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455 results on '"Jaddoe, VWV"'

1. 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

Author: Santos, S, Voerman, E, Amiano, P, Barros, H, Beilin, LJ, Bergström, A, Charles, M‐A, Chatzi, L, Chevrier, C, Chrousos, GP, Corpeleijn, E, Costa, O, Costet, N, Crozier, S, Devereux, G, Doyon, M, Eggesbø, M, Fantini, MP, Farchi, S, Forastiere, F, Georgiu, V, Godfrey, KM, Gori, D, Grote, V, Hanke, W, Hertz‐Picciotto, I, Heude, B, Hivert, M‐F, Hryhorczuk, D, Huang, R‐C, Inskip, H, Karvonen, AM, Kenny, LC, Koletzko, B, Küpers, LK, Lagström, H, Lehmann, I, Magnus, P, Majewska, R, Mäkelä, J, Manios, Y, McAuliffe, FM, McDonald, SW, Mehegan, J, Melén, E, Mommers, M, Morgen, CS, Moschonis, G, Murray, D, Chaoimh, C Ní, Nohr, EA, Andersen, A‐M Nybo, Oken, E, Oostvogels, AJJM, Pac, A, Papadopoulou, E, Pekkanen, J, Pizzi, C, Polanska, K, Porta, D, Richiardi, L, Rifas‐Shiman, SL, Roeleveld, N, Ronfani, L, Santos, AC, Standl, M, Stigum, H, Stoltenberg, C, Thiering, E, Thijs, C, Torrent, M, Tough, SC, Trnovec, T, Turner, S, Gelder, MMHJ, Rossem, L, Berg, A, Vrijheid, M, Vrijkotte, TGM, West, J, Wijga, AH, Wright, J, Zvinchuk, O, Sørensen, TIA, Lawlor, DA, Gaillard, R, and Jaddoe, VWV
Subjects: Obesity, Contraception/Reproduction, Diabetes, Preterm, Low Birth Weight and Health of the Newborn, Infant Mortality, Cardiovascular, Clinical Research, Perinatal Period - Conditions Originating in Perinatal Period, Prevention, Nutrition, Pediatric, Aetiology, 3.1 Primary prevention interventions to modify behaviours or promote wellbeing, 2.1 Biological and endogenous factors, Prevention of disease and conditions, and promotion of well-being, Metabolic and endocrine, Reproductive health and childbirth, Good Health and Well Being, Adult, Australia, Birth Weight, Body Mass Index, Cohort Studies, Europe, Female, Gestational Age, Gestational Weight Gain, Humans, Infant, Newborn, North America, Odds Ratio, Overweight, Pregnancy, Pregnancy Complications, Risk Factors, Birthweight, body mass index, pregnancy complications, preterm birth, weight gain, Medical and Health Sciences, Obstetrics & Reproductive Medicine
Abstract: ObjectiveTo assess the separate and combined associations of maternal pre-pregnancy body mass index (BMI) and gestational weight gain with the risks of pregnancy complications and their population impact.DesignIndividual participant data meta-analysis of 39 cohorts.SettingEurope, North America, and Oceania.Population265 270 births.MethodsInformation on maternal pre-pregnancy BMI, gestational weight gain, and pregnancy complications was obtained. Multilevel binary logistic regression models were used.Main outcome measuresGestational hypertension, pre-eclampsia, gestational diabetes, preterm birth, small and large for gestational age at birth.ResultsHigher maternal pre-pregnancy BMI and gestational weight gain were, across their full ranges, associated with higher risks of gestational hypertensive disorders, gestational diabetes, and large for gestational age at birth. Preterm birth risk was higher at lower and higher BMI and weight gain. Compared with normal weight mothers with medium gestational weight gain, obese mothers with high gestational weight gain had the highest risk of any pregnancy complication (odds ratio 2.51, 95% CI 2.31- 2.74). We estimated that 23.9% of any pregnancy complication was attributable to maternal overweight/obesity and 31.6% of large for gestational age infants was attributable to excessive gestational weight gain.ConclusionsMaternal pre-pregnancy BMI and gestational weight gain are, across their full ranges, associated with risks of pregnancy complications. Obese mothers with high gestational weight gain are at the highest risk of pregnancy complications. Promoting a healthy pre-pregnancy BMI and gestational weight gain may reduce the burden of pregnancy complications and ultimately the risk of maternal and neonatal morbidity.Tweetable abstractPromoting a healthy body mass index and gestational weight gain might reduce the population burden of pregnancy complications.
Published: 2019

2. Analysis of DNA methylation at birth and in childhood reveals changes associated with season of birth and latitude

Author: Universitat Rovira i Virgili, Kadalayil, L; Alam, MZ; White, CH; Ghantous, A; Walton, E; Gruzieva, O; Merid, SK; Kumar, A; Roy, RP; Solomon, O; Huen, K; Eskenazi, B; Rzehak, P; Grote, V; Langhendries, JP; Verduci, E; Ferre, N; Gruszfeld, D; Gao, L; Guan, WH; Zeng, XH; Schisterman, EF; Dou, JF; Bakulski, KM; Feinberg, JI; Soomro, MH; Pesce, G; Baiz, N; Isaevska, E; Plusquin, M; Vafeiadi, M; Roumeliotaki, T; Langie, SAS; Standaert, A; Allard, C; Perron, P; Bouchard, L; van Meel, ER; Felix, JF; Jaddoe, VWV; Yousefi, PD; Ramlau-Hansen, CH; Relton, CL; Tobi, EW; Starling, AP; Yang, IV; Llambrich, M; Santorelli, G; Lepeule, J; Salas, LA; Bustamante, M; Ewart, SL; Zhang, HM; Karmaus, W; Röder, S; Zenclussen, AC; Jin, JP; Nystad, W; Page, CM; Magnus, M; Jima, DD; Hoyo, C; Maguire, RL; Kvist, T; Czamara, D; Räikkönen, K; Gong, T; Ullemar, V; Rifas-Shiman, SL; Oken, E; Almqvist, C; Karlsson, R; Lahti, J; Murphy, SK; Håberg, SE; London, S; Herberth, G; Arshad, H; Sunyer, J; Grazuleviciene, R; Dabelea, D; Steegers-Theunissen, RPM; Nohr, EA; Sorensen, TIA; Duijts, L; Hivert, MF; Nelen, V; Popovic, M; Kogevinas, M; Nawrot, TS; Herceg, Z; Annesi-Maesano, I; Fallin, MD; Yeung, EDA; Breton, CV; Koletzko, B; Holland, N; Wiemels, JL; Melén, E; Sharp, GC; Silver, MJ; Rezwan, F; Holloway, JW, Universitat Rovira i Virgili, and Kadalayil, L; Alam, MZ; White, CH; Ghantous, A; Walton, E; Gruzieva, O; Merid, SK; Kumar, A; Roy, RP; Solomon, O; Huen, K; Eskenazi, B; Rzehak, P; Grote, V; Langhendries, JP; Verduci, E; Ferre, N; Gruszfeld, D; Gao, L; Guan, WH; Zeng, XH; Schisterman, EF; Dou, JF; Bakulski, KM; Feinberg, JI; Soomro, MH; Pesce, G; Baiz, N; Isaevska, E; Plusquin, M; Vafeiadi, M; Roumeliotaki, T; Langie, SAS; Standaert, A; Allard, C; Perron, P; Bouchard, L; van Meel, ER; Felix, JF; Jaddoe, VWV; Yousefi, PD; Ramlau-Hansen, CH; Relton, CL; Tobi, EW; Starling, AP; Yang, IV; Llambrich, M; Santorelli, G; Lepeule, J; Salas, LA; Bustamante, M; Ewart, SL; Zhang, HM; Karmaus, W; Röder, S; Zenclussen, AC; Jin, JP; Nystad, W; Page, CM; Magnus, M; Jima, DD; Hoyo, C; Maguire, RL; Kvist, T; Czamara, D; Räikkönen, K; Gong, T; Ullemar, V; Rifas-Shiman, SL; Oken, E; Almqvist, C; Karlsson, R; Lahti, J; Murphy, SK; Håberg, SE; London, S; Herberth, G; Arshad, H; Sunyer, J; Grazuleviciene, R; Dabelea, D; Steegers-Theunissen, RPM; Nohr, EA; Sorensen, TIA; Duijts, L; Hivert, MF; Nelen, V; Popovic, M; Kogevinas, M; Nawrot, TS; Herceg, Z; Annesi-Maesano, I; Fallin, MD; Yeung, EDA; Breton, CV; Koletzko, B; Holland, N; Wiemels, JL; Melén, E; Sharp, GC; Silver, MJ; Rezwan, F; Holloway, JW
Abstract: Seasonal variations in environmental exposures at birth or during gestation are associated with numerous adult traits and health outcomes later in life. Whether DNA methylation (DNAm) plays a role in the molecular mechanisms underlying the associations between birth season and lifelong phenotypes remains unclear.We carried out epigenome-wide meta-analyses within the Pregnancy And Childhood Epigenetic Consortium to identify associations of DNAm with birth season, both at differentially methylated probes (DMPs) and regions (DMRs). Associations were examined at two time points: at birth (21 cohorts, N = 9358) and in children aged 1-11 years (12 cohorts, N = 3610). We conducted meta-analyses to assess the impact of latitude on birth season-specific associations at both time points.We identified associations between birth season and DNAm (False Discovery Rate-adjusted p values < 0.05) at two CpGs at birth (winter-born) and four in the childhood (summer-born) analyses when compared to children born in autumn. Furthermore, we identified twenty-six differentially methylated regions (DMR) at birth (winter-born: 8, spring-born: 15, summer-born: 3) and thirty-two in childhood (winter-born: 12, spring and summer: 10 each) meta-analyses with few overlapping DMRs between the birth seasons or the two time points. The DMRs were associated with genes of known functions in tumorigenesis, psychiatric/neurological disorders, inflammation, or immunity, amongst others. Latitude-stratified meta-analyses [higher (≥ 50°N), lower (< 50°N, northern hemisphere only)] revealed differences in associations between birth season and DNAm by birth latitude. DMR analysis implicated genes with previously reported links to schizophrenia (LAX1), skin disorders (PSORS1C, LTB4R), and airway inflammation inclu
Published: 2023

3. Association of Assisted Reproductive Technology With Offspring Growth and Adiposity From Infancy to Early Adulthood

Author: Elhakeem, A, Taylor, AE, Inskip, HM, Huang, J, Tafflet, M, Vinther, JL, Asta, F, Erkamp, JS, Gagliardi, L, Guerlich, K, Halliday, J, Harskamp-van Ginkel, MW, He, J-R, Jaddoe, VWV, Lewis, S, Maher, GM, Manios, Y, Mansell, T, McCarthy, FP, McDonald, SW, Medda, E, Nisticò, L, de Moira, AP, Popovic, M, Reiss, IKM, Rodrigues, C, Salika, T, Smith, A, Stazi, MA, Walker, C, Wu, M, Åsvold, BO, Barros, H, Brescianini, S, Burgner, D, Chan, JKY, Charles, M-A, Eriksson, JG, Gaillard, R, Grote, V, Håberg, SE, Heude, B, Koletzko, B, Morton, S, Moschonis, G, Murray, D, O'Mahony, D, Porta, D, Qiu, X, Richiardi, L, Rusconi, F, Saffery, R, Tough, SC, Vrijkotte, TGM, Nelson, SM, Nybo Andersen, A-M, Magnus, MC, Lawlor, DA, and Assisted Reproductive Technology and Future Health (ART-Health) Cohort Collaboration
Subjects: Adult, Male, 42 Health sciences, Adolescent, Reproductive Techniques, Assisted, Infant, 32 Biomedical and clinical sciences, Embryo Transfer, Cohort Studies, Pregnancy, Semen, Child, Preschool, Humans, Female, Obesity, Child, Adiposity
Abstract: IMPORTANCE: People conceived using assisted reproductive technology (ART) make up an increasing proportion of the world's population. OBJECTIVE: To investigate the association of ART conception with offspring growth and adiposity from infancy to early adulthood in a large multicohort study. DESIGN, SETTING, AND PARTICIPANTS: This cohort study used a prespecified coordinated analysis across 26 European, Asia-Pacific, and North American population-based cohort studies that included people born between 1984 and 2018, with mean ages at assessment of growth and adiposity outcomes from 0.6 months to 27.4 years. Data were analyzed between November 2019 and February 2022. EXPOSURES: Conception by ART (mostly in vitro fertilization, intracytoplasmic sperm injection, and embryo transfer) vs natural conception (NC; without any medically assisted reproduction). MAIN OUTCOMES AND MEASURES: The main outcomes were length / height, weight, and body mass index (BMI; calculated as weight in kilograms divided by height in meters squared). Each cohort was analyzed separately with adjustment for maternal BMI, age, smoking, education, parity, and ethnicity and offspring sex and age. Results were combined in random effects meta-analysis for 13 age groups. RESULTS: Up to 158 066 offspring (4329 conceived by ART) were included in each age-group meta-analysis, with between 47.6% to 60.6% females in each cohort. Compared with offspring who were NC, offspring conceived via ART were shorter, lighter, and thinner from infancy to early adolescence, with differences largest at the youngest ages and attenuating with older child age. For example, adjusted mean differences in offspring weight were -0.27 (95% CI, -0.39 to -0.16) SD units at age younger than 3 months, -0.16 (95% CI, -0.22 to -0.09) SD units at age 17 to 23 months, -0.07 (95% CI, -0.10 to -0.04) SD units at age 6 to 9 years, and -0.02 (95% CI, -0.15 to 0.12) SD units at age 14 to 17 years. Smaller offspring size was limited to individuals conceived by fresh but not frozen embryo transfer compared with those who were NC (eg, difference in weight at age 4 to 5 years was -0.14 [95% CI, -0.20 to -0.07] SD units for fresh embryo transfer vs NC and 0.00 [95% CI, -0.15 to 0.15] SD units for frozen embryo transfer vs NC). More marked differences were seen for body fat measurements, and there was imprecise evidence that offspring conceived by ART developed greater adiposity by early adulthood (eg, ART vs NC difference in fat mass index at age older than 17 years: 0.23 [95% CI, -0.04 to 0.50] SD units). CONCLUSIONS AND RELEVANCE: These findings suggest that people conceiving or conceived by ART can be reassured that differences in early growth and adiposity are small and no longer evident by late adolescence.
Published: 2022

4. Epigenome-wide contributions to individual differences in childhood phenotypes: a GREML approach

Author: Alexander Neumann, Esther Walton, Janine F. Felix, Pingault J, Henning Tiemeier, Charlotte A.M. Cecil, Jaddoe Vwv, Child and Adolescent Psychiatry / Psychology, Pediatrics, and Epidemiology
Subjects: Birth weight, Population, Individuality, Context (language use), Biology, Epigenesis, Genetic, Epigenome, SDG 3 - Good Health and Well-being, Genetics, Birth Weight, Humans, education, Molecular Biology, Genetics (clinical), education.field_of_study, Gestational age, Methylation, DNA Methylation, Explained variation, Phenotype, DNA methylation, Generation R, CpG Islands, Human medicine, Developmental Biology, Genome-Wide Association Study
Abstract: BackgroundDNA methylation is an epigenetic mechanism involved in human development. Numerous epigenome-wide association studies (EWAS) have investigated the associations of DNA methylation at single CpG sites with childhood outcomes. However, the overall contribution of DNA methylation across the genome (R2Methylation) towards childhood phenotypes is unknown. An estimate ofR2Methylationwould provide context regarding the importance of DNA methylation explaining variance in health outcomes. We therefore estimated the variance explained by epigenome-wide cord blood methylation (R2Methylation) for five childhood phenotypes: gestational age, birth weight, and body mass index (BMI), IQ and ADHD symptoms at school age. We adapted a genome-based restricted maximum likelihood (GREML) approach with cross-validation (CV) to DNA methylation data and applied it in two population-based birth cohorts: ALSPAC (n = 775) and GenerationR(n = 1382).ResultsUsing information from > 470,000 autosomal probes we estimated that DNA methylation at birth explains 32% (SDCV = 0.06) of gestational age variance and 5% (SDCV = 0.02) of birth weight variance. TheR2Methylationestimates for BMI, IQ and ADHD symptoms at school age estimates were near 0% across almost all cross-validation iterations.ConclusionsThe results suggest that cord blood methylation explains a moderate degree of variance in gestational age and birth weight, in line with the success of previous EWAS in identifying numerous CpG sites associated with these phenotypes. In contrast, we could not obtain a reliable estimate for school-age BMI, IQ and ADHD symptoms. This may reflect a null bias due to insufficient sample size to detect variance explained in more weakly associated phenotypes, although the trueR2Methylationfor these phenotypes is likely below that of gestational age and birth weight when using DNA methylation at birth.
Published: 2022

5. Meta-analysis of epigenome-wide association studies in newborns and children show widespread sex differences in blood DNA methylation.

Author: Solomon, O, Huen, K, Yousefi, P, Küpers, LK, González, JR, Suderman, M, Reese, SE, Page, CM, Gruzieva, O, Rzehak, P, Gao, L, Bakulski, KM, Novoloaca, A, Allard, C, Pappa, I, Llambrich, M, Vives, M, Jima, DD, Kvist, T, Baccarelli, A, White, C, Rezwan, FI, Sharp, GC, Tindula, G, Bergström, A, Grote, V, Dou, JF, Isaevska, E, Magnus, MC, Corpeleijn, E, Perron, P, Jaddoe, VWV, Nohr, EA, Maitre, L, Foraster, M, Hoyo, C, Håberg, SE, Lahti, J, DeMeo, DL, Zhang, H, Karmaus, W, Kull, I, Koletzko, B, Feinberg, JI, Gagliardi, L, Bouchard, L, Ramlau-Hansen, CH, Tiemeier, H, Santorelli, G, Maguire, RL, Czamara, D, Litonjua, AA, Langhendries, J-P, Plusquin, M, Lepeule, J, Binder, EB, Verduci, E, Dwyer, T, Carracedo, Á, Ferre, N, Eskenazi, B, Kogevinas, M, Nawrot, TS, Munthe-Kaas, MC, Herceg, Z, Relton, C, Melén, E, Gruszfeld, D, Breton, C, Fallin, MD, Ghantous, A, Nystad, W, Heude, B, Snieder, H, Hivert, M-F, Felix, JF, Sørensen, TIA, Bustamante, M, Murphy, SK, Raikkönen, K, Oken, E, Holloway, JW, Arshad, SH, London, SJ, Holland, N, Solomon, O, Huen, K, Yousefi, P, Küpers, LK, González, JR, Suderman, M, Reese, SE, Page, CM, Gruzieva, O, Rzehak, P, Gao, L, Bakulski, KM, Novoloaca, A, Allard, C, Pappa, I, Llambrich, M, Vives, M, Jima, DD, Kvist, T, Baccarelli, A, White, C, Rezwan, FI, Sharp, GC, Tindula, G, Bergström, A, Grote, V, Dou, JF, Isaevska, E, Magnus, MC, Corpeleijn, E, Perron, P, Jaddoe, VWV, Nohr, EA, Maitre, L, Foraster, M, Hoyo, C, Håberg, SE, Lahti, J, DeMeo, DL, Zhang, H, Karmaus, W, Kull, I, Koletzko, B, Feinberg, JI, Gagliardi, L, Bouchard, L, Ramlau-Hansen, CH, Tiemeier, H, Santorelli, G, Maguire, RL, Czamara, D, Litonjua, AA, Langhendries, J-P, Plusquin, M, Lepeule, J, Binder, EB, Verduci, E, Dwyer, T, Carracedo, Á, Ferre, N, Eskenazi, B, Kogevinas, M, Nawrot, TS, Munthe-Kaas, MC, Herceg, Z, Relton, C, Melén, E, Gruszfeld, D, Breton, C, Fallin, MD, Ghantous, A, Nystad, W, Heude, B, Snieder, H, Hivert, M-F, Felix, JF, Sørensen, TIA, Bustamante, M, Murphy, SK, Raikkönen, K, Oken, E, Holloway, JW, Arshad, SH, London, SJ, and Holland, N
Abstract: BACKGROUND: Among children, sex-specific differences in disease prevalence, age of onset, and susceptibility have been observed in health conditions including asthma, immune response, metabolic health, some pediatric and adult cancers, and psychiatric disorders. Epigenetic modifications such as DNA methylation may play a role in the sexual differences observed in diseases and other physiological traits. METHODS: We performed a meta-analysis of the association of sex and cord blood DNA methylation at over 450,000 CpG sites in 8438 newborns from 17 cohorts participating in the Pregnancy And Childhood Epigenetics (PACE) Consortium. We also examined associations of child sex with DNA methylation in older children ages 5.5-10 years from 8 cohorts (n = 4268). RESULTS: In newborn blood, sex was associated at Bonferroni level significance with differences in DNA methylation at 46,979 autosomal CpG sites (p < 1.3 × 10-7) after adjusting for white blood cell proportions and batch. Most of those sites had lower methylation levels in males than in females. Of the differentially methylated CpG sites identified in newborn blood, 68% (31,727) met look-up level significance (p < 1.1 × 10-6) in older children and had methylation differences in the same direction. CONCLUSIONS: This is a large-scale meta-analysis examining sex differences in DNA methylation in newborns and older children. Expanding upon previous studies, we replicated previous findings and identified additional autosomal sites with sex-specific differences in DNA methylation. Differentially methylated sites were enriched in genes involved in cancer, psychiatric disorders, and cardiovascular phenotypes.
Published: 2022

6. Household income and maternal education in early childhood and risk of overweight and obesity in late childhood: Findings from seven birth cohort studies in six high-income countries

Author: White, PA, Abu Awad, Y, Gauvin, L, Spencer, NJ, McGrath, JJ, Clifford, SA, Nikiema, B, Yang-Huang, J, Goldhaber-Fiebert, JD, Markham, W, Mensah, FK, van Grieken, A, Raat, H, Jaddoe, VWV, Ludvigsson, J, Faresjo, T, White, PA, Abu Awad, Y, Gauvin, L, Spencer, NJ, McGrath, JJ, Clifford, SA, Nikiema, B, Yang-Huang, J, Goldhaber-Fiebert, JD, Markham, W, Mensah, FK, van Grieken, A, Raat, H, Jaddoe, VWV, Ludvigsson, J, and Faresjo, T
Abstract: BACKGROUND/OBJECTIVES: This study analysed the relationship between early childhood socioeconomic status (SES) measured by maternal education and household income and the subsequent development of childhood overweight and obesity. SUBJECTS/METHODS: Data from seven population-representative prospective child cohorts in six high-income countries: United Kingdom, Australia, the Netherlands, Canada (one national cohort and one from the province of Quebec), USA, Sweden. Children were included at birth or within the first 2 years of life. Pooled estimates relate to a total of N = 26,565 included children. Overweight and obesity were defined using International Obesity Task Force (IOTF) cut-offs and measured in late childhood (8-11 years). Risk ratios (RRs) and pooled risk estimates were adjusted for potential confounders (maternal age, ethnicity, child sex). Slope Indexes of Inequality (SII) were estimated to quantify absolute inequality for maternal education and household income. RESULTS: Prevalence ranged from 15.0% overweight and 2.4% obese in the Swedish cohort to 37.6% overweight and 15.8% obese in the US cohort. Overall, across cohorts, social gradients were observed for risk of obesity for both low maternal education (pooled RR: 2.99, 95% CI: 2.07, 4.31) and low household income (pooled RR: 2.69, 95% CI: 1.68, 4.30); between-cohort heterogeneity ranged from negligible to moderate (p: 0.300 to < 0.001). The association between RRs of obesity by income was lowest in Sweden than in other cohorts. CONCLUSIONS: There was a social gradient by maternal education on the risk of childhood obesity in all included cohorts. The SES associations measured by income were more heterogeneous and differed between Sweden versus the other national cohorts; these findings may be attributable to policy differences, including preschool policies, maternity leave, a ban on advertising to children, and universal free school meals.
Published: 2022

7. Meta-analysis of epigenome-wide association studies in newborns and children show widespread sex differences in blood DNA methylation

Author: Universitat Rovira i Virgili, Solomon, O; Huen, K; Yousefi, P; Küpers, LK; González, JR; Suderman, M; Reese, SE; Page, CM; Gruzieva, O; Rzehak, P; Gao, L; Bakulski, KM; Novoloaca, A; Allard, C; Pappa, I; Llambrich, M; Vives, M; Jima, DD; Kvist, T; Baccarelli, A; White, C; Rezwan, FI; Sharp, GC; Tindula, G; Bergström, A; Grote, V; Dou, JF; Isaevska, E; Magnus, MC; Corpeleijn, E; Perron, P; Jaddoe, VWV; Nohr, EA; Maitre, L; Foraster, M; Hoyo, C; Håberg, SE; Lahti, J; DeMeo, DL; Zhang, HM; Karmaus, W; Kull, I; Koletzko, B; Feinberg, JI; Gagliardi, L; Bouchard, L; Ramlau-Hansen, CH; Tiemeier, H; Santorelli, G; Maguire, RL; Czamara, D; Litonjua, AA; Langhendries, JP; Plusquin, M; Lepeule, J; Binder, EB; Verduci, E; Dwyer, T; Carracedo, A; Ferre, N; Eskenazi, B; Kogevinas, M; Nawrot, TS; Munthe-Kaas, MC; Herceg, Z; Relton, C; Melén, E; Gruszfeld, D; Breton, C; Fallin, MD; Ghantous, A; Nystad, W; Heude, B; Snieder, H; Hivert, MF; Felix, JF; Sorensen, TIA; Bustamante, M; Murphy, SK; Raikkönen, K; Oken, E; Holloway, JW; Arshad, SH; London, SJ; Holland, N, Universitat Rovira i Virgili, and Solomon, O; Huen, K; Yousefi, P; Küpers, LK; González, JR; Suderman, M; Reese, SE; Page, CM; Gruzieva, O; Rzehak, P; Gao, L; Bakulski, KM; Novoloaca, A; Allard, C; Pappa, I; Llambrich, M; Vives, M; Jima, DD; Kvist, T; Baccarelli, A; White, C; Rezwan, FI; Sharp, GC; Tindula, G; Bergström, A; Grote, V; Dou, JF; Isaevska, E; Magnus, MC; Corpeleijn, E; Perron, P; Jaddoe, VWV; Nohr, EA; Maitre, L; Foraster, M; Hoyo, C; Håberg, SE; Lahti, J; DeMeo, DL; Zhang, HM; Karmaus, W; Kull, I; Koletzko, B; Feinberg, JI; Gagliardi, L; Bouchard, L; Ramlau-Hansen, CH; Tiemeier, H; Santorelli, G; Maguire, RL; Czamara, D; Litonjua, AA; Langhendries, JP; Plusquin, M; Lepeule, J; Binder, EB; Verduci, E; Dwyer, T; Carracedo, A; Ferre, N; Eskenazi, B; Kogevinas, M; Nawrot, TS; Munthe-Kaas, MC; Herceg, Z; Relton, C; Melén, E; Gruszfeld, D; Breton, C; Fallin, MD; Ghantous, A; Nystad, W; Heude, B; Snieder, H; Hivert, MF; Felix, JF; Sorensen, TIA; Bustamante, M; Murphy, SK; Raikkönen, K; Oken, E; Holloway, JW; Arshad, SH; London, SJ; Holland, N
Abstract: Background: Among children, sex-specific differences in disease prevalence, age of onset, and susceptibility have been observed in health conditions including asthma, immune response, metabolic health, some pediatric and adult cancers, and psychiatric disorders. Epigenetic modifications such as DNA methylation may play a role in the sexual differences observed in diseases and other physiological traits. Methods: We performed a meta-analysis of the association of sex and cord blood DNA methylation at over 450,000 CpG sites in 8438 newborns from 17 cohorts participating in the Pregnancy And Childhood Epigenetics (PACE) Consortium. We also examined associations of child sex with DNA methylation in older children ages 5.5–10 years from 8 cohorts (n = 4268). Results: In newborn blood, sex was associated at Bonferroni level significance with differences in DNA methylation at 46,979 autosomal CpG sites (p < 1.3 × 10−7) after adjusting for white blood cell proportions and batch. Most of those sites had lower methylation levels in males than in females. Of the differentially methylated CpG sites identified in newborn blood, 68% (31,727) met look-up level significance (p < 1.1 × 10−6) in older children and had methylation differences in the same direction. Conclusions: This is a large-scale meta-analysis examining sex differences in DNA methylation in newborns and older children. Expanding upon previous studies, we replicated previous findings and identified additional autosomal sites with sex-specific differences in DNA methylation. Differentially methylated sites were enriched in genes involved in cancer, psychiatric disorders, and cardiovascular phenotypes.
Published: 2022

8. Incidence rates and symptomatology of community infections with SARS-CoV-2 in children and parents: The CoKids longitudinal household study

Author: de Hoog, MLA, primary, Sluiter-Post, JGC, additional, Westerhof, I, additional, Fourie, E, additional, Heuvelman, VD, additional, Boom, TT, additional, Euser, SM, additional, Badoux, P, additional, Reusken, C, additional, Bont, LJ, additional, Sanders, L, additional, Jaddoe, VWV, additional, Herpers, BL, additional, Eggink, D, additional, Wildenbeest, JG, additional, Duijts, L, additional, van Houten, MA, additional, and Bruijning-Verhagen, PCJL, additional
Published: 2021
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9. Spectacle wear and refractive errors in Dutch children

Author: Iyer, V, primary, Enthoven, CA, additional, van Dommelen, P, additional, Samkar, A van, additional, Groenewoud, JH, additional, Reijneveld, SA, additional, Jaddoe, VWV, additional, and Klaver, CCW, additional
Published: 2021
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10. Epigenome-wide change and variation in DNA methylation from birth to late adolescence

Author: Lotte C Houtepen, Tom R. Gaunt, Henning Tiemeier, Andrew J Simpkin, Cecil Cam, Janine F. Felix, Jolien Rijlaarsdam, Alexander Neumann, van IJzendoorn Mh, Jaddoe Vwv., Rosa H. Mulder, Caroline L Relton, Bastiaan T. Heijmans, Esther Walton, Matthew Suderman, and Marian J. Bakermans-Kranenburg
Subjects: 0303 health sciences, dNaM, Disease, Epigenome, Biology, Genome, 03 medical and health sciences, 0302 clinical medicine, CpG site, Evolutionary biology, DNA methylation, human activities, Gene, 030217 neurology & neurosurgery, 030304 developmental biology, Genetic association
Abstract: DNA methylation (DNAm) is known to play a pivotal role in childhood health and development, but a comprehensive characterization of genome-wide DNAm trajectories across this age period is currently lacking. We have therefore performed a series of epigenome-wide association studies in 5,019 blood samples collected at multiple time-points from birth to late adolescence from 2,348 participants of two large independent cohorts. DNAm profiles of autosomal CpG sites (CpGs) were generated using the Illumina Infinium HumanMethylation450 BeadChip. Change over time was widespread, observed at over one-half (53%) of CpGs. In most cases DNAm was decreasing (36% of CpGs). Inter-individual variation in linear trajectories was similarly widespread (27% of CpGs). Evidence for nonlinear change and inter-individual variation in nonlinear trajectories was somewhat less common (11% and 8% of CpGs, respectively). Very little inter-individual variation in change was explained by sex differences (0.4% of CpGs) even though sex-specific DNAm was observed at 5% of CpGs. DNAm trajectories were distributed non-randomly across the genome. For example, CpGs with decreasing DNAm were enriched in gene bodies and enhancers and were annotated to genes enriched in immune-developmental functions. By contrast, CpGs with increasing DNAm were enriched in promoter regions and annotated to genes enriched in neurodevelopmental functions. These findings depict a methylome undergoing widespread and often nonlinear change throughout childhood. They support a developmental role for DNA methylation that extends beyond birth into late adolescence and has implications for understanding life-long health and disease. DNAm trajectories can be visualized at http://epidelta.mrcieu.ac.uk.
Published: 2020
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11. Novel loci for childhood body mass index and shared heritability with adult cardiometabolic traits.

Author: Vogelezang, S, Bradfield, JP, Ahluwalia, TS, Curtin, JA, Lakka, TA, Grarup, N, Scholz, M, van der Most, PJ, Monnereau, C, Stergiakouli, E, Heiskala, A, Horikoshi, M, Fedko, IO, Vilor-Tejedor, N, Cousminer, DL, Standl, M, Wang, CA, Viikari, J, Geller, F, Íñiguez, C, Pitkänen, N, Chesi, A, Bacelis, J, Yengo, L, Torrent, M, Ntalla, I, Helgeland, Ø, Selzam, S, Vonk, JM, Zafarmand, MH, Heude, B, Farooqi, IS, Alyass, A, Beaumont, RN, Have, CT, Rzehak, P, Bilbao, JR, Schnurr, TM, Barroso, I, Bønnelykke, K, Beilin, LJ, Carstensen, L, Charles, M-A, Chawes, B, Clément, K, Closa-Monasterolo, R, Custovic, A, Eriksson, JG, Escribano, J, Groen-Blokhuis, M, Grote, V, Gruszfeld, D, Hakonarson, H, Hansen, T, Hattersley, AT, Hollensted, M, Hottenga, J-J, Hyppönen, E, Johansson, S, Joro, R, Kähönen, M, Karhunen, V, Kiess, W, Knight, BA, Koletzko, B, Kühnapfel, A, Landgraf, K, Langhendries, J-P, Lehtimäki, T, Leinonen, JT, Li, A, Lindi, V, Lowry, E, Bustamante, M, Medina-Gomez, C, Melbye, M, Michaelsen, KF, Morgen, CS, Mori, TA, Nielsen, TRH, Niinikoski, H, Oldehinkel, AJ, Pahkala, K, Panoutsopoulou, K, Pedersen, O, Pennell, CE, Power, C, Reijneveld, SA, Rivadeneira, F, Simpson, A, Sly, Peter, Stokholm, J, Teo, KK, Thiering, E, Timpson, NJ, Uitterlinden, AG, van Beijsterveldt, CEM, van Schaik, BDC, Vaudel, M, Verduci, E, Vinding, RK, Vogel, M, Zeggini, E, Sebert, S, Lind, MV, Brown, CD, Santa-Marina, L, Reischl, E, Frithioff-Bøjsøe, C, Meyre, D, Wheeler, E, Ong, K, Nohr, EA, Vrijkotte, TGM, Koppelman, GH, Plomin, R, Njølstad, PR, Dedoussis, GD, Froguel, P, Sørensen, TIA, Jacobsson, B, Freathy, RM, Zemel, BS, Raitakari, O, Vrijheid, M, Feenstra, B, Lyytikäinen, L-P, Snieder, H, Kirsten, H, Holt, PG, Heinrich, J, Widén, E, Sunyer, J, Boomsma, DI, Järvelin, M-R, Körner, A, Davey Smith, G, Holm, J-C, Atalay, M, Murray, C, Bisgaard, H, McCarthy, MI, Early Growth Genetics Consortium, Jaddoe, VWV, Grant, SFA, Felix, JF, Vogelezang, S, Bradfield, JP, Ahluwalia, TS, Curtin, JA, Lakka, TA, Grarup, N, Scholz, M, van der Most, PJ, Monnereau, C, Stergiakouli, E, Heiskala, A, Horikoshi, M, Fedko, IO, Vilor-Tejedor, N, Cousminer, DL, Standl, M, Wang, CA, Viikari, J, Geller, F, Íñiguez, C, Pitkänen, N, Chesi, A, Bacelis, J, Yengo, L, Torrent, M, Ntalla, I, Helgeland, Ø, Selzam, S, Vonk, JM, Zafarmand, MH, Heude, B, Farooqi, IS, Alyass, A, Beaumont, RN, Have, CT, Rzehak, P, Bilbao, JR, Schnurr, TM, Barroso, I, Bønnelykke, K, Beilin, LJ, Carstensen, L, Charles, M-A, Chawes, B, Clément, K, Closa-Monasterolo, R, Custovic, A, Eriksson, JG, Escribano, J, Groen-Blokhuis, M, Grote, V, Gruszfeld, D, Hakonarson, H, Hansen, T, Hattersley, AT, Hollensted, M, Hottenga, J-J, Hyppönen, E, Johansson, S, Joro, R, Kähönen, M, Karhunen, V, Kiess, W, Knight, BA, Koletzko, B, Kühnapfel, A, Landgraf, K, Langhendries, J-P, Lehtimäki, T, Leinonen, JT, Li, A, Lindi, V, Lowry, E, Bustamante, M, Medina-Gomez, C, Melbye, M, Michaelsen, KF, Morgen, CS, Mori, TA, Nielsen, TRH, Niinikoski, H, Oldehinkel, AJ, Pahkala, K, Panoutsopoulou, K, Pedersen, O, Pennell, CE, Power, C, Reijneveld, SA, Rivadeneira, F, Simpson, A, Sly, Peter, Stokholm, J, Teo, KK, Thiering, E, Timpson, NJ, Uitterlinden, AG, van Beijsterveldt, CEM, van Schaik, BDC, Vaudel, M, Verduci, E, Vinding, RK, Vogel, M, Zeggini, E, Sebert, S, Lind, MV, Brown, CD, Santa-Marina, L, Reischl, E, Frithioff-Bøjsøe, C, Meyre, D, Wheeler, E, Ong, K, Nohr, EA, Vrijkotte, TGM, Koppelman, GH, Plomin, R, Njølstad, PR, Dedoussis, GD, Froguel, P, Sørensen, TIA, Jacobsson, B, Freathy, RM, Zemel, BS, Raitakari, O, Vrijheid, M, Feenstra, B, Lyytikäinen, L-P, Snieder, H, Kirsten, H, Holt, PG, Heinrich, J, Widén, E, Sunyer, J, Boomsma, DI, Järvelin, M-R, Körner, A, Davey Smith, G, Holm, J-C, Atalay, M, Murray, C, Bisgaard, H, McCarthy, MI, Early Growth Genetics Consortium, Jaddoe, VWV, Grant, SFA, and Felix, JF
Abstract: The genetic background of childhood body mass index (BMI), and the extent to which the well-known associations of childhood BMI with adult diseases are explained by shared genetic factors, are largely unknown. We performed a genome-wide association study meta-analysis of BMI in 61,111 children aged between 2 and 10 years. Twenty-five independent loci reached genome-wide significance in the combined discovery and replication analyses. Two of these, located near NEDD4L and SLC45A3, have not previously been reported in relation to either childhood or adult BMI. Positive genetic correlations of childhood BMI with birth weight and adult BMI, waist-to-hip ratio, diastolic blood pressure and type 2 diabetes were detected (Rg ranging from 0.11 to 0.76, P-values <0.002). A negative genetic correlation of childhood BMI with age at menarche was observed. Our results suggest that the biological processes underlying childhood BMI largely, but not completely, overlap with those underlying adult BMI. The well-known observational associations of BMI in childhood with cardio-metabolic diseases in adulthood may reflect partial genetic overlap, but in light of previous evidence, it is also likely that they are explained through phenotypic continuity of BMI from childhood into adulthood.
Published: 2020

12. Genome-wide association meta-analysis of corneal curvature identifies novel loci and shared genetic influences across axial length and refractive error

Author: Fan, Q, Pozarickij, A, Tan, NYQ, Guo, X, Verhoeven, VJM, Vitart, V, Guggenheim, JA, Miyake, M, Tideman, JWL, Khawaja, AP, Zhang, L, MacGregor, S, Hoehn, R, Chen, P, Biino, G, Wedenoja, J, Saffari, SE, Tedja, MS, Xie, J, Lanca, C, Wang, YX, Sahebjada, S, Mazur, J, Mirshahi, A, Martin, NG, Yazar, S, Pennell, CE, Yap, M, Haarman, AEG, Enthoven, CA, Polling, J, Hewitt, AW, Jaddoe, VWV, van Duijn, CM, Hayward, C, Polasek, O, Tai, E-S, Yoshikatsu, H, Hysi, PG, Young, TL, Tsujikawa, A, Wang, JJ, Mitchell, P, Pfeiffer, N, Parssinen, O, Foster, PJ, Fossarello, M, Yip, SP, Williams, C, Hammond, CJ, Jonas, JB, He, M, Mackey, DA, Wong, T-Y, Klaver, CCW, Saw, S-M, Baird, PN, Cheng, C-Y, Fan, Q, Pozarickij, A, Tan, NYQ, Guo, X, Verhoeven, VJM, Vitart, V, Guggenheim, JA, Miyake, M, Tideman, JWL, Khawaja, AP, Zhang, L, MacGregor, S, Hoehn, R, Chen, P, Biino, G, Wedenoja, J, Saffari, SE, Tedja, MS, Xie, J, Lanca, C, Wang, YX, Sahebjada, S, Mazur, J, Mirshahi, A, Martin, NG, Yazar, S, Pennell, CE, Yap, M, Haarman, AEG, Enthoven, CA, Polling, J, Hewitt, AW, Jaddoe, VWV, van Duijn, CM, Hayward, C, Polasek, O, Tai, E-S, Yoshikatsu, H, Hysi, PG, Young, TL, Tsujikawa, A, Wang, JJ, Mitchell, P, Pfeiffer, N, Parssinen, O, Foster, PJ, Fossarello, M, Yip, SP, Williams, C, Hammond, CJ, Jonas, JB, He, M, Mackey, DA, Wong, T-Y, Klaver, CCW, Saw, S-M, Baird, PN, and Cheng, C-Y
Abstract: Corneal curvature, a highly heritable trait, is a key clinical endophenotype for myopia - a major cause of visual impairment and blindness in the world. Here we present a trans-ethnic meta-analysis of corneal curvature GWAS in 44,042 individuals of Caucasian and Asian with replication in 88,218 UK Biobank data. We identified 47 loci (of which 26 are novel), with population-specific signals as well as shared signals across ethnicities. Some identified variants showed precise scaling in corneal curvature and eye elongation (i.e. axial length) to maintain eyes in emmetropia (i.e. HDAC11/FBLN2 rs2630445, RBP3 rs11204213); others exhibited association with myopia with little pleiotropic effects on eye elongation. Implicated genes are involved in extracellular matrix organization, developmental process for body and eye, connective tissue cartilage and glycosylation protein activities. Our study provides insights into population-specific novel genes for corneal curvature, and their pleiotropic effect in regulating eye size or conferring susceptibility to myopia.
Published: 2020

13. Association Between Portable Music Player Use and Hearing Loss Among Children of School Age in the Netherlands

Author: André Goedegebure, le Clercq Cmp, Hein Raat, Jaddoe Vwv, Baatenburg de Jong Rj, van der Schroeff Mp, Erasmus MC other, Otorhinolaryngology and Head and Neck Surgery, Epidemiology, Pediatrics, and Public Health
Subjects: Male, medicine.medical_specialty, Cross-sectional study, Hearing loss, Population, Audiology, 03 medical and health sciences, 0302 clinical medicine, Audiometry, Risk Factors, 030225 pediatrics, Prevalence, otorhinolaryngologic diseases, medicine, Humans, Prospective Studies, Child, Hearing Loss, High-Frequency, 030223 otorhinolaryngology, education, Netherlands, education.field_of_study, medicine.diagnostic_test, business.industry, Audiogram, Tympanometry, Cross-Sectional Studies, Acoustic Impedance Tests, Hearing Loss, Noise-Induced, Socioeconomic Factors, Otorhinolaryngology, Cohort, Female, Surgery, medicine.symptom, business, Music, Cohort study
Abstract: Importance Portable music player use may have harmful effects on hearing. The magnitude and effect of frequent music exposure, especially at younger ages, on hearing are unclear. Objectives To examine the prevalence of noise-induced hearing loss in a 9- to 11-year-old population and associations with portable music player use and sociodemographic factors. Design, Setting, and Participants A cross-sectional study within an ongoing, prospective, birth cohort study within Rotterdam, the Netherlands was conducted. Between ages 9 and 11 years, 5355 children underwent their first audiometric evaluation. Children were excluded if they had missing or failed tympanometry results. The study was conducted from April 16, 2012, to October 25, 2015. Exposures Portable music player (PMP) use and sociodemographic factors assessed via parental questionnaires. Main Outcomes and Measures Hearing acuity measured by pure-tone audiometry at 0.5 to 8 kHz. Possible noise-induced hearing loss was contingent on a high-frequency notch and/or high-frequency hearing loss in the audiogram, or reported hearing-related symptoms. Results The final sample included 3116 participants who were a mean (interquartile range) age of 9.7 (9.6-9.9) years and equally distributed between boys (1550 [49.7%]) and girls (1566 [50.3%]). Of these, 1244 (39.9%) reported no PMP use, 577 (18.5%) reported use 1 or 2 days per week, 254 (8.2%) reported use 3 or more days per week, and for 1041 (33.4%), PMP use was not reported. Audiometric notches and high-frequency hearing loss were present in 443 (14.2%) of all children; 140 (4.5%) fulfilled the criteria of a notch, 238 (7.6%) of high-frequency hearing loss, and 65 (2.1%) of both. Of the cohort, 52 (1.7%) showed bilateral impairment. Hearing-related symptoms were reported for 232 (11.3%) of the respondents, and 831 (40.0%) of the respondents used portable music players. Portable music player use was associated with high-frequency hearing loss (odds ratio [OR], 2.88; 95% CI, 1.36-6.980 for 1 or 2 days per week and OR, 2.74; 95% CI, 1.22-6.96 for ≥3 days per week), but listening time and duration were not. There was no association of music exposure with high-frequency notches. Conclusions and Relevance In this study, 14.2% of school-aged children showed audiometric notches or high-frequency hearing loss. This hearing impairment is already present prior to exposure to known noise hazards, such as club and concert attendance, and may have lifelong consequences. Repeated measurements are needed to confirm the association of portable music player use with hearing impairment in children.
Published: 2018

14. A periconceptional energy-rich dietary pattern is associated with early fetal growth: the Generation R study

Author: Bouwland-Both, MI, Steegers-Theunissen, RPM, Vujkovic, M, Lesaffre, EMEH, Mook-Kanamori, DO, Hofman, A, Lindemans, J, Russcher, H, Jaddoe, VWV, and Steegers, EAP
Published: 2013
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15. Homocysteine and folate concentrations in early pregnancy and the risk of adverse pregnancy outcomes: the Generation R Study

Author: Bergen, NE, Jaddoe, VWV, Timmermans, S, Hofman, A, Lindemans, J, Russcher, H, Raat, H, Steegers-Theunissen, RPM, and Steegers, EAP
Published: 2012
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16. Maternal smoking during pregnancy, fetal arterial resistance adaptations and cardiovascular function in childhood

Author: Geelhoed, JJM, el Marroun, H, Verburg, BO, van Osch-Gevers, L, Hofman, A, Huizink, AC, Moll, HA, Verhulst, FC, Helbing, WA, Steegers, EAP, and Jaddoe, VWV
Published: 2011
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17. Comparison of pregnancy outcomes in women with repaired versus unrepaired atrial septal defect

Author: Yap, S-C, Drenthen, W, Meijboom, FJ, Moons, P, Mulder, BJM, Vliegen, HW, van Dijk, APJ, Jaddoe, VWV, Steegers, EAP, Roos-Hesselink, JW, and Pieper, PG
Published: 2009
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18. GWAS on longitudinal growth traits reveals different genetic factors influencing infant, child, and adult BMI

Author: Couto Alves, A, De Silva, NMG, Karhunen, V, Sovio, U, Das, S, Taal, HR, Warrington, NM, Lewin, AM, Kaakinen, M, Cousminer, DL, Thiering, E, Timpson, NJ, Bond, TA, Lowry, E, Brown, CD, Estivill, X, Lindi, V, Bradfield, JP, Geller, F, Speed, D, Coin, LJM, Loh, M, Barton, SJ, Beilin, LJ, Bisgaard, H, Bønnelykke, K, Alili, R, Hatoum, IJ, Schramm, K, Cartwright, R, Charles, M, Salerno, V, Clément, K, Claringbould, AAJ, BIOS Consortium, van Duijn, CM, Moltchanova, E, Eriksson, JG, Elks, C, Feenstra, B, Flexeder, C, Franks, S, Frayling, TM, Freathy, RM, Elliott, P, Widén, E, Hakonarson, H, Hattersley, AT, Rodriguez, A, Banterle, M, Heinrich, J, Heude, B, Holloway, JW, Hofman, A, Hyppönen, E, Inskip, H, Kaplan, LM, Hedman, AK, Läärä, E, Prokisch, H, Grallert, H, Lakka, TA, Lawlor, DA, Melbye, M, Ahluwalia, TS, Marinelli, M, Millwood, IY, Palmer, LJ, Pennell, CE, Perry, JR, Ring, SM, Savolainen, MJ, Rivadeneira, F, Standl, M, Sunyer, J, Tiesler, CMT, Uitterlinden, AG, Schierding, W, O’Sullivan, JM, Prokopenko, I, Herzig, K, Smith, GD, O'Reilly, P, Felix, JF, Buxton, JL, Blakemore, AIF, Ong, KK, Jaddoe, VWV, Grant, SFA, Sebert, S, McCarthy, MI, Järvelin, M., and Early Growth Genetics (EGG) Consortium
Abstract: Copyright © 2019 The Authors. Early childhood growth patterns are associated with adult health, yet the genetic factors and the developmental stages involved are not fully understood. Here, we combine genome-wide association studies with modeling of longitudinal growth traits to study the genetics of infant and child growth, followed by functional, pathway, genetic correlation, risk score, and colocalization analyses to determine how developmental timings, molecular pathways, and genetic determinants of these traits overlap with those of adult health. We found a robust overlap between the genetics of child and adult body mass index (BMI), with variants associated with adult BMI acting as early as 4 to 6 years old. However, we demonstrated a completely distinct genetic makeup for peak BMI during infancy, influenced by variation at the LEPR/LEPROT locus. These findings suggest that different genetic factors control infant and child BMI. In light of the obesity epidemic, these findings are important to inform the timing and targets of prevention strategies.
Published: 2019

19. Low-frequency variation in TP53 has large effects on head circumference and intracranial volume

Author: Haworth, S, Shapland, CY, Hayward, C, Prins, BP, Felix, JF, Medina-Gomez, C, Rivadeneira, F, Wang, C, Ahluwalia, TS, Vrijheid, M, Guxens, M, Sunyer, J, Tachmazidou, I, Walter, K, Iotchkova, V, Jackson, A, Cleal, L, Huffmann, J, Min, JL, Sass, L, Timmers, PRHJ, Smith, G, Fisher, SE, Wilson, JF, Cole, TJ, Fernandez-Orth, D, Bønnelykke, K, Bisgaard, H, Pennell, CE, Jaddoe, VWV, Dedoussis, G, Timpson, N, Zeggini, E, Vitart, V, St Pourcain, B, consortium, UK10K, and Bhattacharya, S
Abstract: Cranial growth and development is a complex process which affects the closely related traits of head circumference (HC) and intracranial volume (ICV). The underlying genetic influences shaping these traits during the transition from childhood to adulthood are little understood, but might include both age-specific genetic factors and low-frequency genetic variation. Here, we model the developmental genetic architecture of HC, showing this is genetically stable and correlated with genetic determinants of ICV. Investigating up to 46,000 children and adults of European descent, we identify association with final HC and/or final ICV + HC at 9 novel common and low-frequency loci, illustrating that genetic variation from a wide allele frequency spectrum contributes to cranial growth. The largest effects are reported for low-frequency variants within TP53, with 0.5 cm wider heads in increaser-allele carriers versus non-carriers during mid-childhood, suggesting a previously unrecognized role of TP53 transcripts in human cranial development.
Published: 2019

20. Meta-analysis of epigenome-wide association studies in neonates reveals widespread differential DNA methylation associated with birthweight.

Author: Küpers, LK, Monnereau, C, Sharp, GC, Yousefi, P, Salas, LA, Ghantous, A, Page, CM, Reese, SE, Wilcox, AJ, Czamara, D, Starling, AP, Novoloaca, A, Lent, S, Roy, R, Hoyo, C, Breton, CV, Allard, C, Just, AC, Bakulski, KM, Holloway, JW, Everson, TM, Xu, C-J, Huang, R-C, van der Plaat, DA, Wielscher, M, Merid, SK, Ullemar, V, Rezwan, FI, Lahti, J, van Dongen, J, Langie, SAS, Richardson, TG, Magnus, MC, Nohr, EA, Xu, Z, Duijts, L, Zhao, S, Zhang, W, Plusquin, M, DeMeo, DL, Solomon, O, Heimovaara, JH, Jima, DD, Gao, L, Bustamante, M, Perron, P, Wright, RO, Hertz-Picciotto, I, Zhang, H, Karagas, MR, Gehring, U, Marsit, CJ, Beilin, LJ, Vonk, JM, Jarvelin, M-R, Bergström, A, Örtqvist, AK, Ewart, S, Villa, PM, Moore, SE, Willemsen, G, Standaert, ARL, Håberg, SE, Sørensen, TIA, Taylor, JA, Räikkönen, K, Yang, IV, Kechris, K, Nawrot, TS, Silver, MJ, Gong, YY, Richiardi, L, Kogevinas, M, Litonjua, AA, Eskenazi, B, Huen, K, Mbarek, H, Maguire, RL, Dwyer, T, Vrijheid, M, Bouchard, L, Baccarelli, AA, Croen, LA, Karmaus, W, Anderson, D, de Vries, M, Sebert, S, Kere, J, Karlsson, R, Arshad, SH, Hämäläinen, E, Routledge, MN, Boomsma, DI, Feinberg, AP, Newschaffer, CJ, Govarts, E, Moisse, M, Fallin, MD, Melén, E, Prentice, AM, Kajantie, E, Almqvist, C, Oken, E, Dabelea, D, Boezen, HM, Melton, PE, Wright, RJ, Koppelman, GH, Trevisi, L, Hivert, M-F, Sunyer, J, Munthe-Kaas, MC, Murphy, SK, Corpeleijn, E, Wiemels, J, Holland, N, Herceg, Z, Binder, EB, Davey Smith, G, Jaddoe, VWV, Lie, RT, Nystad, W, London, SJ, Lawlor, DA, Relton, CL, Snieder, H, Felix, JF, Küpers, LK, Monnereau, C, Sharp, GC, Yousefi, P, Salas, LA, Ghantous, A, Page, CM, Reese, SE, Wilcox, AJ, Czamara, D, Starling, AP, Novoloaca, A, Lent, S, Roy, R, Hoyo, C, Breton, CV, Allard, C, Just, AC, Bakulski, KM, Holloway, JW, Everson, TM, Xu, C-J, Huang, R-C, van der Plaat, DA, Wielscher, M, Merid, SK, Ullemar, V, Rezwan, FI, Lahti, J, van Dongen, J, Langie, SAS, Richardson, TG, Magnus, MC, Nohr, EA, Xu, Z, Duijts, L, Zhao, S, Zhang, W, Plusquin, M, DeMeo, DL, Solomon, O, Heimovaara, JH, Jima, DD, Gao, L, Bustamante, M, Perron, P, Wright, RO, Hertz-Picciotto, I, Zhang, H, Karagas, MR, Gehring, U, Marsit, CJ, Beilin, LJ, Vonk, JM, Jarvelin, M-R, Bergström, A, Örtqvist, AK, Ewart, S, Villa, PM, Moore, SE, Willemsen, G, Standaert, ARL, Håberg, SE, Sørensen, TIA, Taylor, JA, Räikkönen, K, Yang, IV, Kechris, K, Nawrot, TS, Silver, MJ, Gong, YY, Richiardi, L, Kogevinas, M, Litonjua, AA, Eskenazi, B, Huen, K, Mbarek, H, Maguire, RL, Dwyer, T, Vrijheid, M, Bouchard, L, Baccarelli, AA, Croen, LA, Karmaus, W, Anderson, D, de Vries, M, Sebert, S, Kere, J, Karlsson, R, Arshad, SH, Hämäläinen, E, Routledge, MN, Boomsma, DI, Feinberg, AP, Newschaffer, CJ, Govarts, E, Moisse, M, Fallin, MD, Melén, E, Prentice, AM, Kajantie, E, Almqvist, C, Oken, E, Dabelea, D, Boezen, HM, Melton, PE, Wright, RJ, Koppelman, GH, Trevisi, L, Hivert, M-F, Sunyer, J, Munthe-Kaas, MC, Murphy, SK, Corpeleijn, E, Wiemels, J, Holland, N, Herceg, Z, Binder, EB, Davey Smith, G, Jaddoe, VWV, Lie, RT, Nystad, W, London, SJ, Lawlor, DA, Relton, CL, Snieder, H, and Felix, JF
Abstract: Birthweight is associated with health outcomes across the life course, DNA methylation may be an underlying mechanism. In this meta-analysis of epigenome-wide association studies of 8,825 neonates from 24 birth cohorts in the Pregnancy And Childhood Epigenetics Consortium, we find that DNA methylation in neonatal blood is associated with birthweight at 914 sites, with a difference in birthweight ranging from -183 to 178 grams per 10% increase in methylation (PBonferroni < 1.06 x 10-7). In additional analyses in 7,278 participants, <1.3% of birthweight-associated differential methylation is also observed in childhood and adolescence, but not adulthood. Birthweight-related CpGs overlap with some Bonferroni-significant CpGs that were previously reported to be related to maternal smoking (55/914, p = 6.12 x 10-74) and BMI in pregnancy (3/914, p = 1.13x10-3), but not with those related to folate levels in pregnancy. Whether the associations that we observe are causal or explained by confounding or fetal growth influencing DNA methylation (i.e. reverse causality) requires further research.
Published: 2019

21. The Early Growth Genetics (EGG) and EArly Genetics and Lifecourse Epidemiology (EAGLE) consortia: design, results and future prospects

Author: Middeldorp, CM, Mahajan, A, Horikoshi, M, Robertson, NR, Beaumont, RN, Bradfield, JP, Bustamante, M, Cousminer, DL, Day, FR, De Silva, NM, Guxens, M, Mook-Kanamori, DO, St Pourcain, B, Warrington, NM, Adair, LS, Ahlqvist, E, Ahluwalia, TS, Almgren, P, Ang, W, Atalay, M, Auvinen, J, Bartels, M, Beckmann, JS, Bilbao, JR, Bond, T, Borja, JB, Cavadino, A, Charoen, P, Chen, Z, Coin, L, Cooper, C, Curtin, JA, Custovic, A, Das, S, Davies, GE, Dedoussis, GV, Duijts, L, Eastwood, PR, Eliasen, AU, Elliott, P, Eriksson, JG, Estivill, X, Fadista, J, Fedko, IO, Frayling, TM, Gaillard, R, Gauderman, WJ, Geller, F, Gilliland, F, Gilsanz, V, Granell, R, Grarup, N, Groop, L, Hadley, D, Hakonarson, H, Hansen, T, Hartman, CA, Hattersley, AT, Hayes, MG, Hebebrand, J, Heinrich, J, Helgeland, O, Henders, AK, Henderson, J, Henriksen, TB, Hirschhorn, JN, Hivert, M-F, Hocher, B, Holloway, JW, Holt, P, Hottenga, J-J, Hypponen, E, Iniguez, C, Johansson, S, Jugessur, A, Kahonen, M, Kalkwarf, HJ, Kaprio, J, Karhunen, V, Kemp, JP, Kerkhof, M, Koppelman, GH, Korner, A, Kotecha, S, Kreiner-Moller, E, Kulohoma, B, Kumar, A, Kutalik, Z, Lahti, J, Lappe, JM, Larsson, H, Lehtimaki, T, Lewin, AM, Li, J, Lichtenstein, P, Lindgren, CM, Lindi, V, Linneberg, A, Liu, X, Liu, J, Lowe, WL, Lundstrom, S, Lyytikainen, L-P, Ma, RCW, Mace, A, Magi, R, Magnus, P, Mamun, AA, Mannikko, M, Martin, NG, Mbarek, H, McCarthy, NS, Medland, SE, Melbye, M, Melen, E, Mohlke, KL, Monnereau, C, Morgen, CS, Morris, AP, Murray, JC, Myhre, R, Najman, JM, Nivard, MG, Nohr, EA, Nolte, IM, Ntalla, I, O'Reilly, P, Oberfield, SE, Oken, E, Oldehinkel, AJ, Pahkala, K, Palviainen, T, Panoutsopoulou, K, Pedersen, O, Pennell, CE, Pershagen, G, Pitkanen, N, Plomin, R, Power, C, Prasad, RB, Prokopenko, I, Pulkkinen, L, Raikkonen, K, Raitakari, OT, Reynolds, RM, Richmond, RC, Rivadeneira, F, Rodriguez, A, Rose, RJ, Salem, R, Santa-Marina, L, Saw, S-M, Schnurr, TM, Scott, JG, Selzam, S, Shepherd, JA, Simpson, A, Skotte, L, Sleiman, PMA, Snieder, H, Sorensen, TIA, Standl, M, Steegers, EAP, Strachan, DP, Straker, L, Strandberg, T, Taylor, M, Teo, Y-Y, Thiering, E, Torrent, M, Tyrrell, J, Uitterlinden, AG, van Beijsterveldt, T, van der Most, PJ, van Duijn, CM, Viikari, J, Vilor-Tejedor, N, Vogelezang, S, Vonk, JM, Vrijkotte, TGM, Vuoksimaa, E, Wang, CA, Watkins, WJ, Wichmann, H-E, Willemsen, G, Williams, GM, Wilson, JF, Wray, NR, Xu, S, Xu, C-J, Yaghootkar, H, Yi, L, Zafarmand, MH, Zeggini, E, Zemel, BS, Hinney, A, Lakka, TA, Whitehouse, AJO, Sunyer, J, Widen, EE, Feenstra, B, Sebert, S, Jacobsson, B, Njolstad, PR, Stoltenberg, C, Smith, GD, Lawlor, DA, Paternoster, L, Timpson, NJ, Ong, KK, Bisgaard, H, Bonnelykke, K, Jaddoe, VWV, Tiemeier, H, Jarvelin, M-R, Evans, DM, Perry, JRB, Grant, SFA, Boomsma, DI, Freathy, RM, McCarthy, MI, Felix, JF, Middeldorp, CM, Mahajan, A, Horikoshi, M, Robertson, NR, Beaumont, RN, Bradfield, JP, Bustamante, M, Cousminer, DL, Day, FR, De Silva, NM, Guxens, M, Mook-Kanamori, DO, St Pourcain, B, Warrington, NM, Adair, LS, Ahlqvist, E, Ahluwalia, TS, Almgren, P, Ang, W, Atalay, M, Auvinen, J, Bartels, M, Beckmann, JS, Bilbao, JR, Bond, T, Borja, JB, Cavadino, A, Charoen, P, Chen, Z, Coin, L, Cooper, C, Curtin, JA, Custovic, A, Das, S, Davies, GE, Dedoussis, GV, Duijts, L, Eastwood, PR, Eliasen, AU, Elliott, P, Eriksson, JG, Estivill, X, Fadista, J, Fedko, IO, Frayling, TM, Gaillard, R, Gauderman, WJ, Geller, F, Gilliland, F, Gilsanz, V, Granell, R, Grarup, N, Groop, L, Hadley, D, Hakonarson, H, Hansen, T, Hartman, CA, Hattersley, AT, Hayes, MG, Hebebrand, J, Heinrich, J, Helgeland, O, Henders, AK, Henderson, J, Henriksen, TB, Hirschhorn, JN, Hivert, M-F, Hocher, B, Holloway, JW, Holt, P, Hottenga, J-J, Hypponen, E, Iniguez, C, Johansson, S, Jugessur, A, Kahonen, M, Kalkwarf, HJ, Kaprio, J, Karhunen, V, Kemp, JP, Kerkhof, M, Koppelman, GH, Korner, A, Kotecha, S, Kreiner-Moller, E, Kulohoma, B, Kumar, A, Kutalik, Z, Lahti, J, Lappe, JM, Larsson, H, Lehtimaki, T, Lewin, AM, Li, J, Lichtenstein, P, Lindgren, CM, Lindi, V, Linneberg, A, Liu, X, Liu, J, Lowe, WL, Lundstrom, S, Lyytikainen, L-P, Ma, RCW, Mace, A, Magi, R, Magnus, P, Mamun, AA, Mannikko, M, Martin, NG, Mbarek, H, McCarthy, NS, Medland, SE, Melbye, M, Melen, E, Mohlke, KL, Monnereau, C, Morgen, CS, Morris, AP, Murray, JC, Myhre, R, Najman, JM, Nivard, MG, Nohr, EA, Nolte, IM, Ntalla, I, O'Reilly, P, Oberfield, SE, Oken, E, Oldehinkel, AJ, Pahkala, K, Palviainen, T, Panoutsopoulou, K, Pedersen, O, Pennell, CE, Pershagen, G, Pitkanen, N, Plomin, R, Power, C, Prasad, RB, Prokopenko, I, Pulkkinen, L, Raikkonen, K, Raitakari, OT, Reynolds, RM, Richmond, RC, Rivadeneira, F, Rodriguez, A, Rose, RJ, Salem, R, Santa-Marina, L, Saw, S-M, Schnurr, TM, Scott, JG, Selzam, S, Shepherd, JA, Simpson, A, Skotte, L, Sleiman, PMA, Snieder, H, Sorensen, TIA, Standl, M, Steegers, EAP, Strachan, DP, Straker, L, Strandberg, T, Taylor, M, Teo, Y-Y, Thiering, E, Torrent, M, Tyrrell, J, Uitterlinden, AG, van Beijsterveldt, T, van der Most, PJ, van Duijn, CM, Viikari, J, Vilor-Tejedor, N, Vogelezang, S, Vonk, JM, Vrijkotte, TGM, Vuoksimaa, E, Wang, CA, Watkins, WJ, Wichmann, H-E, Willemsen, G, Williams, GM, Wilson, JF, Wray, NR, Xu, S, Xu, C-J, Yaghootkar, H, Yi, L, Zafarmand, MH, Zeggini, E, Zemel, BS, Hinney, A, Lakka, TA, Whitehouse, AJO, Sunyer, J, Widen, EE, Feenstra, B, Sebert, S, Jacobsson, B, Njolstad, PR, Stoltenberg, C, Smith, GD, Lawlor, DA, Paternoster, L, Timpson, NJ, Ong, KK, Bisgaard, H, Bonnelykke, K, Jaddoe, VWV, Tiemeier, H, Jarvelin, M-R, Evans, DM, Perry, JRB, Grant, SFA, Boomsma, DI, Freathy, RM, McCarthy, MI, and Felix, JF
Abstract: The impact of many unfavorable childhood traits or diseases, such as low birth weight and mental disorders, is not limited to childhood and adolescence, as they are also associated with poor outcomes in adulthood, such as cardiovascular disease. Insight into the genetic etiology of childhood and adolescent traits and disorders may therefore provide new perspectives, not only on how to improve wellbeing during childhood, but also how to prevent later adverse outcomes. To achieve the sample sizes required for genetic research, the Early Growth Genetics (EGG) and EArly Genetics and Lifecourse Epidemiology (EAGLE) consortia were established. The majority of the participating cohorts are longitudinal population-based samples, but other cohorts with data on early childhood phenotypes are also involved. Cohorts often have a broad focus and collect(ed) data on various somatic and psychiatric traits as well as environmental factors. Genetic variants have been successfully identified for multiple traits, for example, birth weight, atopic dermatitis, childhood BMI, allergic sensitization, and pubertal growth. Furthermore, the results have shown that genetic factors also partly underlie the association with adult traits. As sample sizes are still increasing, it is expected that future analyses will identify additional variants. This, in combination with the development of innovative statistical methods, will provide detailed insight on the mechanisms underlying the transition from childhood to adult disorders. Both consortia welcome new collaborations. Policies and contact details are available from the corresponding authors of this manuscript and/or the consortium websites.
Published: 2019

22. GWAS on longitudinal growth traits reveals different genetic factors influencing infant, child, and adult BMI

Author: Alves, AC, De Silva, NMG, Karhunen, V, Sovio, U, Das, S, Taal, HR, Warrington, NM, Lewin, AM, Kaakinen, M, Cousminer, DL, Thiering, E, Timpson, NJ, Bond, TA, Lowry, E, Brown, CD, Estivill, X, Lindi, V, Bradfield, JP, Geller, F, Speed, D, Coin, LJM, Loh, M, Barton, SJ, Beilin, LJ, Bisgaard, H, Bonnelykke, K, Alili, R, Hatoum, IJ, Schramm, K, Cartwright, R, Charles, M-A, Salerno, V, Clement, K, Claringbould, AAJ, van Duijn, CM, Moltchanova, E, Eriksson, JG, Elks, C, Feenstra, B, Flexeder, C, Franks, S, Frayling, TM, Freathy, RM, Elliott, P, Widen, E, Hakonarson, H, Hattersley, AT, Rodriguez, A, Banterle, M, Heinrich, J, Heude, B, Holloway, JW, Hofman, A, Hypponen, E, Inskip, H, Kaplan, LM, Hedman, AK, Laara, E, Prokisch, H, Grallert, H, Lakka, TA, Lawlor, DA, Melbye, M, Ahluwalia, TS, Marinelli, M, Millwood, IY, Palmer, LJ, Pennell, CE, Perry, JR, Ring, SM, Savolainen, MJ, Rivadeneira, F, Standl, M, Sunyer, J, Tiesler, CMT, Uitterlinden, AG, Schierding, W, O'Sullivan, JM, Prokopenko, I, Herzig, K-H, Smith, GD, O'Reilly, P, Felix, JF, Buxton, JL, Blakemore, AIF, Ong, KK, Jaddoe, VWV, Grant, SFA, Sebert, S, McCarthy, MI, Jarvelin, M-R, Alves, AC, De Silva, NMG, Karhunen, V, Sovio, U, Das, S, Taal, HR, Warrington, NM, Lewin, AM, Kaakinen, M, Cousminer, DL, Thiering, E, Timpson, NJ, Bond, TA, Lowry, E, Brown, CD, Estivill, X, Lindi, V, Bradfield, JP, Geller, F, Speed, D, Coin, LJM, Loh, M, Barton, SJ, Beilin, LJ, Bisgaard, H, Bonnelykke, K, Alili, R, Hatoum, IJ, Schramm, K, Cartwright, R, Charles, M-A, Salerno, V, Clement, K, Claringbould, AAJ, van Duijn, CM, Moltchanova, E, Eriksson, JG, Elks, C, Feenstra, B, Flexeder, C, Franks, S, Frayling, TM, Freathy, RM, Elliott, P, Widen, E, Hakonarson, H, Hattersley, AT, Rodriguez, A, Banterle, M, Heinrich, J, Heude, B, Holloway, JW, Hofman, A, Hypponen, E, Inskip, H, Kaplan, LM, Hedman, AK, Laara, E, Prokisch, H, Grallert, H, Lakka, TA, Lawlor, DA, Melbye, M, Ahluwalia, TS, Marinelli, M, Millwood, IY, Palmer, LJ, Pennell, CE, Perry, JR, Ring, SM, Savolainen, MJ, Rivadeneira, F, Standl, M, Sunyer, J, Tiesler, CMT, Uitterlinden, AG, Schierding, W, O'Sullivan, JM, Prokopenko, I, Herzig, K-H, Smith, GD, O'Reilly, P, Felix, JF, Buxton, JL, Blakemore, AIF, Ong, KK, Jaddoe, VWV, Grant, SFA, Sebert, S, McCarthy, MI, and Jarvelin, M-R
Abstract: Early childhood growth patterns are associated with adult health, yet the genetic factors and the developmental stages involved are not fully understood. Here, we combine genome-wide association studies with modeling of longitudinal growth traits to study the genetics of infant and child growth, followed by functional, pathway, genetic correlation, risk score, and colocalization analyses to determine how developmental timings, molecular pathways, and genetic determinants of these traits overlap with those of adult health. We found a robust overlap between the genetics of child and adult body mass index (BMI), with variants associated with adult BMI acting as early as 4 to 6 years old. However, we demonstrated a completely distinct genetic makeup for peak BMI during infancy, influenced by variation at the LEPR/LEPROT locus. These findings suggest that different genetic factors control infant and child BMI. In light of the obesity epidemic, these findings are important to inform the timing and targets of prevention strategies.
Published: 2019

23. Association of Birth Weight With Type 2 Diabetes and Glycemic Traits: A Mendelian Randomization Study

Author: Universitat Rovira i Virgili, Huang T, Wang T, Zheng Y, Ellervik C, Li X, Gao M, Fang Z, Chai JF, Ahluwalia TVS, Wang Y, Voortman T, Noordam R, Frazier-Wood A, Scholz M, Sonestedt E, Akiyama M, Dorajoo R, Zhou A, Kilpeläinen TO, Kleber ME, Crozier SR, Godfrey KM, Lemaitre R, Felix JF, Shi Y, Gupta P, Khor CC, Lehtimäki T, Wang CA, Tiesler CMT, Thiering E, Standl M, Rzehak P, Marouli E, He M, Lecoeur C, Corella D, Lai CQ, Moreno LA, Pitkänen N, Boreham CA, Zhang T, Saw SM, Ridker PM, Graff M, van Rooij FJA, Uitterlinden AG, Hofman A, van Heemst D, Rosendaal FR, de Mutsert R, Burkhardt R, Schulz CA, Ericson U, Kamatani Y, Yuan JM, Power C, Hansen T, Sørensen TIA, Tjønneland A, Overvad K, Delgado G, Cooper C, Djousse L, Rivadeneira F, Jameson K, Zhao W, Liu J, Lee NR, Raitakari O, Kähönen M, Viikari J, Grote V, Langhendries JP, Koletzko B, Escribano J, Verduci E, Dedoussis G, Yu C, Tham YC, Lim B, Lim SH, Froguel P, Balkau B, Fink NR, Vinding RK, Sevelsted A, Bisgaard H, Coltell O, Dallongeville J, Gottrand F, Pahkala K, Niinikoski H, Hyppönen E, Pedersen O, März W, Inskip H, Jaddoe VWV, Dennison E, Wong TY, Sabanayagam C, Tai ES, Mohlke KL, Mackey DA, Gruszfeld D, Deloukas P, Tucker KL, Fumeron F, Bønnelykke K, Rossing P, Estruch R, Ordovas JM, Arnett DK, Meirhaeghe A, Amouyel P, Cheng CY, Sim X, Teo YY, van Dam RM, Koh WP, Orho-Melander M, Loeffler M, Kubo M, Thiery J, Mook-Kanamori DO, Mozaffarian D, Psaty BM, Franco OH, Wu T, North KE, Davey Smith G, Chavarro JE, Chasman DI, Qi L BIRTH-GENE (BIG) Study Working Group, Universitat Rovira i Virgili, and Huang T, Wang T, Zheng Y, Ellervik C, Li X, Gao M, Fang Z, Chai JF, Ahluwalia TVS, Wang Y, Voortman T, Noordam R, Frazier-Wood A, Scholz M, Sonestedt E, Akiyama M, Dorajoo R, Zhou A, Kilpeläinen TO, Kleber ME, Crozier SR, Godfrey KM, Lemaitre R, Felix JF, Shi Y, Gupta P, Khor CC, Lehtimäki T, Wang CA, Tiesler CMT, Thiering E, Standl M, Rzehak P, Marouli E, He M, Lecoeur C, Corella D, Lai CQ, Moreno LA, Pitkänen N, Boreham CA, Zhang T, Saw SM, Ridker PM, Graff M, van Rooij FJA, Uitterlinden AG, Hofman A, van Heemst D, Rosendaal FR, de Mutsert R, Burkhardt R, Schulz CA, Ericson U, Kamatani Y, Yuan JM, Power C, Hansen T, Sørensen TIA, Tjønneland A, Overvad K, Delgado G, Cooper C, Djousse L, Rivadeneira F, Jameson K, Zhao W, Liu J, Lee NR, Raitakari O, Kähönen M, Viikari J, Grote V, Langhendries JP, Koletzko B, Escribano J, Verduci E, Dedoussis G, Yu C, Tham YC, Lim B, Lim SH, Froguel P, Balkau B, Fink NR, Vinding RK, Sevelsted A, Bisgaard H, Coltell O, Dallongeville J, Gottrand F, Pahkala K, Niinikoski H, Hyppönen E, Pedersen O, März W, Inskip H, Jaddoe VWV, Dennison E, Wong TY, Sabanayagam C, Tai ES, Mohlke KL, Mackey DA, Gruszfeld D, Deloukas P, Tucker KL, Fumeron F, Bønnelykke K, Rossing P, Estruch R, Ordovas JM, Arnett DK, Meirhaeghe A, Amouyel P, Cheng CY, Sim X, Teo YY, van Dam RM, Koh WP, Orho-Melander M, Loeffler M, Kubo M, Thiery J, Mook-Kanamori DO, Mozaffarian D, Psaty BM, Franco OH, Wu T, North KE, Davey Smith G, Chavarro JE, Chasman DI, Qi L BIRTH-GENE (BIG) Study Working Group
Abstract: Importance: Observational studies have shown associations of birth weight with type 2 diabetes (T2D) and glycemic traits, but it remains unclear whether these associations represent causal associations. Objective: To test the association of birth weight with T2D and glycemic traits using a mendelian randomization analysis. Design, Setting, and Participants: This mendelian randomization study used a genetic risk score for birth weight that was constructed with 7 genome-wide significant single-nucleotide polymorphisms. The associations of this score with birth weight and T2D were tested in a mendelian randomization analysis using study-level data. The association of birth weight with T2D was tested using both study-level data (7 single-nucleotide polymorphisms were used as an instrumental variable) and summary-level data from the consortia (43 single-nucleotide polymorphisms were used as an instrumental variable). Data from 180 056 participants from 49 studies were included. Main Outcomes and Measures: Type 2 diabetes and glycemic traits. Results: This mendelian randomization analysis included 49 studies with 41 155 patients with T2D and 80 008 control participants from study-level data and 34 840 patients with T2D and 114 981 control participants from summary-level data. Study-level data showed that a 1-SD decrease in birth weight due to the genetic risk score was associated with higher risk of T2D among all participants (odds ratio [OR], 2.10; 95% CI, 1.69-2.61; P = 4.03 × 10-5), among European participants (OR, 1.96; 95% CI, 1.42-2.71; P = .04), and among East Asian participants (OR, 1.39; 95% CI, 1.18-1.62; P = .04). Similar results were observed from summary-level analyses. In addition, each 1-SD lower birth weight was associated with 0.189 SD higher fasting glucose
Published: 2019

24. Author Correction: Genome-wide association and HLA fine-mapping studies identify risk loci and genetic pathways underlying allergic rhinitis

Author: Waage, J, Standl, M, Curtin, JA, Jessen, LE, Thorsen, J, Tian, C, Schoettler, N, 23andMe Research Team, AAGC collaborators, Flores, C, Abdellaoui, A, Ahluwalia, TS, Alves, AC, Amaral, AFS, Antó, JM, Arnold, A, Barreto-Luis, A, Baurecht, H, van Beijsterveldt, CEM, Bleecker, ER, Bonàs-Guarch, S, Boomsma, DI, Brix, S, Bunyavanich, S, Burchard, EG, Chen, Z, Curjuric, I, Custovic, A, den Dekker, HT, Dharmage, SC, Dmitrieva, J, Duijts, L, Ege, MJ, Gauderman, WJ, Georges, M, Gieger, C, Gilliland, F, Granell, R, Gui, H, Hansen, T, Heinrich, J, Henderson, J, Hernandez-Pacheco, N, Holt, P, Imboden, M, Jaddoe, VWV, Jarvelin, M-R, Jarvis, DL, Jensen, KK, Jónsdóttir, I, Kabesch, M, Kaprio, J, Kumar, A, Lee, Y-A, Levin, AM, Li, X, Lorenzo-Diaz, F, Melén, E, Mercader, JM, Meyers, DA, Myers, R, Nicolae, DL, Nohr, EA, Palviainen, T, Paternoster, L, Pennell, CE, Pershagen, G, Pino-Yanes, M, Probst-Hensch, NM, Rüschendorf, F, Simpson, A, Stefansson, K, Sunyer, J, Sveinbjornsson, G, Thiering, E, Thompson, PJ, Torrent, M, Torrents, D, Tung, JY, Wang, CA, Weidinger, S, Weiss, S, Willemsen, G, Williams, LK, Ober, C, Hinds, DA, Ferreira, MA, Bisgaard, H, Strachan, DP, and Bønnelykke, K
Subjects: ComputingMethodologies_DOCUMENTANDTEXTPROCESSING, ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION, ComputingMethodologies_COMPUTERGRAPHICS
Abstract: In the version of this article initially published, in Fig. 3, the y-axis numbering did not match the log scale indicated in the axis label. The error has been corrected in the HTML and PDF version of the article.
Published: 2018

25. Genome-wide association and HLA fine-mapping studies identify risk loci and genetic pathways underlying allergic rhinitis

Author: Waage, J, Standl, M, Curtin, JA, Jessen, L, Thorsen, J, Tian, C, Schoettler, N, The 23andMe Research Team, AAGC Collaborators, Flores, C, Abdellaoui, A, Ahluwalia, TS, Alves, A, Amaral, AFS, Antó, JM, Arnold, A, Barreto-Luis, A, Baurecht, H, van Beijsterveldt, CEM, Bleecker, ER, Bonàs-Guarch, S, Boomsma, D, Brix, S, Bunyavanich, S, Burchard, E, Chen, Z, Curjuric, I, Custovic, A, den Dekker, HT, Dharmage, SC, Dmitrieva, J, Duijts, L, Ege, MJ, Gauderman, WJ, Georges, M, Gieger, C, Gilliland, F, Granell, R, Gui, H, Hansen, T, Heinrich, J, Henderson, J, Hernandez-Pacheco, N, Holt, P, Imboden, M, Jaddoe, VWV, Jarvelin, M-R, Jarvis, DL, Jensen, KK, Jónsdóttir, I, Kabesch, M, Kaprio, J, Kumar, A, Lee, Y-A, Levin, AM, Li, X, Lorenzo-Diaz, F, Melén, E, Mercader, JM, Meyers, DA, Myers, R, Nicolae, DL, Nohr, EA, Palviainen, T, Paternoster, L, Pennell, C, Pershagen, G, Pino-Yanes, M, Probst-Hensch, NM, Rüschendorf, F, Simpson, A, Stefansson, K, Sunyer, J, Sveinbjornsson, G, Thiering, E, Thompson, PJ, Torrent, M, Torrents, D, Tung, JY, Wang, CA, Weidinger, S, Weiss, S, Willemsen, G, Williams, LK, Ober, C, Hinds, DA, Ferreira, MA, Bisgaard, H, Strachan, DP, and Bønnelykke, K
Abstract: Allergic rhinitis is the most common clinical presentation of allergy, affecting 400 million people worldwide, with increasing incidence in westernized countries1,2. To elucidate the genetic architecture and understand the underlying disease mechanisms, we carried out a meta-analysis of allergic rhinitis in 59,762 cases and 152,358 controls of European ancestry and identified a total of 41 risk loci for allergic rhinitis, including 20 loci not previously associated with allergic rhinitis, which were confirmed in a replication phase of 60,720 cases and 618,527 controls. Functional annotation implicated genes involved in various immune pathways, and fine mapping of the HLA region suggested amino acid variants important for antigen binding. We further performed genome-wide association study (GWAS) analyses of allergic sensitization against inhalant allergens and nonallergic rhinitis, which suggested shared genetic mechanisms across rhinitis-related traits. Future studies of the identified loci and genes might identify novel targets for treatment and prevention of allergic rhinitis.
Published: 2018

26. A genome-wide association study for corneal astigmatism: The CREAM Consortium

Author: Shah, Rupal, Li, Q, Zhao, W, Tedja, MS, Tideman, WL, Khawaja, A, Fan, Q, Yazar, S, Williams, KM, Verhoeven, VJM, Xie, J, Wang, YX, Hess, M, Nickels, S, Lackner, KJ, Pärssinen, O, Wedenoja, J, Biino, G, Concas, MP, Uitterlinden, A, Rivadeneira, F, Jaddoe, VWV, Hysi, PG, Sim, X, Tan, N, Tham, Y, Sensaki, S, Hofman, A, Vingerling, JR, Jonas, JB, Mitchell, P, Hammond, CJ, Höhn, R, Baird, PN, Wong, TY, Cheng, C, Teo, YY, Mackey, DA, Williams, C, Saw, S, Klaver, CCW, Guggenheim, Jeremy, Bailey-Wilson, JE, and The CREAM Consortium
Abstract: Purpose: To identify genes and genetic markers associated with corneal astigmatism.\ud Methods: A meta-analysis was performed of genome-wide association studies (GWAS) of corneal astigmatism undertaken for 14 European ancestry (N = 22,250) and 8 Asian ancestry (N = 9,120) cohorts by the CREAM Consortium. Cases were defined as having >0.75 D of corneal astigmatism. For the meta-analysed results of European ancestry cohorts, subsequent gene-based and gene-set analyses were performed using VEGAS2 and MAGMA software. Additionally, estimates of SNP-based heritability for corneal and refractive astigmatism and spherical equivalent were calculated for Europeans using LD score regression.\ud Results: Meta-analysis of all cohorts identified a genome-wide significant locus near the gene PDGFRA (platelet derived growth factor receptor alpha): top SNP: rs7673984, odds ratio = 1.12 (95% CI: 1.08-1.16), P = 5.55 x 10-9. No other genome-wide significant loci were identified in the combined analysis or European/Asian ancestry-specific analyses. Gene-based analysis identified 3 novel candidate genes for corneal astigmatism in Europeans: CLDN7 (claudin-7), ACP2 (acid phosphatase 2, lysosomal) and TNFAIP8L3 (TNF alpha induced protein 8 like 3).\ud Conclusions: In addition to replicating a previously identified genome-wide significant locus for corneal astigmatism near the PDGFRA gene, gene-based analysis identified 3 novel candidate genes CLDN7, ACP2 and TNFAIP8L3 that warrant further investigation to understand their role in the pathogenesis of corneal astigmatism. The much lower number of genetic variants and genes demonstrating association with corneal astigmatism compared to published spherical equivalent GWAS analyses suggest a greater influence of rare genetic variants, non-additive genetic effects, or environmental factors to the development of astigmatism.
Published: 2018

27. Cohort Profile: Pregnancy And Childhood Epigenetics (PACE) Consortium

Author: Felix, JF, Joubert, BR, Baccarelli, AA, Sharp, GC, Almqvist, C, Annesi-Maesano, I, Arshad, H, Baïz, N, Bakermans-Kranenburg, MJ, Bakulski, KM, Binder, EB, Bouchard, L, Breton, CV, Brunekreef, B, Brunst, KJ, Burchard, EG, Bustamante, M, Chatzi, L, Munthe-Kaas, M, Corpeleijn, E, Czamara, D, Dabelea, D, Smith, G, De Boever, P, Duijts, L, Dwyer, T, Eng, C, Eskenazi, B, Everson, TM, Falahi, F, Fallin, MD, Farchi, S, Fernandez, MF, Gao, L, Gaunt, TR, Ghantous, A, Gillman, MW, Gonseth, S, Grote, V, Gruzieva, O, Håberg, SE, Herceg, Z, Hivert, M-F, Holland, N, Holloway, JW, Hoyo, C, Hu, D, Huang, R-C, Huen, K, Järvelin, M-R, Jima, DD, Just, AC, Karagas, MR, Karlsson, R, Karmaus, W, Kechris, KJ, Kere, J, Kogevinas, M, Koletzko, B, Koppelman, GH, Küpers, LK, Ladd-Acosta, C, Lahti, J, Lambrechts, N, Langie, SAS, Lie, RT, Liu, AH, Magnus, MC, Magnus, P, Maguire, RL, Marsit, CJ, McArdle, W, Melén, E, Melton, P, Murphy, SK, Nawrot, TS, Nisticò, L, Nohr, EA, Nordlund, B, Nystad, W, Oh, SS, Oken, E, Page, CM, Perron, P, Pershagen, G, Pizzi, C, Plusquin, M, Raikkonen, K, Reese, SE, Reischl, E, Richiardi, L, Ring, S, Roy, RP, Rzehak, P, Schoeters, G, Schwartz, DA, Sebert, S, Snieder, H, Sørensen, TIA, Starling, AP, Sunyer, J, Taylor, JA, Tiemeier, H, Ullemar, V, Vafeiadi, M, Van Ijzendoorn, MH, Vonk, JM, Vriens, A, Vrijheid, M, Wang, P, Wiemels, JL, Wilcox, AJ, Wright, RJ, Xu, C-J, Xu, Z, Yang, IV, Yousefi, P, Zhang, H, Zhang, W, Zhao, S, Agha, G, Relton, CL, Jaddoe, VWV, London, SJ, Epidemiology, Erasmus MC other, Pediatrics, Child and Adolescent Psychiatry / Psychology, Psychiatry, Research Methods and Techniques, dIRAS RA-2, One Health Chemisch, Reproductive Origins of Adult Health and Disease (ROAHD), Lifestyle Medicine (LM), Groningen Research Institute for Asthma and COPD (GRIAC), Life Course Epidemiology (LCE), Department of Psychology and Logopedics, Helsinki Collegium for Advanced Studies, Medicum, University of Helsinki, and Developmental Psychology Research Group
Subjects: DNA Methylation/physiology, Epidemiology, Maternal Health, education, Embaràs, DISEASE, Environmental Pollution/analysis, Epigenesis, Genetic, Cohort Studies, Prenatal Exposure Delayed Effects/epidemiology, Folic Acid, Pregnancy, Journal Article, Humans, MATERNAL SMOKING, CORD BLOOD, GeneralLiterature_REFERENCE(e.g.,dictionaries,encyclopedias,glossaries), Cohort Profiles, METAANALYSIS, PRENATAL EXPOSURE, Maternal Exposure/adverse effects, EPIGENOME-WIDE ASSOCIATION, 0104 Statistics, Child Health, Infant, Newborn, DNA METHYLATION DATA, DNA Methylation, Epigenètica, BIRTH-WEIGHT, 3142 Public health care science, environmental and occupational health, Folic Acid/blood, 1117 Public Health And Health Services, Maternal Exposure, Prenatal Exposure Delayed Effects, MENDELIAN RANDOMIZATION, Epigenetics, Female, Human medicine, Environmental Pollution
Abstract: UK Medical Research Council; Wellcome Trust [102215/2/13/2, WT088806, 084762MA]; UK Biotechnology and Biological Sciences Research Council [BB/I025751/1, BB/I025263/1]; UK Medical Research Council Integrative Epidemiology Unit; University of Bristol [MC_UU_12013_1, MC_UU_12013_2, MC_UU_12013_5, MC_UU_12013_8]; United States National Institute of Diabetes and Digestive and Kidney Diseases [R01 DK10324]; Swedish Research Council; Swedish Heart-Lung Foundation; Freemason Child House Foundation in Stockholm; MeDALL (Mechanisms of the Development of ALLergy), within the European Union [261357]; Stockholm County Council (ALF); Swedish Foundation for Strategic Research (SSF) [RBc08-0027]; Strategic Research Programme (SFO) in Epidemiology at Karolinska Institutet; Swedish Research Council Formas; Swedish Environment Protection Agency; Center for Integrative Research on Childhood Leukemia and the Environment [P01ES018172]; NIH [P50ES018172, R01ES09137, 5P30CA082103, P01 ES009605, R01 ES021369, R01ES023067, K01ES017801, R01ES022216, P30ES007048, R01ES014447, P01ES009581, R826708-01, RD831861-01, P50ES026086, R01DK068001, R01 DK100340, R01 DK076648, R01ES022934, R01HL111108, R01NR013945, R37 HD034568, UL1 TR001082, P30 DK56350]; EPA [RD83451101, RD83615901, RD 82670901, RD 83451301, 83615801-0]; UCSF Comprehensive Cancer Center Support grant [P30 CA82103]; Swiss Science National Foundation [P2LAP3_158674]; Sutter-Stottner Foundation; Commission of the European Community, specific RTD Programme 'Quality of Life and Management of Living Resources' within the 5th Framework Programme [QLRT-2001-00389, QLK1-CT-2002-30582]; 6th Framework Programme [007036]; European Union's Seventh Framework Programme (FP7), project EarlyNutrition [289346]; European Research Council Advanced grant ERC-AdG [322605 META-GROWTH]; Autism Speaks grant [260377]; Funds for Research in Respiratory Health; French Ministry of Research: IFR program; INSERM Nutrition Research Program; French Ministry of Health: Perinatality Program; French National Institute for Population Health Surveillance (INVS); Paris-Sud University; French National Institute for Health Education (INPES); Nestle; Mutuelle Generale de l'Education Nationale (MGEN); French-speaking association for the study of diabetes and metabolism (Alfediam) [2012/51290-6]; EU; European Research Council [ERC-2012-StG.310898, 268479-BREATHE]; Flemish Scientific Research Council (FWO) [N1516112 / G.0.873.11N.10]; European Community's Seventh Framework Programme FP7 project EXPOsOMICS [308610]; People Program (Marie Curie Actions) of the European Union's Seventh Framework Program FP7 under REA grant [628858]; Bijzonder Onderzoeksfonds (BOF) Hasselt University; Ministry of the Flemish Community (Department of Economics, Science and Innovation); Ministry of the Flemish Community (Department of Environment, Nature and Energy); CEFIC LRI award by the Research Foundation-Flanders (FWO); CEFIC LRI award by the Research Foundation-Flanders (FWO) [12L5216N]; Flemish Institute for Technological Research (VITO) [12L5216N]; Bill AMP; Melinda Gates Foundation Grand Challenges Exploration grant [OPP119403]; Sandler Family Foundation; American Asthma Foundation; National Institutes of Health; National Heart, Lung and Blood Institute [HL117004]; National Institute of Environmental Health Sciences [ES24844]; National Institute on Minority Health and Health Disparities [MD006902, MD009523]; National Institute of General Medical Sciences [GM007546]; Tobacco-Related Disease Research Program [24RT-0025]; Hutchison Whampoa Ltd, Hong Kong; University of Groningen; Well Baby Clinic Foundation Icare; Noordlease; Youth Health Care Drenthe; Biobanking and Biomolecular Research Infrastructure Netherlands [CP2011-19]; Erasmus Medical Center, Rotterdam; Erasmus University Rotterdam; Netherlands Organization for Health Research and Development; Netherlands Genomics Initiative (NGI)/Netherlands Organization for Scientific Research (NWO); Netherlands Consortium for Healthy Aging (NCHA) [050-060-810]; Genetic Laboratory of the Department of Internal Medicine, Erasmus MC; European Union's Horizon research and innovation programme [733206, 633595]; National Institute of Child and Human Development [R01HD068437]; Netherlands Organization for Health Research and Development [VIDI 016.136.361]; Consolidator grant from the European Research Council [ERC-2014-CoG-648916]; Netherlands' Organization for Scientific Research (NWO VICI); European Research Council ERC; Netherlands' Organization for Scientific Research (NWO Spinoza Award); Gravitation program of the Dutch Ministry of Education, Culture, and Science; Netherlands Organization for Scientific Research (NWO) [024.001.003]; Lung Foundation Netherlands [3.2.12.089]; Fonds de Recherche du Quebec en Sante (FRQ-S) [20697]; Canadian Institute of Health Reseach (CIHR) [MOP 115071]; Diabete Quebec grant; Canadian Diabetes Association operating grant [OG-3-08-2622]; American Diabetes Association Pathways Accelerator Early Investigator Award [1-15-ACE-26]; MRC Integrative Epidemiology Unit - Medical Research Council [MC_UU_12013/1-9]; National Institute of Environmental Health Sciences, National Institutes of Health [K99ES025817]; Instituto de Salud Carlos III [Red INMA G03/176, CB06/02/0041]; Spanish Ministry of Health [FIS-PI04/1436, FIS-PI08/1151]; Spanish Ministry of Health (FEDER funds) [FIS-PI11/00610, FIS-FEDER-PI06/0867, FIS-FEDER-PI03-1615]; Generalitat de Catalunya [CIRIT 1999SGR 00241]; Fundacio La Marato de TV3 [090430]; EU Commission [261357-MeDALL]; National Institute of Allergy and Infectious Diseases [N01-AI90052]; National Institutes of Health USA [R01 HL082925, R01 HL132321]; Asthma UK [364]; NIAID/NIH [R01AI091905, R01AI121226]; National Institute of Health [R01AI121226, R01 AI091905, R01HL132321]; NIH/NIEHS [N01-ES75558]; NIH/NINDS [1 UO1 NS 047537-01, 2 UO1 NS 047537-06A1]; Intramural Research Program of the NIH, National Institute of Environmental Health Sciences [Z01-ES-49019, Z01 ES044005, ES049033, ES049032]; Norwegian Research Council/BIOBANK [221097]; Oslo University Hospital; Unger-Vetlesens foundation; Norwegian American Womens Club; INCA/Plan Cancer-EVA-INSERM, France; International Childhood Cancer Cohort Consortium (I4C); INCA/Plan Cancer-EVA-INSERM (France); IARC Postdoctoral Fellowship; EC FP7 Marie Curie Actions-People-Co-funding of regional, national and international programmes (COFUND); NIEHS [R21ES014947, R01ES016772]; NIDDK [R01DK085173]; National Institute of Environmental Health Science [P30 ES025128]; University of Oulu grant [65354]; Oulu University Hospital [2/97, 8/97]; Ministry of Health and Social Affairs [23/251/97, 160/97, 190/97]; National Institute for Health and Welfare, Helsinki [54121]; Regional Institute of Occupational Health, Oulu, Finland [50621, 54231]; EU [QLG1-CT-2000-01643, E51560]; NorFA grant [731, 20056, 30167]; Academy of Finland; NIH-NIEHS [P01 ES022832]; US EPA [RD83544201]; NIH-NIGMS [P20GM104416]; NCI [R25CA134286]; Netherlands Organization for Scientific Research and Development; Netherlands Asthma Fund; Netherlands Ministry of Spatial Planning, Housing, and the Environment; Netherlands Ministry of Health, Welfare, and Sport; MeDALL; European Union under the Health Cooperation Work Program of the 7th Framework program [261357]; Italian National Centre for Disease Prevention and Control (CCM grant); Italian Ministry of Health (art 12); Italian Ministry of Health (12bis Dl.gs.vo) [502/92]; EraNet; EVO; University of Helsinki Research Funds; Signe and Ane Gyllenberg foundation; Emil Aaltonen Foundation; Finnish Medical Foundation; Jane and Aatos Erkko Foundation; Novo Nordisk Foundation; Paivikki and Sakari Sohlberg Foundation; Sigrid Juselius Foundation; University of Helsinki; University of Western Australia (UWA); Curtin University; Raine Medical Research Foundation; UWA Faculty of Medicine, Dentistry and Health Sciences; Telethon Kids Institute; Women's and Infant's Research Foundation (KEMH); Edith Cowan University; National Health and Medical Research Council [1059711]; National Health and Medical Research Council (NHMRC) fellowship [1053384]; Australian National Health and Medical Research Council; United States National Institute of Health; Greek Ministry of Health (programme of prevention of obesity and neurodevelopmental disorders in preschool children, in Heraklion district, Crete, Greece); Greek Ministry of Health ('Rhea Plus': Primary Prevention Program of Environmental Risk Factors for Reproductive Health, and Child Health); European Union (EU) [EU FP6-2003-Food-3-NewGeneris, EU FP7 ENV.2007.1.2.2.2, 211250 ESCAPE, EU FP7-2008-ENV-1.2.1.4 Envirogenomarkers, EU FP7 ENV.2008.1.2.1.6, 226285 ENRIECO]; National Institutes of Health [NIH-NIMH R01MH094609, NIH-NIEHS R01ES022223, NIH-NIEHS R01ES025145]; Centers for Disease Control and Prevention [U10DD000180, U10DD000181, U10DD000182, U10DD000183, U10DD000184, U10DD000498]; Autism Speaks [7659]; Swedish Research Council through the Swedish Initiative for research on Microdata in the Social And Medical Sciences (SIMSAM) [340-2013-5867]; Stockholm County Council (ALF projects); Strategic Research Program in Epidemiology at Karolinska Institutet; Swedish Asthma and Allergy Association's Research Foundation; Stiftelsen Frimurare Barnahuset Stockholm; Norwegian Ministry of Health and Care Services; Ministry of the Flemish Community (Flemish Agency for Care and Health); University of Bristol; Ministry of Education and Research; European Union (EU) (EU FP7-HEALTH-single stage CHICOS); European Union (EU) (EU-FP7-HEALTH) [308333 HELIX]; European Union (EU) (EU FP6. STREP HiWATE); UK Medical Research Council; Wellcome Trust [102215/2/13/2, WT088806, 084762MA]; UK Biotechnology and Biological Sciences Research Council [BB/I025751/1, BB/I025263/1]; UK Medical Research Council Integrative Epidemiology Unit; University of Bristol [MC_UU_12013_1, MC_UU_12013_2, MC_UU_12013_5, MC_UU_12013_8]; United States National Institute of Diabetes and Digestive and Kidney Diseases [R01 DK10324]; Swedish Research Council; Swedish Heart-Lung Foundation; Freemason Child House Foundation in Stockholm; MeDALL (Mechanisms of the Development of ALLergy), within the European Union [261357]; Stockholm County Council (ALF); Swedish Foundation for Strategic Research (SSF) [RBc08-0027]; Strategic Research Programme (SFO) in Epidemiology at Karolinska Institutet; Swedish Research Council Formas; Swedish Environment Protection Agency; Center for Integrative Research on Childhood Leukemia and the Environment [P01ES018172]; NIH [P50ES018172, R01ES09137, 5P30CA082103, P01 ES009605, R01 ES021369, R01ES023067, K01ES017801, R01ES022216, P30ES007048, R01ES014447, P01ES009581, R826708-01, RD831861-01, P50ES026086, R01DK068001, R01 DK100340, R01 DK076648, R01ES022934, R01HL111108, R01NR013945, R37 HD034568, UL1 TR001082, P30 DK56350]; EPA [RD83451101, RD83615901, RD 82670901, RD 83451301, 83615801-0]; UCSF Comprehensive Cancer Center Support grant [P30 CA82103]; Swiss Science National Foundation [P2LAP3_158674]; Sutter-Stottner Foundation; Commission of the European Community, specific RTD Programme 'Quality of Life and Management of Living Resources' within the 5th Framework Programme [QLRT-2001-00389, QLK1-CT-2002-30582]; 6th Framework Programme [007036]; European Union's Seventh Framework Programme (FP7), project EarlyNutrition [289346]; European Research Council Advanced grant ERC-AdG [322605 META-GROWTH]; Autism Speaks grant [260377]; Funds for Research in Respiratory Health; French Ministry of Research: IFR program; INSERM Nutrition Research Program; French Ministry of Health: Perinatality Program; French National Institute for Population Health Surveillance (INVS); Paris-Sud University; French National Institute for Health Education (INPES); Nestle; Mutuelle Generale de l'Education Nationale (MGEN); French-speaking association for the study of diabetes and metabolism (Alfediam) [2012/51290-6]; EU; European Research Council [ERC-2012-StG.310898, 268479-BREATHE]; Flemish Scientific Research Council (FWO) [N1516112 / G.0.873.11N.10]; European Community's Seventh Framework Programme FP7 project EXPOsOMICS [308610]; People Program (Marie Curie Actions) of the European Union's Seventh Framework Program FP7 under REA grant [628858]; Bijzonder Onderzoeksfonds (BOF) Hasselt University; Ministry of the Flemish Community (Department of Economics, Science and Innovation); Ministry of the Flemish Community (Department of Environment, Nature and Energy); CEFIC LRI award by the Research Foundation-Flanders (FWO); CEFIC LRI award by the Research Foundation-Flanders (FWO) [12L5216N]; Flemish Institute for Technological Research (VITO) [12L5216N]; Bill AMP; Melinda Gates Foundation Grand Challenges Exploration grant [OPP119403]; Sandler Family Foundation; American Asthma Foundation; National Institutes of Health; National Heart, Lung and Blood Institute [HL117004]; National Institute of Environmental Health Sciences [ES24844]; National Institute on Minority Health and Health Disparities [MD006902, MD009523]; National Institute of General Medical Sciences [GM007546]; Tobacco-Related Disease Research Program [24RT-0025]; Hutchison Whampoa Ltd, Hong Kong; University of Groningen; Well Baby Clinic Foundation Icare; Noordlease; Youth Health Care Drenthe; Biobanking and Biomolecular Research Infrastructure Netherlands [CP2011-19]; Erasmus Medical Center, Rotterdam; Erasmus University Rotterdam; Netherlands Organization for Health Research and Development; Netherlands Genomics Initiative (NGI)/Netherlands Organization for Scientific Research (NWO); Netherlands Consortium for Healthy Aging (NCHA) [050-060-810]; Genetic Laboratory of the Department of Internal Medicine, Erasmus MC; European Union's Horizon research and innovation programme [733206, 633595]; National Institute of Child and Human Development [R01HD068437]; Netherlands Organization for Health Research and Development [VIDI 016.136.361]; Consolidator grant from the European Research Council [ERC-2014-CoG-648916]; Netherlands' Organization for Scientific Research (NWO VICI); European Research Council ERC; Netherlands' Organization for Scientific Research (NWO Spinoza Award); Gravitation program of the Dutch Ministry of Education, Culture, and Science; Netherlands Organization for Scientific Research (NWO) [024.001.003]; Lung Foundation Netherlands [3.2.12.089]; Fonds de Recherche du Quebec en Sante (FRQ-S) [20697]; Canadian Institute of Health Reseach (CIHR) [MOP 115071]; Diabete Quebec grant; Canadian Diabetes Association operating grant [OG-3-08-2622]; American Diabetes Association Pathways Accelerator Early Investigator Award [1-15-ACE-26]; MRC Integrative Epidemiology Unit - Medical Research Council [MC_UU_12013/1-9]; National Institute of Environmental Health Sciences, National Institutes of Health [K99ES025817]; Instituto de Salud Carlos III [Red INMA G03/176, CB06/02/0041]; Spanish Ministry of Health [FIS-PI04/1436, FIS-PI08/1151]; Spanish Ministry of Health (FEDER funds) [FIS-PI11/00610, FIS-FEDER-PI06/0867, FIS-FEDER-PI03-1615]; Generalitat de Catalunya [CIRIT 1999SGR 00241]; Fundacio La Marato de TV3 [090430]; EU Commission [261357-MeDALL]; National Institute of Allergy and Infectious Diseases [N01-AI90052]; National Institutes of Health USA [R01 HL082925, R01 HL132321]; Asthma UK [364]; NIAID/NIH [R01AI091905, R01AI121226]; National Institute of Health [R01AI121226, R01 AI091905, R01HL132321]; NIH/NIEHS [N01-ES75558]; NIH/NINDS [1 UO1 NS 047537-01, 2 UO1 NS 047537-06A1]; Intramural Research Program of the NIH, National Institute of Environmental Health Sciences [Z01-ES-49019, Z01 ES044005, ES049033, ES049032]; Norwegian Research Council/BIOBANK [221097]; Oslo University Hospital; Unger-Vetlesens foundation; Norwegian American Womens Club; INCA/Plan Cancer-EVA-INSERM, France; International Childhood Cancer Cohort Consortium (I4C); INCA/Plan Cancer-EVA-INSERM (France); IARC Postdoctoral Fellowship; EC FP7 Marie Curie Actions-People-Co-funding of regional, national and international programmes (COFUND); NIEHS [R21ES014947, R01ES016772]; NIDDK [R01DK085173]; National Institute of Environmental Health Science [P30 ES025128]; University of Oulu grant [65354]; Oulu University Hospital [2/97, 8/97]; Ministry of Health and Social Affairs [23/251/97, 160/97, 190/97]; National Institute for Health and Welfare, Helsinki [54121]; Regional Institute of Occupational Health, Oulu, Finland [50621, 54231]; EU [QLG1-CT-2000-01643, E51560]; NorFA grant [731, 20056, 30167]; Academy of Finland; NIH-NIEHS [P01 ES022832]; US EPA [RD83544201]; NIH-NIGMS [P20GM104416]; NCI [R25CA134286]; Netherlands Organization for Scientific Research and Development; Netherlands Asthma Fund; Netherlands Ministry of Spatial Planning, Housing, and the Environment; Netherlands Ministry of Health, Welfare, and Sport; MeDALL; European Union under the Health Cooperation Work Program of the 7th Framework program [261357]; Italian National Centre for Disease Prevention and Control (CCM grant); Italian Ministry of Health (art 12); Italian Ministry of Health (12bis Dl.gs.vo) [502/92]; EraNet; EVO; University of Helsinki Research Funds; Signe and Ane Gyllenberg foundation; Emil Aaltonen Foundation; Finnish Medical Foundation; Jane and Aatos Erkko Foundation; Novo Nordisk Foundation; Paivikki and Sakari Sohlberg Foundation; Sigrid Juselius Foundation; University of Helsinki; University of Western Australia (UWA); Curtin University; Raine Medical Research Foundation; UWA Faculty of Medicine, Dentistry and Health Sciences; Telethon Kids Institute; Women's and Infant's Research Foundation (KEMH); Edith Cowan University; National Health and Medical Research Council [1059711]; National Health and Medical Research Council (NHMRC) fellowship [1053384]; Australian National Health and Medical Research Council; United States National Institute of Health; Greek Ministry of Health (programme of prevention of obesity and neurodevelopmental disorders in preschool children, in Heraklion district, Crete, Greece); Greek Ministry of Health ('Rhea Plus': Primary Prevention Program of Environmental Risk Factors for Reproductive Health, and Child Health); European Union (EU) [EU FP6-2003-Food-3-NewGeneris, EU FP7 ENV.2007.1.2.2.2, 211250 ESCAPE, EU FP7-2008-ENV-1.2.1.4 Envirogenomarkers, EU FP7 ENV.2008.1.2.1.6, 226285 ENRIECO]; National Institutes of Health [NIH-NIMH R01MH094609, NIH-NIEHS R01ES022223, NIH-NIEHS R01ES025145]; Centers for Disease Control and Prevention [U10DD000180, U10DD000181, U10DD000182, U10DD000183, U10DD000184, U10DD000498]; Autism Speaks [7659]; Swedish Research Council through the Swedish Initiative for research on Microdata in the Social And Medical Sciences (SIMSAM) [340-2013-5867]; Stockholm County Council (ALF projects); Strategic Research Program in Epidemiology at Karolinska Institutet; Swedish Asthma and Allergy Association's Research Foundation; Stiftelsen Frimurare Barnahuset Stockholm; Norwegian Ministry of Health and Care Services; Ministry of the Flemish Community (Flemish Agency for Care and Health); University of Bristol; Ministry of Education and Research; European Union (EU) (EU FP7-HEALTH-single stage CHICOS); European Union (EU) (EU-FP7-HEALTH) [308333 HELIX]; European Union (EU) (EU FP6. STREP HiWATE); [R01ES017646]; [R01ES01900]; [R01ES16443]; [USA / NIHH 2000 G DF682]; [50945]; [R01 HL095606]; [R01 HL1143396]
Published: 2018

28. A prospective study of fetal head growth, autistic traits and autism spectrum disorder

Author: Blanken, LME, Dass, A, Alvares, G, van der Ende, J, Schoemaker, NK, El Marroun, H, Hickey, M, Pennell, C, White, S, Maybery, MT, Dissanayake, C, Jaddoe, VWV, Verhulst, FC, Tiemeier, H, McIntosh, W, White, T, Whitehouse, A, Blanken, LME, Dass, A, Alvares, G, van der Ende, J, Schoemaker, NK, El Marroun, H, Hickey, M, Pennell, C, White, S, Maybery, MT, Dissanayake, C, Jaddoe, VWV, Verhulst, FC, Tiemeier, H, McIntosh, W, White, T, and Whitehouse, A
Published: 2018

29. A genome-wide association study of corneal astigmatism: The CREAM Consortium

Author: Shah, RL, Li, Q, Zhao, W, Tedja, MS, Tideman, JWL, Khawaja, AP, Fan, Q, Yazar, S, Williams, KM, Verhoeven, VJM, Xie, J, Wang, YX, Hess, M, Nickels, S, Lackner, KJ, Parssinen, O, Wedenoja, J, Biino, G, Concas, MP, Uitterlinden, A, Rivadeneira, F, Jaddoe, VWV, Hysi, PG, Sim, X, Tan, N, Tham, Y-C, Sensaki, S, Hofman, A, Vingerling, JR, Jonas, JB, Mitchell, P, Hammond, CJ, Hoehn, R, Baird, PN, Wong, T-Y, Cheng, C-Y, Teo, YY, Mackey, DA, Williams, C, Saw, S-M, Klaver, CCW, Guggenheim, JA, Bailey-Wilson, JE, Shah, RL, Li, Q, Zhao, W, Tedja, MS, Tideman, JWL, Khawaja, AP, Fan, Q, Yazar, S, Williams, KM, Verhoeven, VJM, Xie, J, Wang, YX, Hess, M, Nickels, S, Lackner, KJ, Parssinen, O, Wedenoja, J, Biino, G, Concas, MP, Uitterlinden, A, Rivadeneira, F, Jaddoe, VWV, Hysi, PG, Sim, X, Tan, N, Tham, Y-C, Sensaki, S, Hofman, A, Vingerling, JR, Jonas, JB, Mitchell, P, Hammond, CJ, Hoehn, R, Baird, PN, Wong, T-Y, Cheng, C-Y, Teo, YY, Mackey, DA, Williams, C, Saw, S-M, Klaver, CCW, Guggenheim, JA, and Bailey-Wilson, JE
Abstract: PURPOSE: To identify genes and genetic markers associated with corneal astigmatism. METHODS: A meta-analysis of genome-wide association studies (GWASs) of corneal astigmatism undertaken for 14 European ancestry (n=22,250) and 8 Asian ancestry (n=9,120) cohorts was performed by the Consortium for Refractive Error and Myopia. Cases were defined as having >0.75 diopters of corneal astigmatism. Subsequent gene-based and gene-set analyses of the meta-analyzed results of European ancestry cohorts were performed using VEGAS2 and MAGMA software. Additionally, estimates of single nucleotide polymorphism (SNP)-based heritability for corneal and refractive astigmatism and the spherical equivalent were calculated for Europeans using LD score regression. RESULTS: The meta-analysis of all cohorts identified a genome-wide significant locus near the platelet-derived growth factor receptor alpha (PDGFRA) gene: top SNP: rs7673984, odds ratio=1.12 (95% CI:1.08-1.16), p=5.55×10-9. No other genome-wide significant loci were identified in the combined analysis or European/Asian ancestry-specific analyses. Gene-based analysis identified three novel candidate genes for corneal astigmatism in Europeans-claudin-7 (CLDN7), acid phosphatase 2, lysosomal (ACP2), and TNF alpha-induced protein 8 like 3 (TNFAIP8L3). CONCLUSIONS: In addition to replicating a previously identified genome-wide significant locus for corneal astigmatism near the PDGFRA gene, gene-based analysis identified three novel candidate genes, CLDN7, ACP2, and TNFAIP8L3, that warrant further investigation to understand their role in the pathogenesis of corneal astigmatism. The much lower number of genetic variants and genes demonstrating an association with corneal astigmatism compared to published spherical equivalent GWAS analyses suggest a greater influence of rare genetic variants, non-additive genetic effects, or environmental factors in the development of astigmatism.
Published: 2018

30. Gestational hypertensive disorders and retinal microvasculature: the Generation R Study.

Author: Benschop, L, Schalekamp-Timmermans, S, Roeters van Lennep, JE, Jaddoe, VWV, Wong, TY, Cheung, CY, Steegers, EAP, Ikram, MK, Benschop, L, Schalekamp-Timmermans, S, Roeters van Lennep, JE, Jaddoe, VWV, Wong, TY, Cheung, CY, Steegers, EAP, and Ikram, MK
Abstract: BACKGROUND: Changes in the microvasculature associated with pre-eclampsia and gestational hypertension have been proposed as a potential pathway in the development of cardiovascular disease. We examined whether gestational hypertensive disorders, such as pre-eclampsia and gestational hypertension, are related to the maternal retinal microvasculature status after pregnancy. METHODS: This study is part of an ongoing population-based prospective cohort study. During pregnancy and 6.2 years after the index pregnancy (90% range 5.7-7.4 years), we examined 3391 women with available information on pre-eclampsia, gestational hypertension, and retinal vascular calibers. Retinal arteriolar and venular calibers were measured in the left eye from digitized retinal photographs. RESULTS: Women with pre-eclampsia had smaller retinal arteriolar calibers 6 years after pregnancy than women with a normotensive pregnancy (adjusted difference: -0.40 standard deviation score [SDS]; 95% confidence interval [CI]: -0.62, -0.19). For women with previous gestational hypertension, similar trends were observed (-0.20 SDS; 95% CI: -0.34, -0.05). With respect to retinal venular calibers, we did not observe consistent trends for women with previous pre-eclampsia. However, in women with previous gestational hypertension, we observed larger venular calibers (0.22 SDS; 95% CI: 0.07-0.36) than in women with a previous normotensive pregnancy. The association of gestational hypertensive disorders with retinal vessel calibers was mediated through mean arterial pressure at the time of retinal imaging. CONCLUSIONS: Compared to women with a previous normotensive pregnancy, women with pre-eclampsia and gestational hypertension show an altered status of the microvasculature 6 years after the index pregnancy. This is reflected by smaller retinal arteriolar calibers and wider retinal venular calibers. These microvascular changes may possibly contribute to the development of cardiovascular disease in later life.
Published: 2017

31. Correction to: Gestational hypertensive disorders and retinal microvasculature: the Generation R Study.

Author: Benschop, L, Schalekamp-Timmermans, S, Roeters van Lennep, JE, Jaddoe, VWV, Wong, TY, Cheung, CY, Steegers, EAP, Ikram, MK, Benschop, L, Schalekamp-Timmermans, S, Roeters van Lennep, JE, Jaddoe, VWV, Wong, TY, Cheung, CY, Steegers, EAP, and Ikram, MK
Published: 2017

32. Bivariate genome-wide association meta-analysis of pediatric musculoskeletal traits reveals pleiotropic effects at the SREBF1/TOM1L2 locus

Author: Medina-Gomez, C, Kemp, JP, Dimou, NL, Kreiner, E, Chesi, A, Zemel, BS, Bonnelykke, K, Boer, CG, Ahluwalia, TS, Bisgaard, H, Evangelou, E, Heppe, DHM, Bonewald, LF, Gorski, JP, Ghanbari, M, Demissie, S, Duque, G, Maurano, MT, Kiel, DP, Hsu, Y-H, van der Eerden, BCJ, Ackert-Bicknell, C, Reppe, S, Gautvik, KM, Raastad, T, Karasik, D, van de Peppel, J, Jaddoe, VWV, Uitterlinden, AG, Tobias, JH, Grant, SFA, Bagos, PG, Evans, DM, Rivadeneira, F, Medina-Gomez, C, Kemp, JP, Dimou, NL, Kreiner, E, Chesi, A, Zemel, BS, Bonnelykke, K, Boer, CG, Ahluwalia, TS, Bisgaard, H, Evangelou, E, Heppe, DHM, Bonewald, LF, Gorski, JP, Ghanbari, M, Demissie, S, Duque, G, Maurano, MT, Kiel, DP, Hsu, Y-H, van der Eerden, BCJ, Ackert-Bicknell, C, Reppe, S, Gautvik, KM, Raastad, T, Karasik, D, van de Peppel, J, Jaddoe, VWV, Uitterlinden, AG, Tobias, JH, Grant, SFA, Bagos, PG, Evans, DM, and Rivadeneira, F
Abstract: Bone mineral density is known to be a heritable, polygenic trait whereas genetic variants contributing to lean mass variation remain largely unknown. We estimated the shared SNP heritability and performed a bivariate GWAS meta-analysis of total-body lean mass (TB-LM) and total-body less head bone mineral density (TBLH-BMD) regions in 10,414 children. The estimated SNP heritability is 43% (95% CI: 34-52%) for TBLH-BMD, and 39% (95% CI: 30-48%) for TB-LM, with a shared genetic component of 43% (95% CI: 29-56%). We identify variants with pleiotropic effects in eight loci, including seven established bone mineral density loci: WNT4, GALNT3, MEPE, CPED1/WNT16, TNFSF11, RIN3, and PPP6R3/LRP5. Variants in the TOM1L2/SREBF1 locus exert opposing effects TB-LM and TBLH-BMD, and have a stronger association with the former trait. We show that SREBF1 is expressed in murine and human osteoblasts, as well as in human muscle tissue. This is the first bivariate GWAS meta-analysis to demonstrate genetic factors with pleiotropic effects on bone mineral density and lean mass.Bone mineral density and lean skeletal mass are heritable traits. Here, Medina-Gomez and colleagues perform bivariate GWAS analyses of total body lean mass and bone mass density in children, and show genetic loci with pleiotropic effects on both traits.
Published: 2017

33. Genetic Basis for Gestation Length

Author: Pennell, CE, Warrington, NM, Mook-Kanamori, D, Lye, SJ, Newnham, JP, Palmer, LJ, Jaddoe, VWV, Freathy, RM, Jacobssen, B, Holloway, J, McCarthy, MI, Frayling, TM, Consortium, PGP, and Consortium, EGG
Published: 2016

34. The influence of maternal obesity on the long-term health of the offspring

Author: Godfrey, KM, Reynolds, RM, Prescott, SL, Nyirenda, M, Jaddoe, VWV, Eriksson, JG, Broekman, BFP, and Psychiatry
Abstract: In addition to immediate implications for pregnancy complications, increasing evidence implicates maternal obesity as a major determinant of off spring health during childhood and later adult life. Observational studies provide evidence for eff ects of maternal obesity on her off spring's risks of obesity, coronary heart disease, stroke, type 2 diabetes, and asthma. Maternal obesity could also lead to poorer cognitive performance and increased risk of neurodevelopmental disorders, including cerebral palsy. Preliminary evidence suggests potential implications for immune and infectious-disease-related outcomes. Insights from experimental studies support causal eff ects of maternal obesity on off spring outcomes, which are mediated at least partly through changes in epigenetic processes, such as alterations in DNA methylation, and perhaps through alterations in the gut microbiome. Although the off spring of obese women who lose weight before pregnancy have a reduced risk of obesity, few controlled intervention studies have been done in which maternal obesity is reversed and the consequences for off spring have been examined. Because the long-term eff ects of maternal obesity could have profound public health implications, there is an urgent need for studies on causality, underlying mechanisms, and eff ective interventions to reverse the epidemic of obesity in women of childbearing age and to mitigate consequences for off spring.
Published: 2016

35. Multi-ancestry genome-wide association study of 21,000 cases and 95,000 controls identifies new risk loci for atopic dermatitis

Author: Paternoster, L, Standl, M, Waage, J, Baurecht, H, Hotze, M, Strachan, DP, Curtin, JA, Bonnelykke, K, Tian, C, Takahashi, A, Esparza-Gordillo, J, Alves, AC, Thyssen, JP, den Dekker, HT, Ferreira, MA, Altmaier, E, Sleiman, PMA, Xiao, FL, Gonzalez, JR, Marenholz, I, Kalb, B, Pino-Yanes, M, Xu, C-J, Carstensen, L, Groen-Blokhuis, MM, Venturini, C, Pennell, CE, Barton, SJ, Levin, AM, Curjuric, I, Bustamante, M, Kreiner-Moller, E, Lockett, GA, Bacelis, J, Bunyavanich, S, Myers, RA, Matanovic, A, Kumar, A, Tung, JY, Hirota, T, Kubo, M, McArdle, WL, Henderson, AJ, Kemp, JP, Zheng, J, Smith, GD, Rueschendorf, F, Bauerfeind, A, Lee-Kirsch, MA, Arnold, A, Homuth, G, Schmidt, CO, Mangold, E, Cichon, S, Keil, T, Rodriguez, E, Peters, A, Franke, A, Lieb, W, Novak, N, Foelster-Holst, R, Horikoshi, M, Pekkanen, J, Sebert, S, Husemoen, LL, Grarup, N, De Jongste, JC, Rivadeneira, F, Hofman, A, Jaddoe, VWV, Pasmans, SGMA, Elbert, NJ, Uitterlinden, AG, Marks, GB, Thompson, PJ, Matheson, MC, Robertson, CF, Ried, JS, Li, J, Zuo, XB, Zheng, XD, Yin, XY, Sun, LD, McAleer, MA, O'Regan, GM, Fahy, CMR, Campbell, LE, Macek, M, Kurek, M, Hu, D, Eng, C, Postma, DS, Feenstra, B, Geller, F, Hottenga, JJ, Middeldorp, CM, Hysi, P, Bataille, V, Spector, T, Tiesler, CMT, Thiering, E, Pahukasahasram, B, Yang, JJ, Imboden, M, Huntsman, S, Vilor-Tejedor, N, Relton, CL, Myhre, R, Nystad, W, Custovic, A, Weiss, ST, Meyers, DA, Soederhaell, C, Melen, E, Ober, C, Raby, BA, Simpson, A, Jacobsson, B, Holloway, JW, Bisgaard, H, Sunyer, J, Probst-Hensch, NM, Williams, LK, Godfrey, KM, Wang, CA, Boomsma, DI, Melbye, M, Koppelman, GH, Jarvis, D, McLean, WHI, Irvine, AD, Zhang, XJ, Hakonarson, H, Gieger-, C, Burchard, EG, Martin, NG, Duijts, L, Linneberg, A, Jarvelin, M-R, Noethen, MM, Lau, S, Huebner, N, Lee, Y-A, Tamari, M, Hinds, DA, Glass, D, Brown, SJ, Heinrich, J, Evans, DM, Weidinger, S, AAGC, AAGC, and Epidemio, EGL
Abstract: Genetic association studies have identified 21 loci associated with atopic dermatitis risk predominantly in populations of European ancestry. To identify further susceptibility loci for this common, complex skin disease, we performed a meta-analysis of >15 million genetic variants in 21,399 cases and 95,464 controls from populations of European, African, Japanese and Latino ancestry, followed by replication in 32,059 cases and 228,628 controls from 18 studies. We identified ten new risk loci, bringing the total number of known atopic dermatitis risk loci to 31 (with new secondary signals at four of these loci). Notably, the new loci include candidate genes with roles in the regulation of innate host defenses and T cell function, underscoring the important contribution of (auto)immune mechanisms to atopic dermatitis pathogenesis.
Published: 2015

36. Influence of fetal blood flow redistribution on fetal and childhood growth and fat distribution: the Generation R Study

Author: Kooijman, MN, primary, Gaillard, R, additional, Reiss, IKM, additional, Hofman, A, additional, Steegers, EAP, additional, and Jaddoe, VWV, additional
Published: 2016
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37. Associations of maternal prepregnancy body mass index and gestational weight gain with cardio-metabolic risk factors in adolescent offspring: a prospective cohort study

Author: Gaillard, R, primary, Welten, M, additional, Oddy, WH, additional, Beilin, LJ, additional, Mori, TA, additional, Jaddoe, VWV, additional, and Huang, R-C, additional
Published: 2015
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38. Fetal sex dependency of maternal vascular adaptation to pregnancy: a prospective population‐based cohort study

Author: Broere‐Brown, ZA, primary, Schalekamp‐Timmermans, S, additional, Hofman, A, additional, Jaddoe, VWV, additional, and Steegers, EAP, additional
Published: 2015
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39. Variants in ADCY5 and near CCNL1 are associated with fetal growth and birth weight

Author: James F. Wilson, Leena Peltonen, Ida Surakka, D S Postma, Albert Hofman, Jouke-Jan Hottenga, Johan G. Eriksson, Ulla Sovio, Dennis O. Mook-Kanamori, Joachim Heinrich, Beverley M. Shields, Nicholas J. Timpson, George Dedoussis, A. H. Wijga, Paul F. O'Reilly, Chen C-M., Hong Xiang Zhang, Jarvelin M-R., Marika Kaakinen, Nabila Bouatia-Naji, Chris Power, Paul Elliott, A Pouta, Jonathan P. Bradfield, Andrew T. Hattersley, Marjan Kerkhof, Inga Prokopenko, Fernando Rivadeneira, Steegers Eap., Linda S. Adair, Jaddoe Vwv., Craig E. Pennell, Philippe Froguel, Panagiotis Deloukas, Dorret I. Boomsma, Anja Taanila, Hartikainen A-L., Julie A. Marsh, Holly Jmp., Nicole M. Warrington, Mirna Kirin, Bridget A. Knight, Rachel M. Freathy, Gonneke Willemsen, E. Widen, Timothy M. Frayling, André G. Uitterlinden, Gerard H. Koppelman, Diana L. Cousminer, Judith B. Borja, de Geus Ejc., Adaikalavan Ramasamy, Amanda J. Bennett, Jianhua Zhao, Matthew W. Gillman, Mark I. McCarthy, Cecilia M. Lindgren, Karen L. Mohlke, Coin Ljm., Joel N. Hirschhorn, Nigel W. Rayner, Y S Aulchenko, Carla M. T. Tiesler, Christopher J. Groves, Susan M. Ring, Lyle J. Palmer, G. Davey Smith, C.M. van Duijn, Beate Glaser, Wendy L. McArdle, J. Laitinen, Reedik Mägi, Hakon Hakonarson, David M. Evans, David P. Strachan, Diane J. Berry, Grant Sfa., Neelam Hassanali, Leslie A. Lange, Pimphen Charoen, Helen N. Lyon, Stavroula Kanoni, Elina Hyppönen, Faculteit Medische Wetenschappen/UMCG, Groningen Research Institute for Asthma and COPD (GRIAC), Freathy, Rachel M, Mook-Kanamori, Dennis O, Sovio, Ulla, Prokopenko, Inga, Hypponen, Elina, McCarthy, Mark I, Biological Psychology, EMGO+ - Mental Health, Erasmus MC other, Epidemiology, Gastroenterology & Hepatology, Internal Medicine, Obstetrics & Gynecology, Public Health, and Medical Research Council (MRC)
Subjects: Netherlands Twin Register (NTR), Male, Genome-wide association study, Type 2 diabetes, Cohort Studies, 0302 clinical medicine, Pregnancy, Ethnicity, Birth Weight, GESTATIONAL-AGE, Genetics & Heredity, 0303 health sciences, Gestational age, 11 Medical And Health Sciences, 3. Good health, Isoenzymes, HEAD CIRCUMFERENCE, Wellcome Trust Case Control Consortium, Female, Life Sciences & Biomedicine, Adenylyl Cyclases, Adenylate Cyclase, EXPRESSION, medicine.medical_specialty, Genotype, Genetic Investigation of ANthropometric Traits (GIANT) Consortium, Birth weight, Ethnic Groups, 030209 endocrinology & metabolism, Single-nucleotide polymorphism, ISOFORMS, Biology, Article, 03 medical and health sciences, SDG 3 - Good Health and Well-being, Early Growth Genetics (EGG) Consortium, Internal medicine, Diabetes mellitus, Cyclins, Genetics, medicine, Humans, Genetic Predisposition to Disease, COHORT, GENOME-WIDE ASSOCIATION, Alleles, METAANALYSIS, 030304 developmental biology, Fetus, Science & Technology, Models, Genetic, ADENYLYL-CYCLASE, 06 Biological Sciences, medicine.disease, GENE, Endocrinology, Glucose, Diabetes Mellitus, Type 2, Meta-Analyses of Glucose and Insulin-related traits Consortium, TYPE-2 DIABETES RISK, Developmental Biology
Abstract: To identify genetic variants associated with birth weight, we meta-analyzed six genome-wide association (GWA) studies (n = 10,623 Europeans from pregnancy/birth cohorts) and followed up two lead signals in 13 replication studies (n = 27,591). rs900400 near LEKR1 and CCNL1 (P = 2 × 10 35) and rs9883204 in ADCY5 (P = 7 × 10 15) were robustly associated with birth weight. Correlated SNPs in ADCY5 were recently implicated in regulation of glucose levels and susceptibility to type 2 diabetes, providing evidence that the well-described association between lower birth weight and subsequent type 2 diabetes has a genetic component, distinct from the proposed role of programming by maternal nutrition. Using data from both SNPs, we found that the 9% of Europeans carrying four birth weight-lowering alleles were, on average, 113g (95% CI 89-137g) lighter at birth than the 24% with zero or one alleles (P trend = 7 × 10 30). The impact on birth weight is similar to that of a mother smoking 4-5 cigarettes per day in the third trimester of pregnancy. © 2010 Nature America, Inc. All rights reserved.
Published: 2010

40. O-214 Growth Trajectories And Bone Mineral Density In Children With Subclinical Celiac Disease: The Generation R Study

Author: Jansen, MAE, primary, Kiefte-de Jong, JC, additional, Gaillard, R, additional, Escher, JC, additional, Hofman, A, additional, Jaddoe, VWV, additional, Hooijkaas, H, additional, and Moll, HA, additional
Published: 2014
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41. O-172 Infant Feeding And Anti-tissue Transglutaminase Antibody Levels In Children With Subclinical Celiac Disease: The Generation R Study

Author: Tromp, IIM, primary, Jansen, MAE, additional, Kiefte-de Jong, JC, additional, Jaddoe, VWV, additional, Hofman, A, additional, Escher, JC, additional, Hooijkaas, H, additional, and Moll, HA, additional
Published: 2014
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42. Maternal haemoglobin levels and cardio-metabolic risk factors in childhood: the Generation R Study

Author: Welten, M, primary, Gaillard, R, additional, Hofman, A, additional, de Jonge, LL, additional, and Jaddoe, VWV, additional
Published: 2014
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43. Meta-analysis of genome-wide association studies identifies three new risk loci for atopic dermatitis

Author: Paternoster, L, Standl, M, Chen, C-M, Ramasamy, A, Bonnelykke, K, Duijts, L, Ferreira, MA, Alves, AC, Thyssen, JP, Albrecht, E, Baurecht, H, Feenstra, B, Sleiman, PMA, Hysi, P, Warrington, NM, Curjuric, I, Myhre, R, Curtin, JA, Groen-Blokhuis, MM, Kerkhof, M, Saaf, A, Franke, A, Ellinghaus, D, Foelster-Holst, R, Dermitzakis, E, Montgomery, SB, Prokisch, H, Heim, K, Hartikainen, A-L, Pouta, A, Pekkanen, J, Blakemore, AIF, Buxton, JL, Kaakinen, M, Duffy, DL, Madden, PA, Heath, AC, Montgomery, GW, Thompson, PJ, Matheson, MC, Le Souef, P, St Pourcain, B, Smith, GD, Henderson, J, Kemp, JP, Timpson, NJ, Deloukas, P, Ring, SM, Wichmann, H-E, Mueller-Nurasyid, M, Novak, N, Klopp, N, Rodriguez, E, McArdle, W, Linneberg, A, Menne, T, Nohr, EA, Hofman, A, Uitterlinden, AG, van Duijin, CM, Rivadeneira, F, de Jongste, JC, van der Valk, RJP, Wjst, M, Jogi, R, Geller, F, Boyd, HA, Murray, JC, Kim, C, Mentch, F, March, M, Mangino, M, Spector, TD, Bataille, V, Pennell, CE, Holt, PG, Sly, P, Tiesler, CMT, Thiering, E, Illig, T, Imboden, M, Nystad, W, Simpson, A, Hottenga, J-J, Postma, D, Koppelman, GH, Smit, HA, Soderhall, C, Chawes, B, Kreiner-Moller, E, Bisgaard, H, Melen, E, Boomsma, DI, Custovic, A, Jacobsson, B, Probst-Hensch, NM, Palmer, LJ, Glass, D, Hakonarson, H, Melbye, M, Jarvis, DL, Jaddoe, VWV, Gieger, C, Strachan, DP, Martin, NG, Jarvelin, M-R, Heinrich, J, Evans, DM, Weidinger, S, Paternoster, L, Standl, M, Chen, C-M, Ramasamy, A, Bonnelykke, K, Duijts, L, Ferreira, MA, Alves, AC, Thyssen, JP, Albrecht, E, Baurecht, H, Feenstra, B, Sleiman, PMA, Hysi, P, Warrington, NM, Curjuric, I, Myhre, R, Curtin, JA, Groen-Blokhuis, MM, Kerkhof, M, Saaf, A, Franke, A, Ellinghaus, D, Foelster-Holst, R, Dermitzakis, E, Montgomery, SB, Prokisch, H, Heim, K, Hartikainen, A-L, Pouta, A, Pekkanen, J, Blakemore, AIF, Buxton, JL, Kaakinen, M, Duffy, DL, Madden, PA, Heath, AC, Montgomery, GW, Thompson, PJ, Matheson, MC, Le Souef, P, St Pourcain, B, Smith, GD, Henderson, J, Kemp, JP, Timpson, NJ, Deloukas, P, Ring, SM, Wichmann, H-E, Mueller-Nurasyid, M, Novak, N, Klopp, N, Rodriguez, E, McArdle, W, Linneberg, A, Menne, T, Nohr, EA, Hofman, A, Uitterlinden, AG, van Duijin, CM, Rivadeneira, F, de Jongste, JC, van der Valk, RJP, Wjst, M, Jogi, R, Geller, F, Boyd, HA, Murray, JC, Kim, C, Mentch, F, March, M, Mangino, M, Spector, TD, Bataille, V, Pennell, CE, Holt, PG, Sly, P, Tiesler, CMT, Thiering, E, Illig, T, Imboden, M, Nystad, W, Simpson, A, Hottenga, J-J, Postma, D, Koppelman, GH, Smit, HA, Soderhall, C, Chawes, B, Kreiner-Moller, E, Bisgaard, H, Melen, E, Boomsma, DI, Custovic, A, Jacobsson, B, Probst-Hensch, NM, Palmer, LJ, Glass, D, Hakonarson, H, Melbye, M, Jarvis, DL, Jaddoe, VWV, Gieger, C, Strachan, DP, Martin, NG, Jarvelin, M-R, Heinrich, J, Evans, DM, and Weidinger, S
Abstract: Atopic dermatitis (AD) is a commonly occurring chronic skin disease with high heritability. Apart from filaggrin (FLG), the genes influencing atopic dermatitis are largely unknown. We conducted a genome-wide association meta-analysis of 5,606 affected individuals and 20,565 controls from 16 population-based cohorts and then examined the ten most strongly associated new susceptibility loci in an additional 5,419 affected individuals and 19,833 controls from 14 studies. Three SNPs reached genome-wide significance in the discovery and replication cohorts combined, including rs479844 upstream of OVOL1 (odds ratio (OR) = 0.88, P = 1.1 × 10(-13)) and rs2164983 near ACTL9 (OR = 1.16, P = 7.1 × 10(-9)), both of which are near genes that have been implicated in epidermal proliferation and differentiation, as well as rs2897442 in KIF3A within the cytokine cluster at 5q31.1 (OR = 1.11, P = 3.8 × 10(-8)). We also replicated association with the FLG locus and with two recently identified association signals at 11q13.5 (rs7927894; P = 0.008) and 20q13.33 (rs6010620; P = 0.002). Our results underline the importance of both epidermal barrier function and immune dysregulation in atopic dermatitis pathogenesis.
Published: 2012

44. Genetic variation in the 15q25 nicotinic acetylcholine receptor gene cluster (CHRNA5- CHRNA3-CHRNB4) interacts with maternal selfreported smoking status during pregnancy to influence birth weight

Author: Tyrrell, J, Huikari, V, Christie, JT, Cavadino, A, Bakker, R, Brion, MJA, Geller, F, Paternoster, L, Myhre, R, Potter, C, Johnson, PCD, Ebrahim, S, Feenstra, B, Hartikainen, AL, Hattersley, AT, Hofman, A, Kaakinen, M, Lowe, LP, Magnus, P, McConnachie, A, Melbye, M, Ng, JWY, Nohr, EA, Power, C, Ring, SM, Sebert, SP, Sengpiel, V, Taal, HR, Watt, GCM, Sattar, N, Relton, CL, Jacobsson, B, Frayling, TM, Sørensen, TIA, Murray, JC, Lawlor, DA, Pennell, CE, Jaddoe, VWV, Hypponen, E, Lowe, WL, Jarvelin, MR, Smith, GD, Freathy, RM, Tyrrell, J, Huikari, V, Christie, JT, Cavadino, A, Bakker, R, Brion, MJA, Geller, F, Paternoster, L, Myhre, R, Potter, C, Johnson, PCD, Ebrahim, S, Feenstra, B, Hartikainen, AL, Hattersley, AT, Hofman, A, Kaakinen, M, Lowe, LP, Magnus, P, McConnachie, A, Melbye, M, Ng, JWY, Nohr, EA, Power, C, Ring, SM, Sebert, SP, Sengpiel, V, Taal, HR, Watt, GCM, Sattar, N, Relton, CL, Jacobsson, B, Frayling, TM, Sørensen, TIA, Murray, JC, Lawlor, DA, Pennell, CE, Jaddoe, VWV, Hypponen, E, Lowe, WL, Jarvelin, MR, Smith, GD, and Freathy, RM
Abstract: Maternal smoking during pregnancy is associated with low birth weight. Common variation at rs1051730 is robustly associated with smoking quantity and was recently shown to influence smoking cessation during pregnancy, but its influence on birth weight is not clear. We aimed to investigate the association between this variant and birth weight of term, singleton offspring in a well-powered meta-analysis. We stratified 26 241 European origin study participants by smoking status (women who smoked during pregnancy versus women who did not smoke during pregnancy) and, in each stratum, analysed the association between maternal rs1051730 genotype and offspring birth weight. There was evidence of interaction between genotype and smoking (P 5 0.007). In women who smoked during pregnancy, each additional smoking-related T-allele was associated with a 20 g [95% confidence interval (95% CI): 4-36 g] lower birth weight (P 5 0.014). However, in women who did not smoke during pregnancy, the effect size estimate was 5 g per T-allele (95% CI: 24 to 14 g; P 5 0.268). To conclude, smoking status during pregnancy modifies the association between maternal rs1051730 genotype and offspring birth weight. This strengthens the evidence that smoking during pregnancy is causally related to lower offspring birth weight and suggests that population interventions that effectively reduce smoking in pregnant women would result in a reduced prevalence of low birth weight. © The Author 2012. Published by Oxford University Press. All rights reserved.
Published: 2012

45. Variants in ADCY5 and near CCNL1 are associated with fetal growth and birth weight

Author: Freathy, RM, Mook-Kanamori, DO, Sovio, U, Prokopenko, I, Timpson, NJ, Berry, DJ, Warrington, NM, Widen, E, Hottenga, JJ, Kaakinen, M, Lange, LA, Bradfield, JP, Kerkhof, M, Marsh, JA, Maegi, R, Chen, C-M, Lyon, HN, Kirin, M, Adair, LS, Aulchenko, YS, Bennett, AJ, Borja, JB, Bouatia-Naji, N, Charoen, P, Coin, LJM, Cousminer, DL, de Geus, EJC, Deloukas, P, Elliott, P, Evans, DM, Froguel, P, Glaser, B, Groves, CJ, Hartikainen, A-L, Hassanali, N, Hirschhorn, JN, Hofman, A, Holly, JMP, Hyppoenen, E, Kanoni, S, Knight, BA, Laitinen, J, Lindgren, CM, McArdle, WL, O'Reilly, PF, Pennell, CE, Postma, DS, Pouta, A, Ramasamy, A, Rayner, NW, Ring, SM, Rivadeneira, F, Shields, BM, Strachan, DP, Surakka, I, Taanila, A, Tiesler, C, Uitterlinden, AG, van Duijn, CM, Wijga, AH, Willemsen, G, Zhang, H, Zhao, J, Wilson, JF, Steegers, EAP, Hattersley, AT, Eriksson, JG, Peltonen, L, Mohlke, KL, Grant, SFA, Hakonarson, H, Koppelman, GH, Dedoussis, GV, Heinrich, J, Gillman, MW, Palmer, LJ, Frayling, TM, Boomsma, DI, Smith, GD, Power, C, Jaddoe, VWV, Jarvelin, M-R, McCarthy, MI, Freathy, RM, Mook-Kanamori, DO, Sovio, U, Prokopenko, I, Timpson, NJ, Berry, DJ, Warrington, NM, Widen, E, Hottenga, JJ, Kaakinen, M, Lange, LA, Bradfield, JP, Kerkhof, M, Marsh, JA, Maegi, R, Chen, C-M, Lyon, HN, Kirin, M, Adair, LS, Aulchenko, YS, Bennett, AJ, Borja, JB, Bouatia-Naji, N, Charoen, P, Coin, LJM, Cousminer, DL, de Geus, EJC, Deloukas, P, Elliott, P, Evans, DM, Froguel, P, Glaser, B, Groves, CJ, Hartikainen, A-L, Hassanali, N, Hirschhorn, JN, Hofman, A, Holly, JMP, Hyppoenen, E, Kanoni, S, Knight, BA, Laitinen, J, Lindgren, CM, McArdle, WL, O'Reilly, PF, Pennell, CE, Postma, DS, Pouta, A, Ramasamy, A, Rayner, NW, Ring, SM, Rivadeneira, F, Shields, BM, Strachan, DP, Surakka, I, Taanila, A, Tiesler, C, Uitterlinden, AG, van Duijn, CM, Wijga, AH, Willemsen, G, Zhang, H, Zhao, J, Wilson, JF, Steegers, EAP, Hattersley, AT, Eriksson, JG, Peltonen, L, Mohlke, KL, Grant, SFA, Hakonarson, H, Koppelman, GH, Dedoussis, GV, Heinrich, J, Gillman, MW, Palmer, LJ, Frayling, TM, Boomsma, DI, Smith, GD, Power, C, Jaddoe, VWV, Jarvelin, M-R, and McCarthy, MI
Abstract: To identify genetic variants associated with birth weight, we meta-analyzed six genome-wide association (GWA) studies (n = 10,623 Europeans from pregnancy/birth cohorts) and followed up two lead signals in 13 replication studies (n = 27,591). rs900400 near LEKR1 and CCNL1 (P = 2 x 10(-35)) and rs9883204 in ADCY5 (P = 7 x 10(-15)) were robustly associated with birth weight. Correlated SNPs in ADCY5 were recently implicated in regulation of glucose levels and susceptibility to type 2 diabetes, providing evidence that the well-described association between lower birth weight and subsequent type 2 diabetes has a genetic component, distinct from the proposed role of programming by maternal nutrition. Using data from both SNPs, we found that the 9% of Europeans carrying four birth weight-lowering alleles were, on average, 113 g (95% CI 89-137 g) lighter at birth than the 24% with zero or one alleles (P(trend) = 7 x 10(-30)). The impact on birth weight is similar to that of a mother smoking 4-5 cigarettes per day in the third trimester of pregnancy.
Published: 2010

46. Fetal sex dependency of maternal vascular adaptation to pregnancy: a prospective population-based cohort study.

Author: Broere‐Brown, ZA, Schalekamp‐Timmermans, S, Hofman, A, Jaddoe, VWV, Steegers, EAP, Broere-Brown, Z A, and Schalekamp-Timmermans, S
Subjects: PREGNANCY complications, VASCULAR resistance, FETAL growth retardation, PREECLAMPSIA, DURATION of pregnancy, PREMATURE labor, THERAPEUTICS, ARTERIAL physiology, DOPPLER ultrasonography, PHYSIOLOGICAL adaptation, BIRTH weight, BLOOD pressure, FETAL ultrasonic imaging, LONGITUDINAL method, MATERNAL age, PHYSICS, PLACENTA, SEX distribution, CASE-control method
Abstract: Objective: To investigate fetal sex dependency of maternal vascular adaptation to pregnancy as assessed by uteroplacental vascular resistance and maternal blood pressure.Design: Prospective population-based cohort study.Setting: Rotterdam, the Netherlands.Population: In total, 8224 liveborn singleton pregnancies were included.Methods: Maternal vascular adaptation was assessed in all trimesters of pregnancy. Pregnancies were stratified into being either complicated by the placental syndrome (i.e. pre-eclampsia, fetal growth restriction or preterm birth, n = 1229) or uncomplicated (n = 6995).Main Outcome Measures: First trimester: blood pressures. Second trimester: blood pressures, pulsatility index of the uterine artery (PI-UtA). Third trimester: blood pressures, PI-UtA, presence of notching in the uterine artery.Results: In women carrying a male fetus PI-UtA was higher than in women with a female fetus in the total group (second trimester P < 0.001, third trimester P = 0.005). Effect estimates differed between women with or without the placental syndrome. In the total group, women with a male fetus more often showed notching in the Doppler resistance pattern (odds ratio 1.42, 95% confidence interval 1.17-1.72). Different blood pressure patterns were observed between pregnant women with a male fetus and pregnant women with a female fetus and between complicated pregnancies and uncomplicated pregnancies.Conclusion: Fetal sex is significantly associated with maternal vascular adaptation to pregnancy with differential effects in uncomplicated pregnancies and in pregnancies complicated by the placental syndrome.Tweetable Abstract: Fetal sex is significantly associated with maternal vascular adaptation to pregnancy. [ABSTRACT FROM AUTHOR]
Published: 2016
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47. Associations of maternal prepregnancy body mass index and gestational weight gain with cardio-metabolic risk factors in adolescent offspring: a prospective cohort study.

Author: Gaillard, R, Welten, M, Oddy, WH, Beilin, LJ, Mori, TA, Jaddoe, VWV, Huang, R‐C, Oddy, W H, Beilin, L J, Mori, T A, Jaddoe, V W V, and Huang, R-C
Subjects: PREGNANCY complications, WEIGHT gain, COHORT analysis, BODY mass index, METABOLISM, CARDIOVASCULAR disease prevention, PREVENTION of obesity, OBESITY complications, BLOOD pressure, CARDIOVASCULAR diseases, LONGITUDINAL method, OBESITY, RESEARCH funding, DISEASE prevalence, METABOLIC syndrome, WAIST-hip ratio, WAIST circumference, PRENATAL exposure delayed effects, PREVENTION
Abstract: Objective: To assess the associations of maternal prepregnancy body mass index (BMI) and rates of early-pregnancy, mid-pregnancy and total gestational weight gain with adolescent body fat distribution and cardio-metabolic outcomes.Design: Population-based prospective cohort study.Setting: Western Australia.Population: Thousand three hundred and ninety-two mothers and their children.Methods: Maternal prepregnancy weight was assessed by questionnaire. Maternal weights at a mean of 16.5 ± 2.2 SD and 34.1 ± 1.5 SD weeks of gestation were obtained from medical records. Offspring adiposity and cardio-metabolic outcomes were assessed at a median age 17.0 years [95% confidence interval (CI) range: 16.7, 17.7].Main Outcome Measures: Adolescent BMI, waist circumference (WC), waist-to-hip ratio (WHR), blood pressure, total and HDL-cholesterol, triglycerides, insulin, glucose and HOMA-IR.Results: Higher prepregnancy BMI was associated with higher adolescent BMI, WC, WHR, systolic blood pressure, insulin, glucose and HOMA-IR levels (P-values <0.05). Adjustment for adolescent current BMI attenuated the associations of prepregnancy BMI with adolescent cardio-metabolic outcomes. Higher weight gain in early-pregnancy, but not mid-pregnancy, was associated with higher adolescent BMI, WC and WHR (P-values <0.05), but not with other cardio-metabolic risk factors. Total gestational weight gain was associated with adolescent BMI and WC (P-values <0.05). Higher prepregnancy BMI and early-pregnancy weight gain were associated with increased risks of the high-metabolic risk cluster in adolescents (OR 1.57, 95% CI 1.33, 1.85 and OR 1.23, 95% CI 1.03, 1.47 per SD increase in prepregnancy BMI and early-pregnancy weight gain, respectively).Conclusions: Higher maternal prepregnancy BMI and early-pregnancy weight gain rate are associated with an adverse adolescent cardio-metabolic profile. These associations are largely mediated by adolescent BMI. [ABSTRACT FROM AUTHOR]
Published: 2016
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48. A periconceptional energy-rich dietary pattern is associated with early fetal growth: the Generation R study

Author: Bouwland-Both, MI, primary, Steegers-Theunissen, RPM, additional, Vujkovic, M, additional, Lesaffre, EMEH, additional, Mook-Kanamori, DO, additional, Hofman, A, additional, Lindemans, J, additional, Russcher, H, additional, Jaddoe, VWV, additional, and Steegers, EAP, additional
Published: 2012
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49. Perinatal outcomes and gestational weight gain in women with eating disorders: a population‐based cohort study

Author: Micali, N, primary, De Stavola, B, additional, dos‐Santos‐Silva, I, additional, Steenweg‐de Graaff, J, additional, Jansen, PW, additional, Jaddoe, VWV, additional, Hofman, A, additional, Verhulst, FC, additional, Steegers, EAP, additional, and Tiemeier, H, additional
Published: 2012
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50. Explaining differences in birth outcomes in relation to maternal age: the Generation R Study

Author: Bakker, R, primary, Steegers, EAP, additional, Biharie, AA, additional, Mackenbach, JP, additional, Hofman, A, additional, and Jaddoe, VWV, additional
Published: 2011
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