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• W1981190999 abstract "We have studied the largely unknown genetic underpinnings of height growth by using a unique resource of longitudinal childhood height data available in Finnish population cohorts. After applying GWAS mapping of potential genes influencing pubertal height growth followed by further characterization of the genetic effects on complete postnatal growth trajectories, we have identified strong association between variants near LIN28B and pubertal growth (rs7759938; female p = 4.0 × 10−9, male p = 1.5 × 10−4, combined p = 5.0 × 10−11, n = 5038). Analysis of growth during early puberty confirmed an effect on the timing of the growth spurt. Correlated SNPs have previously been implicated as influencing both adult stature and age at menarche, the same alleles associating with taller height and later age of menarche in other studies as with later pubertal growth here. Additionally, a partially correlated LIN28B SNP, rs314277, has been associated previously with final height. Testing both rs7759938 and rs314277 (pairwise r2 = 0.29) for independent effects on postnatal growth in 8903 subjects indicated that the pubertal timing-associated marker rs7759938 affects prepubertal growth in females (p = 7 × 10−5) and final height in males (p = 5 × 10−4), whereas rs314277 has sex-specific effects on growth (p for interaction = 0.005) that were distinct from those observed at rs7759938. In conclusion, partially correlated variants at LIN28B tag distinctive, complex, and sex-specific height-growth-regulating effects, influencing the entire period of postnatal growth. These findings imply a critical role for LIN28B in the regulation of human growth. We have studied the largely unknown genetic underpinnings of height growth by using a unique resource of longitudinal childhood height data available in Finnish population cohorts. After applying GWAS mapping of potential genes influencing pubertal height growth followed by further characterization of the genetic effects on complete postnatal growth trajectories, we have identified strong association between variants near LIN28B and pubertal growth (rs7759938; female p = 4.0 × 10−9, male p = 1.5 × 10−4, combined p = 5.0 × 10−11, n = 5038). Analysis of growth during early puberty confirmed an effect on the timing of the growth spurt. Correlated SNPs have previously been implicated as influencing both adult stature and age at menarche, the same alleles associating with taller height and later age of menarche in other studies as with later pubertal growth here. Additionally, a partially correlated LIN28B SNP, rs314277, has been associated previously with final height. Testing both rs7759938 and rs314277 (pairwise r2 = 0.29) for independent effects on postnatal growth in 8903 subjects indicated that the pubertal timing-associated marker rs7759938 affects prepubertal growth in females (p = 7 × 10−5) and final height in males (p = 5 × 10−4), whereas rs314277 has sex-specific effects on growth (p for interaction = 0.005) that were distinct from those observed at rs7759938. In conclusion, partially correlated variants at LIN28B tag distinctive, complex, and sex-specific height-growth-regulating effects, influencing the entire period of postnatal growth. These findings imply a critical role for LIN28B in the regulation of human growth. Human growth in height is a multifaceted process including periods of accelerated and decelerated growth velocities. The postnatal growth trajectory can be conceptualized as consisting of three partially overlapping phases of growth: infant growth characterized by rapidly declining growth velocities, slowly decelerating childhood growth, and the pubertal height growth spurt.1Okasha M. Gunnell D. Holly J. Davey Smith G. Childhood growth and adult cancer.Best Pract. Res. Clin. Endocrinol. Metab. 2002; 16: 225-241Abstract Full Text PDF PubMed Scopus (70) Google Scholar Genes are estimated to account for up to 60%–80% of the within-population variation of overall height growth.2Weedon M.N. Frayling T.M. Reaching new heights: Insights into the genetics of human stature.Trends Genet. 2008; 24: 595-603Abstract Full Text Full Text PDF PubMed Scopus (116) Google Scholar, 3Silventoinen K. Pietiläinen K.H. Tynelius P. Sørensen T.I. Kaprio J. Rasmussen F. Genetic regulation of growth from birth to 18 years of age: The Swedish young male twins study.Am. J. Hum. Biol. 2008; 20: 292-298Crossref PubMed Scopus (41) Google Scholar Although the individual genes still remain largely unknown, epidemiological studies propose partly overlapping genetic regulation covering multiple aspects of growth. For example, a longitudinal study of Swedish male twins suggested that a large proportion of the genes affecting postnatal growth in height are the same or are closely linked throughout the whole growth period.3Silventoinen K. Pietiläinen K.H. Tynelius P. Sørensen T.I. Kaprio J. Rasmussen F. Genetic regulation of growth from birth to 18 years of age: The Swedish young male twins study.Am. J. Hum. Biol. 2008; 20: 292-298Crossref PubMed Scopus (41) Google Scholar Furthermore, a significant proportion of shared genes is thought to account for the correlation between increased prepubertal body mass index and the timing of pubertal growth and maturation.4Kaprio J. Rimpelä A. Winter T. Viken R.J. Rimpelä M. Rose R.J. Common genetic influences on BMI and age at menarche.Hum. Biol. 1995; 67: 739-753PubMed Google Scholar Thus far, there have been no genome-wide association studies (GWAS) specifically targeting childhood height growth, whereas there have been many recent large-scale association studies successfully identifying loci influencing both body size and pubertal timing. Although there are as many as 47 verified hits influencing final stature,2Weedon M.N. Frayling T.M. Reaching new heights: Insights into the genetics of human stature.Trends Genet. 2008; 24: 595-603Abstract Full Text Full Text PDF PubMed Scopus (116) Google Scholar, 5Lettre G. Genetic regulation of adult stature.Curr. Opin. Pediatr. 2009; 21: 515-522Crossref PubMed Scopus (60) Google Scholar 11 loci influencing adult body mass index,6Cotsapas C. Speliotes E.K. Hatoum I.J. Greenawalt D.M. Dobrin R. Lum P.Y. Suver C. Chudin E. Kemp D. Reitman M. et al.GIANT ConsortiumCommon body mass index-associated variants confer risk of extreme obesity.Hum. Mol. Genet. 2009; 18: 3502-3507Crossref PubMed Scopus (84) Google Scholar, 7Willer C.J. Speliotes E.K. Loos R.J.F. Li S. Lindgren C.M. Heid I.M. Berndt S.I. Elliott A.L. Jackson A.U. Lamina C. et al.Wellcome Trust Case Control ConsortiumGenetic Investigation of ANthropometric Traits ConsortiumSix new loci associated with body mass index highlight a neuronal influence on body weight regulation.Nat. Genet. 2009; 41: 25-34Crossref PubMed Scopus (1366) Google Scholar, 8Thorleifsson G. Walters G.B. Gudbjartsson D.F. Steinthorsdottir V. Sulem P. Helgadottir A. Styrkarsdottir U. Gretarsdottir S. Thorlacius S. Jonsdottir I. et al.Genome-wide association yields new sequence variants at seven loci that associate with measures of obesity.Nat. Genet. 2009; 41: 18-24Crossref PubMed Scopus (1053) Google Scholar and 2 loci influencing age at menarche,9Ong K.K. Elks C.E. Li S. Zhao J.H. Luan J. Andersen L.B. Bingham S.A. Brage S. Davey Smith G. Ekelund U. et al.Genetic variation in LIN28B is associated with the timing of puberty.Nat. Genet. 2009; 41: 729-733Crossref PubMed Scopus (268) Google Scholar, 10Sulem P. Gudbjartsson D.F. Rafnar T. Holm H. Olafsdottir E.J. Olafsdottir G.H. Jonsson T. Alexandersen P. Feenstra B. Boyd H.A. et al.Genome-wide association study identifies sequence variants on 6q21 associated with age at menarche.Nat. Genet. 2009; 41: 734-738Crossref PubMed Scopus (174) Google Scholar, 11He C. Kraft P. Chen C. Buring J.E. Paré G. Hankinson S.E. Chanock S.J. Ridker P.M. Hunter D.J. Chasman D.I. Genome-wide association studies identify loci associated with age at menarche and age at natural menopause.Nat. Genet. 2009; 41: 724-728Crossref PubMed Scopus (302) Google Scholar, 12Perry J.R.B. Stolk L. Franceschini N. Lunetta K.L. Zhai G. McArdle P.F. Smith A.V. Aspelund T. Bandinelli S. Boerwinkle E. et al.Meta-analysis of genome-wide association data identifies two loci influencing age at menarche.Nat. Genet. 2009; 41: 648-650Crossref PubMed Scopus (226) Google Scholar these findings explain only a marginal proportion of the overall variance of each trait. Additionally, we know very little about how these loci may influence longitudinal growth. To elucidate the genetic framework influencing height growth, we utilized the unique resource of longitudinal childhood height data available in Finnish cohorts.13Taponen S. Martikainen H. Järvelin M.-R. Sovio U. Laitinen J. Pouta A. Hartikainen A.-L. McCarthy M.I. Franks S. Paldanius M. Ruokonen A. Northern Finland Birth Cohort 1966 StudyMetabolic cardiovascular disease risk factors in women with self-reported symptoms of oligomenorrhea and/or hirsutism: Northern Finland Birth Cohort 1966 Study.J. Clin. Endocrinol. Metab. 2004; 89: 2114-2118Crossref PubMed Scopus (85) Google Scholar, 14Laitinen J. Power C. Järvelin M.-R. Family social class, maternal body mass index, childhood body mass index, and age at menarche as predictors of adult obesity.Am. J. Clin. Nutr. 2001; 74: 287-294PubMed Google Scholar, 15Ylihärsilä H. Kajantie E. Osmond C. Forsén T. Barker D.J. Eriksson J.G. Body mass index during childhood and adult body composition in men and women aged 56-70 y.Am. J. Clin. Nutr. 2008; 87: 1769-1775PubMed Google Scholar, 16Eriksson J.G. Forsén T. Tuomilehto J. Osmond C. Barker D.J. Early growth and coronary heart disease in later life: Longitudinal study.BMJ. 2001; 322: 949-953Crossref PubMed Scopus (782) Google Scholar, 17Raitakari O.T. Juonala M. Rönnemaa T. Keltikangas-Järvinen L. Räsänen L. Pietikäinen M. Hutri-Kähönen N. Taittonen L. Jokinen E. Marniemi J. et al.Cohort profile: The cardiovascular risk in Young Finns study.Int. J. Epidemiol. 2008; 37: 1220-1226Crossref PubMed Scopus (521) Google Scholar, 18Kivimäki M. Lawlor D.A. Smith G.D. Elovainio M. Jokela M. Keltikangas-Järvinen L. Vahtera J. Taittonen L. Juonala M. Viikari J.S.A. Raitakari O.T. Association of age at menarche with cardiovascular risk factors, vascular structure, and function in adulthood: The Cardiovascular Risk in Young Finns study.Am. J. Clin. Nutr. 2008; 87: 1876-1882PubMed Google Scholar, 19Heistaro S. Methodology Report: Health 2000 Survey. National Public Health Institute, Helsinki, Finland2008Google Scholar We chose pubertal growth as the primary mapping target for many reasons. Importantly, this growth phase regulates final height, accounting for as much as 15%–20% of adult stature.20Luo Z.C. Karlberg J. Critical growth phases for adult shortness.Am. J. Epidemiol. 2000; 152: 125-131Crossref PubMed Scopus (38) Google Scholar, 21Perry R.J. Farquharson C. Ahmed S.F. The role of sex steroids in controlling pubertal growth.Clin. Endocrinol. (Oxf.). 2008; 68: 4-15Crossref PubMed Scopus (90) Google Scholar Furthermore, most aspects of this growth period are highly heritable.3Silventoinen K. Pietiläinen K.H. Tynelius P. Sørensen T.I. Kaprio J. Rasmussen F. Genetic regulation of growth from birth to 18 years of age: The Swedish young male twins study.Am. J. Hum. Biol. 2008; 20: 292-298Crossref PubMed Scopus (41) Google Scholar, 22Fischbein S. Intra-pair similarity in physical growth of monozygotic and of dizygotic twins during puberty.Ann. Hum. Biol. 1977; 4: 417-430Crossref PubMed Scopus (79) Google Scholar, 23Sharma J.C. The genetic contribution to pubertal growth and development studied by longitudinal growth data on twins.Ann. Hum. Biol. 1983; 10: 163-171Crossref PubMed Scopus (46) Google Scholar Finally, the phenotypic variation is very large, with as much within-sex variation in timing as 4 yrs.24Palmert M.R. Boepple P.A. Variation in the timing of puberty: Clinical spectrum and genetic investigation.J. Clin. Endocrinol. Metab. 2001; 86: 2364-2368Crossref PubMed Scopus (162) Google Scholar The design of our study is presented in Figure 1. Altogether, three different Finnish population cohorts with longitudinal height data collected at different time points during childhood and adulthood, in addition to a fourth cohort with data on adult height, were included. A precise assessment of the pubertal growth spurt requires very frequent height measurements spanning a large age range, data which typically are not readily obtained in an epidemiological setting. Therefore, we monitored this growth phase with a simple and robust measurement capturing growth during late adolescence, the increase in height between age 14 and adulthood. This approach allowed us to maximize the number of subjects available for genome-wide association mapping, thereby also increasing the statistical power. A similar measurement, i.e., the change in relative height between age 12 and adulthood in females and between age 14 and adulthood in males, has previously been shown to correlate strongly with the timing of the pubertal growth spurt.25Wehkalampi K. Silventoinen K. Kaprio J. Dick D.M. Rose R.J. Pulkkinen L. Dunkel L. Genetic and environmental influences on pubertal timing assessed by height growth.Am. J. Hum. Biol. 2008; 20: 417-423Crossref PubMed Scopus (63) Google Scholar Thus, our study design primarily facilitated the detection of loci influencing the timing of the pubertal growth spurt. Moreover, the availability of longitudinal data on childhood height enabled the exploration of putative shared genetic effects influencing multiple periods of postnatal height growth. We first performed GWAS analysis of height growth during late adolescence in Northern Finland Birth Cohort 1966 (NFBC1966). The increase in height between age 14 and adulthood was used as an estimate of pubertal growth in 2073 males and 2248 females with genotypes from Illumina Infinium 370CNV Duo arrays (Figure 1).26Sabatti C. Service S.K. Hartikainen A.-L. Pouta A. Ripatti S. Brodsky J. Jones C.G. Zaitlen N.A. Varilo T. Kaakinen M. et al.Genome-wide association analysis of metabolic traits in a birth cohort from a founder population.Nat. Genet. 2009; 41: 35-46Crossref PubMed Scopus (570) Google Scholar Applying previously established thresholds,26Sabatti C. Service S.K. Hartikainen A.-L. Pouta A. Ripatti S. Brodsky J. Jones C.G. Zaitlen N.A. Varilo T. Kaakinen M. et al.Genome-wide association analysis of metabolic traits in a birth cohort from a founder population.Nat. Genet. 2009; 41: 35-46Crossref PubMed Scopus (570) Google Scholar five markers all located in a single block of linkage disequilibrium (LD) spanning 111 kb on chromosome 6q21, a block containing the 5′ end and upstream region of LIN28B (MIM 611044) (lin-28 homolog B [C. elegans]) and an uncharacterized open reading frame c6orf220, yielded evidence for a significant association signal in the combined analysis of males and females (p < 5 × 10−7). The signal predominantly came from females and to a lesser extent also from males (rs7759938; beta = 0.159, standard error [SE] = 0.032, p = 7.2 × 10−7 in females versus beta = 0.093, SE = 0.033, p = 0.005 in males; Table 1). Testing the best-associated SNP (rs7759938) and a proxy (rs314268; beta = 0.140, SE = 0.032, p = 1.4 × 10−5 in females versus beta = 0.095, SE = 0.033, p = 0.004 in males) in the longitudinal replication cohort Cardiovascular Risk in Young Finns Study (YF), including 1241 individuals (Figure 1), added further support to the original observation (rs7759938, combined p in all subjects = 5.0 × 10−11). The strongest associated marker explained approximately 1% of the total phenotypic variation in females and roughly 0.5% in males, estimated with the regression r2 in the Northern Finland Birth Cohort Study with the normalized phenotype as the outcome in an additive regression model adjusting for the first two dimensions obtained from the multidimensional scaling analysis.27Purcell S. Neale B. Todd-Brown K. Thomas L. Ferreira M.A. Bender D. Maller J. Sklar P. de Bakker P.I. Daly M.J. Sham P.C. PLINK: A tool set for whole-genome association and population-based linkage analyses.Am. J. Hum. Genet. 2007; 81: 559-575Abstract Full Text Full Text PDF PubMed Scopus (19303) Google Scholar Also, the genome-wide association p values showed more apparent departure from the quantile-quantile plot in females (see Figure S1 available online). The reason for this phenomenon remains unclear. Prior to regression analysis, the phenotypic outcome was normalized and standardized, but the underlying raw phenotype differed between males and females. The average peak growth velocity occurs at approximately 12 yrs in females and 14 yrs in males. As a consequence, the GWAS outcome captures growth a bit later relative to the average peak growth velocity in girls than in boys. Thus, the difference in association signals could in part be a reflection that our measurement of growth during late adolescence targets pubertal growth with a slightly different focus and resolution in both sexes.Table 1Association Signals between Pubertal Growth during Late Adolescence and LIN28B Obtained in Northern Finland Birth Cohort 1966 and the Replication Cohort Cardiovascular Risk of Young Finns StudyNFBC1966 FemalesYF FemalesChr.SNPPositionnBeta (SE)p ValueA1MAFnBeta (SE)p ValueMAF6rs1048531110544548922450.107 (0.058)0.06334G0.07----6rs692349010545539822470.083 (0.036)0.02258A0.207----6rs494665110547620322350.146 (0.03)1.481 × 10−6A0.435----6rs775993810548564722420.159 (0.032)7.204 × 10−7G0.3186640.167 (0.058)0.0043110.336rs31426210550131422000.15 (0.031)9.103 × 10−7G0.44----6rs31428010550753022410.151 (0.03)5.401 × 10−7A0.436----6rs121949741055108912248−0.052 (0.051)0.31A0.09----6rs31427710551435522140.126 (0.04)0.001654A0.167----6rs31426810552467122400.14 (0.032)1.422 × 10−5G0.326660.135 (0.058)0.019670.336NFBC1966 MalesYF MalesChr.SNPPositionnBeta (SE)p ValueA1MAFnBeta (SE)p ValueMAF6rs1048531110544548920730.124 (0.058)0.03156G0.076----6rs692349010545539820720.04 (0.038)0.3027A0.201----6rs494665110547620320600.076 (0.031)0.01611A0.436----6rs775993810548564720680.093 (0.033)0.004647G0.3245690.144 (0.066)0.029690.3086rs31426210550131420190.082 (0.032)0.009394G0.44----6rs31428010550753020660.072 (0.031)0.02155A0.436----6rs1219497410551089120720.001 (0.058)0.9874A0.084----6rs31427710551435520470.062 (0.041)0.1263A0.174----6rs31426810552467120650.095 (0.033)0.003559G0.3295700.121(0.066)0.066810.315Pubertal growth was estimated as height increase after age 14 (in NFBC1966) or age 15 (in YF). The data were analyzed by linear regression implemented in PLINK27Purcell S. Neale B. Todd-Brown K. Thomas L. Ferreira M.A. Bender D. Maller J. Sklar P. de Bakker P.I. Daly M.J. Sham P.C. PLINK: A tool set for whole-genome association and population-based linkage analyses.Am. J. Hum. Genet. 2007; 81: 559-575Abstract Full Text Full Text PDF PubMed Scopus (19303) Google Scholar covering the autosomes, assuming additive inheritance and including individual-specific scores of the first two dimensions of the multidimensional scaling identical-by-state (IBS) analysis as covariates. The phenotype distribution for the increase in height between ages 14 and 31 was normalized by logarithm transformation, and sex-specific Z scores computed from the normalized phenotype were used as input in the association analysis. The genomic inflation factor λ was 1.04 in both sexes. The association results from males and females were combined into fixed-effect meta-analysis with reciprocal weighting on the square of standard errors of the effect size estimates via the MetABEL package for the R software. Positions are based on the NCBI B36 assembly. Abbreviations are as follows: NFBC1966, Northern Finland Birth Cohort 1966; YF, Cardiovascular Risk in Young Finns Study; SE, standard error; MAF, minor allele frequency. Open table in a new tab Pubertal growth was estimated as height increase after age 14 (in NFBC1966) or age 15 (in YF). The data were analyzed by linear regression implemented in PLINK27Purcell S. Neale B. Todd-Brown K. Thomas L. Ferreira M.A. Bender D. Maller J. Sklar P. de Bakker P.I. Daly M.J. Sham P.C. PLINK: A tool set for whole-genome association and population-based linkage analyses.Am. J. Hum. Genet. 2007; 81: 559-575Abstract Full Text Full Text PDF PubMed Scopus (19303) Google Scholar covering the autosomes, assuming additive inheritance and including individual-specific scores of the first two dimensions of the multidimensional scaling identical-by-state (IBS) analysis as covariates. The phenotype distribution for the increase in height between ages 14 and 31 was normalized by logarithm transformation, and sex-specific Z scores computed from the normalized phenotype were used as input in the association analysis. The genomic inflation factor λ was 1.04 in both sexes. The association results from males and females were combined into fixed-effect meta-analysis with reciprocal weighting on the square of standard errors of the effect size estimates via the MetABEL package for the R software. Positions are based on the NCBI B36 assembly. Abbreviations are as follows: NFBC1966, Northern Finland Birth Cohort 1966; YF, Cardiovascular Risk in Young Finns Study; SE, standard error; MAF, minor allele frequency. We hypothesized that the observed association might be a consequence of an effect on the timing of the pubertal growth spurt. Therefore, we conducted follow-up analyses to characterize the growth effect at marker locus rs7759938 in more detail. Heights at ages 9, 12, and 15 were available in YF, prompting analysis of the height increase between ages 9 and 12 and between ages 12 and 14/15 to estimate pubertal growth during early and midpuberty separately in the subset of NFBC1966 study subjects with archived growth charts available. Finally, we estimated growth during early adolescence based on archived growth charts in a third Finnish cohort, the Helsinki Birth Cohort Study (HBCS) (Figure 1). The results are presented in Table S1. Considering growth between ages 9 and 12 as a proxy for the onset of the pubertal growth spurt, the observed correlation between the G (ancestral) allele at rs7759938 and decreased growth during early puberty both in males and females (p = 1.7 × 10−4) further supports an association between the G allele and later timing of the pubertal growth spurt. Interestingly, the LIN28B region has previously been associated with the timing of menarche in females.9Ong K.K. Elks C.E. Li S. Zhao J.H. Luan J. Andersen L.B. Bingham S.A. Brage S. Davey Smith G. Ekelund U. et al.Genetic variation in LIN28B is associated with the timing of puberty.Nat. Genet. 2009; 41: 729-733Crossref PubMed Scopus (268) Google Scholar, 10Sulem P. Gudbjartsson D.F. Rafnar T. Holm H. Olafsdottir E.J. Olafsdottir G.H. Jonsson T. Alexandersen P. Feenstra B. Boyd H.A. et al.Genome-wide association study identifies sequence variants on 6q21 associated with age at menarche.Nat. Genet. 2009; 41: 734-738Crossref PubMed Scopus (174) Google Scholar, 11He C. Kraft P. Chen C. Buring J.E. Paré G. Hankinson S.E. Chanock S.J. Ridker P.M. Hunter D.J. Chasman D.I. Genome-wide association studies identify loci associated with age at menarche and age at natural menopause.Nat. Genet. 2009; 41: 724-728Crossref PubMed Scopus (302) Google Scholar, 12Perry J.R.B. Stolk L. Franceschini N. Lunetta K.L. Zhai G. McArdle P.F. Smith A.V. Aspelund T. Bandinelli S. Boerwinkle E. et al.Meta-analysis of genome-wide association data identifies two loci influencing age at menarche.Nat. Genet. 2009; 41: 648-650Crossref PubMed Scopus (226) Google Scholar Four independent studies reported significant association either with rs7759938, yielding the strongest evidence for association in our study, or with markers in tight correlation, the same alleles associating with later age of menarche in other studies as with later timing of pubertal growth here (Table S2; Figure S3). Marker rs7759938 was also associated with age of menarche in the Finnish cohorts (n = 4379, beta = 0.124, SE = 0.023, p = 8.3 × 10−8). Even though both the pubertal growth spurt and menarche are secondary manifestations of pubertal maturation, the growth spurt represents an early marker of pubertal development in girls, whereas menarche is a late event. To clarify the possible causal direction of the associations, we performed multiple regression analysis including both rs7759938 and height growth during early puberty (between ages 9 and 12) as a proxy for timing of the pubertal growth spurt in the regression model. This conditioned analysis resulted in a major reduction of the association signal with age of menarche (beta = 0.046, SE = 0.030, p = 0.13, n = 1932), suggesting that the effects on both the timing of the growth spurt and the timing of menarche might not be independent. Rather, the timing of pubertal growth and age of menarche may be mediated through a common underlying mechanism. In addition to association with pubertal timing, the LIN28B region also coincides with a previously verified height locus.28Lettre G. Jackson A.U. Gieger C. Schumacher F.R. Berndt S.I. Sanna S. Eyheramendy S. Voight B.F. Butler J.L. Guiducci C. et al.Diabetes Genetics InitiativeFUSIONKORAProstate, Lung Colorectal and Ovarian Cancer Screening TrialNurses' Health StudySardiNIAIdentification of ten loci associated with height highlights new biological pathways in human growth.Nat. Genet. 2008; 40: 584-591Crossref PubMed Scopus (455) Google Scholar, 29Gudbjartsson D.F. Walters G.B. Thorleifsson G. Stefansson H. Halldorsson B.V. Zusmanovich P. Sulem P. Thorlacius S. Gylfason A. Steinberg S. et al.Many sequence variants affecting diversity of adult human height.Nat. Genet. 2008; 40: 609-615Crossref PubMed Scopus (496) Google Scholar Contrary to the published association findings with age of menarche, association to final height has been reported at two distinct marker loci that are only partially correlated with each other (pairwise r2 = 0.26), at rs314277 with a p value of 1.1 × 10−8 in roughly 25,000 individuals28Lettre G. Jackson A.U. Gieger C. Schumacher F.R. Berndt S.I. Sanna S. Eyheramendy S. Voight B.F. Butler J.L. Guiducci C. et al.Diabetes Genetics InitiativeFUSIONKORAProstate, Lung Colorectal and Ovarian Cancer Screening TrialNurses' Health StudySardiNIAIdentification of ten loci associated with height highlights new biological pathways in human growth.Nat. Genet. 2008; 40: 584-591Crossref PubMed Scopus (455) Google Scholar and at rs314268 with a p value of 7.7 × 10−7 in 49,000 individuals.29Gudbjartsson D.F. Walters G.B. Thorleifsson G. Stefansson H. Halldorsson B.V. Zusmanovich P. Sulem P. Thorlacius S. Gylfason A. Steinberg S. et al.Many sequence variants affecting diversity of adult human height.Nat. Genet. 2008; 40: 609-615Crossref PubMed Scopus (496) Google Scholar Marker rs314268 appears to overlap with the pubertal timing effect, showing strong correlation with the pubertal timing-associated SNP rs7759938 (r2 = 0.94; Figure S3). Thus, the effect on final height could be mediated through pubertal timing because individuals maturing later, as a result of a delayed growth spurt and an extended overall period of height growth, may grow taller than their earlier-maturing peers.30He Q. Karlberg J. Bmi in childhood and its association with height gain, timing of puberty, and final height.Pediatr. Res. 2001; 49: 244-251Crossref PubMed Scopus (323) Google Scholar, 31Sandhu J. Ben-Shlomo Y. Cole T.J. Holly J. Davey Smith G. The impact of childhood body mass index on timing of puberty, adult stature and obesity: A follow-up study based on adolescent anthropometry recorded at Christ's Hospital (1936–1964).Int. J. Obes. 2006; 30: 14-22Crossref PubMed Scopus (167) Google Scholar Also, the previously published association finding at rs314277 could reflect the same underlying functional mutation, in spite of the modest pairwise correlation between rs314277 and the pubertal timing-associated marker rs7759938 (r2 = 0.29). Alternatively, rs314277 might tag a second independent effect influencing final height. To test for the presence of two separate height-regulating effects at LIN28B, we analyzed final stature in three Finnish cohorts, both by considering the effect of the pubertal timing-associated markers rs7759938 and rs314277 separately and by including both markers simultaneously in the regression model. Consistent with the previous studies on adult height, we found the markers to be associated with adult stature when analyzed individually (n = 8903 at rs7759938, n = 8860 at rs314277; Table 2). Separate evaluation of females and males showed that rs314277 appeared to contribute to final height more significantly in females, whereas the effect at rs7759938 was, if anything, stronger in males. An analysis of rs314277 conditional on rs7759938 showed opposite effects on height in males and females, also suggestive of a sex-specific effect of this SNP (Table 2). To formally test for interaction between genotypes and sex, we performed multiple regression analysis, including both of the SNPs, sex, and all of their possible interactions in the model (Table 3), finding evidence for sex-genotype interaction at rs314277 (p = 0.005). The data thus support two independent effects at LIN28B influencing final height, one tagged by the pubertal timing-associated markers and one tagged by rs314277.Table 2Linear Regression Analysis of Final Height in Three Finnish Population Cohorts Evaluating the Effects of rs7759938 and rs314277Regression of Single MarkersSimultaneous Regression of Both Markersrs7759938rs314277rs7759938rs314277NFBC1966 males0.087 (0.030)0.036 (0.037)0.121 (0.041)−0.063 (0.050)HBCS males0.061 (0.057)0.034 (0.077)0.072 (0.072)−0.025 (0.097)H2000 males0.066 (0.048)0.000 (0.062)0.102 (0.060" @default.
• W1981190999 created "2016-06-24" @default.
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