 2020: highlights from the Paediatric AssemblyERJ Open Res 7(1).
  2. Bell JA et al. (2021). Sex differences in systemic metabolites at four life stages: cohort study with repeated metabolomics. BMC Med 19(1): 58.
  3. Birks LE et al. (2021). Radiofrequency electromagnetic fields from mobile communication: Description of modeled dose in brain regions and the body in European children and adolescentsEnviron Res 193: 110505.
  4. Bond TA et al. (2021). Exploring the causal effect of maternal pregnancy adiposity on offspring adiposity: Mendelian randomization using polygenic risk scores. medRxiv Preprint.
  5. Brands B et al. (2021). Global e-Learning in Early Nutrition and Lifestyle for International Healthcare Professionals: Design and Evaluation of the Early Nutrition Specialist Programme (ENS)Nutrients 13(3).
  6. Cadman T et al. (2021). Joint associations of parental personality traits and socio‐economic position with trajectories of offspring depression: Findings from up to 6925 families in a UK birth cohort. JCPP Advances 1(3): e12028.
  7. Cadman T et al. (2021). The role of school enjoyment and connectedness in the association between depressive and externalising symptoms and academic attainment: Findings from a UK prospective cohort study. J Affect Disord 295: 974-980.
  8. Chen LW et al. (2021). Associations of maternal dietary inflammatory potential and quality with offspring birth outcomes: An individual participant data pooled analysis of 7 European cohorts in the ALPHABET consortiumPLoS Med 18(1): e1003491.
  9. Chen LW et al. (2021). Maternal dietary quality, inflammatory potential and childhood adiposity: an individual participant data pooled analysis of seven European cohorts in the ALPHABET consortiumBMC Med 19(1): 33.
  10. Choedon T et al. (2021). Population estimates and determinants of severe maternal thinness in India. Int J Gynaecol Obstet 155(3): 380-397.
  11. de Prado-Bert P et al. (2021). The early-life exposome and epigenetic age acceleration in childrenEnviron Int 155: 106683.
  12. Elhakeem A et al. (2021). Using linear and natural cubic splines, SITAR, and latent trajectory models to characterise nonlinear longitudinal growth trajectories in cohort studies. medRxiv Preprint
  13. Eriksson MD et al. (2021). Higher carotid-radial pulse wave velocity is associated with non-melancholic depressive symptoms in men – findings from Helsinki Birth Cohort StudyAnn Med 53(1): 531-40.
  14. Florian S et al. (2021). Parental migrant status and health inequalities at birth: The role of immigrant educational selectivity. Soc Sci Med 278: 113915.
  15. Geurtsen ML et al. (2021). Associations Between Intake of Sugar-Containing Beverages in Infancy With Liver Fat Accumulation at School AgeHepatology 73(2): 560-70.
  16. Geurtsen ML et al. (2021). Maternal Early-Pregnancy Glucose Concentrations and Liver Fat Among School-Age ChildrenHepatology.
  17. Gomez-Alonso MDC et al. (2021). DNA methylation and lipid metabolism: an EWAS of 226 metabolic measuresClin Epigenetics 13(1): 7.
  18. Gonzalez J. et al (2021). Metabolomic Signatures in Pediatric Crohn’s Disease Patients with Mild or Quiescent Disease Treated with Partial Enteral Nutrition: A Feasibility StudySLAS TECHNOLOGY 26(2): 165-177
  19. Guerlich K et al. (2021). Sleep duration and problem behaviour in 8-year-old children in the Childhood Obesity Project. Eur Child Adolesc Psychiatry.
  20. Hartwig FP et al. (2021). Bias in two-sample Mendelian randomization when using heritable covariable-adjusted summary associations. Int J Epidemiol.
  21. Huang RC et al. (2021). Adiposity associated DNA methylation signatures in adolescents are related to leptin and perinatal factorsEpigenetics: 1-18.
  22. Hu C et al. (2021). A population-based study on associations of stool microbiota with atopic diseases in school-age children. J Allergy Clin Immunol 148(2): 612-20.
  23. Hu C et al. (2021). Association between nasal and nasopharyngeal bacterial colonization in early life and eczema phenotypesClin Exp Allergy 51(5): 716-25.
  24. Hughes RA et al. (2021). Combining Longitudinal Data From Different Cohorts to Examine the Life-Course Trajectory. Am J Epidemiol.
  25. Jacob CM et al. (2021). A systematic review and meta-analysis of school-based interventions with health education to reduce body mass index in adolescents aged 10 to 19 yearsInt J Behav Nutr Phys Act 18(1): 1.
  26. Jacob CM et al. (2021). Test, Trace and Learn: lessons about COVID-19 from young people Testare, tracciare e imparare: lezioni sul COVID-19 dai giovani. Epidemiol Prev 45(6): 441-442.
  27. Julvez J et al. (2021). Early life multiple exposures and child cognitive function: A multi-centric birth cohort study in six European countriesEnviron Pollut 284: 117404.
  28. Kurilshikov A et al. (2021). Large-scale association analyses identify host factors influencing human gut microbiome compositionNat Genet 53(2): 156-65.
  29. Larrosa S. et al (2021). Fibre Intake Is Associated with Cardiovascular Health in European ChildrenNutrients 13(1):12.
  30. Looman KIM et al. (2021). Increased Th22 cell numbers in a general pediatric population with filaggrin haploinsufficiency: The Generation R StudyPediatr Allergy Immunol 32(6): 1360-8.
  31. Lubczynska MJ et al. (2021). Air pollution exposure during pregnancy and childhood and brain morphology in preadolescents. Environ Res 198: 110446.
  32. Luo M et al. (2021). Neonatal DNA methylation and childhood low prosocial behavior: An epigenome-wide association meta-analysisAm J Med Genet B Neuropsychiatr Genet 186(4): 228-41.
  33. Maitre L et al. (2021). Early-life environmental exposure determinants of child behavior in Europe: A longitudinal, population-based studyEnviron Int 153: 106523.
  34. Mensink-Bout SM et al. (2021). Cardio-metabolic risk factors during childhood in relation to lung function and asthmaPediatr Allergy Immunol 32(5): 945-52.
  35. Moccia C et al. (2021). Birthweight DNA methylation signatures in infant salivaClin Epigenetics 13(1): 57.
  36. Modi N et al. (2021). Health of women and children is central to covid-19 recoveryBMJ 373: n899.
  37. Monasso GS et al. (2021). Associations of circulating folate, vitamin B12 and homocysteine concentrations in early pregnancy and cord blood with epigenetic gestational age: the Generation R StudyClin Epigenetics 13(1): 95.
  38. Monasso GS et al. (2021). Associations of Early Pregnancy and Neonatal Circulating Folate, Vitamin B-12, and Homocysteine Concentrations with Cardiometabolic Risk Factors in Children at 10 y of AgeJ Nutr 151(6): 1628-36.
  39. Mulder RH et al. (2021). Epigenome-wide change and variation in DNA methylation in childhood: trajectories from birth to late adolescenceHum Mol Genet 30(1): 119-34.
  40. Nader JL et al. (2021). Cohort description: Measures of early-life behaviour and later psychopathology in the LifeCycle Project – EU Child Cohort Network. J Epidemiol.  Online ahead of print.
  41. Nedelec R et al. (2021). Maternal and infant prediction of the child BMI trajectories; studies across two generations of Northern Finland birth cohortsInt J Obes (Lond) 45(2): 404-14.
  42. Penkler M et al. (2021). Developmental Origins of Health and Disease, resilience and social justice in the COVID era. J Dev Orig Health Dis. Online ahead of print.
  43. Penova-Veselinovic B et al. (2021). DNA methylation patterns within whole blood of adolescents born from assisted reproductive technology are not different from adolescents born from natural conception. Hum Reprod 36(7): 2035-49.
  44. Pinot de Moira A et al. (2021). The EU Child Cohort Network’s core data: establishing a set of findable, accessible, interoperable and re-usable (FAIR) variablesEur J Epidemiol 36(5): 565-80.
  45. Polanska K et al. (2021). Dietary Quality and Dietary Inflammatory Potential During Pregnancy and Offspring Emotional and Behavioral Symptoms in Childhood: An Individual Participant Data Meta-analysis of Four European Cohorts. Biol Psychiatry 89(6): 550-9.
  46. Popovic M et al. (2021). Determination of saliva epigenetic age in infancy, and its association with parental socio-economic characteristics and pregnancy outcomes. J Dev Orig Health Dis, 12(2), 319-327.
  47. Quezada-Pinedo HG et al. (2021). Maternal iron status during early pregnancy and school-age, lung function, asthma, and allergy: The Generation R Study. Pediatr Pulmonol 56(6): 1771-8.
  48. Quezada-Pinedo HG et al. (2021). Maternal Iron Status in Pregnancy and Child Health Outcomes after Birth: A Systematic Review and Meta-Analysis. Nutrients 13(7).
  49. Rasella D et al. (2021). Developing an integrated microsimulation model for the impact of fiscal policies on child health in Europe: the example of childhood obesity in Italy. BMC Med 19(1): 310.
  50. Rijlaarsdam J et al. (2021). Genome-wide DNA methylation patterns associated with general psychopathology in childrenJ Psychiatr Res 140: 214-20.
  51. Ronkainen J et al. (2021). Maternal haemoglobin levels in pregnancy and child DNA methylation: a study in the pregnancy and childhood epigenetics consortiumEpigenetics: 1-13.
  52. Sammallahti S et al. (2021). Maternal anxiety during pregnancy and newborn epigenome-wide DNA methylationMol Psychiatry 26(6): 1832-45.
  53. Sethi V et al. (2021). Screening and management options for severe thinness during pregnancy in India. Int J Gynaecol Obstet 155(3): 357-379.
  54. Sharp GC et al. (2021). Paternal body mass index and offspring DNA methylation: findings from the PACE consortium. Int J Epidemiol 50(4): 1297-315.
  55. Taylor K et al. (2021). Effect of Maternal Prepregnancy/Early-Pregnancy Body Mass Index and Pregnancy Smoking and Alcohol on Congenital Heart Diseases: A Parental Negative Control Study. J Am Heart Assoc 10(11): e020051.
  56. van den Dries MA et al. (2021). Prenatal Exposure to Nonpersistent Chemical Mixtures and Fetal Growth: A Population-Based Study. Environ Health Perspect 129(11): 117008.
  57. van Dongen J et al. (2021). DNA methylation signatures of aggression and closely related constructs: A meta-analysis of epigenome-wide studies across the lifespanMol Psychiatry 26(6): 2148-62.
  58. Vehmeijer FOL et al. (2021). Associations of Hair Cortisol Concentrations With Cardiometabolic Risk Factors in ChildhoodJ Clin Endocrinol Metab 106(9): e3400-e13.
  59. Warembourg C et al. (2021). Urban environment during early-life and blood pressure in young childrenEnviron Int 146: 106174.
  60. Wiertsema CJ et al. (2021). First trimester fetal proportion volumetric measurements using a Virtual Reality approachPrenat Diagn 41(7): 868-76.
  61. Zou R et al. (2021). Maternal polyunsaturated fatty acids during pregnancy and offspring brain development in childhood. Am J Clin Nutr 114(1): 124-33.


  1. Beaumont RN et al. (2020). Common maternal and fetal genetic variants show expected polygenic effects on risk of small- or large-for-gestational-age (SGA or LGA), except in the smallest 3% of babiesPLoS Genet 16(12): e1009191.
  2. Caramaschi D. et al. (2020). Epigenome-wide association study of seizures in childhood and adolescence. Clin Epigenetics. 12(1): 8.
  3. Ehakeem A et al. (2020). Age at puberty and accelerometer-measured physical activity: Findings from two independent UK cohorts. Ann Hum Biol 47(4): 391-9.
  4. El Marroun H et al. (2020). Association of Gestational Age at Birth With Brain Morphometry. JAMA Pediatr 174(12): 1149-58.
  5. Geurtsen ML et al. (2020). Associations of maternal early-pregnancy blood glucose and insulin concentrations with DNA methylation in newborns. Clin Epigenetics 12(1): 134.
  6. Hamoen M et al. (2020). Development of a prediction model to target screening for high blood pressure in children. Prev Med 132: 105997.
  7. Hanson M. et al. (2020). New guidelines, position paper, and insights from the FIGO Pregnancy Obesity and Nutrition Initiative (PONI). Int J Gynaecol Obstet. 151(S1), 1-3.
  8. Hu C et al. (2020). Associations of eczema phenotypes with emotional and behavioural problems from birth until school age. The Generation R StudyBr J Dermatol 183(2): 311-20.
  9. Jacob C.M. et al. (2020). Building resilient societies after COVID-19 requires multifaceted investment targeting maternal, neonatal and child health. Lancet Public Health. Online first: 21 September 2020.
  10. Jacob C.M. et al. (2020). Implications of the Developmental Origins of Health and Disease (DOHaD) concept for policy-making. Curr Opin Endocr Metab Res. 13: 20-27.
  11. Jacob C.M. et al. (2020). Prevention on non-communicable diseases by interventions in the preconception period: A FIGO position paper for action by the healthcare practitioners. Int J Gynaecol Obstet. 151(S1), 6-15.
  12. Jaddoe V.W.V. et al. (2020). The LifeCycle Project-EU Child Cohort Network: a federated analysis infrastructure and harmonized data of more than 250,000 children and parents. Eur J Epidemiol. 35(7): 709-724.
  13. Kirchberg F.F. et al. (2020). Impact of infant protein supply and other early life factors on plasma metabolome at 5.5 and 8 years of age: a randomized trial. Int J Obesity. 44: 69-81.
  14. Looman KIM et al. (2020). Associations of Th2, Th17, Treg cells, and IgA(+) memory B cells with atopic disease in children: The Generation R StudyAllergy 75(1): 178-87.
  15. Lubczynska M.J. et al. (2020). Exposure to Air Pollution during Pregnancy and Childhood, and White Matter Microstructure in Preadolescents. Environ Health Perspect. 128(2): 27005.
  16. Mensink-Bout SM et al. (2020). Associations of Plasma Fatty Acid Patterns during Pregnancy with Respiratory and Allergy Outcomes at School AgeNutrients 12(10).
  17. Mikkola T.M. et al. (2020). Associations of Fat and Lean Body Mass with Circulating Amino Acids in Older Men and Women. J Gerontol A Biol Sci Med Sci. 75(5): 885-891.
  18. Mikkola T.M. et al. (2020). Body composition and changes in health-related quality of life in older age: a 10-year follow-up of the Helsinki Birth Cohort Study. Qual Life Res. [e-pub ahead of print].
  19. Mulder R.H. et al. (2020). Epigenomics of being bullied: changes in DNA methylation following bullying exposure. Epigenetics. 1-15.
  20. Neumann A et al. (2020). Association between DNA methylation and ADHD symptoms from birth to school age: a prospective meta-analysisTransl Psychiatry 10(1): 398.
  21. Palaniswamy S et al. (2020). Could vitamin D reduce obesity-associated inflammation? Observational and Mendelian randomization studyAm J Clin Nutr 111(5): 1036-47.
  22. Philips EM et al. (2020). Changes in parental smoking during pregnancy and risks of adverse birth outcomes and childhood overweight in Europe and North America: An individual participant data meta-analysis of 229,000 singleton birthsPLoS Med 17(8): e1003182.
  23. Pizzi C. et al. (2020). Measuring Child Socio-Economic Position in Birth Cohort Research: The Development of a Novel Standardized Household Income Indicator. Int J Environ Res Public Health. 17(5): 1700.
  24. Robinson O et al. (2020). Determinants of accelerated metabolomic and epigenetic aging in a UK cohortAging Cell 19(6): e13149.
  25. Santos S. et al. (2020). Applying the exposome concept in birth cohort research: a review of statistical approaches. Eur J Epidemiol. 35: 193–204.
  26. Toemen L et al. (2020). Body Fat Distribution, Overweight, and Cardiac Structures in School-Age Children: A Population-Based Cardiac Magnetic Resonance Imaging Study. J Am Heart Assoc 9(13): e014933.
  27. Vehmeijer FOL et al. (2021). Associations of Hair Cortisol Concentrations with General and Organ Fat Measures in ChildhoodJ Clin Endocrinol Metab 106(2): e551-e61.
  28. Voerman E. et al. (2020). A population-based resource for intergenerational metabolomics analyses in pregnant women and their children: the Generation R StudyMetabolomics 16(4): 43.
  29. Yeung EH et al. (2020). Cord blood DNA methylation reflects cord blood C-reactive protein levels but not maternal levels: a longitudinal study and meta-analysisClin Epigenetics 12(1): 60.
  30. Zou R. et al. (2020). A prospective population-based study of gestational vitamin D status and brain morphology in preadolescents. Neuroimage. 209: 116514.


  1. Alemany S. et al. (2019). Common Polygenic Variations for Psychiatric Disorders and Cognition in Relation to Brain Morphology in the General Pediatric Population. J Am Acad Child Adolesc Psychiatry. Online first: S0890-8567(19)30007-3.
  2. Aubert A.M. et al. (2019). Deriving the Dietary Approaches to Stop Hypertension (DASH) Score in Women from Seven Pregnancy Cohorts from the European ALPHABET Consortium. Nutrients. 11(11): pii: E2706.
  3. Ballon M. et al. (2019). Which modifiable prenatal factors mediate the relation between socio-economic position and a child’s weight and length at birth? Matern Child Nutr. 15(4): e12878.
  4. Bird P.K. et al. (2019). Income inequality and social gradients in children’s height: a comparison of cohort studies from five high-income countries. BMJ Paediatr Open. 3(1): e000568
  5. Birth-Gene Study Working Group et al. (2019). Association of Birth Weight With Type 2 Diabetes and Glycemic Traits: A Mendelian Randomization Study. JAMA Netw Open. 2(9): e1910915.
  6. Bond T.A. et al. (2019). Exploring the role of genetic confounding in the association between maternal and offspring body mass index: evidence from three birth cohorts. Int J Epidemiol. dyz095.
  7. Bradfield J.P. et al. (2019). A trans-ancestral meta-analysis of genome-wide association studies reveals loci associated with childhood obesity. Hum Mol Genet. 28(19): 3327-3338.
  8. Brand J.S. et al. (2019). Associations of maternal quitting, reducing, and continuing smoking during pregnancy with longitudinal fetal growth: Findings from Mendelian randomization and parental negative control studies. PLoS Med.  16(11): e1002972.
  9. Cardenas A. et al. (2019). Prenatal maternal antidepressants, anxiety, and depression and offspring DNA methylation: epigenome-wide associations at birth and persistence into early childhood. Clin Epigenetics. 11(1): 56.
  10. Chandni M.J. (2019). Do the concepts of “life course approach” and “developmental origins of health and disease” underpin current maternity care? Study protocol. Int J Gynaecol Obstet. 147(2): 140-146.
  11. Cortes Hidalgo A.P. et al. (2019). Observed infant-parent attachment and brain morphology in middle childhood- A population-based study. Dev Cogn Neurosci. 40: 100724.
  12. Couto Alves A. et al. (2019). GWAS on longitudinal growth traits reveals different genetic factors influencing infant, child, and adult BMI. Sci Adv. 5(9): eaaw3095.
  13. den Dekker H.T. et al. (2019). Newborn DNA-methylation, childhood lung function, and the risks of asthma and COPD across the life course. Eur Respir J. 53(4): 1801795.
  14. Elhakeem A. (2019). Association Between Age at Puberty and Bone Accrual From 10 to 25 Years of Age. JAMA Netw Open. 2(8): e198918.
  15. Geurtsen M.L. (2019). Newborn and childhood differential DNA methylation and liver fat in school-age children. Clin Epigenetics. 12(1): 3.
  16. Gruzieva O. et al. (2019). Prenatal Particulate Air Pollution and DNA Methylation in Newborns: An Epigenome-Wide Meta-Analysis. Environ Health Perspect. 127(5): 57012.
  17. Haworth S. et al. (2019). Low-frequency variation in TP53 has large effects on head circumference and intracranial volume. Nat Commun, online first: 10(1): 357.
  18. Hwang L.D. et al. (2019). Using a two-sample Mendelian randomization design to investigate a possible causal effect of maternal lipid concentrations on offspring birth weight. Int J Epidemiol. 48(5): 1457-1467.
  19. Jacob C.M. et al. (2019). What quantitative and qualitative methods have been developed to measure the implementation of a life-course approach in public health policies at the national level? in Health Evidence Network synthesis report 63. Copenhagen. Publisher: WHO Europe.
  20. Jacob C.M. et al. (2019). Do the concepts of “life course approach” and “developmental origins of health and disease” underpin current maternity care? Study protocol. Int J Gynaecol Obstet. 147(2): 140-146.
  21. Jacob C.M., Newell M.L., and Hanson M. (2019). Narrative review of reviews of preconception interventions to prevent an increased risk of obesity and non-communicable diseases in children. Obes Rev. 20 Suppl 1: 5-17.
  22. Juonala M. et al. (2019). A Cross-Cohort Study Examining the Associations of Metabolomic Profile and Subclinical Atherosclerosis in Children and Their Parents: The Child Health CheckPoint Study and Avon Longitudinal Study of Parents and Children. J Am Heart Assoc. 8(14): e011852.
  23. Kazmi N. et al. (2019). Hypertensive Disorders of Pregnancy and DNA Methylation in Newborns. Hypertension. 74(2): 375-383.
  24. Kirchberg F.F. et al. (2019). Are All Breast-fed Infants Equal? Clustering Metabolomics Data to Identify Predictive Risk Clusters for Childhood Obesity. J Pediatr Gastroenterol Nutr. 68(3): 408-415.
  25. Koletzko B. et al. (2019). Nutrition During Pregnancy, Lactation and Early Childhood and its Implications for Maternal and Long-Term Child Health. Ann Nutr Metab. 74: 93–106.
  26. Küpers L.K. et al. (2019). Meta-analysis of epigenome-wide association studies in neonates reveals widespread differential DNA methylation associated with birthweight. Nat Commun. 10: 1893.
  27. LifeCycle Project – Maternal Obesity and Childhood Outcomes Study Group et al. (2019). Association of Gestational Weight Gain With Adverse Maternal and Infant Outcomes. JAMA. 321(17): 1702-1715.
  28. Liu J. et al. (2019). An integrative cross-omics analysis of DNA methylation sites of glucose and insulin homeostasis. Nat Commun. 10(1): 2581.
  29. Maas S.C.E. et al. (2019). Validated inference of smoking habits from blood with a finite DNA methylation marker set. Eur J Epidemiol. 34(11): 1055-1074.
  30. Marchioro L. et al. (2019). Effect of a low glycaemic index diet during pregnancy on maternal and cord blood metabolomic profiles: results from the ROLO randomized controlled trial. Nutr Metab (Lond). 16: 59
  31. Marchioro L. et al. (2019). Caesarean section, but not induction of labor, is associated with major changes in cord blood metabolome. Sci Rep. 9(1): 17562.
  32. Middeldorp C. M. et al. (2019). The Early Growth Genetics (EGG) and EArly Genetics and Lifecourse Epidemiology (EAGLE) consortia: design, results and future prospects. Eur J Epidemiol. 34 (3): 279–300.
  33. Mikkola T. (2019). Physical heaviness of work and sitting at work as predictors of mortality: a 26-year follow-up of the Helsinki Birth Cohort Study. BMJ Open. 9: e026280.
  34. Miliku K. et al. (2019). Associations of maternal and fetal vitamin D status with childhood body composition and cardiovascular risk factors. Matern Child Nutr. 15(2): e12672.
  35. Mills H.L. et al. (2019). The effect of a lifestyle intervention in obese pregnant women on gestational metabolic profiles: findings from the UK Pregnancies Better Eating and Activity Trial (UPBEAT) randomised controlled trial. BMC Med. 17(1): 15.
  36. Neumann A. et al. (2019). Association between DNA methylation and ADHD symptoms from birth to school age: A prospective meta-analysis. Preprint /content/10.1101/806844v1.
  37. Pearce N., Vandenbroucke J.P., and Lawlor D.A. (2019). Causal Inference in Environmental Epidemiology: Old and New Approaches. Epidemiology. 30(3): 311-316.
  38. Popovic M. et al. (2019). Differentially methylated DNA regions in early childhood wheezing: An epigenome‐wide study using saliva. Pediatr Allergy Immunol. 30: 305– 314
  39. Poulsen G. et al. (2019). Does smoking during pregnancy mediate educational disparities in preterm delivery? Findings from three large birth cohorts. Paediatr Perinat Epidemiol. 33: 164– 171.
  40. Reese S.E. et al. (2019). Epigenome-wide meta-analysis of DNA methylation and childhood asthma. J Allergy Clin Immunol. 143(6): 2062–2074.
  41. Richiardi L. et al. (2019). Baseline selection on a collider: a ubiquitous mechanism occurring in both representative and selected cohort studies. J Epidemiol Community Health. 73: 475-480.
  42. Santos S. et al. (2019). Maternal body mass index, gestational weight gain, and childhood abdominal, pericardial and liver fat assessed by magnetic resonance imaging. Int J Obes. 43(3): 581-593.
  43. Santos S. et al. (2019). Impact of maternal body mass index and gestational weight gain on pregnancy complications: an individual participant data meta-analysis of European, North American, and Australian cohorts. BJOG. 126(8): 984-995.
  44. Santos S. et al. (2019). Sources of confounding in life course epidemiology. J Dev Orig Health Dis. 10(3): 299-305.
  45. Sikdar S. et al. (2019). Comparison of smoking-related DNA methylation between newborns from prenatal exposure and adults from personal smoking. Epigenomics. 11(13): 1487-500.
  46. Teumer A. et al. (2019). Genome-wide association meta-analyses and fine-mapping elucidate pathways influencing albuminuria. Nat Commun. 10(1): 4130.
  47. Theurich M.A. et al. (2019). Commerical complementary food use amongst European infants and children: results from the EU Childhood Obesity Project. Eur J Nutr. [Epub ahead of print].
  48. Thyssen J.P. et al. (2019). Interaction between filaggrin mutations and neonatal cat exposure in atopic dermatitis. Allergy. [Epub ahead of print].
  49. Vehmeijer FOL. (2019). Maternal psychological distress during pregnancy and childhood health outcomes: a narrative review. J Dev Orig Health Dis. 10(3): 274-285.
  50. Verdejo-Roman J. et al. (2019). Maternal prepregnancy body mass index and offspring white matter microstructure: results from three birth cohorts. Int J Obes (Lond). 43(10): 1995-2006.
  51. Voerman E. and the LifeCycle Project-Maternal Obesity and Childhood Outcomes Study Group (2019). Association of Gestational Weight Gain With Adverse Maternal and Infant Outcomes. JAMA. 321 (17): 1702-1715.
  52. Voerman E. et al. (2019). Maternal body mass index, gestational weight gain, and the risk of overweight and obesity across childhood: An individual participant data meta-analysis. PLOS Medicine. Online first: 16(2): e1002744.
  53. Warrington N.M. et al. (2019). Maternal and fetal genetic effects on birth weight and their relevance to cardio-metabolic risk factors. Nat Genet. 51(5): 804-814.
  54. Wiklund P. et al. DNA methylation links prenatal smoking exposure to later life health outcomes in offspring. Clin Epigenetics. 11(1): 97.
  55. Wuttke M. et al. (2019). A catalog of genetic loci associated with kidney function from analyses of a million individuals. Nat Genet. 51(6): 957-972.
  56. Zou R. et al. (2019). Exposure to Maternal Depressive Symptoms in Fetal Life or Childhood and Offspring Brain Development: A Population-Based Imaging Study. Am J Psychiatry. 176(9): 702-710.


  1. Beaumont R.N. et al. (2018). Genome-wide association study of offspring birth weight in 86 577 women identifies five novel loci and highlights maternal genetic effects that are independent of fetal genetics. Hum Mol Genet. 27(4): 742-756.
  2. Björkqvist J. et al. (2018). Premature birth and circadian preference in young adulthood: evidence from two birth cohorts. Chronobiol Int. 35 (4): 555-564.
  3. Brand J.S. et al. (2018). Gestational diabetes and ultrasound-assessed fetal growth in South Asian and White European women: findings from a prospective pregnancy cohort. BMC Med. 16(1): 203.
  4. Casas M. et al. (2018). The effect of early growth patterns and lung function on the development of childhood asthma: a population-based study. Thorax. Online first: 31 July 2018.
  5. Contreras Z.A., et al. (2018). Does early-onset asthma increase childhood obesity risk? A pooled analysis of 16 European cohorts. Eur Respir J. Online first: 52 (3):
  6. Demenais F. et al. (2018). Multiancestry association study identifies new asthma risk loci that colocalize with immune-cell enhancer marks. Nat Genet. 50(1): 42-53.
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