Search tips
Search criteria 


Logo of wtpaEurope PMCEurope PMC Funders GroupSubmit a Manuscript
J Clin Endocrinol Metab. Author manuscript; available in PMC 2012 November 22.
Published in final edited form as:
PMCID: PMC3504301

Associations between the Pubertal Timing-Related Variant in LIN28B and BMI Vary Across the Life Course



The common C allele of rs314276 in LIN28B has been robustly associated with earlier age at menarche in girls and associated with earlier timing of other pubertal traits in both sexes.


Our objective was to explore the associations between rs314276, as a marker of earlier pubertal timing, and body mass index (BMI), weight, and height across the life course.


The rs314276 in LIN28B was genotyped in 1242 men and 1209 women born in 1946 and participating in the Medical Research Council National Survey of Health and Development. Birth weight was recorded, and height and weight were measured or self-reported repeatedly at 11 time points between ages 2 and 53 yr. Polynomial mixed models were used to test whether additive genetic associations with SD scores (SDS) for BMI and height changed with age between 0 and 53 yr.


Longitudinal analyses revealed age-dependent associations between rs314276 genotype and BMI (P < 0.001 for genotype-by-age2 interaction) and body weight (P < 0.001 for genotype-by-age2 interaction) in women, but not in men. In women only, the C allele at rs314276 was associated with higher BMI SDS from ages 15–43 yr. In contrast, C allele associations with shorter height SDS were apparent in both men and women and did not vary with age.


A common genetic variant in LIN28B that confers earlier puberty was associated with a prolonged increase in BMI during adolescence and early to mid-adulthood in women only. Such genetic associations may provide insights into the direct effects of pubertal timing on obesity risk.

Genome-wide association studies recently identified association between common genetic variation in LIN28B and age at menarche (14). The common C allele at the single-nucleotide polymorphism (SNP) rs314276 was associated with earlier onset of menstruation and also with earlier breast development in girls and earlier pubic hair development and voice breaking in boys (1). In those studies, the C allele at rs314276 was also associated with faster childhood weight gain and greater gains in body mass index (BMI) from ages 7–11 yr in girls (1), consistent with the well-recognized effects of puberty on weight gain (5). In addition, this variant was associated with shorter adult height in both men and women (1), putatively due to a shorter time span for childhood growth (6).

Earlier menarche is associated with increased risks for later metabolic disease outcomes including hypertension, type 2 diabetes, and cardiovascular disease (7, 8). Puberty is associated with marked accelerations in gains in weight and height due to the actions of sex steroids. After pubertal maturation, young women often continue to gain rapidly in BMI and body fat, and women with earlier menarche continue to gain weight more rapidly into adulthood (8). Although these disease risks appear to be mediated through adult adiposity (8, 9), it is not clear whether increased adult adiposity is a direct consequence of early puberty or whether early puberty is simply a marker of the long-term tracking of a predisposition to excess adiposity from prepuberty through to adult life (10).

We previously reported the associations between the C allele at rs314276 and earlier pubertal timing in girls and boys in the Medical Research Council National Survey of Health and Development (NSHD) (1). We now report life-course associations between rs314276 genotype and growth and weight gain in NSHD, which has repeated measurements of heights and weights from age 2–53 yr (11). We hypothesized that such associations might indicate the direct effects of puberty on BMI and growth because this variant was previously shown to be unrelated to BMI or body weight in prepubertal children (at age <8 yr old) (1).

Materials and Methods

NSHD is a socially stratified birth cohort of 2547 women and 2815 men, who have been followed up since their birth in 1946 (11). In the most recent contact, 1472 men and 1563 women aged 53 yr and largely representative of the native-born population of that age provided information (12). The majority (n = 2989) were interviewed and examined in their homes by trained research nurses, with others completing a postal questionnaire (n = 46). Contact was not attempted for the 1979 individuals who had previously refused to take part, were living abroad, were untraced since last contact at 43 yr, or had already died. The data collection received Multi-Centre Research Ethics Committee approval, and participants gave informed consent.

Data collection

Birth weight to the nearest quarter pound (113 g) was extracted from medical records and converted into kilograms. Height and weight were measured using standardized protocols at ages 2, 4, 6, 7, 11, 15, 36, 43, and 53 yr and self-reported at ages 20 and 26 yr. BMI, defined as weight (kilograms)/height (meters)2, was calculated at each age. Blood samples were collected from 2756 participants at age 53 yr. DNA was extracted from 2718 participants, and rs314276 genotypes were assigned in 2451 (call rate was 90.4%). Genotypes were identified by custom TaqMan SNP genotyping assays (Applied Biosystems, Warrington, UK) as recently described (1). Genotype frequencies were in Hardy-Weinberg equilibrium (P > 0.6).


Sex-specific SD scores (SDS) for height, weight, and BMI were calculated using internally generated growth charts; constructed using the LMS (L = skewness; M = median; S = coefficient of variation) method (13). This is preferable to the use of an external reference, which can be misleading for historical cohorts (14).

Statistical methods

Longitudinal analyses were performed using multilevel models, which take account of the correlation between repeated measures on the same individual and allow for incomplete outcome data on the assumption that data are missing at random. To test whether the association between genotype and each measure of body size (height, weight, or BMI SDS) changed with age, we first fitted linear age and genotype-by-age interaction terms and then added, in turn, quadratic and cubic ages and their interactions with genotype. Change in height was modeled to adulthood and, because the first two measures of adult height (at age 20 and 26 yr) were self-reported, measured height at 36 yr was used as final attained height and was assumed to have been achieved by age 20 yr. Likelihood ratio tests were used to assess the improvement in fit on addition of each new term in the model. Formal tests for interaction showed significant sex differences in the associations (e.g. P = 0.02 for genotype × age2 × sex interaction on BMI), and therefore all results are shown separately by sex.

Cross-sectional associations at each age were tested between genotype and height, weight, or BMI SDS by sex using linear regression, assuming an additive genetic model. Analyses were performed using Stata version 10.1 (StataCorp, College Station, TX).


Details of the 2451 individuals with genotype data available are shown in Supplemental Table 1 (published on The Endocrine Society’s Journals Online web site at Their growth measures did not differ substantially from NSHD participants without genotype data.

BMI and weight

In longitudinal analyses, in women only, the additive association between the rs314276 C allele and BMI SDS changed in a quadratic manner with age (P < 0.001 for genotype by age2 interaction; Table 1). Differences in BMI SDS by genotype widened during childhood and adolescence, reached a peak at around 26 yr, and then decreased (Supplemental Fig. 1). A similar age-dependent genetic association was seen with weight SDS (P < 0.001 for genotype by age2 interaction; Table 1), again in women but not in men.

Longitudinal associations between LIN28B rs314276 genotype with BMI and weight SDS and from birth to age 53 yr in women and men

In cross-sectional analyses, the rs314276 C allele was associated with greater BMI SDS in women from ages 15–43 yr, and similar (nonsignificant) trends were seen with body weight at these ages (Fig. 1). In men, the rs314276 C allele was associated with greater BMI only at age 4 yr, coincident with an association with shorter height rather than increased weight (Fig. 1).

FIG. 1
Cross-sectional associations between LIN28B rs314276 genotype with BMI, weight, and height SDS at up to 12 different time points from birth to age 53 yr in men and women. Error bars represent mean (95% CI) regression coefficient from additive genetic ...


In longitudinal analyses, throughout childhood and adult life, there was a constant association between the LIN28B rs314276 C allele and shorter height, which was of similar magnitude in women [−0.08 SDS per C allele, 95% confidence interval (CI) = −0.15 to −0.01] and in men [−0.07 SDS per C allele, 95% CI = −0.14 to 0.01]. Cross-sectional analyses were consistent with a constant association with height across most ages, although the associations were more apparent in women than in men (Fig. 1).


In a unique prospective birth cohort study, we observed that a common genetic variant in LIN28B that confers earlier puberty was associated with a prolonged increase in BMI during adolescence and early to mid-adulthood in women only. This variant was also associated with a constant reduction in height. Although this variant has only relatively small effects on pubertal timing (1) and BMI, our findings allow us to make inferences about the causal relationships between these outcomes.

The main strength of this study was the availability of longitudinal data on weight and height across childhood, adolescence, and adulthood up to age 53 yr, which allowed a unique exploration of life-course genetic associations with body size. Our longitudinal analyses make full use of all available outcome data under the assumption that missing data are missing at random. This is a reasonable assumption given that the DNA was collected at the most recent contact with participants, and hence the sample represents those still alive and in the study at age 53 yr.

We recently described rs314276 in LIN28B to be the first common genetic determinant of the timing of puberty (1). This locus was also identified in three other studies of menarche timing (24). LIN28B is homologous to the heterochronic gene lin-28 in Caenorhabditis elegans and encodes a potent and specific regulator of preprocessing of the let-7 family of micro-RNAs (15). In contrast to its consistent association with pubertal timing, our earlier studies showed that rs314276 was not associated with obesity risk in older adults; in a large cross-sectional analysis of 10,166 women and 9,840 men aged 40–75 yr, rs314276 showed no association with BMI, waist circum-ference, or body fat (1). Together with our current findings, these observations suggest that the rs314276 C allele is associated with greater weight and BMI during adolescence and early adult life in women, but its effects become gradually attenuated from around ages 30–40 yr onward, suggesting that different genetic or lifestyle factors contribute to the ongoing rise in adult BMI.

The relevance of this prolonged but transient increase in BMI on disease risk is uncertain. He et al. (8) described that the association between earlier menarche and increased type 2 diabetes risk was stronger in women aged under 45 yr, and in the Bogalusa Heart Study (16), childhood and adolescent BMI predicted carotid intimal thickness in young adults. Therefore, elevated adiposity even during adolescence and early to mid-adult life are important for metabolic disease outcomes.

Surprisingly, given that rs314276 is related to pubertal timing in both boys and girls (1), no associations were seen with weight or BMI in men. There is a marked sexual divergence in body composition during puberty; girls show preferential accumulation of fat mass over fat-free mass (17) in parallel with changes in estrogen levels (18), whereas boys gain relatively more fat-free mass (17), likely driven by changes in androgen levels (19). It is therefore possible that early puberty has different effects on adiposity according to sex. Furthermore, although we confirmed the rs314276 C allele association with shorter adult height, there was no evidence to support our earlier hypothesis that this is due to accelerated gains in childhood height followed by earlier growth cessation (1). Instead, the association with shorter height was constant throughout childhood and adult life in both sexes.

Although it is well established that earlier pubertal maturation in girls is related to increased body weight, the causal direction is unclear. There are plausible biological mechanisms to explain why girls who are already over-weight before puberty could have earlier pubertal onset and progression (20). Conversely, earlier puberty in girls could also have a direct influence on adiposity, for example due to longer exposure to estrogens. The lack of any clear association between rs314276 and BMI or weight during young childhood (before age 7–8 yr) in either our current or earlier studies (1) needs further confirmation but leads us to infer that the current associations with this variant illustrate the direct effects of early pubertal timing on adolescent and early adult BMI. However, further studies are needed to exclude pleiotropic effects of this SNP on the timing of puberty and energy homeostasis.

In conclusion, genetic variation in LIN28B that confers earlier puberty was associated with a prolonged increase in BMI in women during adolescence and early to mid-adulthood.


We are very grateful to the members of this birth cohort for their continuing interest and participation in the study.

This work was supported by the Medical Research Council.


Body mass index
confidence interval
National Survey of Health and Development
SD score
single-nucleotide polymorphism.


Disclosure Summary: The authors have no conflict of interests regarding the publication of this article.


1. Ong KK, Elks CE, Li S, Zhao JH, Luan J, Andersen LB, Bingham SA, Brage S, Smith GD, Ekelund U, Gillson CJ, Glaser B, Golding J, Hardy R, Khaw KT, Kuh D, Luben R, Marcus M, McGeehin MA, Ness AR, Northstone K, Ring SM, Rubin C, Sims MA, Song K, Strachan DP, Vollenweider P, Waeber G, Waterworth DM, Wong A, Deloukas P, Barroso I, Mooser V, Loos RJ, Wareham NJ. Genetic variation in LIN28B is associated with the timing of puberty. Nat Genet. 2009;41:729–733. [PMC free article] [PubMed]
2. Perry JR, Stolk L, Franceschini N, Lunetta KL, Zhai G, McArdle PF, Smith AV, Aspelund T, Bandinelli S, Boerwinkle E, Cherkas L, Eiriksdottir G, Estrada K, Ferrucci L, Folsom AR, Garcia M, Gudnason V, Hofman A, Karasik D, Kiel DP, Launer LJ, van Meurs J, Nalls MA, Rivadeneira F, Shuldiner AR, Singleton A, Soranzo N, Tanaka T, Visser JA, Weedon MN, Wilson SG, Zhuang V, Streeten EA, Harris TB, Murray A, Spector TD, Demerath EW, Uitterlinden AG, Murabito JM. Meta-analysis of genome-wide association data identifies two loci influencing age at menarche. Nat Genet. 2009;41:648–650. [PMC free article] [PubMed]
3. He C, Kraft P, Chen C, Buring JE, Paré G, Hankinson SE, Chanock SJ, Ridker PM, Hunter DJ, Chasman DI. Genome-wide association studies identify loci associated with age at menarche and age at natural menopause. Nat Genet. 2009;41:724–728. [PMC free article] [PubMed]
4. Sulem P, Gudbjartsson DF, Rafnar T, Holm H, Olafsdottir EJ, Olafsdottir GH, Jonsson T, Alexandersen P, Feenstra B, Boyd HA, Aben KK, Verbeek AL, Roeleveld N, Jonasdottir A, Styrkarsdottir U, Steinthorsdottir V, Karason A, Stacey SN, Gudmundsson J, Jakobsdottir M, Thorleifsson G, Hardarson G, Gulcher J, Kong A, Kiemeney LA, Melbye M, Christiansen C, Tryggvadottir L, Thorsteinsdottir U, Stefansson K. Genome-wide association study identifies sequence variants on 6q21 associated with age at menarche. Nat Genet. 2009;41:734–738. [PubMed]
5. Jasik CB, Lustig RH. Adolescent obesity and puberty: the “perfect storm. Ann NY Acad Sci. 2008;1135:265–279. [PubMed]
6. Onland-Moret NC, Peeters PH, van Gils CH, Clavel-Chapelon F, Key T, Tjønneland A, Trichopoulou A, Kaaks R, Manjer J, Panico S, Palli D, Tehard B, Stoikidou M, Bueno-De-Mesquita HB, Boeing H, Overvad K, Lenner P, Quirós JR, Chirlaque MD, Miller AB, Khaw KT, Riboli E. Age at menarche in relation to adult height: the EPIC study. Am J Epidemiol. 2005;162:623–632. [PubMed]
7. Lakshman R, Forouhi NG, Sharp SJ, Luben R, Bingham SA, Khaw KT, Wareham NJ, Ong KK. Early age at menarche associated with cardiovascular disease and mortality. J Clin Endocrinol Metab. 2009;94:4953–4960. [PubMed]
8. He C, Zhang C, Hunter DJ, Hankinson SE, Buck Louis GM, Hediger ML, Hu FB. Age at menarche and risk of type 2 diabetes: results from 2 large prospective cohort studies. Am J Epidemiol. 2010;171:334–344. [PubMed]
9. Lakshman R, Forouhi N, Luben R, Bingham S, Khaw K, Wareham N, Ong KK. Association between age at menarche and risk of diabetes in adults: results from the EPIC-Norfolk cohort study. Diabetologia. 2008;51:781–786. [PubMed]
10. Lee JM, Appugliese D, Kaciroti N, Corwyn RF, Bradley RH, Lumeng JC. Weight status in young girls and the onset of puberty. Pediatrics. 2007;119:e624–630. [PubMed]
11. Wadsworth M, Kuh D, Richards M, Hardy R. Cohort Profile: The 1946 National Birth Cohort (MRC National Survey of Health and Development) Int J Epidemiol. 2006;35:49–54. [PubMed]
12. Wadsworth ME, Butterworth SL, Hardy RJ, Kuh DJ, Richards M, Langenberg C, Hilder WS, Connor M. The life course prospective design: an example of benefits and problems associated with study longevity. Social Science, Medicine. 2003;57:2193–2205. [PubMed]
13. Cole TJ, Green PJ. Smoothing reference centile curves: the LMS method and penalized likelihood. Stat Med. 1992;11:1305–1319. [PubMed]
14. Silverwood R, Leon D, De Stavola B. Long-term trends in BMI: are contemporary childhood BMI growth references appropriate when looking at historical datasets? Longitudinal Life Course Studies. 2009;1:27–44.
15. Viswanathan SR, Daley GQ, Gregory RI. Selective blockade of microRNA processing by Lin28. Science. 2008;320:97–100. [PMC free article] [PubMed]
16. Li S, Chen W, Srinivasan SR, Bond MG, Tang R, Urbina EM, Berenson GS. Childhood cardiovascular risk factors and carotid vascular changes in adulthood: the Bogalusa Heart Study. JAMA. 2003;290:2271–2276. [PubMed]
17. Ahmed ML, Ong KK, Morrell DJ, Cox L, Drayer N, Perry L, Preece MA, Dunger DB. Longitudinal study of leptin concentrations during puberty: sex differences and relationship to changes in body composition. J Clin Endocrinol Metab. 1999;84:899–905. [PubMed]
18. Bandini LG, Must A, Naumova EN, Anderson S, Caprio S, Spadano-Gasbarro JI, Dietz WH. Change in leptin, body composition and other hormones around menarche: a visual representation. Acta Paediatr. 2008;97:1454–1459. [PMC free article] [PubMed]
19. Rogol AD. Growth at puberty: interaction of androgens and growth hormone. Med Sci Sports Exerc. 1994;26:767–770. [PubMed]
20. Ahmed ML, Ong KK, Dunger DB. Childhood obesity and the timing of puberty. Trends Endocrinol Metab. 2009;20:237–242. [PubMed]