New loci associated with birth weight identify genetic links between intrauterine growth and adult height and metabolism

Horikoshi, Momoko; Yaghootkar, Hanieh; Mook‐Kanamori, Dennis O.; Sovio, Ulla; Taal, H. Rob; Hennig, Branwen J.; Bradfield, Jonathan P.; Pourcain, Beaté St; Evans, David M.; Charoen, Pimphen; Kaakinen, Marika; Cousminer, Diana L.; Lehtimäki, Terho; Kreiner‐Møller, Eskil; Warrington, Nicole M.; Bustamante, Mariona; Feenstra, Bjarke; Berry, Diane J.; Thiering, Elisabeth; Pfab, Thiemo; Barton, Sheila J.; Shields, Beverley M.; Kerkhof, Marjan; Leeuwen, Elisabeth M. van; Fulford, Anthony J.; Kutalik, Zoltán; Zhao, Jing Hua; Hoed, Marcel den; Mahajan, Anubha; Lindi, Virpi; Goh, Liang Kee; Hottenga, Jouke Jan; Wu, Ying; Raitakari, Olli T.; Harder, Marie Neergaard; Meirhaeghe, Aline; Ντάλλα, Ιωάννα; Salem, Rany M.; Jameson, Karen; Zhou, Kaixin; Monies, Dorota; Lagou, Vasiliki; Kirin, Mirna; Heikkinen, Jani; Adair, Linda S.; Alkuraya, Fowzan S.; Al‐Odaib, Ali; Amouyel, Philippe; Andersson, Ehm A.; Bennett, Amanda J.; Blakemore, Alexandra I. F.; Buxton, Jessica L.; Dallongeville, Jean; Das, Shikta; Geus, Eco J. C. de; Estivill, Xavier; Flexeder, Claudia; Froguel, Philippe; Geller, Frank; Godfrey, Keith M.; Gottrand, Frédéric; Groves, Christopher J.; Hansen, Torben; Hirschhorn, Joel N.; Hofman, Albert; Hollegaard, Mads Vilhelm; Hougaard, David M.; Hyppönen, Elina; Inskip, Hazel; Isaacs, Aaron; Jørgensen, Torben; Kanaka‐Gantenbein, Christina; Kemp, John P.; Kieß, Wieland; Kilpeläinen, Tuomas O.; Klopp, Norman; Knight, Bridget; Kuzawa, Christopher W.; McMahon, George; Newnham, John P.; Niinikoski, Harri; Oostra, Ben A.; Pedersen, Louise; Postma, Dirkje S.; Ring, Susan M.; Rivadeneira, Fernando; Robertson, Neil; Sebért, Sylvain; Simell, Olli; Slowinski, Torsten; Tiesler, Carla M. T.; Tönjes, Anke; Vaag, Allan; Viikari, Jorma; Vink, Jacqueline M.; Vissing, Nadja Hawwa; Wareham, Nicholas J.; Willemsen, Gonneke; Witte, Daniel R.; Zhang, Haitao; Zhao, Jianhua; Wilson, James F.; Stümvoll, Michael; Prentice, Andrew M.; Meyer, Brian F.; Pearson, Ewan R.; Boreham, Colin; Cooper, Cyrus; Gillman, Matthew W.; Dedoussis, George; Moreno, Luís A.; Pedersen, Oluf; Saarinen, Maiju; Mohlke, Karen L.; Boomsma, Dorret I.; Saw, Seang Mei; Lakka, Timo A.; Körner, Antje; Loos, Ruth J.F.; Ong, Ken K.; Vollenweider, Péter; Duijn, Cornelia M. van; Koppelman, Gerard H.; Hattersley, Andrew T.; Holloway, John W.; Hocher, Berthold; Heinrich, Joachim; Power, Chris; Melbye, Mads; Guxens, Mònica; Pennell, Craig E.; Bønnelykke, Klaus; Bisgaard, Hans; Eriksson, Johan G.; Widén, Elisabeth; Hákonarson, Hákon; Uitterlinden, André G.; Pouta, Anneli; Lawlor, Debbie A.; Smith, George Davey; Frayling, Timothy M.; McCarthy, Mark I.; Grant, Struan F A; Jaddoe, Vincent W.V.; Järvelin, Marjo‐Riitta; Timpson, Nicholas J.; Prokopenko, Inga; Freathy, Rachel M.

doi:10.1038/ng.2477

Cited by 294 publications

(312 citation statements)

References 54 publications

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“…Horikoshi et al published the results of a meta-analysis of genome-wide studies of birth weight [14]. They identified seven loci that replicated with a p-value below 5 × 10 − 8 .…”

Section: Birth Weight and Glucose Levels In Adulthoodmentioning

confidence: 99%

Mendelian Randomization using Public Data from Genetic Consortia

Thompson

Minelli

2016

The International Journal of Biostatistics

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Mendelian randomization (MR) is a technique that seeks to establish causation between an exposure and an outcome using observational data. It is an instrumental variable analysis in which genetic variants are used as the instruments. Many consortia have meta-analysed genome-wide associations between variants and specific traits and made their results publicly available. Using such data, it is possible to derive genetic risk scores for one trait and to deduce the association of that same risk score with a second trait. The properties of this approach are investigated by simulation and by evaluating the potentially causal effect of birth weight on adult glucose level. In such analyses, it is important to decide whether one is interested in the risk score based on a set of estimated regression coefficients or the score based on the true underlying coefficients. MR is primarily concerned with the latter. Methods designed for the former question will under-estimate the variance if used for MR. This variance can be corrected but it needs to be done with care to avoid introducing bias. MR based on public data sources is useful and easy to perform, but care must be taken to avoid false precision or bias.

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“…Horikoshi et al published the results of a meta-analysis of genome-wide studies of birth weight [14]. They identified seven loci that replicated with a p-value below 5 × 10 − 8 .…”

Section: Birth Weight and Glucose Levels In Adulthoodmentioning

confidence: 99%

Mendelian Randomization using Public Data from Genetic Consortia

Thompson

Minelli

2016

The International Journal of Biostatistics

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“…Other modifiable factors exist in utero, such as maternal smoking during pregnancy (Ward et al, 2007) and maternal health and nutrition (e.g., caloric intake; Kramer, 1987aKramer, , 1987b. Several genetic variants have been associated with birth weight (Freathy et al, 2010;Horikoshi et al, 2013); however, these show only a modest genetic contribution to the total variance in birth weight (Barker, 2004;Battaglia & Lubchenco, 1967;Freathy et al, 2010;Heijmans et al, 2008;Horikoshi et al, 2013;Jarvelin et al, 2004;McIntire et al, 1999). Heritability estimates for birth weight from twin and family studies have given highly variable results, ranging from 15% to 72% (Baird et al, 2001;Clausson et al, 2000;Gielen et al, 2008;Lunde et al, 2007;Magnus, 1984aMagnus, , 1984bMagnus et al, 2001;Mook-Kanamori et al, 2012).…”

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confidence: 99%

DNA Methylation Changes in theIGF1RGene in Birth Weight Discordant Adult Monozygotic Twins

et al. 2015

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Low birth weight (LBW) can have an impact on health outcomes in later life, especially in relation to predisposition to metabolic disease. Several studies suggest that LBW resulting from restricted intrauterine growth leaves a footprint on DNA methylation in utero, and this influence likely persists into adulthood. To investigate this further, we performed epigenome-wide association analyses of blood DNA methylation using Infinium HumanMethylation450 BeadChip profiles in 71 adult monozygotic (MZ) twin pairs who were extremely discordant for birth weight. A signal mapping to the IGF1R gene (cg12562232, p = 2.62 × 10 −8 ), was significantly associated with birth weight discordance at a genome-wide false-discovery rate (FDR) of 0.05. We pursued replication in three additional independent datasets of birth weight discordant MZ pairs and observed the same direction of association, but the results were not significant. However, a meta-analysis across the four independent samples, in total 216 birth-weight discordant MZ twin pairs, showed a significant positive association between birth weight and DNA methylation differences at IGF1R (random-effects meta-analysis p = .04), and the effect was particularly pronounced in older twins (randomeffects meta-analysis p = .008, 98 older birth-weight discordant MZ twin pairs). The results suggest that severe intra-uterine growth differences (birth weight discordance >20%) are associated with methylation changes in the IGF1R gene in adulthood, independent of genetic effects.

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“…These findings again highlight genetic links between fetal growth and postnatal growth and metabolism (Horikoshi et al, 2013).…”

Section: Ntrk2 Gene and Birth Weight In Female Twinsmentioning

confidence: 79%

Variants Close to NTRK2 Gene Are Associated With Birth Weight in Female Twins

et al. 2014

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Low weight at birth has previously been shown to be associated with a number of adult diseases such as type 2 diabetes, cardiovascular disease, high blood pressure, and obesity later in life. Genome-wide association studies (GWAS) have been published for singleton-born individuals, but the role of genetic variation in birth weight (BW) in twins has not yet been fully investigated. A GWAS was performed in 4,593 female study participants with BW data available from the TwinsUK cohort. A genome-wide significant signal was found in chromosome 9, close to the NTRK2 gene (OMIM: 600456). QIMR, an Australian twin cohort (n = 3,003), and UK-based singleton-birth individuals from the Hertfordshire cohort (n = 2,997) were used as replication for the top two single nucleotide polymorphism (SNPs) underpinning this signal, rs12340987 and rs7849941. The top SNP, rs12340987, was found to be in the same direction in the Australian twins and in the singleton-born females (fixed effects meta-analysis beta = -0.13, SE = 0.02, and p = 1.48 × 10 −8 ) but not in the singleton-born males tested. These findings provide an important insight into the genetic component of BW in twins who are normally excluded due to their lower BW when compared with singleton births, as well as the difference in BW between twins. The NTRK2 gene identified in this study has previously been associated with obesity.

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New loci associated with birth weight identify genetic links between intrauterine growth and adult height and metabolism

Cited by 294 publications

References 54 publications

Mendelian Randomization using Public Data from Genetic Consortia

Mendelian Randomization using Public Data from Genetic Consortia

DNA Methylation Changes in theIGF1RGene in Birth Weight Discordant Adult Monozygotic Twins

Variants Close to NTRK2 Gene Are Associated With Birth Weight in Female Twins

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