In a recent study published in Genetics of Nature, researchers examined nearly 800,000 female deoxyribonucleic acid (DNA) to explore the complexities of puberty timing. They identified signals associated with the timing of menstruation and investigated their influence on the onset of puberty.
Record
Age at menarche (AAM) is a vital indicator of the timing of puberty in women, affecting reproductive maturity in association with health problems such as cardiovascular disease, diabetes, hormone-related malignancies, and obesity. AAM is polygenic, with 400 genetic loci identified in European populations. It is highly genetically correlated with the timing of puberty and obesity among males, with the melanocortin-3 receptor (MC3R) as the main hypothalamic sensor linking nutritional status to the timing of puberty.
About the study
In the present study, researchers investigated genetic variables that influence women’s age at menarche and potential links between reproductive timing and health outcomes in later life.
To discover independent markers for AAM, the researchers analyzed an extensive genome-wide association study (GWAS) of 799,845 women, among whom 166,890 were East Asian. They also conducted an extensive study of unusual variations in the timing of puberty among 222,283 females using exome sequencing data.
The researchers conducted a GWAS meta-analysis of age at menarche in 799,845 women using data from five strata: ReproGen consortium groups (n=38), the UK Biobank, the Ovarian Cancer Association Consortium (OCAC), the A consortium of the Breast Cancer Association (BCAC), 23andMe, and three East Asian biobanks.
The biobanks were Korean Genome and Epidemiology Study (KoGES), China Kadoorie Biobank (CKB) and Biobank Japan (BBJ). They also indirectly validated AAM signals by assessing age at voice breaking (AVB) in men from the UK Biobank survey and 23andMe.
The researchers conducted an exome-wide association study of 222,283 women of European descent from the UK Biobank. They investigated uncommon gene variants, including high confidence protein truncating variants (HC PTV) and deleterious variants with combined annotation-dependent depletion (CADD) scores ≥25. They also examined associations of rare variants with AAM or VB for ANOS1, CHD7, FGF8 and WDR11, all clinically evaluated in hypogonadotropic hypogonadism. They used lassosum and data from a meta-analysis of cohorts of European ancestry to calculate the AAM polygenic score (PGS).
The researchers combined AAM markers with phenotypic predictions in 3,140 female children from the Avon Longitudinal Research on Parents and Children (ALSPAC), creating a framework known as ‘GWAS to genes’ (G2G). They grouped 1,080 AAM markers in the Norwegian Mother, Father and Child Cohort Study (MoBa) based on their relationships with body weight from birth to eight years of age. They also investigated biological pathways based on early weight trajectories and AAM-related gene expression dynamics in GnRH neurons.
Results
The study found 1,080 distinct adrenal amino acid (AAM) signals with genome-wide significance, accounting for 11.0% of trait variation in the independent sample dataset. Women in the bottom and top 1.0% of polygenic risk had 14-fold and 11-fold increased odds of early and late puberty, respectively. Rarer alleles had an effect size of 3.50 months, while more common variants had an effect size of five days.
The researchers observed a 1.2-fold (median) increase in χ2 values ​​for their association with age at menarche in the combined ancestry study compared to those restricted to Europeans. The finding is consistent with the increasing number of samples from East Asia (21%). Among 1,080 age-at-menarche markers, 84% (n=909) revealed directionally concordant relationships with age at voice break in the UK Biobank, while 79% (n=852) were present in 23andMe. Analysis of the combined data set, including 205,354 subjects, showed that 83% (n=893) of the signals showed directionally compatible results.
Several genes among 200,000 females contained uncommon loss-of-function variants, including mutations in zinc finger protein 483 (ZNF483), which counteracted multigenic risk effects. Gene-variant maps and neuronal ribonucleic acid (RNA) sequencing of mouse gonadotropin-releasing hormone identified 665 genes such as G Protein-Coupled Receptor 83 (GPR83), an unidentified receptor that increased MC3R signaling, a critical nutritional sensor. Common signals and timing of menopause in DNA damage response-related genes suggest that ovarian reserves may communicate centrally to initiate puberty.
The Danish Blood Donor Study (DBDS) found that variation in AAM quadrupled from 5.60% to 11.0% for 969 accessible brands. There were six genes significantly associated with age at menarche at the exome level, including two genes previously implicated in unusual monogenic disorders of puberty: Tachykinin receptor 3 (TACR3) in normosomal idiopathic hypogonadotropic hypogonadism (IHH) and Makorin Ring Protein 3 ( MKRN3 ) in familial precocious puberty of the central type.
AAM signals with ALSPAC data explained higher variance in AAM than childhood body mass index (BMI), parental BMI, or maternal AAM. They were equally good at predicting extreme AAMs as a multiphenotype predictor, and a combined genotype-phenotype model performed well for both early and late AAMs.
conclusion
The study identified signals associated with age at menarche, which accounted for 11% of trait variation. Polygenic risk affects the timing of puberty, with the top and bottom 1% of risk indicating higher rates of late and early puberty. Rare genetic loss-of-function mutations in ZNF483 influence polygenic risk and timing of menarche.
The study shows potential genetic links between reproductive timing and health outcomes in later life, highlighting the importance of understanding genetic influences on adolescent development. The extended multi-ancestry GWAS signal doubles the variation explained by AAM.
Journal Reference:
- Kentistou, KA, Kaisinger, LR, Stankovic, S. et al. Understanding the genetic complexity of the timing of puberty across the allele frequency spectrum. Nat Genet (2024). DOI: 10.1038/s41588-024-01798-4