Understanding the genetic complexity of puberty timing across the allele frequency spectrum

Pubertal timing varies considerably and is associated with later health outcomes. We performed multi-ancestry genetic analyses on ~800,000 women, identifying 1,080 signals for age at menarche. Collectively, these explained 11% of trait variance in an independent sample. Women at the top and bottom 1% of polygenic risk exhibited ~11 and ~14-fold higher risks of delayed and precocious puberty, respectively. We identified several genes harboring rare loss-of-function variants in ~200,000 women, including variants in ZNF483, which abolished the impact of polygenic risk. Variant-to-gene mapping approaches and mouse gonadotropin-releasing hormone neuron RNA sequencing implicated 665 genes, including an uncharacterized G-protein-coupled receptor, GPR83, which amplified the signaling of MC3R, a key nutritional sensor. Shared signals with menopause timing at genes involved in DNA damage response suggest that the ovarian reserve might signal centrally to trigger puberty. We also highlight body size-dependent and independent mechanisms that potentially link reproductive timing to later life disease

Understanding the genetic complexity of puberty timing across the allele frequency spectrum

Pubertal timing varies considerably and is associated with later health outcomes. We performed multi-ancestry genetic analyses on ~800,000 women, identifying 1,080 signals for age at menarche. Collectively, these explained 11% of trait variance in an independent sample. Women at the top and bottom 1% of polygenic risk exhibited ~11 and ~14-fold higher risks of delayed and precocious puberty, respectively. We identified several genes harboring rare loss-of-function variants in ~200,000 women, including variants in ZNF483, which abolished the impact of polygenic risk. Variant-to-gene mapping approaches and mouse gonadotropin-releasing hormone neuron RNA sequencing implicated 665 genes, including an uncharacterized G-protein-coupled receptor, GPR83, which amplified the signaling of MC3R, a key nutritional sensor. Shared signals with menopause timing at genes involved in DNA damage response suggest that the ovarian reserve might signal centrally to trigger puberty. We also highlight body size-dependent and independent mechanisms that potentially link reproductive timing to later life disease

Rare variants in the MECP2 gene in girls with central precocious puberty: a translational cohort study.

BACKGROUND: Identification of genetic causes of central precocious puberty have revealed epigenetic mechanisms as regulators of human pubertal timing. MECP2, an X-linked gene, encodes a chromatin-associated protein with a role in gene transcription. MECP2 loss-of-function mutations usually cause Rett syndrome, a severe neurodevelopmental disorder. Early pubertal development has been shown in several patients with Rett syndrome. The aim of this study was to explore whether MECP2 variants are associated with an idiopathic central precocious puberty phenotype. METHODS: In this translational cohort study, participants were recruited from seven tertiary centres from five countries (Brazil, Spain, France, the USA, and the UK). Patients with idiopathic central precocious puberty were investigated for rare potentially damaging variants in the MECP2 gene, to assess whether MECP2 might contribute to the cause of central precocious puberty. Inclusion criteria were the development of progressive pubertal signs (Tanner stage 2) before the age of 8 years in girls and 9 years in boys and basal or GnRH-stimulated LH pubertal concentrations. Exclusion criteria were the diagnosis of peripheral precocious puberty and the presence of any recognised cause of central precocious puberty (CNS lesions, known monogenic causes, genetic syndromes, or early exposure to sex steroids). All patients included were followed up at the outpatient clinics of participating academic centres. We used high-throughput sequencing in 133 patients and Sanger sequencing of MECP2 in an additional 271 patients. Hypothalamic expression of Mecp2 and colocalisation with GnRH neurons were determined in mice to show expression of Mecp2 in key nuclei related to pubertal timing regulation. FINDINGS: Between Jun 15, 2020, and Jun 15, 2022, 404 patients with idiopathic central precocious puberty (383 [95%] girls and 21 [5%] boys; 261 [65%] sporadic cases and 143 [35%] familial cases from 134 unrelated families) were enrolled and assessed. We identified three rare heterozygous likely damaging coding variants in MECP2 in five girls: a de novo missense variant (Arg97Cys) in two monozygotic twin sisters with central precocious puberty and microcephaly; a de novo missense variant (Ser176Arg) in one girl with sporadic central precocious puberty, obesity, and autism; and an insertion (Ala6_Ala8dup) in two unrelated girls with sporadic central precocious puberty. Additionally, we identified one rare heterozygous 3'UTR MECP2 insertion (36_37insT) in two unrelated girls with sporadic central precocious puberty. None of them manifested Rett syndrome. Mecp2 protein colocalised with GnRH expression in hypothalamic nuclei responsible for GnRH regulation in mice. INTERPRETATION: We identified rare MECP2 variants in girls with central precocious puberty, with or without mild neurodevelopmental abnormalities. MECP2 might have a role in the hypothalamic control of human pubertal timing, adding to the evidence of involvement of epigenetic and genetic mechanisms in this crucial biological process. FUNDING: Fundação de Amparo à Pesquisa do Estado de São Paulo, Conselho Nacional de Desenvolvimento Científico e Tecnológico, and the Wellcome Trust

Protein-truncating variants in BSN are associated with severe adult-onset obesity, type 2 diabetes and fatty liver disease.

Acknowledgements: We thank the participants and investigators in the UK Biobank study who made this work possible (resource application number 26041; 9905), the UK Biobank Exome Sequencing Consortium (UKB-ESC) members AbbVie, Alnylam Pharmaceuticals, AstraZeneca, Biogen, Bristol-Myers Squibb, Pfizer, Regeneron and Takeda for funding the generation of the data; the Regeneron Genetics Center for completing the sequencing and initial quality control of the exome sequencing data; and the AstraZeneca Centre for Genomics Research analytics and informatics team for processing and analyzing the sequencing and phenotype data. We thank the physicians who referred people to the GOOS and the participants and families for their involvement. Y.Z., K.A.K., R.Y.J., E.J.G., F.R.D., L.R.K., N.J.W., K.K.O. and J.R.B.P. are supported by the UK MRC (Unit Programmes MC_UU_00006/1 and MC_UU_00006/2). M.C. and A.M.S. are supported by a project grant from the MRC (MR/S026193/1). Y.-C.L.T., B.Y.H.L. and G.S.H.Y. are supported by the MRC Metabolic Diseases Unit (MC_UU_00014/1). G.K.C.D. is supported by the BBSRC Doctoral Training Programme. The MCPS has received funding from the Mexican Health Ministry, the National Council of Science and Technology for Mexico, the Wellcome Trust (058299/Z/99), Cancer Research UK, the British Heart Foundation and the UK MRC (MC_UU_00017/2). I.S.F. is supported by a Wellcome Principal Research Fellowship (207462/Z/17/Z), the National Institute for Health and Care Research (NIHR) Cambridge Biomedical Research Centre, the Botnar Foundation, the Bernard Wolfe Health Neuroscience Endowment and an NIHR Senior Investigator award. I.B. acknowledges funding from an ‘Expanding Excellence in England’ award from Research England. F.M. is a New York Stem Cell Foundation−Robertson Investigator (NYSCF-R-156) and is supported by the Wellcome Trust and Royal Society (211221/Z/18/Z) and a Ben Barres Early Career Acceleration Award from the Chan Zuckerberg Initiative (CZI NDCN 191942). This work was supported by the NIHR Exeter Biomedical Research Centre. Next-generation sequencing was performed at the Institute of Metabolic Science Genomics and Bioinformatics Core supported by the MRC (MC_UU_00014/5) and the Wellcome Trust (208363/Z/17/Z) and the Cancer Research UK Cambridge Institute Genomics Core. This study was supported by the NIHR Cambridge Biomedical Research Centre. These funding sources had no role in the design, conduct, or analysis of the study or in the decision to submit the manuscript for publication.Funder: Chan Zuckerberg Initiative (CZI NDCN 191942)Obesity is a major risk factor for many common diseases and has a substantial heritable component. To identify new genetic determinants, we performed exome-sequence analyses for adult body mass index (BMI) in up to 587,027 individuals. We identified rare loss-of-function variants in two genes (BSN and APBA1) with effects substantially larger than those of well-established obesity genes such as MC4R. In contrast to most other obesity-related genes, rare variants in BSN and APBA1 were not associated with normal variation in childhood adiposity. Furthermore, BSN protein-truncating variants (PTVs) magnified the influence of common genetic variants associated with BMI, with a common variant polygenic score exhibiting an effect twice as large in BSN PTV carriers than in noncarriers. Finally, we explored the plasma proteomic signatures of BSN PTV carriers as well as the functional consequences of BSN deletion in human induced pluripotent stem cell-derived hypothalamic neurons. Collectively, our findings implicate degenerative processes in synaptic function in the etiology of adult-onset obesity

Protein-truncating variants in BSN are associated with severe adult-onset obesity, type 2 diabetes and fatty liver disease

Acknowledgements: We thank the participants and investigators in the UK Biobank study who made this work possible (resource application number 26041; 9905), the UK Biobank Exome Sequencing Consortium (UKB-ESC) members AbbVie, Alnylam Pharmaceuticals, AstraZeneca, Biogen, Bristol-Myers Squibb, Pfizer, Regeneron and Takeda for funding the generation of the data; the Regeneron Genetics Center for completing the sequencing and initial quality control of the exome sequencing data; and the AstraZeneca Centre for Genomics Research analytics and informatics team for processing and analyzing the sequencing and phenotype data. We thank the physicians who referred people to the GOOS and the participants and families for their involvement. Y.Z., K.A.K., R.Y.J., E.J.G., F.R.D., L.R.K., N.J.W., K.K.O. and J.R.B.P. are supported by the UK MRC (Unit Programmes MC_UU_00006/1 and MC_UU_00006/2). M.C. and A.M.S. are supported by a project grant from the MRC (MR/S026193/1). Y.-C.L.T., B.Y.H.L. and G.S.H.Y. are supported by the MRC Metabolic Diseases Unit (MC_UU_00014/1). G.K.C.D. is supported by the BBSRC Doctoral Training Programme. The MCPS has received funding from the Mexican Health Ministry, the National Council of Science and Technology for Mexico, the Wellcome Trust (058299/Z/99), Cancer Research UK, the British Heart Foundation and the UK MRC (MC_UU_00017/2). I.S.F. is supported by a Wellcome Principal Research Fellowship (207462/Z/17/Z), the National Institute for Health and Care Research (NIHR) Cambridge Biomedical Research Centre, the Botnar Foundation, the Bernard Wolfe Health Neuroscience Endowment and an NIHR Senior Investigator award. I.B. acknowledges funding from an ‘Expanding Excellence in England’ award from Research England. F.M. is a New York Stem Cell Foundation−Robertson Investigator (NYSCF-R-156) and is supported by the Wellcome Trust and Royal Society (211221/Z/18/Z) and a Ben Barres Early Career Acceleration Award from the Chan Zuckerberg Initiative (CZI NDCN 191942). This work was supported by the NIHR Exeter Biomedical Research Centre. Next-generation sequencing was performed at the Institute of Metabolic Science Genomics and Bioinformatics Core supported by the MRC (MC_UU_00014/5) and the Wellcome Trust (208363/Z/17/Z) and the Cancer Research UK Cambridge Institute Genomics Core. This study was supported by the NIHR Cambridge Biomedical Research Centre. These funding sources had no role in the design, conduct, or analysis of the study or in the decision to submit the manuscript for publication.Funder: Chan Zuckerberg Initiative (CZI NDCN 191942)Obesity is a major risk factor for many common diseases and has a substantial heritable component. To identify new genetic determinants, we performed exome-sequence analyses for adult body mass index (BMI) in up to 587,027 individuals. We identified rare loss-of-function variants in two genes (BSN and APBA1) with effects substantially larger than those of well-established obesity genes such as MC4R. In contrast to most other obesity-related genes, rare variants in BSN and APBA1 were not associated with normal variation in childhood adiposity. Furthermore, BSN protein-truncating variants (PTVs) magnified the influence of common genetic variants associated with BMI, with a common variant polygenic score exhibiting an effect twice as large in BSN PTV carriers than in noncarriers. Finally, we explored the plasma proteomic signatures of BSN PTV carriers as well as the functional consequences of BSN deletion in human induced pluripotent stem cell-derived hypothalamic neurons. Collectively, our findings implicate degenerative processes in synaptic function in the etiology of adult-onset obesity

Understanding the genetic complexity of puberty timing across the allele frequency spectrum

Pubertal timing varies considerably and has been associated with a range of health outcomes in later life. To elucidate the underlying biological mechanisms, we performed multi-ancestry genetic analyses in ∼800,000 women, identifying 1,080 independent signals associated with age at menarche. Collectively these loci explained 11% of the trait variance in an independent sample, with women at the top and bottom 1% of polygenic risk exhibiting a ∼11 and ∼14-fold higher risk of delayed and precocious pubertal development, respectively. These common variant analyses were supported by exome sequence analysis of ∼220,000 women, identifying several genes, including rare loss of function variants in ZNF483 which abolished the impact of polygenic risk. Next, we implicated 660 genes in pubertal development using a combination of in silico variant-to-gene mapping approaches and integration with dynamic gene expression data from mouse embryonic GnRH neurons. This included an uncharacterized G-protein coupled receptor GPR83 , which we demonstrate amplifies signaling of MC3R , a key sensor of nutritional status. Finally, we identified several genes, including ovary-expressed genes involved in DNA damage response that co-localize with signals associated with menopause timing, leading us to hypothesize that the ovarian reserve might signal centrally to trigger puberty. Collectively these findings extend our understanding of the biological complexity of puberty timing and highlight body size dependent and independent mechanisms that potentially link reproductive timing to later life disease. </p

Understanding the genetic complexity of puberty timing across the allele frequency spectrum

Acknowledgements: This research was supported by the UK Medical Research Council (MRC; Unit program MC_UU_00006/2) and has been conducted using the UK Biobank Resource under application 9905. Other study-specific acknowledgements can be found in the Supplementary Information.Pubertal timing varies considerably and is associated with later health outcomes. We performed multi-ancestry genetic analyses on ~800,000 women, identifying 1,080 signals for age at menarche. Collectively, these explained 11% of trait variance in an independent sample. Women at the top and bottom 1% of polygenic risk exhibited ~11 and ~14-fold higher risks of delayed and precocious puberty, respectively. We identified several genes harboring rare loss-of-function variants in ~200,000 women, including variants in ZNF483, which abolished the impact of polygenic risk. Variant-to-gene mapping approaches and mouse gonadotropin-releasing hormone neuron RNA sequencing implicated 665 genes, including an uncharacterized G-protein-coupled receptor, GPR83, which amplified the signaling of MC3R, a key nutritional sensor. Shared signals with menopause timing at genes involved in DNA damage response suggest that the ovarian reserve might signal centrally to trigger puberty. We also highlight body size-dependent and independent mechanisms that potentially link reproductive timing to later life disease

Understanding the genetic complexity of puberty timing across the allele frequency spectrum

Acknowledgements: This research was supported by the UK Medical Research Council (MRC; Unit program MC_UU_00006/2) and has been conducted using the UK Biobank Resource under application 9905. Other study-specific acknowledgements can be found in the Supplementary Information.Pubertal timing varies considerably and is associated with later health outcomes. We performed multi-ancestry genetic analyses on ~800,000 women, identifying 1,080 signals for age at menarche. Collectively, these explained 11% of trait variance in an independent sample. Women at the top and bottom 1% of polygenic risk exhibited ~11 and ~14-fold higher risks of delayed and precocious puberty, respectively. We identified several genes harboring rare loss-of-function variants in ~200,000 women, including variants in ZNF483, which abolished the impact of polygenic risk. Variant-to-gene mapping approaches and mouse gonadotropin-releasing hormone neuron RNA sequencing implicated 665 genes, including an uncharacterized G-protein-coupled receptor, GPR83, which amplified the signaling of MC3R, a key nutritional sensor. Shared signals with menopause timing at genes involved in DNA damage response suggest that the ovarian reserve might signal centrally to trigger puberty. We also highlight body size-dependent and independent mechanisms that potentially link reproductive timing to later life disease

Research data supporting: "Understanding the genetic complexity of puberty timing across the allele frequency spectrum"

This dataset is made up of GWAS meta-analysis for age at menarche (AAM), in up to 799,845 women. All studies provided GWAS data imputed to at least 1000 Genomes reference panel density, yielding a total of ~12.7 million genetic variants in the final meta-analysis. Variants were meta-analysed using a fixed-effects inverse-variance-weighted model in METAL and filtered to include minor allele frequency (MAF) >= 0.1%. Summary statistics made available for download are from an analysis excluding 23andMe (ancestry combined up to n=723,014 and European-only up to n=556,124) and following all the filtering steps as outlined above. Datasets available for download: 1) Ancestry combined GWAS summary statistics Menarche2024_AncestryCombined_RELEASE_EXC23andMe.txt.gz 2) European-only GWAS summary statistics Menarche2024_EuropeanOnly_RELEASE_EXC23andMe.txt.gz Both tab-delimited files, with one row per SNP including the same columns as the above. For further information please check the supplied readme file or the associated publication.MC_UU_00006/