Common maternal and fetal genetic variants show expected polygenic effects on risk of small- or large-for-gestational-age (SGA or LGA), except in the smallest 3% of babies
Autoři:
Robin N. Beaumont aff001; Sarah J. Kotecha aff002; Andrew R. Wood aff001; Bridget A. Knight aff001; Sylvain Sebert aff003; Mark I. McCarthy aff005; Andrew T. Hattersley aff001; Marjo-Riitta Jarvelin aff003; Nicholas J. Timpson aff010; Rachel M. Freathy aff001; Sailesh Kotecha aff002
Působiště autorů:
Institute of Biomedical and Clinical Science, College of Medicine and Health, University of Exeter, Exeter, United Kingdom
aff001; Department of Child Health, School of Medicine, Cardiff University, Cardiff, United Kingdom
aff002; Center for Life Course Health Research, Faculty of Medicine, University of Oulu, Oulun yliopisto, Finland
aff003; Unit of Primary Health Care, Oulu University Hospital, OYS, Oulu, Finland
aff004; Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, United Kingdom
aff005; Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Oxford, United Kingdom
aff006; Oxford National Institute for Health Research (NIHR) Biomedical Research Centre, Churchill Hospital, Oxford, United Kingdom
aff007; Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, London, United Kingdom
aff008; Department of Life Sciences, College of Health and Life Sciences, Brunel University London, Kingston Lane, Uxbridge, Middlesex, United Kingdom
aff009; Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom
aff010
Vyšlo v časopise:
Common maternal and fetal genetic variants show expected polygenic effects on risk of small- or large-for-gestational-age (SGA or LGA), except in the smallest 3% of babies. PLoS Genet 16(12): e1009191. doi:10.1371/journal.pgen.1009191
Kategorie:
Research Article
doi:
https://doi.org/10.1371/journal.pgen.1009191
Souhrn
Babies born clinically Small- or Large-for-Gestational-Age (SGA or LGA; sex- and gestational age-adjusted birth weight (BW) <10th or >90th percentile, respectively), are at higher risks of complications. SGA and LGA include babies who have experienced environment-related growth-restriction or overgrowth, respectively, and babies who are heritably small or large. However, the relative proportions within each group are unclear. We assessed the extent to which common genetic variants underlying variation in birth weight influence the probability of being SGA or LGA. We calculated independent fetal and maternal genetic scores (GS) for BW in 11,951 babies and 5,182 mothers. These scores capture the direct fetal and indirect maternal (via intrauterine environment) genetic contributions to BW, respectively. We also calculated maternal fasting glucose (FG) and systolic blood pressure (SBP) GS. We tested associations between each GS and probability of SGA or LGA. For the BW GS, we used simulations to assess evidence of deviation from an expected polygenic model.
Higher BW GS were strongly associated with lower odds of SGA and higher odds of LGA (ORfetal = 0.75 (0.71,0.80) and 1.32 (1.26,1.39); ORmaternal = 0.81 (0.75,0.88) and 1.17 (1.09,1.25), respectively per 1 decile higher GS). We found evidence that the smallest 3% of babies had a higher BW GS, on average, than expected from their observed birth weight (assuming an additive polygenic model: Pfetal = 0.014, Pmaternal = 0.062). Higher maternal SBP GS was associated with higher odds of SGA P = 0.005.
We conclude that common genetic variants contribute to risk of SGA and LGA, but that additional factors become more important for risk of SGA in the smallest 3% of babies.
Klíčová slova:
Birth – Birth weight – Genetic polymorphism – Genetics – Genome-wide association studies – Medical risk factors – Metaanalysis – Single nucleotide polymorphisms
Zdroje
1. Hilby SE, Apps R, Chazara O, Farrell LE, Magnus P, Trogstad L, et al. Maternal KIR in combination with paternal HLA-C2 regulate human birth weight. J Immunol. 2014;509:385–8.
2. Clausson B, Gardosi J, Francis A, Cnattingius S. Perinatal outcome in SGA births defined by customised versus population-based birthweight standards. Br. J. Obstet. Gynaecol. 2001;108:830–4. doi: 10.1111/j.1471-0528.2001.00205.x 11510708
3. Gordijn SJ, Beune IM, Wynia K. Consensus definition of fetal growth restriction: a Delphi procedure. Ultrasound Obs. Gynecol. 2016;48:333–9. doi: 10.1002/uog.15884 26909664
4. Gardosi J, Madurasinghe V, Williams M, Malik A. Maternal and fetal risk factors for stillbirth: population based study. BMJ. 2013;108:1–14. doi: 10.1136/bmj.f108 23349424
5. McCowan LM, Figueras F, Anderson NH. Evidence-based national guidelines for the management of suspected fetal growth restriction: comparison, consensus, and controversy. Am. J. Obstet. Gynecol. 2018;218:S855–68. doi: 10.1016/j.ajog.2017.12.004 29422214
6. Alberry M, Soothill P. Management of fetal growth restriction. Arch Dis Child Fetal Neonatal Ed. 2007;92:62–7. doi: 10.1136/adc.2005.082297 17185432
7. Snijders RJM, Sherrod C, Gosden CM. Nicolaides KH. Fetal growth retardation: associated malormations and chromosomal abnormalities. Am. J. Obstet. Gynecol. 1993;168:547–55. doi: 10.1016/0002-9378(93)90491-z 8438926
8. Moffett A, Hiby SE, Sharkey AM. The role of the maternal immune system in the regulation of human birthweight. Philos Trans R Soc L. B Biol Sci. 2015;370:20140071. doi: 10.1098/rstb.2014.0071 25602075
9. Metzger BE, Lowe LP, Dyer AR, Trimble ER, Chaovarindr U, et al. Hyperglycemia and Adverse Pregnancy Outcomes. N. Engl. J. Med. 2008;358:1991–2002. doi: 10.1056/NEJMoa0707943 18463375
10. Sacks DA, Liu AI, Wolde-tsadik G, Amini SB, Huston-presley L, Catalano PM. What proportion of birth weight is attributable to maternal glucose among infants of diabetic women? Am. J. Obstet. Gynecol. 2006;194:501–7. doi: 10.1016/j.ajog.2005.07.042 16458653
11. Breschi MC, Seghieri G, Bartolomei G, Gironi A, Baldi S, Ferrannini E. Relation of birthweight to maternal plasma glucose and insulin concentrations during normal pregnancy. Diabetologia. 1993;36:1315–21. doi: 10.1007/BF00400812 8307262
12. Surkan PJ, Hsieh C, Johansson AL V, Dickman PW, Cnattingius S. Reasons for Increasing Trends in Large for Gestational Age Births. Obs. Gynecol. 2004;104:720–6. doi: 10.1097/01.AOG.0000141442.59573.cd 15458892
13. Hughes AE, Nodzenski M, Beaumont RN, Talbot O, Shields BM, Scholtens DM, et al. Fetal Genotype and Maternal Glucose Have Independent and Additive Effects on Birth Weight. Diabetes. 2018;67:1024–9. doi: 10.2337/db17-1188 29463506
14. Chawla R, Badon SE, Rangarajan J, Reisetter AC, Armstrong LL, Lowe LP, et al. Genetic Risk Score for Prediction of Newborn Adiposity and Large-for-Gestational-Age Birth. J Clin Endocrinol Metab. 2014;99:2377–86. doi: 10.1210/jc.2013-4221 25137420
15. Chan Y, Holmen OL, Dauber A, Vatten L, Havulinna AS, Kvaløy K, et al. Common Variants Show Predicted Polygenic Effects on Height in the Tails of the Distribution, Except in Extremely Short Individuals. PLOS Genet. 2011;7. doi: 10.1371/journal.pgen.1002439 22242009
16. Warrington NM, Beaumont RN, Horikoshi M, Day F, Helgeland Ø, Laurin C, et al. Maternal and fetal genetic effects on birth weight and their relevance to cardio-metabolic risk factors. Nat. Genet. 2019;51:804–14. doi: 10.1038/s41588-019-0403-1 31043758
17. Tyrrell J, Richmond RC, Palmer TM, Feenstra B, Rangarajan J, Metrustry S, et al. Genetic Evidence for Causal Relationships Between Maternal Obesity-Related Traits and Birth Weight. JAMA. 2016;315:1129–40. doi: 10.1001/jama.2016.1975 26978208
18. Fraser A, Macdonald-wallis C, Tilling K, Boyd A, Golding J, Smith GD, et al. Cohort Profile: The Avon Longitudinal Study of Parents and Children: ALSPAC mothers cohort. Int. J. Epidemiol. 2013;42:97–110. doi: 10.1093/ije/dys066 22507742
19. Boyd A, Golding J, Macleod J, Lawlor DA, Fraser A, Henderson J, et al. Cohort Profile: The ‘ Children of the 90s ‘—the index offspring of the Avon Longitudinal Study of Parents and Children. Int. J. Epidemiol. 2013;42:111–27. doi: 10.1093/ije/dys064 22507743
20. Knight B, Shields BM, Hattersley AT. The Exeter Family Study of Childhood Health (EFSOCH): study protocol and methodology. Paediatr Perinat Epidemiol. 2006;20:172–9. doi: 10.1111/j.1365-3016.2006.00701.x 16466435
21. Sabatti C, Service SK, Hartikainen A, Pouta A, Ripatti S, Brodsky J, et al. Genome-wide association analysis of metabolic traits in a birth cohort from a founder population. Nat Genet. 2009;41:35–46. doi: 10.1038/ng.271 19060910
22. Sebert S, Lowry E, Aumu N, Bjerregaard LG, Rooij SR De, Silva M De, et al. Cohort Profile: The DynaHEALTH consortium–a European consortium for a life-course bio-psychosocial model of healthy ageing of glucose homeostasis. 2019; doi: 10.1093/ije/dyz056 31321419
23. Cole TJ, Freeman JV, Preece MA. British 1990 Growth reference centiles for weight, height, body mass index and head circumference fitted by maximum penalized likelihood. Stat Med. 1998 9496720
24. Niklasson A. An Update of the Swedish Reference Standards for Weight, Length and Head Circumference at Birth for Given. 2000;756–62.
25. Willer CJ, Li Y, Abecasis GR, Overall P. METAL: fast and efficient meta-analysis of genomewide association scans. 2010;26:2190–1. doi: 10.1093/bioinformatics/btq340 20616382
26. Murki S, Sharma D. Intrauterine Growth Retardation—A Review Article. J. Neonatal Biol. 2014;3.
27. McIntyre DD, Bloom SL, Casey BM, Leveno KJ. Birth Weight In Relation To Morbidity And Mortality Among Newborn Infants. N. Engl. J. Med. 1999;340:1234–8. doi: 10.1056/NEJM199904223401603 10210706
28. Zhang X, Platt RW, Cnattingius S, Joseph KS. The use of customised versus population-based birthweight standards in predicting perinatal mortality. BJOG. 2007;114:474–7. doi: 10.1111/j.1471-0528.2007.01273.x 17378820
29. Odibo AO, Francis A, Cahill AG, Macones GA, Crane P, Gardosi J, et al. Association between pregnancy complications and small-for–gestational-age birth weight defined by customized fetal growth standard versus a population-based standard. J. Matern. Neonatal Med. 2011;24:411–7. doi: 10.3109/14767058.2010.506566 20698736
30. Sovio U, Smith GCS. The effect of customization and use of a fetal growth standard on the association between birthweight percentile and adverse perinatal outcome. Am. J. Obstet. Gynecol.; 2018;218:S738–44 doi: 10.1016/j.ajog.2017.11.563 29199029
31. Iliodromiti S, Mackay DF, Smith GCS, Pell JP, Sattar N, Lawlor DA, et al. Customised and Noncustomised Birth Weight Centiles and Prediction of Stillbirth and Infant Mortality and Morbidity: A Cohort Study of 979, 912 Term Singleton Pregnancies in Scotland. PLoS Med. 2017;14:1–16. doi: 10.1371/journal.pmed.1002228 28141865
32. Fisher SC, Van Zutphen AR, Ronitti PA, Browne ML. Maternal Hypertension, Antihypertensive Medication Use, and Small for Gestational Age Births in the National Birth Defects Prevention Study 1997–2011. Maternal Child Health J. 2018;22:237–246.
Článek vyšel v časopise
PLOS Genetics
2020 Číslo 12
- Antibiotika na nachlazení nezabírají! Jak můžeme zpomalit šíření rezistence?
- FDA varuje před selfmonitoringem cukru pomocí chytrých hodinek. Jak je to v Česku?
- Prof. Jan Škrha: Metformin je bezpečný, ale je třeba jej bezpečně užívat a léčbu kontrolovat
- Ibuprofen jako alternativa antibiotik při léčbě infekcí močových cest
- Jak a kdy u celiakie začíná reakce na lepek? Možnou odpověď poodkryla čerstvá kanadská studie
Nejčtenější v tomto čísle
- Exploiting codon usage identifies intensity-specific modifiers of Ras/MAPK signaling in vivo
- Common maternal and fetal genetic variants show expected polygenic effects on risk of small- or large-for-gestational-age (SGA or LGA), except in the smallest 3% of babies
- PEA15 loss of function and defective cerebral development in the domestic cat
- Precision medicine in cats—The right biomedical model may not be the mouse!