More than 1,000 small changes in DNA identified that influence age of first period

By Pooja Toshniwal PahariaReviewed by Danielle Ellis, B.Sc.Jul 4 2024

In a recent study published in Nature Genetics, researchers examined nearly 800,000 women's deoxyribonucleic acid (DNA) to explore puberty timing complexities. They identified signals related to menarche timing and investigated their influence on puberty onset.

Background

Age at menarche (AAM) is a vital indicator of puberty timing in females, influencing reproductive maturity in association with health concerns such as cardiovascular diseases, diabetes, hormone-related malignancies, and obesity. AAM is polygenic, with 400 genetic loci identified in European populations. It has a high genetic association with puberty timing and obesity among males, with melanocortin-3 receptor (MC3R) as the primary hypothalamic sensor that links nutrition status to pubertal timing.

About the study

In the present study, researchers investigated genetic variables influencing women's age at menarche and potential linkages between reproductive timing and later-life health outcomes.

To discover independent markers for AAM, the researchers analyzed an extended genome-wide association study (GWAS) of 799,845 females, among whom 166,890 were East Asian. They also conducted an extensive study of uncommon variations in pubertal timing among 222,283 females using exome sequencing data.

The researchers conducted GWAS meta-analytical research for age at menarche among 799,845 females using data from five strata: ReproGen consortium groups (n=38), the United Kingdom Biobank, the Ovarian Cancer Association Consortium (OCAC), the Breast Cancer Association Consortium (BCAC), 23andMe, and three biobanks of East Asian individuals.

The biobanks were the Korean Genome and Epidemiology Study (KoGES), the China Kadoorie Biobank (CKB), and the Biobank Japan (BBJ). They also indirectly validated AAM signals by assessing the age at voice breaking (AVB) in men from UK Biobank research and 23andMe.

Researchers conducted an exome-wide association investigation on 222,283 European-ancestry women from the UK Biobank. They investigated unusual gene variations, including high-confidence protein truncating variants (HC PTVs) and harmful variants with combined annotation-dependent depletion (CADD) scores of ≥25. They also examined rare variant relationships 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 European ancestry cohorts to calculate AAM's polygenic score (PGS).

Researchers matched AAM signals to phenotypic predictions in 3,140 female children from the Avon Longitudinal Research on Parents and Children (ALSPAC) research, creating a framework known as 'GWAS to genes' (G2G). They grouped 1,080 AAM signals 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 the expressional dynamics of AAM-associated genes in GnRH neurons.

Results

The study found 1,080 distinct Adrenal Amino Acid (AAM) signals of genome-level significance, accounting for 11.0% of trait variation in the independent sample dataset. Women in the lowermost and uppermost 1.0% of polygenic risk had 14-fold and 11-fold increased chances of precocious and delayed puberty, respectively. Rarer alleles had an effect size of 3.50 months, whereas more frequent variations had an effect size of five days.

The researchers noticed a 1.2-fold (median) rise in χ2 values for their connection with age at menarche in the combined ancestry study than those limited to Europeans. The finding is commensurate with the increasing count of samples from East Asia (21%). Among 1,080 age-at-menarche signals, 84% (n=909) revealed directionally concordant relationships with the age at voice break in the United Kingdom Biobank, whereas 79% (n=852) were present in 23andMe. Analysis of the combined dataset, including 205,354 individuals, showed that 83% (n=893) of signals demonstrated directionally accordant effects.

Several genes among 200,000 females included unusual loss-of-function variations, including mutations in Zinc Finger Protein 483 (ZNF483), which neutralized polygenic risk effects. Variant-to-gene maps and murine gonadotropin-releasing hormone neuronal ribonucleic acid (RNA) sequencing identified 665 genes like G Protein-Coupled Receptor 83 (GPR83), an unidentified receptor that increased MC3R signaling, a crucial nutrition sensor. Shared signals and menopausal timing at DNA damage response-related genes indicate that ovarian reserves may communicate centrally to initiate puberty.

The Danish Blood Donor Study (DBDS) discovered that the variation in AAM quadrupled from 5.60% to 11.0% for 969 accessible signals. There were six genes significantly associated with the age at menarche at the exome level, including two genes priorly implicated in uncommon monogenic puberty disorders: Tachykinin Receptor 3 (TACR3) in normosmic idiopathic-type hypogonadotropic hypogonadism (IHH) and Makorin Ring Finger Protein 3 (MKRN3) in familial central-type precocious puberty.

AAM signals with ALSPAC data explained a higher variance in AAM than childhood body mass index (BMI), parental BMI, or a mother's AAM. They were as good at predicting AAM extremes as a multi-phenotype predictor, and a combination genotype and phenotype model performed well for both early and late AAM.

Conclusion

The study identified age-related signals during menarche, which accounted for 11% of trait variation. Polygenic risk affects puberty timing, with the top and bottom 1% of risk indicating higher rates of delayed and precocious puberty. Rare loss-of-function genetic mutations in ZNF483 affect polygenic risk and menarche timing.

The study shows possible genetic linkages between reproductive timing and later-life health consequences, stressing the significance of understanding genetic impacts on pubertal development. The extended multi-ancestry GWAS signal doubles the variation explained by AAM.