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: 107


  1. Jacob C.M. 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 years. International Journal of Behavioral Nutrition and Physical Activity 18:1
  2. 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) variables. European journal of epidemiology, 1-16.


  1. Warembourg C. et al. (2020). Urban environment during early-life and blood pressure in young children. Environ Int. Online first: 21 October 2020
  2. 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
  3. 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
  4. 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
  5. 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
  6. 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
  7. Caramaschi D. et al. (2020). Epigenome-wide association study of seizures in childhood and adolescence. Clin Epigenetics. 12(1): 8
  8. 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
  9. 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
  10. Mulder R.H. et al. (2020). Epigenomics of being bullied: changes in DNA methylation following bullying exposure. Epigenetics. 1-15
  11. 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
  12. Popovic M. et al. (2020). Determination of saliva epigenetic age in infancy, and its association with parental socio-economic characteristics and pregnancy outcomes. J Dev Orig Health Dis. [Epub ahead of print]
  13. Santos S. et al. (2020). Applying the exposome concept in birth cohort research: a review of statistical approaches. Eur J Epidemiol. 35: 193–204
  14. 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
  15. 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]
  16. 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
  7. den Dekker H.T. et al. (2018). Fetal and Infant Growth Patterns and Risk of Lower Lung Function and Asthma. The Generation R Study. Am J Respir Crit Care Med. 197(2): 183-192
  8. Felix J.F. and Cecil C.A.M. (2018). Population DNA methylation studies in the Developmental Origins of Health and Disease (DOHaD) framework. J Dev Orig Health Dis. 10(3): 306-313
  9. Felix J.F. et al. (2018). Cohort Profile: Pregnancy And Childhood Epigenetics (PACE) Consortium. Int J Epidemiol. 47 (1): 22-3u
  10. Gaillard R., Wright J. and Jaddoe V.W.V. (2018). Lifestyle intervention strategies in early life to improve pregnancy outcomes and long-term health of offspring: a narrative review. J Dev Ori Health Dis. 10(3): 314-321
  11. Golab B.P. et al. (2018). Influence of maternal obesity on the association between common pregnancy complications and risk of childhood obesity: an individual participant data meta-analysis. Lancet Child Adolesc Health. 2 (11): 812-821
  12. Guxens M. et al. (2018). Air Pollution Exposure During Fetal Life, Brain Morphology, and Cognitive Function in School-Age Children. Biol Psychiatry. 84(4): 295-303
  13. Magnus M.C. et al. (2018). Vitamin D and risk of pregnancy related hypertensive disorders: mendelian randomisation study. BMJ. 361: k2167
  14. McEachan R.R.C. et al. (2018). Availability, use of, and satisfaction with green space, and children’s mental wellbeing at age 4 years in a multicultural, deprived, urban area: results from the Born in Bradford cohort study. Lancet Planet Health. 2 (6): e244-e54
  15. Parmar P. et al. (2018). Association of maternal prenatal smoking GFI1-locus and cardio-metabolic phenotypes in 18,212 adults. EBioMedicine. 38: 206-216
  16. Peng C. et al. (2018). Residential Proximity to Major Roadways at Birth, DNA Methylation at Birth and Midchildhood, and Childhood Cognitive Test Scores: Project Viva (Massachusetts, USA). Environ Health Perspect. 126(9): 97006.
  17. Santos S. et. al. (2018). Gestational weight gain charts for different body mass index groups for women in Europe, North America, and Oceania. BMC Medicine. Online first: 16 (201): 1-15
  18. Santos S. et al. (2018). Sources of confounding in life course epidemiology. J Dev Ori Health Dis. 10(3): 299-305
  19. Sharp G.C. et al. (2018). Maternal alcohol consumption and offspring DNA methylation: findings from six general population-based birth cohorts. Epigenomics. 10 (1): 27-42
  20. van Meel E.R. et al. (2018). A population-based prospective cohort study examining the influence of early-life respiratory tract infections on school-age lung function and asthma. Thorax. 73 (2): 167-173
  21. Viuff A.C. et al. (2018). Maternal depression during pregnancy and cord blood DNA methylation: findings from the Avon Longitudinal Study of Parents and Children. Transl Psychiatry. 8(1): 244
  22. Vogelezang S. et al. (2018). Infant breastfeeding and childhood general, visceral, liver, and pericardial fat measures assessed by magnetic resonance imaging. Am J Clin Nutr. 108(4): 722-729
  23. Waage J. et al. (2018). Genome-wide association and HLA fine-mapping studies identify risk loci and genetic pathways underlying allergic rhinitis. Nat Genet. 50 (8): 1072-1080
  24. Warrington N.M. et al. (2018). Maternal and fetal genetic contribution to gestational weight gain. Int J Obes (Lond). 42 (4): 775-784
  25. Wilmink F.A. et al. (2018). Maternal blood pressure and hypertensive disorders during pregnancy and childhood respiratory morbidity: the Generation R Study. Eur Respir J. Online first: 52(5):
  26. Zugna D. and Richiardi L. (2018). Effects decomposition in mediation analysis: a numerical example. Epidemiol Prev. 42 (2): 127-133


  1. Herzog E.M. et al. (2017). Early- and late-onset preeclampsia and the tissue-specific epigenome of the placenta and newborn. Placenta. 58: 122-132
  2. Lubczynska M.J. et al. (2017). Exposure to elemental composition of outdoor PM2.5 at birth and cognitive and psychomotor function in childhood in four European birth cohorts. Environ Int. 109: 170-180
  3. Popovic M. et al. (2017). Increased correlation between methylation sites in epigenome-wide replication studies:impact on analysis and results. Epigenomics. 9: 1489-1502
  4. Rautio N. et al. (2017). Living environment and its relationship to depressive mood: A systematic review. Int J Soc Psychiatry. 64 (1): 92-103
  5. Richmond R.C. et al. (2017). Using Genetic Variation to Explore the Causal Effect of Maternal Pregnancy Adiposity on Future Offspring Adiposity: A Mendelian Randomisation Study. PLoS Med. 14 (1): e1002221
  6. Sharp G.C. et al. (2017). Maternal BMI at the start of pregnancy and offspring epigenome-wide DNA methylation: findings from the pregnancy and childhood epigenetics (PACE) consortium. Hum Mol Genet. 26 (20): 4067-4085
  7. van Meel E.R. et al. (2017). The role of respiratory tract infections and the microbiome in the development of asthma: A narrative review. Pediatr Pulmonol. 52 (10): 1363-1370