30 results on '"Nohr, E.A."'
Search Results
2. Analysis of DNA methylation at birth and in childhood reveals changes associated with season of birth and latitude
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Kadalayil, L., Alam, M., White, C.H., Ghantous, A., Walton, E., Gruzieva, O., Merid, S.K., Kumar, A., Roy, R., Solomon, O., Huen, K., Eskenazi, B., Rzehak, P., Grote, V., Langhendries, J.-P., Verduci, E., Ferre, N., Gruszfeld, D., Gao, L., Guan, W., Zeng, X., Schisterman, E.F., Dou, J., Bakulski, K.M., Feinberg, J.I., Soomro, M.H., Pesce, G., Baiz, N., Isaevska, E., Plusquin, M., Vafeiadi, M., Roumeliotaki, T., Langie, S.A.S., Standaert, A., Allard, C., Perron, P., Bouchard, L., van Meel, E.R., Felix, J.F., Jaddoe, V.W.V., Yousefi, P.D., Ramlau‑Hansen, C.H., Relton, C.L., Tobi, E.W., Starling, A.P., Yang, I.V., Llambrich, M., Santorelli, G., Lepeule, J., Salas, L.A., Bustamante, M., Ewart, S.L., Zhang, H., Karmaus, W., Röder, Stefan, Zenclussen, Ana Claudia, Jin, J., Nystad, W., Page, C.M., Magnus, M., Jima, D.D., Hoyo, C., Maguire, R.L., Kvist, T., Czamara, D., Räikkönen, K., Gong, T., Ullemar, V., Rifas‐Shiman, S.L., Oken, E., Almqvist, C., Karlsson, R., Lahti, J., Murphy, S.K., Håberg, S.E., London, S., Herberth, Gunda, Arshad, H., Sunyer, J., Grazuleviciene, R., Dabelea, D., Steegers‑Theunissen, R.P.M., Nohr, E.A., Sørensen, T.I.A., Duijts, L., Hivert, M.-F., Nelen, V., Popovic, M., Kogevinas, M., Nawrot, T.S., Herceg, Z., Annesi-Maesano, I., Fallin, M.D., Yeung, E., Breton, C.V., Koletzko, B., Holland, N., Melén, E., Sharp, G.C., Silver, M.J., Kadalayil, L., Alam, M., White, C.H., Ghantous, A., Walton, E., Gruzieva, O., Merid, S.K., Kumar, A., Roy, R., Solomon, O., Huen, K., Eskenazi, B., Rzehak, P., Grote, V., Langhendries, J.-P., Verduci, E., Ferre, N., Gruszfeld, D., Gao, L., Guan, W., Zeng, X., Schisterman, E.F., Dou, J., Bakulski, K.M., Feinberg, J.I., Soomro, M.H., Pesce, G., Baiz, N., Isaevska, E., Plusquin, M., Vafeiadi, M., Roumeliotaki, T., Langie, S.A.S., Standaert, A., Allard, C., Perron, P., Bouchard, L., van Meel, E.R., Felix, J.F., Jaddoe, V.W.V., Yousefi, P.D., Ramlau‑Hansen, C.H., Relton, C.L., Tobi, E.W., Starling, A.P., Yang, I.V., Llambrich, M., Santorelli, G., Lepeule, J., Salas, L.A., Bustamante, M., Ewart, S.L., Zhang, H., Karmaus, W., Röder, Stefan, Zenclussen, Ana Claudia, Jin, J., Nystad, W., Page, C.M., Magnus, M., Jima, D.D., Hoyo, C., Maguire, R.L., Kvist, T., Czamara, D., Räikkönen, K., Gong, T., Ullemar, V., Rifas‐Shiman, S.L., Oken, E., Almqvist, C., Karlsson, R., Lahti, J., Murphy, S.K., Håberg, S.E., London, S., Herberth, Gunda, Arshad, H., Sunyer, J., Grazuleviciene, R., Dabelea, D., Steegers‑Theunissen, R.P.M., Nohr, E.A., Sørensen, T.I.A., Duijts, L., Hivert, M.-F., Nelen, V., Popovic, M., Kogevinas, M., Nawrot, T.S., Herceg, Z., Annesi-Maesano, I., Fallin, M.D., Yeung, E., Breton, C.V., Koletzko, B., Holland, N., Melén, E., Sharp, G.C., and Silver, M.J.
- Abstract
BackgroundSeasonal 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.MethodsWe 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.ResultsWe 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 including asthma (LTB4R), present only at birth in the higher latitudes (≥ 50°N).ConclusiosIn this large epigenome-wide meta-analysis study, we provide eviden
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- 2023
3. Genetic Associations With Gestational Duration and Spontaneous Preterm Birth
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Zhang, G., Feenstra, B., Bacelis, J., Liu, X., Muglia, L.M., Juodakis, J., Miller, D.E., Litterman, N., Jiang, P.P., Russell, L., Hinds, D.A., Hu, Y., Weirauch, M.T., Chen, X., Chavan, A.R., Wagner, G.P., Pavličev, M., Nnamani, M.C., Maziarz, J., Karjalainen, M.K., Rämet, M., Sengpiel, V., Geller, F., Boyd, H.A., Palotie, A., Momany, A., Bedell, B., Ryckman, K.K., Huusko, J.M., Forney, C.R., Kottyan, L.C., Hallman, M., Teramo, K., Nohr, E.A., Davey Smith, G., Melbye, M., Jacobsson, B., and Muglia, L.J.
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- 2018
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4. Changes in parental smoking during pregnancy and risks of adverse birth outcomes and childhood overweight in Europe and North America: An individual participant data meta-analysis of 229,000 singleton births
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Philips, E.M. Santos, S. Trasande, L. Aurrekoetxea, J.J. Barros, H. von Berg, A. Bergström, A. Bird, P.K. Brescianini, S. Chaoimh, C.N. Charles, M.-A. Chatzi, L. Chevrier, C. Chrousos, G.P. Costet, N. Criswell, R. Crozier, S. Eggesbø, M. Fantini, M.P. Farchi, S. Forastiere, F. van Gelder, M.M.H.J. Georgiu, V. Godfrey, K.M. Gori, D. Hanke, W. Heude, B. Hryhorczuk, D. Iñiguez, C. Inskip, H. Karvonen, A.M. Kenny, L.C. Kull, I. Lawlor, D.A. Lehmann, I. Magnus, P. Manios, Y. Melén, E. Mommers, M. Morgen, C.S. Moschonis, G. Murray, D. Nohr, E.A. Nybo Andersen, A.-M. Oken, E. Oostvogels, A.J.J.M. Papadopoulou, E. Pekkanen, J. Pizzi, C. Polanska, K. Porta, D. Richiardi, L. Rifas-Shiman, S.L. Roeleveld, N. Rusconi, F. Santos, A.C. Sørensen, T.I.A. Standl, M. Stoltenberg, C. Sunyer, J. Thiering, E. Thijs, C. Torrent, M. Vrijkotte, T.G.M. Wright, J. Zvinchuk, O. Gaillard, R. Jaddoe, V.W.V.
- Abstract
Background Fetal smoke exposure is a common and key avoidable risk factor for birth complications and seems to influence later risk of overweight. It is unclear whether this increased risk is also present if mothers smoke during the first trimester only or reduce the number of cigarettes during pregnancy, or when only fathers smoke. We aimed to assess the associations of parental smoking during pregnancy, specifically of quitting or reducing smoking and maternal and paternal smoking combined, with preterm birth, small size for gestational age, and childhood overweight. Methods and findings We performed an individual participant data meta-analysis among 229,158 families from 28 pregnancy/birth cohorts from Europe and North America. All 28 cohorts had information on maternal smoking, and 16 also had information on paternal smoking. In total, 22 cohorts were population-based, with birth years ranging from 1991 to 2015. The mothers’ median age was 30.0 years, and most mothers were medium or highly educated. We used multilevel binary logistic regression models adjusted for maternal and paternal sociodemographic and lifestyle-related characteristics. Compared with nonsmoking mothers, maternal first trimester smoking only was not associated with adverse birth outcomes but was associated with a higher risk of childhood overweight (odds ratio [OR] 1.17 [95% CI 1.02–1.35], P value = 0.030). Children from mothers who continued smoking during pregnancy had higher risks of preterm birth (OR 1.08 [95% CI 1.02–1.15], P value = 0.012), small size for gestational age (OR 2.15 [95% CI 2.07–2.23], P value < 0.001), and childhood overweight (OR 1.42 [95% CI 1.35–1.48], P value < 0.001). Mothers who reduced the number of cigarettes between the first and third trimester, without quitting, still had a higher risk of small size for gestational age. However, the corresponding risk estimates were smaller than for women who continued the same amount of cigarettes throughout pregnancy (OR 1.89 [95% CI 1.52–2.34] instead of OR 2.20 [95% CI 2.02–2.42] when reducing from 5–9 to ≤4 cigarettes/day; OR 2.79 [95% CI 2.39–3.25] and OR 1.93 [95% CI 1.46–2.57] instead of OR 2.95 [95% CI 2.75–3.15] when reducing from ≥10 to 5–9 and ≤4 cigarettes/day, respectively [P values < 0.001]). Reducing the number of cigarettes during pregnancy did not affect the risks of preterm birth and childhood overweight. Among nonsmoking mothers, paternal smoking was associated with childhood overweight (OR 1.21 [95% CI 1.16–1.27], P value < 0.001) but not with adverse birth outcomes. Limitations of this study include the self-report of parental smoking information and the possibility of residual confounding. As this study only included participants from Europe and North America, results need to be carefully interpreted regarding other populations. Conclusions We observed that as compared to nonsmoking during pregnancy, quitting smoking in the first trimester is associated with the same risk of preterm birth and small size for gestational age, but with a higher risk of childhood overweight. Reducing the number of cigarettes, without quitting, has limited beneficial effects. Paternal smoking seems to be associated, independently of maternal smoking, with the risk of childhood overweight. Population strategies should focus on parental smoking prevention before or at the start, rather than during, pregnancy. © 2020 Philips et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
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- 2020
5. Changes in parental smoking during pregnancy and risks of adverse birth outcomes and childhood overweight in Europe and North America: An individual participant data meta-analysis of 229,000 singleton births
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Philips, E.M., Santos, S., Trasande, L., Aurrekoetxea, J.J., Barros, H., von Berg, A., Bergström, A., Bird, P.K., Brescianini, S., Ní Chaoimh, C., Charles, M.-A., Chatzi, L., Chevrier, C., Chrousos, G.P., Costet, N., Criswell, R., Crozier, S., Eggesbø, M., Fantini, M.P., Farchi, S., Forastiere, F., van Gelder, M.M.H.J., Georgiu, V., Godfrey, K.M., Gori, D., Hanke, W., Heude, B., Hryhorczuk, D., Iñiguez, C., Inskip, H., Karvonen, A.M., Kenny, L.C., Kull, I., Lawlor, D.A., Lehmann, Irina, Magnus, P., Manios, Y., Melén, E., Mommers, M., Morgen, C.S., Moschonis, G., Murray, D., Nohr, E.A., Nybo Andersen, A.-M., Oken, E., Oostvogels, A.J.J.M., Papadopoulou, E., Pekkanen, J., Pizzi, C., Polanska, K., Porta, D., Richiardi, L., Rifas‐Shiman, S.L., Roeleveld, N., Rusconi, F., Santos, A.C., Sørensen, T.I.A., Standl, M., Stoltenberg, C., Sunyer, J., Thiering, E., Thijs, C., Torrent, M., Vrijkotte, T.G.M., Wright, J., Zvinchuk, O., Gaillard, R., Jaddoe, V.W.V., Philips, E.M., Santos, S., Trasande, L., Aurrekoetxea, J.J., Barros, H., von Berg, A., Bergström, A., Bird, P.K., Brescianini, S., Ní Chaoimh, C., Charles, M.-A., Chatzi, L., Chevrier, C., Chrousos, G.P., Costet, N., Criswell, R., Crozier, S., Eggesbø, M., Fantini, M.P., Farchi, S., Forastiere, F., van Gelder, M.M.H.J., Georgiu, V., Godfrey, K.M., Gori, D., Hanke, W., Heude, B., Hryhorczuk, D., Iñiguez, C., Inskip, H., Karvonen, A.M., Kenny, L.C., Kull, I., Lawlor, D.A., Lehmann, Irina, Magnus, P., Manios, Y., Melén, E., Mommers, M., Morgen, C.S., Moschonis, G., Murray, D., Nohr, E.A., Nybo Andersen, A.-M., Oken, E., Oostvogels, A.J.J.M., Papadopoulou, E., Pekkanen, J., Pizzi, C., Polanska, K., Porta, D., Richiardi, L., Rifas‐Shiman, S.L., Roeleveld, N., Rusconi, F., Santos, A.C., Sørensen, T.I.A., Standl, M., Stoltenberg, C., Sunyer, J., Thiering, E., Thijs, C., Torrent, M., Vrijkotte, T.G.M., Wright, J., Zvinchuk, O., Gaillard, R., and Jaddoe, V.W.V.
- Abstract
Background Fetal smoke exposure is a common and key avoidable risk factor for birth complications and seems to influence later risk of overweight. It is unclear whether this increased risk is also present if mothers smoke during the first trimester only or reduce the number of cigarettes during pregnancy, or when only fathers smoke. We aimed to assess the associations of parental smoking during pregnancy, specifically of quitting or reducing smoking and maternal and paternal smoking combined, with preterm birth, small size for gestational age, and childhood overweight. Methods and findings We performed an individual participant data meta-analysis among 229,158 families from 28 pregnancy/birth cohorts from Europe and North America. All 28 cohorts had information on maternal smoking, and 16 also had information on paternal smoking. In total, 22 cohorts were population-based, with birth years ranging from 1991 to 2015. The mothers’ median age was 30.0 years, and most mothers were medium or highly educated. We used multilevel binary logistic regression models adjusted for maternal and paternal sociodemographic and lifestyle-related characteristics. Compared with nonsmoking mothers, maternal first trimester smoking only was not associated with adverse birth outcomes but was associated with a higher risk of childhood overweight (odds ratio [OR] 1.17 [95% CI 1.02–1.35], P value = 0.030). Children from mothers who continued smoking during pregnancy had higher risks of preterm birth (OR 1.08 [95% CI 1.02–1.15], P value = 0.012), small size for gestational age (OR 2.15 [95% CI 2.07–2.23], P value < 0.001), and childhood overweight (OR 1.42 [95% CI 1.35–1.48], P value < 0.001). Mothers who reduced the number of cigarettes between the first and third trimester, without quitting, still had a higher risk of small size for gestational age. However, the corresponding risk estimates were smaller than for women who continued the same amount of cigarettes throughout preg
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- 2020
6. Maternal bereavement in the antenatal period and oral cleft in the offspring
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Ingstrup, K.G., Liang, H., Olsen, J., Nohr, E.A., Bech, B.H., Wu, C.S., Christensen, K., and Li, J.
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- 2013
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7. Waiting time to pregnancy according to maternal birthweight and prepregnancy BMI
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Nohr, E.A., Vaeth, M., Rasmussen, S., Ramlau-Hansen, C.H., and Olsen, J.
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- 2009
8. 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
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Santos, S. Voerman, E. Amiano, P. Barros, H. Beilin, L.J. Bergström, A. Charles, M.-A. Chatzi, L. Chevrier, C. Chrousos, G.P. Corpeleijn, E. Costa, O. Costet, N. Crozier, S. Devereux, G. Doyon, M. Eggesbø, M. Fantini, M.P. Farchi, S. Forastiere, F. Georgiu, V. Godfrey, K.M. Gori, D. Grote, V. Hanke, W. Hertz-Picciotto, I. Heude, B. Hivert, M.-F. Hryhorczuk, D. Huang, R.-C. Inskip, H. Karvonen, A.M. Kenny, L.C. Koletzko, B. Küpers, L.K. Lagström, H. Lehmann, I. Magnus, P. Majewska, R. Mäkelä, J. Manios, Y. McAuliffe, F.M. McDonald, S.W. Mehegan, J. Melén, E. Mommers, M. Morgen, C.S. Moschonis, G. Murray, D. Ní Chaoimh, C. Nohr, E.A. Nybo Andersen, A.-M. Oken, E. Oostvogels, A.J.J.M. Pac, A. Papadopoulou, E. Pekkanen, J. Pizzi, C. Polanska, K. Porta, D. Richiardi, L. Rifas-Shiman, S.L. Roeleveld, N. Ronfani, L. Santos, A.C. Standl, M. Stigum, H. Stoltenberg, C. Thiering, E. Thijs, C. Torrent, M. Tough, S.C. Trnovec, T. Turner, S. van Gelder, M.M.H.J. van Rossem, L. von Berg, A. Vrijheid, M. Vrijkotte, T.G.M. West, J. Wijga, A.H. Wright, J. Zvinchuk, O. Sørensen, T.I.A. Lawlor, D.A. Gaillard, R. Jaddoe, V.W.V.
- Abstract
Objective: To 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. Design: Individual participant data meta-analysis of 39 cohorts. Setting: Europe, North America, and Oceania. Population: 265 270 births. Methods: Information on maternal pre-pregnancy BMI, gestational weight gain, and pregnancy complications was obtained. Multilevel binary logistic regression models were used. Main outcome measures: Gestational hypertension, pre-eclampsia, gestational diabetes, preterm birth, small and large for gestational age at birth. Results: Higher 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. Conclusions: Maternal 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 abstract: Promoting a healthy body mass index and gestational weight gain might reduce the population burden of pregnancy complications. © 2019 Royal College of Obstetricians and Gynaecologists
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- 2019
9. Association of Gestational Weight Gain With Adverse Maternal and Infant Outcomes
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LifeCycle Project-Maternal Obesity Childhood Outcomes Study Group Voerman, E. Santos, S. Inskip, H. Amiano, P. Barros, H. Charles, M.-A. Chatzi, L. Chrousos, G.P. Corpeleijn, E. Crozier, S. Doyon, M. Eggesbø, M. Fantini, M.P. Farchi, S. Forastiere, F. Georgiu, V. Gori, D. Hanke, W. Hertz-Picciotto, I. Heude, B. Hivert, M.-F. Hryhorczuk, D. Iñiguez, C. Karvonen, A.M. Küpers, L.K. Lagström, H. Lawlor, D.A. Lehmann, I. Magnus, P. Majewska, R. Mäkelä, J. Manios, Y. Mommers, M. Morgen, C.S. Moschonis, G. Nohr, E.A. Nybo Andersen, A.-M. Oken, E. Pac, A. Papadopoulou, E. Pekkanen, J. Pizzi, C. Polanska, K. Porta, D. Richiardi, L. Rifas-Shiman, S.L. Roeleveld, N. Ronfani, L. Santos, A.C. Standl, M. Stigum, H. Stoltenberg, C. Thiering, E. Thijs, C. Torrent, M. Trnovec, T. van Gelder, M.M.H.J. van Rossem, L. von Berg, A. Vrijheid, M. Wijga, A. Zvinchuk, O. Sørensen, T.I.A. Godfrey, K. Jaddoe, V.W.V. Gaillard, R.
- Abstract
Importance: Both low and high gestational weight gain have been associated with adverse maternal and infant outcomes, but optimal gestational weight gain remains uncertain and not well defined for all prepregnancy weight ranges. Objectives: To examine the association of ranges of gestational weight gain with risk of adverse maternal and infant outcomes and estimate optimal gestational weight gain ranges across prepregnancy body mass index categories. Design, Setting, and Participants: Individual participant-level meta-analysis using data from 196 670 participants within 25 cohort studies from Europe and North America (main study sample). Optimal gestational weight gain ranges were estimated for each prepregnancy body mass index (BMI) category by selecting the range of gestational weight gain that was associated with lower risk for any adverse outcome. Individual participant-level data from 3505 participants within 4 separate hospital-based cohorts were used as a validation sample. Data were collected between 1989 and 2015. The final date of follow-up was December 2015. Exposures: Gestational weight gain. Main Outcomes and Measures: The main outcome termed any adverse outcome was defined as the presence of 1 or more of the following outcomes: preeclampsia, gestational hypertension, gestational diabetes, cesarean delivery, preterm birth, and small or large size for gestational age at birth. Results: Of the 196 670 women (median age, 30.0 years [quartile 1 and 3, 27.0 and 33.0 years] and 40 937 were white) included in the main sample, 7809 (4.0%) were categorized at baseline as underweight (BMI
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- 2019
10. Associations of Mitochondrial and Nuclear Mitochondrial Variants and Genes with Seven Metabolic Traits
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Harris, S.E., Corley, J., Wojczynski, M.K., Nauck, M., Levy, D., Gu, C., Sorensen, T.I.A., Noordam, R., Guo, X., Hill, W.D., Chen, Y.-D.I., Liu, C., Yao, J., Kraja, A.T., Daw, E.W., Irvin, M.R., Christensen, C., Newman, A.B., Hansen, T., Hudson, G., Zeng, D., Wu, H., Uitterlinden, A.G., Wareham, N.J., Perls, T.T., Grarup, N., Broeckel, U., Luan, J., Fu, M., Hemani, G., de Mutsert, R., Lin, S.J., Wilson, J.G., Jorgensen, M.E., Witte, D.R., Have, C.T., Ribel-Madsen, R., Wang, Y., Love-Gregory, L.D., Bowden, D.W., Province, M.A., Rotter, J.I., Taylor, A.M., Hunt, S.C., Thyagarajan, B., Goodarzi, M.O., Ridker, P.M., Torp-Pedersen, C., Ligthart, S., Starr, J.M., Feitosa, M.F., Arnett, D.K., de Haan, H.G., Jorgensen, T., Weeke, P.E., Graff, M., de las Fuentes, L., Justice, A.E., Hayward, C., Kerrison, N.D., Pedersen, O., Bonnelykke, K., Perry, J.A., Fetterman, J.L., Hai, Y., Malik, A.N., Vestergaard, H., Cropp, C.D., Ryan, K.A., Christensen, K., The Population Sciences Branch, NHLBI/NIH, Armasu, S.M., Langenberg, C., Forouhi, N.G., Yang, W., Teumer, A., Rodriguez, S., Kardia, S.L.R., Qi, Q., Becker, D.M., Baranski, T.J., Yanek, L.R., Rao, D.C., Fernandez, E.P., Lin, K.-H., Li-Gao, R., Sofer, T., Nohr, E.A., Larson, N.B., Sheu, W.H.-H., Elliott, P., An, P., Schnurr, T.M., Gu, Z., Taylor, K.D., Davies, G., Kilpelainen, T.O., Lee, W.-J., Patki, A., Barve, R.A., Brandslund, I., Sandow, K., Weiss, S., Wang, L., Stergiakouli, E., Mathias, R.A., Ghanbari, M., Tiwari, H.K., Rivadeneira, F., Davila-Roman, V.G., de Andrade, M., North, K.E., Richardson, T.G., Horta, B.L., Bielinski, S.J., Linneberg, A., Young, K., Argos, M., Dehghan, A., Chasman, D.I., Mook-Kanamori, D.O., Vaidya, D., Petersmann, A., Scott, R.A., Meigs, J.B., Ahluwalia, T.S., Gao, H., Rosendaal, F.R., Chakravarti, A., van Heemst, D., Cox, S.R., Williams, C., Pankow, J., Giulianini, F., Weir, B.S., Jonsson, A.E., Hartwig, F.P., Rohde, R., Ikram, M.A., Homuth, G., Lee, J.H., Deary, I.J., Erzurumluoglu, A.M., Chu, A.Y., Emery, L.S., Franco, O.H., Ong, K.K., Arking, D.E., Loos, R.J.F., Tzoulaki, I., Pattie, A., Timpson, N.J., and Turner, S.T.
- Abstract
Mitochondria (MT), the major site of cellular energy production, are under dual genetic control by 37 mitochondrial DNA (mtDNA) genes and numerous nuclear genes (MT-nDNA). In the CHARGEmtDNA+ Consortium, we studied genetic associations of mtDNA and MT-nDNA associations with body mass index (BMI), waist-hip-ratio (WHR), glucose, insulin, HOMA-B, HOMA-IR, and HbA1c. This 45-cohort collaboration comprised 70,775 (insulin) to 170,202 (BMI) pan-ancestry individuals. Validation and imputation of mtDNA variants was followed by single-variant and gene-based association testing. We report two significant common variants, one in MT-ATP6 associated (p ≤ 5E−04) with WHR and one in the D-loop with glucose. Five rare variants in MT-ATP6, MT-ND5, and MT-ND6 associated with BMI, WHR, or insulin. Gene-based meta-analysis identified MT-ND3 associated with BMI (p ≤ 1E−03). We considered 2,282 MT-nDNA candidate gene associations compiled from online summary results for our traits (20 unique studies with 31 dataset consortia's genome-wide associations [GWASs]). Of these, 109 genes associated (p ≤ 1E−06) with at least 1 of our 7 traits. We assessed regulatory features of variants in the 109 genes, cis- and trans-gene expression regulation, and performed enrichment and protein-protein interactions analyses. Of the identified mtDNA and MT-nDNA genes, 79 associated with adipose measures, 49 with glucose/insulin, 13 with risk for type 2 diabetes, and 18 with cardiovascular disease, indicating for pleiotropic effects with health implications. Additionally, 21 genes related to cholesterol, suggesting additional important roles for the genes identified. Our results suggest that mtDNA and MT-nDNA genes and variants reported make important contributions to glucose and insulin metabolism, adipocyte regulation, diabetes, and cardiovascular disease.
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- 2019
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11. Is maternal obesity related to semen quality in the male offspring? A pilot study
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Ramlau-Hansen, C.H., Nohr, E.A., Thulstrup, A.M., Bonde, J.P., Storgaard, L., and Olsen, J.
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- 2007
12. Subfecundity in overweight and obese couples
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Ramlau-Hansen, C.H., Thulstrup, A.M., Nohr, E.A., Bonde, J.P., Sørensen, T.I.A., and Olsen, J.
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- 2007
13. Association of gestational weight gain with adverse maternal and infant outcomes
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Voerman, E., Santos, S., Inskip, H., Amiano, P., Barros, H., Charles, M.-A., Chatzi, L., Chrousos, G.P., Corpeleijn, E., Crozier, S., Doyon, M., Eggesbø, M., Fantini, M.P., Farchi, S., Forastiere, F., Georgiu, V., Gori, D., Hanke, W., Hertz-Picciotto, I., Heude, B., Hivert, M.-F., Hryhorczuk, D., Iniguez, C., Karvonen, A.M., Kupers, L.K., Lagström, H., Lawlor, D.A., Lehmann, Irina, Magnus, P., Majewska, R., Mäkelä, J., Manios, Y., Mommers, M., Morgen, C.S., Moschonis, G., Nohr, E.A., Nybo Andersen, A.-M., Oken, E., Pac, A., Papadopoulou, E., Pekkanen, J., Pizzi, C., Polanska, K., Porta, D., Richiardi, L., Rifas-Shiman, S.-L., Roeleveld, N., Ronfani, L., Santos, A.C., Standl, M., Stigum, H., Stoltenberg, C., Thiering, E., Thijs, C., Torrent, M., Trnovec, T., van Gelder, M.M.H.J., van Rossem, L., von Berg, A., Vijheid, M., Wijga, A., Zvinchuk, O., Sørensen, T.I.A., Godfrey, K., Jaddoe, V.W.V., Gaillard, R., Voerman, E., Santos, S., Inskip, H., Amiano, P., Barros, H., Charles, M.-A., Chatzi, L., Chrousos, G.P., Corpeleijn, E., Crozier, S., Doyon, M., Eggesbø, M., Fantini, M.P., Farchi, S., Forastiere, F., Georgiu, V., Gori, D., Hanke, W., Hertz-Picciotto, I., Heude, B., Hivert, M.-F., Hryhorczuk, D., Iniguez, C., Karvonen, A.M., Kupers, L.K., Lagström, H., Lawlor, D.A., Lehmann, Irina, Magnus, P., Majewska, R., Mäkelä, J., Manios, Y., Mommers, M., Morgen, C.S., Moschonis, G., Nohr, E.A., Nybo Andersen, A.-M., Oken, E., Pac, A., Papadopoulou, E., Pekkanen, J., Pizzi, C., Polanska, K., Porta, D., Richiardi, L., Rifas-Shiman, S.-L., Roeleveld, N., Ronfani, L., Santos, A.C., Standl, M., Stigum, H., Stoltenberg, C., Thiering, E., Thijs, C., Torrent, M., Trnovec, T., van Gelder, M.M.H.J., van Rossem, L., von Berg, A., Vijheid, M., Wijga, A., Zvinchuk, O., Sørensen, T.I.A., Godfrey, K., Jaddoe, V.W.V., and Gaillard, R.
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Importance Both low and high gestational weight gain have been associated with adverse maternal and infant outcomes, but optimal gestational weight gain remains uncertain and not well defined for all prepregnancy weight ranges.Objectives To examine the association of ranges of gestational weight gain with risk of adverse maternal and infant outcomes and estimate optimal gestational weight gain ranges across prepregnancy body mass index categories.Design, Setting, and Participants Individual participant-level meta-analysis using data from 196 670 participants within 25 cohort studies from Europe and North America (main study sample). Optimal gestational weight gain ranges were estimated for each prepregnancy body mass index (BMI) category by selecting the range of gestational weight gain that was associated with lower risk for any adverse outcome. Individual participant-level data from 3505 participants within 4 separate hospital-based cohorts were used as a validation sample. Data were collected between 1989 and 2015. The final date of follow-up was December 2015.Exposures Gestational weight gain.Main Outcomes and Measures The main outcome termed any adverse outcome was defined as the presence of 1 or more of the following outcomes: preeclampsia, gestational hypertension, gestational diabetes, cesarean delivery, preterm birth, and small or large size for gestational age at birth.Results Of the 196 670 women (median age, 30.0 years [quartile 1 and 3, 27.0 and 33.0 years] and 40 937 were white) included in the main sample, 7809 (4.0%) were categorized at baseline as underweight (BMI <18.5); 133 788 (68.0%), normal weight (BMI, 18.5-24.9); 38 828 (19.7%), overweight (BMI, 25.0-29.9); 11 992 (6.1%), obesity grade 1 (BMI, 30.0-34.9); 3284 (1.7%), obesity grade 2 (BMI, 35.0-39.9); and 969 (0.5%), obesity grade 3 (BMI, ≥40.0). Overall, any adverse outcome occurred in 37.2% (n = 73 161) of women, ranging fro
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- 2019
14. 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
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Santos, S., Voerman, E., Amiano, P., Barros, H., Beilin, L.J., Bergström, A., Charles, M.-A., Chatzi, L., Chevrier, C., Chrousos, G.P., Corpeleijn, E., Costa, O., Costet, N., Crozier, S., Devereux, G., Doyon, M., Eggesbø, M., Fantini, M.P., Farchi, S., Forastiere, F., Georgiu, V., Godfrey, K.M., Gori, D., Grote, V., Hanke, W., Hertz‐Picciotto, I., Heude, B., Hivert, M.-F., Hryhorczuk, D., Huang, R.-C., Inskip, H., Karvonen, A.M., Kenny, L.C., Koletzko, B., Küpers, L.K., Lagström, H., Lehmann, Irina, Magnus, P., Majewska, R., Mäkelä, J., Manios, Y., McAuliffe, F.M., McDonald, S.W., Mehegan, J., Melén, E., Mommers, M., Morgen, C.S., Moschonis, G., Murray, D., Ní Chaoimh, C., Nohr, E.A., Nybo Andersen, A.-M., Oken, E., Oostvogels, A.J.J.M., Pac, A., Papadopoulou, E., Pekkanen, J., Pizzi, C., Polanska, K., Porta, D., Richiardi, L., Rifas‐Shiman, S.L., Roeleveld, N., Ronfani, L., Santos, A.C., Standl, M., Stigum, H., Stoltenberg, C., Thiering, E., Thijs, C., Torrent, M., Tough, S.C., Trnovec, T., Turner, S., van Gelder, M.M.H.J., van Rossem, L., von Berg, A., Vrijheid, M., Vrijkotte, T.G.M., West, J., Wijga, A.H., Wright, J., Zvinchuk, O., Sørensen, T.I.A., Lawlor, D.A., Gaillard, R., Jaddoe, V.W.V., Santos, S., Voerman, E., Amiano, P., Barros, H., Beilin, L.J., Bergström, A., Charles, M.-A., Chatzi, L., Chevrier, C., Chrousos, G.P., Corpeleijn, E., Costa, O., Costet, N., Crozier, S., Devereux, G., Doyon, M., Eggesbø, M., Fantini, M.P., Farchi, S., Forastiere, F., Georgiu, V., Godfrey, K.M., Gori, D., Grote, V., Hanke, W., Hertz‐Picciotto, I., Heude, B., Hivert, M.-F., Hryhorczuk, D., Huang, R.-C., Inskip, H., Karvonen, A.M., Kenny, L.C., Koletzko, B., Küpers, L.K., Lagström, H., Lehmann, Irina, Magnus, P., Majewska, R., Mäkelä, J., Manios, Y., McAuliffe, F.M., McDonald, S.W., Mehegan, J., Melén, E., Mommers, M., Morgen, C.S., Moschonis, G., Murray, D., Ní Chaoimh, C., Nohr, E.A., Nybo Andersen, A.-M., Oken, E., Oostvogels, A.J.J.M., Pac, A., Papadopoulou, E., Pekkanen, J., Pizzi, C., Polanska, K., Porta, D., Richiardi, L., Rifas‐Shiman, S.L., Roeleveld, N., Ronfani, L., Santos, A.C., Standl, M., Stigum, H., Stoltenberg, C., Thiering, E., Thijs, C., Torrent, M., Tough, S.C., Trnovec, T., Turner, S., van Gelder, M.M.H.J., van Rossem, L., von Berg, A., Vrijheid, M., Vrijkotte, T.G.M., West, J., Wijga, A.H., Wright, J., Zvinchuk, O., Sørensen, T.I.A., Lawlor, D.A., Gaillard, R., and Jaddoe, V.W.V.
- Abstract
Objective To assess the separate and combined associations of maternal pre‐pregnancy BMI and gestational weight gain with the risks of pregnancy complications and their population impact.Design Individual participant data meta‐analysis of 39 cohorts.SettingEurope, North America and Oceania. Population 265,270 births. Methods Information on maternal pre‐pregnancy BMI, gestational weight gain, and pregnancy complications was obtained. Multilevel binary logistic regression models were used. Main outcome measures Gestational hypertension, pre‐eclampsia, gestational diabetes, preterm birth, small and large size for gestational age at birth. Results Higher 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 size for gestational age at birth. Preterm birth risk was higher at lower and higher BMI and weight gain. Compared to 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% Confidence Interval 2.31, 2.74)). We estimated that 23.9% of any pregnancy complication was attributable to maternal overweight/obesity and 31.6% of large size for gestational age infants was attributable to excessive gestational weight gain. Conclusions Maternal pre‐pregnancy BMI and gestational weight gain are, across their full ranges, associated with the 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.
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- 2019
15. Maternal body mass index, gestational weight gain, and the risk of overweight and obesity across childhood: An individual participant data meta-analysis
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Voerman, E., Santos, S., Patro Golab, B., Amiano, P., Ballester, F., Barros, H., Bergström, A., Charles, M.-A., Chatzi, L., Chevrier, C., Chrousos, G.P., Corpeleijn, E., Costet, N., Crozier, S., Devereux, G., Eggesbø, M., Ekström, S., Fantini, M.P., Farchi, S., Forastiere, F., Georgiu, V., Godfrey, K.M., Gori, D., Grote, V., Hanke, W., Hertz-Picciotto, I., Heude, B., Hryhorczuk, D., Huang, R.-C., Inskip, H., Iszatt, N., Karvonen, A.M., Kenny, L.C., Koletzko, B., Küpers, L.K., Lagström, H., Lehmann, Irina, Magnus, P., Majewska, R., Mäkelä, J., Manios, Y., McAuliffe, F.M., McDonald, S.W., Mehegan, J., Mommers, M., Morgen, C.S., Mori, T.A., Moschonis, G., Murray, D., Ní Chaoimh, C., Nohr, E.A., Nybo Andersen, A.-M., Oken, E., Oostvogels, A.J.J.M., Pac, A., Papadopoulou, E., Pekkanen, J., Pizzi, C., Polanska, K., Porta, D., Richiardi, L., Rifas-Shiman, S.-L., Ronfani, L., Santos, A.C., Standl, M., Stoltenberg, C., Thiering, E., Thijs, C., Torrent, M., Tough, S.C., Trnovec, T., Turner, S., van Rossem, L., von Berg, A., Vrijheid, M., Vrijkotte, T.G.M., West, J., Wijga, A., Wright, J., Zvinchuk, O., Sørensen, T.I.A., Lawlor, D.A., Gaillard, R., Jaddoe, V.W.V., Voerman, E., Santos, S., Patro Golab, B., Amiano, P., Ballester, F., Barros, H., Bergström, A., Charles, M.-A., Chatzi, L., Chevrier, C., Chrousos, G.P., Corpeleijn, E., Costet, N., Crozier, S., Devereux, G., Eggesbø, M., Ekström, S., Fantini, M.P., Farchi, S., Forastiere, F., Georgiu, V., Godfrey, K.M., Gori, D., Grote, V., Hanke, W., Hertz-Picciotto, I., Heude, B., Hryhorczuk, D., Huang, R.-C., Inskip, H., Iszatt, N., Karvonen, A.M., Kenny, L.C., Koletzko, B., Küpers, L.K., Lagström, H., Lehmann, Irina, Magnus, P., Majewska, R., Mäkelä, J., Manios, Y., McAuliffe, F.M., McDonald, S.W., Mehegan, J., Mommers, M., Morgen, C.S., Mori, T.A., Moschonis, G., Murray, D., Ní Chaoimh, C., Nohr, E.A., Nybo Andersen, A.-M., Oken, E., Oostvogels, A.J.J.M., Pac, A., Papadopoulou, E., Pekkanen, J., Pizzi, C., Polanska, K., Porta, D., Richiardi, L., Rifas-Shiman, S.-L., Ronfani, L., Santos, A.C., Standl, M., Stoltenberg, C., Thiering, E., Thijs, C., Torrent, M., Tough, S.C., Trnovec, T., Turner, S., van Rossem, L., von Berg, A., Vrijheid, M., Vrijkotte, T.G.M., West, J., Wijga, A., Wright, J., Zvinchuk, O., Sørensen, T.I.A., Lawlor, D.A., Gaillard, R., and Jaddoe, V.W.V.
- Abstract
BackgroundMaternal obesity and excessive gestational weight gain may have persistent effects on offspring fat development. However, it remains unclear whether these effects differ by severity of obesity, and whether these effects are restricted to the extremes of maternal body mass index (BMI) and gestational weight gain. We aimed to assess the separate and combined associations of maternal BMI and gestational weight gain with the risk of overweight/obesity throughout childhood, and their population impact. Methods and findingsWe conducted an individual participant data meta-analysis of data from 162,129 mothers and their children from 37 pregnancy and birth cohort studies from Europe, North America, and Australia. We assessed the individual and combined associations of maternal pre-pregnancy BMI and gestational weight gain, both in clinical categories and across their full ranges, with the risks of overweight/obesity in early (2.0–5.0 years), mid (5.0–10.0 years) and late childhood (10.0–18.0 years), using multilevel binary logistic regression models with a random intercept at cohort level adjusted for maternal sociodemographic and lifestyle-related characteristics. We observed that higher maternal pre-pregnancy BMI and gestational weight gain both in clinical categories and across their full ranges were associated with higher risks of childhood overweight/obesity, with the strongest effects in late childhood (odds ratios [ORs] for overweight/obesity in early, mid, and late childhood, respectively: OR 1.66 [95% CI: 1.56, 1.78], OR 1.91 [95% CI: 1.85, 1.98], and OR 2.28 [95% CI: 2.08, 2.50] for maternal overweight; OR 2.43 [95% CI: 2.24, 2.64], OR 3.12 [95% CI: 2.98, 3.27], and OR 4.47 [95% CI: 3.99, 5.23] for maternal obesity; and OR 1.39 [95% CI: 1.30, 1.49], OR 1.55 [95% CI: 1.49, 1.60], and OR 1.72 [95% CI: 1.56, 1.91] for excessive gestational weight gain). The proportions of childhood overweight/obesity prevalence attributable to maternal overweight, maternal
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- 2019
16. Gestational weight gain charts for different body mass index groups for women in Europe, North America, and Oceania
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Santos, S. Eekhout, I. Voerman, E. Gaillard, R. Barros, H. Charles, M.-A. Chatzi, L. Chevrier, C. Chrousos, G.P. Corpeleijn, E. Costet, N. Crozier, S. Doyon, M. Eggesbø, M. Fantini, M.P. Farchi, S. Forastiere, F. Gagliardi, L. Georgiu, V. Godfrey, K.M. Gori, D. Grote, V. Hanke, W. Hertz-Picciotto, I. Heude, B. Hivert, M.-F. Hryhorczuk, D. Huang, R.-C. Inskip, H. Jusko, T.A. Karvonen, A.M. Koletzko, B. Küpers, L.K. Lagström, H. Lawlor, D.A. Lehmann, I. Lopez-Espinosa, M.-J. Magnus, P. Majewska, R. Mäkelä, J. Manios, Y. McDonald, S.W. Mommers, M. Morgen, C.S. Moschonis, G. Murínová, L. Newnham, J. Nohr, E.A. Andersen, A.-M.N. Oken, E. Oostvogels, A.J.J.M. Pac, A. Papadopoulou, E. Pekkanen, J. Pizzi, C. Polanska, K. Porta, D. Richiardi, L. Rifas-Shiman, S.L. Roeleveld, N. Santa-Marina, L. Santos, A.C. Smit, H.A. Sørensen, T.I.A. Standl, M. Stanislawski, M. Stoltenberg, C. Thiering, E. Thijs, C. Torrent, M. Tough, S.C. Trnovec, T. Van Gelder, M.M.H.J. Van Rossem, L. Von Berg, A. Vrijheid, M. Vrijkotte, T.G.M. Zvinchuk, O. Van Buuren, S. Jaddoe, V.W.V.
- Abstract
Background: Gestational weight gain differs according to pre-pregnancy body mass index and is related to the risks of adverse maternal and child health outcomes. Gestational weight gain charts for women in different pre-pregnancy body mass index groups enable identification of women and offspring at risk for adverse health outcomes. We aimed to construct gestational weight gain reference charts for underweight, normal weight, overweight, and grades 1, 2 and 3 obese women and to compare these charts with those obtained in women with uncomplicated term pregnancies. Methods: We used individual participant data from 218,216 pregnant women participating in 33 cohorts from Europe, North America, and Oceania. Of these women, 9065 (4.2%), 148,697 (68.1%), 42,678 (19.6%), 13,084 (6.0%), 3597 (1.6%), and 1095 (0.5%) were underweight, normal weight, overweight, and grades 1, 2, and 3 obese women, respectively. A total of 138, 517 women from 26 cohorts had pregnancies with no hypertensive or diabetic disorders and with term deliveries of appropriate for gestational age at birth infants. Gestational weight gain charts for underweight, normal weight, overweight, and grade 1, 2, and 3 obese women were derived by the Box-Cox t method using the generalized additive model for location, scale, and shape. Results: We observed that gestational weight gain strongly differed per maternal pre-pregnancy body mass index group. The median (interquartile range) gestational weight gain at 40 weeks was 14.2 kg (11.4-17.4) for underweight women, 14.5 kg (11.5-17.7) for normal weight women, 13.9 kg (10.1-17.9) for overweight women, and 11.2 kg (7.0-15.7), 8.7 kg (4.3-13.4) and 6.3 kg (1.9-11.1) for grades 1, 2, and 3 obese women, respectively. The rate of weight gain was lower in the first half than in the second half of pregnancy. No differences in the patterns of weight gain were observed between cohorts or countries. Similar weight gain patterns were observed in mothers without pregnancy complications. Conclusions: Gestational weight gain patterns are strongly related to pre-pregnancy body mass index. The derived charts can be used to assess gestational weight gain in etiological research and as a monitoring tool for weight gain during pregnancy in clinical practice. © 2018 The Author(s).
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- 2018
17. Rare and Common Variants Conferring Risk of Tooth Agenesis
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Jonsson, L., Magnusson, T.E., Thordarson, A., Jonsson, T., Geller, F., Feenstra, B., Melbye, M., Nohr, E.A., Vucic, S., Dhamo, B., Rivadeneira, F., Ongkosuwito, E.M., Wolvius, E.B., Leslie, E.J., Marazita, M.L., Howe, B.J., Uribe, L.M. Moreno, Alonso, I., Santos, M., Pinho, T., Jonsson, R., Audolfsson, G., Gudmundsson, L., Nawaz, M.S., Olafsson, S., Gustafsson, O., Ingason, A., Unnsteinsdottir, U., Bjornsdottir, G., Walters, G.B., Zervas, M., Oddsson, A., Gudbjartsson, D.F., Steinberg, S., Stefansson, H., Stefansson, K., Jonsson, L., Magnusson, T.E., Thordarson, A., Jonsson, T., Geller, F., Feenstra, B., Melbye, M., Nohr, E.A., Vucic, S., Dhamo, B., Rivadeneira, F., Ongkosuwito, E.M., Wolvius, E.B., Leslie, E.J., Marazita, M.L., Howe, B.J., Uribe, L.M. Moreno, Alonso, I., Santos, M., Pinho, T., Jonsson, R., Audolfsson, G., Gudmundsson, L., Nawaz, M.S., Olafsson, S., Gustafsson, O., Ingason, A., Unnsteinsdottir, U., Bjornsdottir, G., Walters, G.B., Zervas, M., Oddsson, A., Gudbjartsson, D.F., Steinberg, S., Stefansson, H., and Stefansson, K.
- Abstract
Item does not contain fulltext, We present association results from a large genome-wide association study of tooth agenesis (TA) as well as selective TA, including 1,944 subjects with congenitally missing teeth, excluding third molars, and 338,554 controls, all of European ancestry. We also tested the association of previously identified risk variants, for timing of tooth eruption and orofacial clefts, with TA. We report associations between TA and 9 novel risk variants. Five of these variants associate with selective TA, including a variant conferring risk of orofacial clefts. These results contribute to a deeper understanding of the genetic architecture of tooth development and disease. The few variants previously associated with TA were uncovered through candidate gene studies guided by mouse knockouts. Knowing the etiology and clinical features of TA is important for planning oral rehabilitation that often involves an interdisciplinary approach.
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- 2018
18. Consortium-based genome-wide meta-analysis for childhood dental caries traits.
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Haworth, S., Shungin, D., Tas, J.T. van der, Vucic, S., Medina-Gomez, C., Yakimov, V., Feenstra, B., Shaffer, J.R., Lee, M.K., Standl, M., Thiering, E., Wang, C, Bonnelykke, K., Waage, J., Jessen, L.E., Norrisgaard, P.E., Joro, R., Seppala, I., Raitakari, O., Dudding, T., Grgic, O., Ongkosuwito, E.M., Vierola, A., Eloranta, A.M., West, N.X., Thomas, S.J., McNeil, D.W., Levy, S.M., Slayton, R., Nohr, E.A., Lehtimaki, T., Lakka, T., Bisgaard, H., Pennell, C., Kuhnisch, J., Marazita, M.L., Melbye, M., Geller, F., Rivadeneira, F., Wolvius, E.B., Franks, P.W., Johansson, I., Timpson, N.J., Haworth, S., Shungin, D., Tas, J.T. van der, Vucic, S., Medina-Gomez, C., Yakimov, V., Feenstra, B., Shaffer, J.R., Lee, M.K., Standl, M., Thiering, E., Wang, C, Bonnelykke, K., Waage, J., Jessen, L.E., Norrisgaard, P.E., Joro, R., Seppala, I., Raitakari, O., Dudding, T., Grgic, O., Ongkosuwito, E.M., Vierola, A., Eloranta, A.M., West, N.X., Thomas, S.J., McNeil, D.W., Levy, S.M., Slayton, R., Nohr, E.A., Lehtimaki, T., Lakka, T., Bisgaard, H., Pennell, C., Kuhnisch, J., Marazita, M.L., Melbye, M., Geller, F., Rivadeneira, F., Wolvius, E.B., Franks, P.W., Johansson, I., and Timpson, N.J.
- Abstract
Contains fulltext : 200710.pdf (Publisher’s version ) (Open Access), Prior studies suggest dental caries traits in children and adolescents are partially heritable, but there has been no large-scale consortium genome-wide association study (GWAS) to date. We therefore performed GWAS for caries in participants aged 2.5-18.0 years from nine contributing centres. Phenotype definitions were created for the presence or absence of treated or untreated caries, stratified by primary and permanent dentition. All studies tested for association between caries and genotype dosage and the results were combined using fixed-effects meta-analysis. Analysis included up to 19 003 individuals (7530 affected) for primary teeth and 13 353 individuals (5875 affected) for permanent teeth. Evidence for association with caries status was observed at rs1594318-C for primary teeth [intronic within ALLC, odds ratio (OR) 0.85, effect allele frequency (EAF) 0.60, P 4.13e-8] and rs7738851-A (intronic within NEDD9, OR 1.28, EAF 0.85, P 1.63e-8) for permanent teeth. Consortium-wide estimated heritability of caries was low [h2 of 1% (95% CI: 0%: 7%) and 6% (95% CI 0%: 13%) for primary and permanent dentitions, respectively] compared with corresponding within-study estimates [h2 of 28% (95% CI: 9%: 48%) and 17% (95% CI: 2%: 31%)] or previously published estimates. This study was designed to identify common genetic variants with modest effects which are consistent across different populations. We found few single variants associated with caries status under these assumptions. Phenotypic heterogeneity between cohorts and limited statistical power will have contributed; these findings could also reflect complexity not captured by our study design, such as genetic effects which are conditional on environmental exposure.
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- 2018
19. Gestational weight gain charts for different body mass index groups for women in Europe, North America, and Oceania
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Santos, S., Eekhout, I., Voerman, I., Gaillard, R., Barros, H., Charles, M.-A., Chatzi, L., Chevrier, C., Chrousos, G.P., Corpeleijn, E., Costet, N., Crozier, S., Doyon, M., Eggesbø, M., Fantini, M.P., Farchi, S., Forastiere, F., Gagliardi, L., Georgiu, V., Godfrey, K.M., Gori, D., Grote, V., Hanke, W., Hertz-Picciotto, I., Heude, B., Hivert, M.-F., Hryhorczuk, D., Huang, R.-C., Inskip, H., Jusko, T.A., Karvonen, A.M., Koletzko, B., Küpers, L.K., Lagström, H., Lawlor, D.A., Lehmann, Irina, Lopez-Espinosa, M.-J., Magnus, P., Majewska, R., Mäkelä, J., Manios, Y., McDonald, S.W., Mommers, M., Morgen, C.S., Moschonis, G., Murínová, L., Newnham, J., Nohr, E.A., Nybo Andersen, A.-M., Oken, E., Oostvogels, A.J.J.M., Pac, A., Papadopoulou, E., Pekkanen, J., Pizzi, C., Polanska, K., Porta, D., Richiardi, L., Rifas-Shiman, S.-L., Roeleveld, N., Santa-Marina, L., Santos, A.C., Smit, H.A., Sørensen, T.I.A., Standl, M., Stanislawski, M., Stoltenberg, C., Thiering, E., Thijs, C., Torrent, M., Tough, S.C., Trnovec, T., van Gelder, M.M.H.J., van Rossem, L., von Berg, A., Vrijheid, M., Vrijkotte, T.G.M., Zvinchuk, O., van Buuren, S., Jaddoe, V.W.V., Santos, S., Eekhout, I., Voerman, I., Gaillard, R., Barros, H., Charles, M.-A., Chatzi, L., Chevrier, C., Chrousos, G.P., Corpeleijn, E., Costet, N., Crozier, S., Doyon, M., Eggesbø, M., Fantini, M.P., Farchi, S., Forastiere, F., Gagliardi, L., Georgiu, V., Godfrey, K.M., Gori, D., Grote, V., Hanke, W., Hertz-Picciotto, I., Heude, B., Hivert, M.-F., Hryhorczuk, D., Huang, R.-C., Inskip, H., Jusko, T.A., Karvonen, A.M., Koletzko, B., Küpers, L.K., Lagström, H., Lawlor, D.A., Lehmann, Irina, Lopez-Espinosa, M.-J., Magnus, P., Majewska, R., Mäkelä, J., Manios, Y., McDonald, S.W., Mommers, M., Morgen, C.S., Moschonis, G., Murínová, L., Newnham, J., Nohr, E.A., Nybo Andersen, A.-M., Oken, E., Oostvogels, A.J.J.M., Pac, A., Papadopoulou, E., Pekkanen, J., Pizzi, C., Polanska, K., Porta, D., Richiardi, L., Rifas-Shiman, S.-L., Roeleveld, N., Santa-Marina, L., Santos, A.C., Smit, H.A., Sørensen, T.I.A., Standl, M., Stanislawski, M., Stoltenberg, C., Thiering, E., Thijs, C., Torrent, M., Tough, S.C., Trnovec, T., van Gelder, M.M.H.J., van Rossem, L., von Berg, A., Vrijheid, M., Vrijkotte, T.G.M., Zvinchuk, O., van Buuren, S., and Jaddoe, V.W.V.
- Abstract
BackgroundGestational weight gain differs according to pre-pregnancy body mass index and is related to the risks of adverse maternal and child health outcomes. Gestational weight gain charts for women in different pre-pregnancy body mass index groups enable identification of women and offspring at risk for adverse health outcomes. We aimed to construct gestational weight gain reference charts for underweight, normal weight, overweight, and grades 1, 2 and 3 obese women and to compare these charts with those obtained in women with uncomplicated term pregnancies.MethodsWe used individual participant data from 218,216 pregnant women participating in 33 cohorts from Europe, North America, and Oceania. Of these women, 9065 (4.2%), 148,697 (68.1%), 42,678 (19.6%), 13,084 (6.0%), 3597 (1.6%), and 1095 (0.5%) were underweight, normal weight, overweight, and grades 1, 2, and 3 obese women, respectively. A total of 138, 517 women from 26 cohorts had pregnancies with no hypertensive or diabetic disorders and with term deliveries of appropriate for gestational age at birth infants. Gestational weight gain charts for underweight, normal weight, overweight, and grade 1, 2, and 3 obese women were derived by the Box-Cox t method using the generalized additive model for location, scale, and shape.ResultsWe observed that gestational weight gain strongly differed per maternal pre-pregnancy body mass index group. The median (interquartile range) gestational weight gain at 40 weeks was 14.2 kg (11.4–17.4) for underweight women, 14.5 kg (11.5–17.7) for normal weight women, 13.9 kg (10.1–17.9) for overweight women, and 11.2 kg (7.0–15.7), 8.7 kg (4.3–13.4) and 6.3 kg (1.9–11.1) for grades 1, 2, and 3 obese women, respectively. The rate of weight gain was lower in the first half than in the second half of pregnancy. No differences in the patterns of weight gain were observed between cohorts or countries. Similar weight gain pat
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- 2018
20. Rare and Common Variants Conferring Risk of Tooth Agenesis
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Jonsson, L., primary, Magnusson, T.E., additional, Thordarson, A., additional, Jonsson, T., additional, Geller, F., additional, Feenstra, B., additional, Melbye, M., additional, Nohr, E.A., additional, Vucic, S., additional, Dhamo, B., additional, Rivadeneira, F., additional, Ongkosuwito, E.M., additional, Wolvius, E.B., additional, Leslie, E.J., additional, Marazita, M.L., additional, Howe, B.J., additional, Moreno Uribe, L.M., additional, Alonso, I., additional, Santos, M., additional, Pinho, T., additional, Jonsson, R., additional, Audolfsson, G., additional, Gudmundsson, L., additional, Nawaz, M.S., additional, Olafsson, S., additional, Gustafsson, O., additional, Ingason, A., additional, Unnsteinsdottir, U., additional, Bjornsdottir, G., additional, Walters, G.B., additional, Zervas, M., additional, Oddsson, A., additional, Gudbjartsson, D.F., additional, Steinberg, S., additional, Stefansson, H., additional, and Stefansson, K., additional
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- 2018
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21. Heavier smoking may lead to a relative increase in waist circumference: Evidence for a causal relationship from a Mendelian randomisation meta-analysis. The CARTA consortium
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Morris, R.W., Taylor, A.E., Fluharty, M.E., Bjorngaard, J.H., Asvold, B.O., Elvestad Gabrielsen, M., Campbell, A., Marioni, R., Kumari, M., Korhonen, T., Männistö, S., Marques-Vidal, P., Kaakinen, M., Cavadino, A., Postmus, I., Husemoen, L.L.N., Skaaby, T., Ahluwalia, T.S., Treur, J.L., Willemsen, G., Dale, C., Wannamethee, S.G., Lahti, J., Palotie, A., Räikkönen, K., McConnachie, A., Padmanabhan, S., Wong, A., Dalgard, C., Paternoster, L., Ben-Shlomo, Y., Tyrrell, J., Horwood, J., Fergusson, D.M., Kennedy, M.A., Nohr, E.A., Christiansen, L., Kyvik, K.O., Kuh, D, Watt, G., Eriksson, J.G., Whincup, P.H., Vink, J.M., Boomsma, D.I., Davey Smith, G., Lawlor, D., Linneberg, A., Ford, I., Jukema, J.W., Power, C., Hyppönen, E., Jarvelin, M.R., Preisig, M., Borodulin, K., Kaprio, J., Kivimaki, M., Smith, B.H., Hayward, C., Romundstad, P.R., Sørensen, T.I.A., Munafò, M., Sattar, N., Medical Research Council (MRC), Biological Psychology, Neuroscience Campus Amsterdam - Neurobiology of Mental Health, and EMGO+ - Lifestyle, Overweight and Diabetes
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Adult ,Male ,Netherlands Twin Register (NTR) ,Adolescent ,GENETICS ,Aged ,Body Mass Index ,Female ,Humans ,Mendelian Randomization Analysis ,Middle Aged ,Obesity, Abdominal/complications ,Sex Factors ,Smoking/adverse effects ,Smoking/genetics ,Waist Circumference ,Waist-Hip Ratio ,Young Adult ,Brain and Behaviour ,Medicine, General & Internal ,SDG 3 - Good Health and Well-being ,General & Internal Medicine ,EPIDEMIOLOGY ,CORONARY-HEART-DISEASE ,WEIGHT CONCERNS ,Smoking and Tobacco ,Science & Technology ,MORTALITY ,Research ,Tobacco and Alcohol ,Smoking ,WOMEN ,MEN ,ASSOCIATION ,BODY-MASS INDEX ,Obesity, Abdominal ,RISK-FACTORS ,ADIPOSITY ,CIGARETTE-SMOKING ,Life Sciences & Biomedicine ,Developmental Psychopathology - Abstract
OBJECTIVES: To investigate, using a Mendelian randomisation approach, whether heavier smoking is associated with a range of regional adiposity phenotypes, in particular those related to abdominal adiposity.DESIGN: Mendelian randomisation meta-analyses using a genetic variant (rs16969968/rs1051730 in the CHRNA5-CHRNA3-CHRNB4 gene region) as a proxy for smoking heaviness, of the associations of smoking heaviness with a range of adiposity phenotypes.PARTICIPANTS: 148 731 current, former and never-smokers of European ancestry aged ≥16 years from 29 studies in the consortium for Causal Analysis Research in Tobacco and Alcohol (CARTA).PRIMARY OUTCOME MEASURES: Waist and hip circumferences, and waist-hip ratio.RESULTS: The data included up to 66 809 never-smokers, 43 009 former smokers and 38 913 current daily cigarette smokers. Among current smokers, for each extra minor allele, the geometric mean was lower for waist circumference by -0.40% (95% CI -0.57% to -0.22%), with effects on hip circumference, waist-hip ratio and body mass index (BMI) being -0.31% (95% CI -0.42% to -0.19), -0.08% (-0.19% to 0.03%) and -0.74% (-0.96% to -0.51%), respectively. In contrast, among never-smokers, these effects were higher by 0.23% (0.09% to 0.36%), 0.17% (0.08% to 0.26%), 0.07% (-0.01% to 0.15%) and 0.35% (0.18% to 0.52%), respectively. When adjusting the three central adiposity measures for BMI, the effects among current smokers changed direction and were higher by 0.14% (0.05% to 0.22%) for waist circumference, 0.02% (-0.05% to 0.08%) for hip circumference and 0.10% (0.02% to 0.19%) for waist-hip ratio, for each extra minor allele.CONCLUSIONS: For a given BMI, a gene variant associated with increased cigarette consumption was associated with increased waist circumference. Smoking in an effort to control weight may lead to accumulation of central adiposity. OBJECTIVES: To investigate, using a Mendelian randomisation approach, whether heavier smoking is associated with a range of regional adiposity phenotypes, in particular those related to abdominal adiposity.DESIGN: Mendelian randomisation meta-analyses using a genetic variant (rs16969968/rs1051730 in the CHRNA5-CHRNA3-CHRNB4 gene region) as a proxy for smoking heaviness, of the associations of smoking heaviness with a range of adiposity phenotypes.PARTICIPANTS: 148 731 current, former and never-smokers of European ancestry aged ≥16 years from 29 studies in the consortium for Causal Analysis Research in Tobacco and Alcohol (CARTA).PRIMARY OUTCOME MEASURES: Waist and hip circumferences, and waist-hip ratio.RESULTS: The data included up to 66 809 never-smokers, 43 009 former smokers and 38 913 current daily cigarette smokers. Among current smokers, for each extra minor allele, the geometric mean was lower for waist circumference by -0.40% (95% CI -0.57% to -0.22%), with effects on hip circumference, waist-hip ratio and body mass index (BMI) being -0.31% (95% CI -0.42% to -0.19), -0.08% (-0.19% to 0.03%) and -0.74% (-0.96% to -0.51%), respectively. In contrast, among never-smokers, these effects were higher by 0.23% (0.09% to 0.36%), 0.17% (0.08% to 0.26%), 0.07% (-0.01% to 0.15%) and 0.35% (0.18% to 0.52%), respectively. When adjusting the three central adiposity measures for BMI, the effects among current smokers changed direction and were higher by 0.14% (0.05% to 0.22%) for waist circumference, 0.02% (-0.05% to 0.08%) for hip circumference and 0.10% (0.02% to 0.19%) for waist-hip ratio, for each extra minor allele.CONCLUSIONS: For a given BMI, a gene variant associated with increased cigarette consumption was associated with increased waist circumference. Smoking in an effort to control weight may lead to accumulation of central adiposity.
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- 2015
22. Investigating the possible causal association of smoking with depression and anxiety using Mendelian randomisation meta-analysis: the CARTA consortium
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Taylor, A.E., Fluharty, M.E., Björngaard, J.H., Gabrielsen, M.E., Skorpen, F., Marioni, R.E., Campbell, A., Engmann, J., Mirza, S.S., Loukola, A., Laatikainen, T., Partonen, T., Kaakinen, M., Ducci, F., Cavadino, A., Husemoen, L.L.N., Ahluwalia, T.V.S., Jacobsen, R.K., Skaaby, T., Ebstrup, J.F., Mortensen, E.L., Minica, C.C., Vink, J.M., Willemsen, G., Marques-Vidal, P., Dale, C.E., Amuzu, A., Lennon, L.T., Lahti, J., Palotie, A., Raikkonen, K., Wong, A., Paternoster, L., Wong, A.P.Y, Horwood, L.J., Murphy, M., Johnstone, E.C., Kennedy, M.A., Pausova, Z., Paus, T., Ben-Shlomo, Y., Nohr, E.A., Kuh, D., Kivimäki, M., Eriksson, J.G., Morris, R.W., Casas, J.P., Preisig, M., Boomsma, D.I., Linneberg, A., Power, C., Hypponen, E., Veijola, J., Jarvelin, M.R., Korhonen, T., Tiemeier, H., Kumari, M., Porteous, D.J., Hayward, C., Romundstad, P.R., Smith, G.D., Munafò, M.R., Taylor, A.E., Fluharty, M.E., Björngaard, J.H., Gabrielsen, M.E., Skorpen, F., Marioni, R.E., Campbell, A., Engmann, J., Mirza, S.S., Loukola, A., Laatikainen, T., Partonen, T., Kaakinen, M., Ducci, F., Cavadino, A., Husemoen, L.L.N., Ahluwalia, T.V.S., Jacobsen, R.K., Skaaby, T., Ebstrup, J.F., Mortensen, E.L., Minica, C.C., Vink, J.M., Willemsen, G., Marques-Vidal, P., Dale, C.E., Amuzu, A., Lennon, L.T., Lahti, J., Palotie, A., Raikkonen, K., Wong, A., Paternoster, L., Wong, A.P.Y, Horwood, L.J., Murphy, M., Johnstone, E.C., Kennedy, M.A., Pausova, Z., Paus, T., Ben-Shlomo, Y., Nohr, E.A., Kuh, D., Kivimäki, M., Eriksson, J.G., Morris, R.W., Casas, J.P., Preisig, M., Boomsma, D.I., Linneberg, A., Power, C., Hypponen, E., Veijola, J., Jarvelin, M.R., Korhonen, T., Tiemeier, H., Kumari, M., Porteous, D.J., Hayward, C., Romundstad, P.R., Smith, G.D., and Munafò, M.R.
- Abstract
Contains fulltext : 160020.pdf (publisher's version ) (Open Access), Objectives: To investigate whether associations of smoking with depression and anxiety are likely to be causal, using a Mendelian randomisation approach. Design: Mendelian randomisation meta-analyses using a genetic variant (rs16969968/rs1051730) as a proxy for smoking heaviness, and observational meta-analyses of the associations of smoking status and smoking heaviness with depression, anxiety and psychological distress. Participants: Current, former and never smokers of European ancestry aged >= 16 years from 25 studies in the Consortium for Causal Analysis Research in Tobacco and Alcohol (CARTA). Primary outcome measures: Binary definitions of depression, anxiety and psychological distress assessed by clinical interview, symptom scales or self-reported recall of clinician diagnosis. Results: The analytic sample included up to 58 176 never smokers, 37 428 former smokers and 32 028 current smokers (total N=127 632). In observational analyses, current smokers had 1.85 times greater odds of depression (95% CI 1.65 to 2.07), 1.71 times greater odds of anxiety (95% CI 1.54 to 1.90) and 1.69 times greater odds of psychological distress (95% CI 1.56 to 1.83) than never smokers. Former smokers also had greater odds of depression, anxiety and psychological distress than never smokers. There was evidence for positive associations of smoking heaviness with depression, anxiety and psychological distress (ORs per cigarette per day: 1.03 (95% CI 1.02 to 1.04), 1.03 (95% CI 1.02 to 1.04) and 1.02 (95% CI 1.02 to 1.03) respectively). In Mendelian randomisation analyses, there was no strong evidence that the minor allele of rs16969968/rs1051730 was associated with depression (OR=1.00, 95% CI 0.95 to 1.05), anxiety (OR= 1.02, 95% CI 0.97 to 1.07) or psychological distress (OR= 1.02, 95% CI 0.98 to 1.06) in current smokers. Results were similar for former smokers. Conclusions: Findings from Mendelian randomisation analyses do not support a causal role of smoking heaviness in the dev
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- 2014
23. Stratification by smoking status reveals an association of CHRNA5-A3-B4 genotype with body mass index in never smokers
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Taylor, A.E., Morris, R.W., Fluharty, M.E., Björngaard, J.H., Asvold, B.A., Gabrielsen, M.E., Campbell, A., Marioni, R.E., Kumari, M., Hällfors, J., Mannisto, S., Marques-Vidal, P., Kaakinen, M., Cavadino, A., Postmus, I., Husemoen, L.L.N., Skaaby, T., Ahluwalia, T.V.S., Treur, J.L., Willemsen, G., Dale, C.E., Wannamethee, S.G., Lahti, J., Palotie, A., Raikkonen, K., Kisialiou, A., McConnachie, A., Padmanabhan, S., Wong, A., Dalgard, C., Paternoster, L., Ben-Shlomo, Y., Tyrrell, J., Horwood, J., Fergusson, D.M., Kennedy, M.A., Frayling, T., Nohr, E.A., Christiansen, L., Kyvik, K.O., Kuh, D., Watt, G., Eriksson, J., Whincup, P.H., Vink, J.M., Boomsma, D.I., Smith, G.D., Lawlor, D.A., Linneberg, A., Ford, I., Jukema, J.W., Power, C., Hypponen, E., Jarvelin, M.R., Preisig, M., Borodulin, K., Kaprio, J., Kivimäki, M., Smith, B.H., Hayward, C., Romundstad, P.R., Sorensen, T.I.A., Munafò, M.R., Sattar, N., Taylor, A.E., Morris, R.W., Fluharty, M.E., Björngaard, J.H., Asvold, B.A., Gabrielsen, M.E., Campbell, A., Marioni, R.E., Kumari, M., Hällfors, J., Mannisto, S., Marques-Vidal, P., Kaakinen, M., Cavadino, A., Postmus, I., Husemoen, L.L.N., Skaaby, T., Ahluwalia, T.V.S., Treur, J.L., Willemsen, G., Dale, C.E., Wannamethee, S.G., Lahti, J., Palotie, A., Raikkonen, K., Kisialiou, A., McConnachie, A., Padmanabhan, S., Wong, A., Dalgard, C., Paternoster, L., Ben-Shlomo, Y., Tyrrell, J., Horwood, J., Fergusson, D.M., Kennedy, M.A., Frayling, T., Nohr, E.A., Christiansen, L., Kyvik, K.O., Kuh, D., Watt, G., Eriksson, J., Whincup, P.H., Vink, J.M., Boomsma, D.I., Smith, G.D., Lawlor, D.A., Linneberg, A., Ford, I., Jukema, J.W., Power, C., Hypponen, E., Jarvelin, M.R., Preisig, M., Borodulin, K., Kaprio, J., Kivimäki, M., Smith, B.H., Hayward, C., Romundstad, P.R., Sorensen, T.I.A., Munafò, M.R., and Sattar, N.
- Abstract
Contains fulltext : 155640.PDF (publisher's version ) (Open Access), We previously used a single nucleotide polymorphism (SNP) in the CHRNA5-A3-B4 gene cluster associated with heaviness of smoking within smokers to confirm the causal effect of smoking in reducing body mass index (BMI) in a Mendelian randomisation analysis. While seeking to extend these findings in a larger sample we found that this SNP is associated with 0.74% lower body mass index (BMI) per minor allele in current smokers (95% CI -0.97 to -0.51, P = 2.00x10(-10)), but also unexpectedly found that it was associated with 0.35% higher BMI in never smokers (95% CI + 0.18 to + 0.52, P = 6.38x10(-5)). An interaction test confirmed that these estimates differed from each other (P = 4.95x10(-13)). This difference in effects suggests the variant influences BMI both via pathways unrelated to smoking, and via the weight-reducing effects of smoking. It would therefore be essentially undetectable in an unstratified genome-wide association study of BMI, given the opposite association with BMI in never and current smokers. This demonstrates that novel associations may be obscured by hidden population sub-structure. Stratification on well-characterized environmental factors known to impact on health outcomes may therefore reveal novel genetic associations.
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- 2014
24. Self-Hypnosis for Coping With Labor Pain
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Werner, A., primary, Uldbjerg, N., additional, Zachariae, R., additional, Rosen, G., additional, and Nohr, E.A., additional
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- 2014
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25. Combined associations of prepregnancy body mass index and gestational weight gain with the outcome of pregnancy
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Nohr, E.A., Vaeth, M., Baker, J.L., Sørensen, Thorkild I.A., Olsen, J., Rasmussen, K.M., Nohr, E.A., Vaeth, M., Baker, J.L., Sørensen, Thorkild I.A., Olsen, J., and Rasmussen, K.M.
- Abstract
BACKGROUND: Although both maternal prepregnancy body mass index (BMI) and gestational weight gain (GWG) may affect birth weight, their separate and joint associations with complications of pregnancy and delivery and with postpartum weight retention are unclear. OBJECTIVES: We aimed to investigate the combined associations of prepregnancy BMI and GWG with pregnancy outcomes and to evaluate the trade-offs between mother and infant for different weight gains. DESIGN: Data for 60892 term pregnancies in the Danish National Birth Cohort were linked to birth and hospital discharge registers. Self-reported total GWG was categorized as low (<10 kg), medium (10-15 kg), high (16-19 kg), or very high (>or=20 kg). Adjusted associations of prepregnancy BMI and GWG with outcomes of interest were estimated by logistic regression analyses. RESULTS: High and very high GWG added to the associations of high prepregnancy BMI with cesarean delivery and were strongly associated with high postpartum weight retention. Moreover, greater weight gains and high maternal BMI decreased the risk of growth restriction and increased the risk of the infant's being born large-for-gestational-age or with a low Apgar score. Generally, low GWG was advantageous for the mother, but it increased the risk of having a small baby, particularly for underweight women. CONCLUSIONS: Heavier women may benefit from avoiding high and very high GWG, which brings only a slight increase in the risk of growth restriction for the infant. High weight gain in underweight women does not appear to have deleterious consequences for them or their infants, but they may want to avoid low GWG to prevent having a small baby Udgivelsesdato: 2008/6
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- 2008
26. How is pregnancy‐related weight changes and breastfeeding related to long‐term maternal weight and waist circumference? A path analysis
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Kirkegaard, Helene, primary, Stovring, H, additional, Rasmussen, K.M., additional, Abrams, B, additional, Sorensen, T.I.A., additional, and Nohr, E.A., additional
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- 2013
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27. Mode of Delivery After Epidural Analgesia in a Cohort of Low-risk Nulliparas
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Eriksen, L.M., primary, Nohr, E.A., additional, and Kjaergaard, H., additional
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- 2012
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28. Health of Children Born to Mothers who had Preeclampsia
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Wu, C.S., primary, Nohr, E.A., additional, Bech, B.H., additional, Vestergaard, M., additional, Catov, J.M., additional, and Olsen, J., additional
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- 2010
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29. Waiting time to pregnancy according to maternal birthweight and prepregnancy BMI
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Nohr, E.A., primary, Vaeth, M., additional, Rasmussen, S., additional, Ramlau-Hansen, C.H., additional, and Olsen, J., additional
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- 2008
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30. Changes in parental smoking during pregnancy and risks of adverse birth outcomes and childhood overweight in Europe and North America
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Andrea von Berg, Per Magnus, Camilla Stoltenberg, George P. Chrousos, Cécile Chevrier, Costanza Pizzi, Marleen M.H.J. van Gelder, Tanja G. M. Vrijkotte, Oleksandr Zvinchuk, Elise M. Philips, Daniel O. Hryhorczuk, Vincent W. V. Jaddoe, Philippa K Bird, Deirdre M. Murray, Elisabeth Thiering, Marie Standl, Merete Eggesbø, Sara Farchi, Daniela Porta, Lorenzo Richiardi, Maria Pia Fantini, Francesco Forastiere, Carel Thijs, Vagelis Georgiu, Camilla Schmidt Morgen, Yannis Manios, Leda Chatzi, Henrique Barros, Irina Lehmann, Juan J. Aurrekoetxea, Thorkild I. A. Sørensen, Juha Pekkanen, Emily Oken, Adriette J. J. M. Oostvogels, Nel Roeleveld, Jordi Sunyer, Anne-Marie Nybo Andersen, Ellen A. Nohr, Romy Gaillard, Anna Bergström, Sheryl L. Rifas-Shiman, George Moschonis, Monique Mommers, Ana Cristina Santos, Hazel Inskip, Sonia Brescianini, Wojciech Hanke, Kinga Polańska, Louise C. Kenny, Leonardo Trasande, Debbie A Lawlor, Inger Kull, Anne M. Karvonen, Nathalie Costet, Marie-Aline Charles, Susana Santos, Sarah Crozier, John Wright, Barbara Heude, Carmen Iñiguez, Erik Melén, Maties Torrent, Davide Gori, Rachel Criswell, Eleni Papadopoulou, Franca Rusconi, Keith M. Godfrey, Carol Ní Chaoimh, Centre de Recherche Épidémiologie et Statistique Sorbonne Paris Cité (CRESS (U1153 / UMR_A_1125 / UMR_S_1153)), Conservatoire National des Arts et Métiers [CNAM] (CNAM)-Université Sorbonne Paris Cité (USPC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Paris (UP)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), European Commission733206United States Department of Health & Human ServicesNational Institutes of Health (NIH) - USAR01ES022972United States Department of Health & Human ServicesNational Institutes of Health (NIH) - USANIH National Institute of Environmental Health Sciences (NIEHS)P30ES007048R21ES029681R01ES029944R01ES030364R21ES028903UK MRC fundingMC_UU_12013/5Portuguese Foundation for Science and TechnologyEuropean CommissionIF/01060/2015Netherlands Heart Foundation2017T013Dutch Diabetes Foundation2017.81.002Netherlands Organization for Health Research and Development543003109European Research Council (ERC)European CommissionERC-2014-CoG-64891, Epidemiologie, RS: CAPHRI - R5 - Optimising Patient Care, Philips E.M., Santos S., Trasande L., Aurrekoetxea J.J., Barros H., von Berg A., Bergstrom A., Bird P.K., Brescianini S., Chaoimh C.N., Charles M.-A., Chatzi L., Chevrier C., Chrousos G.P., Costet N., Criswell R., Crozier S., Eggesbo M., Fantini M.P., Farchi S., Forastiere F., van Gelder M.M.H.J., Georgiu V., Godfrey K.M., Gori D., Hanke W., Heude B., Hryhorczuk D., Iniguez C., Inskip H., Karvonen A.M., Kenny L.C., Kull I., Lawlor D.A., Lehmann I., Magnus P., Manios Y., Melen E., Mommers M., Morgen C.S., Moschonis G., Murray D., Nohr E.A., Nybo Andersen A.-M., Oken E., Oostvogels A.J.J.M., Papadopoulou E., Pekkanen J., Pizzi C., Polanska K., Porta D., Richiardi L., Rifas-Shiman S.L., Roeleveld N., Rusconi F., Santos A.C., Sorensen T.I.A., Standl M., Stoltenberg C., Sunyer J., Thiering E., Thijs C., Torrent M., Vrijkotte T.G.M., Wright J., Zvinchuk O., Gaillard R., Jaddoe V.W.V., Department of Public Health, University of Helsinki, Instituto de Saúde Pública da Universidade do Porto, Erasmus MC other, Pediatrics, Graduate School, Public and occupational health, APH - Aging & Later Life, APH - Health Behaviors & Chronic Diseases, ARD - Amsterdam Reproduction and Development, and APH - Methodology
- Subjects
Male ,Parents ,embarazo ,Epidemiology ,Maternal Health ,Social Sciences ,CHILDREN ,0302 clinical medicine ,Pregnancy ,nacimiento prematuro ,Smoking/adverse effects ,Psychology ,MATERNAL SMOKING ,estudios de cohortes ,Body mass index ,education.field_of_study ,General Medicine ,ASSOCIATION ,16. Peace & justice ,3. Good health ,Prenatal Exposure Delayed Effects ,Medicine ,GROWTH ,efectos diferidos por exposición prenatal ,Cohort study ,Human ,PRETERM BIRTH ,Europe/epidemiology ,03 medical and health sciences ,Humans ,Smoking habits ,Risk factor ,education ,Behavior ,Biology and Life Sciences ,Infant ,Odds ratio ,hábito de fumar ,medicine.disease ,Pregnancy Complications ,CESSATION ,Demography ,Pediatric Obesity ,Physiology ,humanos ,030204 cardiovascular system & hematology ,Overweight ,North America/epidemiology ,Cohort Studies ,Habits ,Risk Factors ,Medicine and Health Sciences ,030212 general & internal medicine ,DNA METHYLATION ,Smoking ,Obstetrics and Gynecology ,Gestational age ,edad gestacional ,Prenatal Exposure Delayed Effects/diagnosis ,3142 Public health care science, environmental and occupational health ,obesidad pediátrica ,Pediatric Obesity/diagnosis ,Europe ,Physiological Parameters ,Female ,Gestational Age ,Infant, Newborn ,North America ,Premature Birth ,OBESITY ,medicine.symptom ,Research Article ,Birth weight ,Population ,Premature Birth/diagnosis ,padres ,Prenatal Exposure Delayed Effect ,Healthcare improvement science Radboud Institute for Health Sciences [Radboudumc 18] ,All institutes and research themes of the Radboud University Medical Center ,medicine ,factores de riesgo ,EXPOSURE ,lactante ,business.industry ,Risk Factor ,Body Weight ,Newborn ,Reconstructive and regenerative medicine Radboud Institute for Health Sciences [Radboudumc 10] ,Medical risk factors ,3121 General medicine, internal medicine and other clinical medicine ,Birth ,Women's Health ,WEIGHT ,Cohort Studie ,business ,[SDV.MHEP]Life Sciences [q-bio]/Human health and pathology - Abstract
Background Fetal smoke exposure is a common and key avoidable risk factor for birth complications and seems to influence later risk of overweight. It is unclear whether this increased risk is also present if mothers smoke during the first trimester only or reduce the number of cigarettes during pregnancy, or when only fathers smoke. We aimed to assess the associations of parental smoking during pregnancy, specifically of quitting or reducing smoking and maternal and paternal smoking combined, with preterm birth, small size for gestational age, and childhood overweight. Methods and findings We performed an individual participant data meta-analysis among 229,158 families from 28 pregnancy/birth cohorts from Europe and North America. All 28 cohorts had information on maternal smoking, and 16 also had information on paternal smoking. In total, 22 cohorts were population-based, with birth years ranging from 1991 to 2015. The mothers’ median age was 30.0 years, and most mothers were medium or highly educated. We used multilevel binary logistic regression models adjusted for maternal and paternal sociodemographic and lifestyle-related characteristics. Compared with nonsmoking mothers, maternal first trimester smoking only was not associated with adverse birth outcomes but was associated with a higher risk of childhood overweight (odds ratio [OR] 1.17 [95% CI 1.02–1.35], P value = 0.030). Children from mothers who continued smoking during pregnancy had higher risks of preterm birth (OR 1.08 [95% CI 1.02–1.15], P value = 0.012), small size for gestational age (OR 2.15 [95% CI 2.07–2.23], P value < 0.001), and childhood overweight (OR 1.42 [95% CI 1.35–1.48], P value < 0.001). Mothers who reduced the number of cigarettes between the first and third trimester, without quitting, still had a higher risk of small size for gestational age. However, the corresponding risk estimates were smaller than for women who continued the same amount of cigarettes throughout pregnancy (OR 1.89 [95% CI 1.52–2.34] instead of OR 2.20 [95% CI 2.02–2.42] when reducing from 5–9 to ≤4 cigarettes/day; OR 2.79 [95% CI 2.39–3.25] and OR 1.93 [95% CI 1.46–2.57] instead of OR 2.95 [95% CI 2.75–3.15] when reducing from ≥10 to 5–9 and ≤4 cigarettes/day, respectively [P values < 0.001]). Reducing the number of cigarettes during pregnancy did not affect the risks of preterm birth and childhood overweight. Among nonsmoking mothers, paternal smoking was associated with childhood overweight (OR 1.21 [95% CI 1.16–1.27], P value < 0.001) but not with adverse birth outcomes. Limitations of this study include the self-report of parental smoking information and the possibility of residual confounding. As this study only included participants from Europe and North America, results need to be carefully interpreted regarding other populations. Conclusions We observed that as compared to nonsmoking during pregnancy, quitting smoking in the first trimester is associated with the same risk of preterm birth and small size for gestational age, but with a higher risk of childhood overweight. Reducing the number of cigarettes, without quitting, has limited beneficial effects. Paternal smoking seems to be associated, independently of maternal smoking, with the risk of childhood overweight. Population strategies should focus on parental smoking prevention before or at the start, rather than during, pregnancy., Elise Philips and co-workers investigate parental smoking and associated birth and child outcomes., Author summary Why was this study done? Maternal smoking during pregnancy is an important risk factor for various birth complications and childhood overweight. It is not clear whether this increased risk is also present if mothers smoke during the first trimester only or reduce the number of cigarettes during pregnancy. The associations of paternal smoking with birth and childhood outcomes also remain unknown. What did the researchers do and find? We conducted an individual participant data meta-analysis using data from 229,158 families from 28 pregnancy and birth cohorts from Europe and North America to assess the associations of parental smoking during pregnancy, specifically of quitting or reducing smoking and maternal and paternal smoking combined, with preterm birth, small size for gestational age, and childhood overweight. We observed that smoking in the first trimester only did not increase the risk of preterm birth and small size for gestational age but was associated with a higher risk of childhood overweight, as compared to nonsmoking. Reducing the number of cigarettes during pregnancy, without quitting, was still associated with higher risks of these adverse outcomes. Paternal smoking seems to be associated, independently of maternal smoking, with the risks of childhood overweight. What do these findings mean? Population strategies should focus on parental smoking prevention before or at the start of, rather than during, pregnancy. Future studies are needed to assess the specific associations of smoking in the preconception and childhood periods with offspring outcomes.
- Published
- 2020
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