MC3R links nutritional state to childhood growth and the timing of puberty

The state of somatic energy stores in metazoans is communicated to the brain, which regulates key aspects of behaviour, growth, nutrient partitioning and development1. The central melanocortin system acts through melanocortin 4 receptor (MC4R) to control appetite, food intake and energy expenditure2. Here we present evidence that MC3R regulates the timing of sexual maturation, the rate of linear growth and the accrual of lean mass, which are all energy-sensitive processes. We found that humans who carry loss-of-function mutations in MC3R, including a rare homozygote individual, have a later onset of puberty. Consistent with previous findings in mice, they also had reduced linear growth, lean mass and circulating levels of IGF1. Mice lacking Mc3r had delayed sexual maturation and an insensitivity of reproductive cycle length to nutritional perturbation. The expression of Mc3r is enriched in hypothalamic neurons that control reproduction and growth, and expression increases during postnatal development in a manner that is consistent with a role in the regulation of sexual maturation. These findings suggest a bifurcating model of nutrient sensing by the central melanocortin pathway with signalling through MC4R controlling the acquisition and retention of calories, whereas signalling through MC3R primarily regulates the disposition of calories into growth, lean mass and the timing of sexual maturation.

Voice break in boys-temporal relations with other pubertal milestones and likely causal effects of BMI

STUDY QUESTION

How is timing of voice break related to other male pubertal milestones as well as to BMI?

SUMMARY ANSWER

We provide a comprehensive temporal analysis of male pubertal milestones, including reproductive hormone dynamics, confirm voice break as a late milestone of male puberty and report a likely causal relationship between higher BMI and earlier age at voice break in men.

WHAT IS KNOWN ALREADY

Voice break represents a late pubertal milestone and recalled age at voice break is frequently used in epidemiological studies as a measure of puberty. In contrast, clinical studies use mainly testicular enlargement and/or genital tanner stage as the marker of pubertal onset. However, neither correlation of pubertal milestones nor reproductive hormone dynamics have been assessed in detail previously. Further, although BMI and puberty timing are known to be closely linked, cause and effect between these traits are not known.

STUDY DESIGN, SIZE, DURATION

The study included a population-based mixed cross-sectional and longitudinal cohort (2006–2014, COPENHAGEN Puberty Study) of 730 healthy Danish boys. Data for 55 871 male research participants from the 23andMe study were obtained, including genome-wide single nucleotide polymorphism data and age at voice break.

PARTICIPANTS/MATERIALS, SETTING, METHODS

We performed a detailed evaluation of pubertal milestones and reproductive hormone levels (study population 1). A Mendelian randomization (MR) approach was used to determine the likely causal link between BMI and timing of voice break (study population 2).

MAIN RESULTS AND THE ROLE OF CHANCE

Voice break occurred at mean age 13.6 (95% CI: 13.5–13.8) years. At voice break, mean (95% CI) testosterone levels, LH levels and bi-testicular volume were 10.9 (10.0–11.7) nmol/L, 2.4 (2.2–2.5) IU/L and 24 (23–25) mL, respectively. Voice break correlated moderately strongly with timing of male pubertal milestones, including testicular enlargement, gonadarche, pubarche, sweat odor, axillary hair growth and testosterone above limit of detection (r² range: 0.43–0.61). Timing of all milestones was negatively associated with age-specific BMI (all P ≤ 0.001). MR analyses inferred likely causal effects of higher BMI on earlier voice break in males (−0.35 years/approximate SD, P < 0.001).

LIMITATIONS, REASONS FOR CAUTION

Participation rate of the population-based cohort was 25%. Further, boys that were followed longitudinally were examined approximately every 6 months limiting the time resolution of pubertal milestones. Using adult BMI as exposure instead of prepubertal BMI in the MR analysis and the known inaccuracies of the testosterone immunoassay at low testosterone levels may be further limitations.

WIDER IMPLICATIONS OF THE FINDINGS

We provide valuable normative data on the temporal relation of male pubertal milestones. Further, the likely causal relationship between BMI and puberty timing highlights the importance of preventing obesity in childhood.

STUDY FUNDING/COMPETING INTEREST(S)

This work was supported by Danish Agency for Science, Technology and Innovation (09-067 180); Danish Ministry of the Environment, CeHoS (MST-621-00 065); Capital Region of Denmark (R129-A3966); Ministry of Higher Education and Science (DFF-1331-00 113); Innovation Fund Denmark (InnovationsFonden, 14-2013-4); The International Center for Research and Research Training in Endocrine Disrupting Effects of Male Reproduction and Child Health. B.H., F.R.D., J.R.B.P. and K.K.O. are supported by the Medical Research Council (MC_UU_12015/2). The 23andMe study is supported by the National Human Genome Research Institute of the National Institutes of Health (R44HG006981). Members of the 23andMe Research Team are employees of 23andMe, Inc. and hold stock or stock options in 23andMe.

TRIAL REGISTRATION NUMBER

NCT01411527

Associations between body mass index-related genetic variants and adult body composition: The Fenland cohort study

BACKGROUND/OBJECTIVE

Body mass index (BMI) is a surrogate measure of adiposity but does not distinguish fat from lean or bone mass. The genetic determinants of BMI are thought to predominantly influence adiposity but this has not been confirmed. Here we characterise the association between BMI-related genetic variants and body composition in adults.

SUBJECTS/METHODS

Among 9667 adults aged 29-64 years from the Fenland study, a genetic risk score for BMI (BMI-GRS) was calculated for each individual as the weighted sum of BMI-increasing alleles across 96 reported BMI-related variants. Associations between the BMI-GRS and body composition, estimated by dual-energy X-ray absorptiometry (DXA) scans, were examined using age-adjusted linear regression models, separately by sex.

RESULTS

The BMI-GRS was positively associated with all fat, lean and bone variables. Across body regions, associations of the greatest magnitude were observed for adiposity variables, for example, for each s.d. increase in BMI-GRS predicted BMI, we observed a 0.90 s.d. (95% confidence interval (CI): 0.71, 1.09) increase in total fat mass for men (P=3.75 × 10^-21) and a 0.96 s.d. (95% CI: 0.77, 1.16) increase for women (P=6.12 × 10^-22). Associations of intermediate magnitude were observed with lean variables, for example, total lean mass: men: 0.68 s.d. (95% CI: 0.49, 0.86; P=1.91 × 10^-12); women: 0.85 s.d. (95% CI: 0.65, 1.04; P=2.66 × 10^-17) and of a lower magnitude with bone variables, for example, total bone mass: men: 0.39 s.d. (95% CI: 0.20, 0.58; P=5.69 × 10^-5); women: 0.45 s.d. (95% CI: 0.26, 0.65; P=3.96 × 10⁶). Nominally significant associations with BMI were observed for 28 single-nucleotide polymorphisms. All 28 were positively associated with fat mass and 13 showed adipose-specific effects.

CONCLUSIONS

In adults, genetic susceptibility to elevated BMI influences adiposity more than lean or bone mass. This mirrors the association between BMI and body composition. The BMI-GRS can be used to model the effects of measured BMI and adiposity on health and other outcomes.