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- Parental education and genetics of BMI from infancy to old age: a pooled analysis of 29 twin cohortsPublication . Silventoinen, Karri; Jelenkovic, Aline; Latvala, Antti; Yokoyama, Yoshie; Sund, Reijo; Sugawara, Masumi; Tanaka, Mami; Matsumoto, Satoko; Aaltonen, Sari; Piirtola, Maarit; Freitas, Duarte L.; Maia, José A.; Öncel, Sevgi Y.; Aliev, Fazil; Ji, Fuling; Ning, Feng; Pang, Zengchang; Rebato, Esther; Saudino, Kimberly J.; Cutler, Tessa L.; Hopper, John L.; Ullemar, Vilhelmina; Almqvist, Catarina; Magnusson, Patrik K. E.; Cozen, Wendy; Hwang, Amie E.; Mack, Thomas M.; Willemsen, Gonneke; Bartels, Meike; van Beijsterveldt, Catharina E. M.; Nelson, Tracy L.; Whitfield, Keith E.; Sung, Joohon; Kim, Jina; Lee, Jooyeon; Lee, Sooji; Llewellyn, Clare H.; Fisher, Abigail; Medda, Emanuela; Nisticò, Lorenza; Toccaceli, Virgilia; Baker, Laura A.; Tuvblad, Catherine; Corley, Robin P.; Huibregtse, Brooke M.; Derom, Catherine A.; Vlietinck, Robert F.; Loos, Ruth J. F.; Knafo‐Noam, Ariel; Mankuta, David; Abramson, Lior; Burt, S. Alexandra; Klump, Kelly L.; Silberg, Judy L.; Maes, Hermine H.; Krueger, Robert F.; McGue, Matt; Pahlen, Shandell; Gatz, Margaret; Butler, David A.; Harris, Jennifer R.; Nilsen, Thomas S.; Harden, K. Paige; Tucker‐Drob, Elliot M.; Franz, Carol E.; Kremen, William S.; Lyons, Michael J.; Lichtenstein, Paul; Jeong, Hoe‐Uk; Hur, Yoon‐Mi; Boomsma, Dorret I.; Sørensen, Thorkild I. A.; Kaprio, JaakkoObjective: The objective of this study was to analyze how parental education modifies the genetic and environmental variances of BMI from infancy to old age in three geographic-cultural regions. Methods: A pooled sample of 29 cohorts including 143,499 twin individuals with information on parental education and BMI from age 1 to 79 years (299,201 BMI measures) was analyzed by genetic twin modeling. Results: Until 4 years of age, parental education was not consistently associated with BMI. Thereafter, higher parental education level was associated with lower BMI in males and females. Total and additive genetic variances of BMI were smaller in the offspring of highly educated parents than in those whose parents had low education levels. Especially in North American and Australian children, environmental factors shared by co-twins also contributed to the higher BMI variation in the low education level category. In Europe and East Asia, the associations of parental education with mean BMI and BMI variance were weaker than in North America and Australia. Conclusions: Lower parental education level is associated with higher mean BMI and larger genetic vari ance of BMI after early childhood, especially in the obesogenic macro-environment. The interplay among genetic predisposition, childhood social environment, and macro-social context is important for socioeco nomic differences in BMI
- Genetic regulation of body size and morphology in children: a twin study of 22 anthropometric traitsPublication . Silventoinen, Karri; Maia, José; Li, Weilong; Sund, Reijo; Gouveia, Élvio R.; Antunes, António; Marques, Gonçalo; Thomis, Martine; Jelenkovic, Aline; Kaprio, Jaakko; Freitas, Duarte Luís deAnthropometric measures show high heritability, and genetic correlations have been found between obesity related traits. However, we lack a comprehensive analysis of the genetic background of human body morphology using detailed anthropometric measures. METHODS: Height, weight, 7 skinfold thicknesses, 7 body circumferences and 4 body diameters (skeletal breaths) were measured in 214 pairs of twin children aged 3–18 years (87 monozygotic pairs) in the Autonomous Region of Madeira, Portugal. Factor analysis (Varimax rotation) was used to analyze the underlying structure of body physique. Genetic twin modeling was used to estimate genetic and environmental contributions to the variation and co-variation of the anthropometric traits. RESULTS: Together, two factors explained 80% of the variation of all 22 anthropometric traits in boys and 73% in girls. Obesity measures (body mass index, skinfold thickness measures, as well as waist and hip circumferences) and limb circumferences loaded most strongly on the first factor, whereas height and body diameters loaded especially on the second factor. These factors as well as all anthropometric measures showed high heritability (80% or more for most of the traits), whereas the rest of the variation was explained by environmental factors not shared by co-twins. Obesity measures showed high genetic correlations (0.75–0.98). Height showed the highest genetic correlations with body diameter measures (0.58–0.76). Correlations between environmental factors not shared by co-twins were weaker than the genetic correlations but still substantial. The correlation patterns were roughly similar in boys and girls. CONCLUSIONS: Our results show high genetic correlations underlying the human body physique, suggesting that there are sets of genes widely affecting anthropometric traits. Better knowledge of these genetic variants can help to understand the development of obesity and other features of the human physique.
- The genetic background of metabolic trait clusters in children and adolescentsPublication . Silventoinen, Karri; Gouveia, Élvio; Jelenkovic, Aline; Maia, José; Antunes, António M.; Carvalho, Miguel Â. A. Pinheiro de; Brehm, António M.; Thomis, Martine; Lefevre, Johan; Kaprio, Jaakko; Freitas, DuarteBackground: It is well known that the metabolic risk factors of cardiovascular diseases are correlated, but the background of this clustering in children is more poorly known than in adults. Thus, we studied the contribution of genetic and environmental factors to the clustering of metabolic traits in childhood and adolescence. Methods: Nine metabolic traits were measured in 214 complete twin pairs aged 3 to 18 years in the Autonomous Region of Madeira, Portugal, in 2007 and 2008. The variation of and covariations between the traits were decomposed into genetic and environmental components by using classical genetic twin modeling. Results: A model including additive genetic and environmental factors unique for each twin individual explained the variation of the metabolic factors well. Under this model, the heritability estimates varied from 0.47 (systolic blood pressure in children under 12 years of age) to 0.91 (HDL cholesterol in adolescents 12 years of age or older). The most systematic correlations were found between adiposity (body mass index and waist circumference) and blood lipids (HDL cholesterol, LDL cholesterol and triglycerides), as well as blood pressure. These correlations were mainly explained by common genetic factors. Conclusions: Our results suggest that obesity, in particular, is behind the clustering of metabolic factors in children and adolescents. Both general and abdominal obesity partly share the same genetic background as blood lipids and blood pressure. Obesity prevention already in childhood is important in reducing the risk of metabolic diseases in adulthood.
- Genetic and environmental effects on body mass index from infancy to the onset of adulthood: an individual-based pooled analysis of 45 twin cohorts participating in the COllaborative project of Development of Anthropometrical measures in Twins (CODATwins) studyPublication . Silventoinen, Karri; Jelenkovic, Aline; Sund, Reijo; Hur, Yoon-Mi; Yokoyama, Yoshie; Honda, Chika; Hjelmborg, Jacob vB; Möller, Sören; Ooki, Syuichi; Aaltonen, Sari; Ji, Fuling; Saudino, Kimberly J; Jang, Kerry L; Cozen, Wendy; Hwang, Amie E; Mack, Thomas M.; Gao, Wenjing; Yu, Canqing; Li, Liming; Corley, Robin P.; Huibregtse, Brooke M; Christensen, Kaare; Skytthe, Axel; Kyvik, Kirsten O; Derom, Catherine A.; Vlietinck, Robert F.; Loos, Ruth J. F.; Heikkilä, Kauko; Wardle, Jane; Llewellyn, Clare H.; Fisher, Abigail; McAdams, Tom A; Eley, Thalia C.; Gregory, Alice M; He, Mingguang; Ding, Xiaohu; Bjerregaard-Andersen, Morten; Beck-Nielsen, Henning; Sodemann, Morten; Tarnoki, Adam D.; Tarnoki, David L.; Stazi, Maria A; Fagnani, Corrado; D’Ippolito, Cristina; Knafo-Noam, Ariel; Mankuta, David; Abramson, Lior; Burt, S. Alexandra; Klump, Kelly L.; Silberg, Judy L; Eaves, Lindon J.; Maes, Hermine H.; Krueger, Robert F; McGue, Matt; Pahlen, Shandell; Gatz, Margaret; Butler, David A.; Bartels, Meike; van Beijsterveldt, Toos CEM; Craig, Jeffrey M.; Saffery, Richard; Freitas, Duarte L.; Maia, José Antonio; Dubois, Lise; Boivin, Michel; Brendgen, Mara; Dionne, Ginette; Vitaro, Frank; Martin, Nicholas G; Medland, Sarah E; Montgomery, Grant W; Chong, Youngsook; Swan, Gary E.; Krasnow, Ruth; Magnusson, Patrik K. E.; Pedersen, Nancy L; Tynelius, Per; Lichtenstein, Paul; Haworth, Claire MA; Plomin, Robert; Bayasgalan, Gombojav; Narandalai, Danshiitsoodol; Harden, K Paige; Tucker-Drob, Elliot M.; Öncel, Sevgi Y; Aliev, Fazil; Spector, Timothy; Mangino, Massimo; Lachance, Genevieve; Baker, Laura A.; Tuvblad, Catherine; Duncan, Glen E.; Buchwald, Dedra; Willemsen, Gonneke; Rasmussen, Finn; Goldberg, Jack H; Sørensen, Thorkild IA; Boomsma, Dorret I.; Kaprio, Jaakko; Ning, Feng; Pang, Zengchang; Rebato, Esther; Busjahn, Andreas; Kandler, ChristianBackground: Both genetic and environmental factors are known to affect body mass index (BMI), but detailed understanding of how their effects differ during childhood and adolescence is lacking. Objectives: We analyzed the genetic and environmental contribu tions to BMI variation from infancy to early adulthood and the ways they differ by sex and geographic regions representing high (North America and Australia), moderate (Europe), and low levels (East Asia) of obesogenic environments. Design: Data were available for 87,782 complete twin pairs from 0.5 to 19.5 y of age from 45 cohorts. Analyses were based on 383,092 BMI measurements. Variation in BMI was decomposed into genetic and en vironmental components through genetic structural equation modeling. Results: The variance of BMI increased from 5 y of age along with increasing mean BMI. The proportion of BMI variation explained by additive genetic factors was lowest at 4 y of age in boys (a2 = 0.42) and girls (a2 = 0.41) and then generally increased to 0.75 in both sexes at 19 y of age. This was because of a stronger influence of environmental factors shared by co-twins in midchildhood. After 15 y of age, the effect of shared environment was not observed. The sex-specific expression of genetic factors was seen in infancy but was most prominent at 13 y of age and older. The variance of BMI was highest in North America and Australia and lowest in East Asia, but the relative proportion of genetic variation to total variation remained roughly similar across different regions. Conclusions: Environmental factors shared by co-twins affect BMI in childhood, but little evidence for their contribution was found in late adolescence. Our results suggest that genetic factors play a ma jor role in the variation of BMI in adolescence among populations of different ethnicities exposed to different environmental factors related to obesity.