Parent, A.S. et al. The timing of normal puberty and the age limits of sexual precocity: variations around the world, secular trends, and changes after migration. Endocr. Rev. 24, 668–693 (2003).
Perry, J.R., Murray, A., Day, F.R. & Ong, K.K. Molecular insights into the aetiology of female reproductive ageing. Nat. Rev. Endocrinol. 11, 725–734 (2015).
Perry, J.R. et al. Parent-of-origin-specific allelic associations among 106 genomic loci for age at menarche. Nature 514, 92–97 (2014).
Lunetta, K.L. et al. Rare coding variants and X-linked loci associated with age at menarche. Nat. Commun. 6, 7756 (2015).
Day, F.R. et al. Shared genetic aetiology of puberty timing between sexes and with health-related outcomes. Nat. Commun. 6, 8842 (2015).
Westra, H.J. et al. Systematic identification of trans eQTLs as putative drivers of known disease associations. Nat. Genet. 45, 1238–1243 (2013).
Zhu, Z. et al. Integration of summary data from GWAS and eQTL studies predicts complex trait gene targets. Nat. Genet. 48, 481–487 (2016).
Finucane, H.K. et al. Heritability enrichment of specifically expressed genes identifies disease-relevant tissues and cell types. Preprint at bioRxiv https://dx.doi.org/10.1101/103069 (2017).
Rao, S.S. et al. A 3D map of the human genome at kilobase resolution reveals principles of chromatin looping. Cell 159, 1665–1680 (2014).
Smemo, S. et al. Obesity-associated variants within FTO form long-range functional connections with IRX3. Nature 507, 371–375 (2014).
Mbarek, H. et al. Identification of common genetic variants influencing spontaneous dizygotic twinning and female fertility. Am. J. Hum. Genet. 98, 898–908 (2016).
Ong, K.K. et al. Genetic variation in LIN28B is associated with the timing of puberty. Nat. Genet. 41, 729–733 (2009).
Perry, J.R. et al. Meta-analysis of genome-wide association data identifies two loci influencing age at menarche. Nat. Genet. 41, 648–650 (2009).
Zhang, J. et al. LIN28 regulates stem cell metabolism and conversion to primed pluripotency. Cell Stem Cell 19, 66–80 (2016).
Zhu, H. et al. Lin28a transgenic mice manifest size and puberty phenotypes identified in human genetic association studies. Nat. Genet. 42, 626–630 (2010).
Zhu, H. et al. The Lin28/let-7 axis regulates glucose metabolism. Cell 147, 81–94 (2011).
Baran, Y. et al. The landscape of genomic imprinting across diverse adult human tissues. Genome Res. 25, 927–936 (2015).
van den Berg, S.M. & Boomsma, D.I. The familial clustering of age at menarche in extended twin families. Behav. Genet. 37, 661–667 (2007).
Ahlgren, M., Melbye, M., Wohlfahrt, J. & Sørensen, T.I. Growth patterns and the risk of breast cancer in women. N. Engl. J. Med. 351, 1619–1626 (2004).
Collaborative Group on Hormonal Factors in Breast Cancer. Menarche, menopause, and breast cancer risk: individual participant meta-analysis, including 118 964 women with breast cancer from 117 epidemiological studies. Lancet Oncol. 13, 1141–1151 (2012).
Bhaskaran, K. et al. Body-mass index and risk of 22 specific cancers: a population-based cohort study of 5·24 million UK adults. Lancet 384, 755–765 (2014).
Locke, A.E. et al. Genetic studies of body mass index yield new insights for obesity biology. Nature 518, 197–206 (2015).
Gao, C. et al. Mendelian randomization study of adiposity-related traits and risk of breast, ovarian, prostate, lung and colorectal cancer. Int. J. Epidemiol. 45, 896–908 (2016).
Guo, Y. et al. Genetically predicted body mass index and breast cancer risk: Mendelian randomization analyses of data from 145,000 women of European descent. PLoS Med. 13, e1002105 (2016).
Abreu, A.P. et al. Central precocious puberty caused by mutations in the imprinted gene MKRN3. N. Engl. J. Med. 368, 2467–2475 (2013).
da Rocha, S.T., Edwards, C.A., Ito, M., Ogata, T. & Ferguson-Smith, A.C. Genomic imprinting at the mammalian Dlk1–Dio3 domain. Trends Genet. 24, 306–316 (2008).
Giles, G.G. et al. Early growth, adult body size and prostate cancer risk. Int. J. Cancer 103, 241–245 (2003).
de Vries, L., Kauschansky, A., Shohat, M. & Phillip, M. Familial central precocious puberty suggests autosomal dominant inheritance. J. Clin. Endocrinol. Metab. 89, 1794–1800 (2004).
Wehkalampi, K., Widén, E., Laine, T., Palotie, A. & Dunkel, L. Patterns of inheritance of constitutional delay of growth and puberty in families of adolescent girls and boys referred to specialist pediatric care. J. Clin. Endocrinol. Metab. 93, 723–728 (2008).
Winkler, T.W. et al. Quality control and conduct of genome-wide association meta-analyses. Nat. Protoc. 9, 1192–1212 (2014).
Willer, C.J., Li, Y. & Abecasis, G.R. METAL: fast and efficient meta-analysis of genomewide association scans. Bioinformatics 26, 2190–2191 (2010).
Sudlow, C. et al. UK biobank: an open access resource for identifying the causes of a wide range of complex diseases of middle and old age. PLoS Med. 12, e1001779 (2015).
Day, F.R., Elks, C.E., Murray, A., Ong, K.K. & Perry, J.R. Puberty timing associated with diabetes, cardiovascular disease and also diverse health outcomes in men and women: the UK Biobank study. Sci. Rep. 5, 11208 (2015).
Bulik-Sullivan, B.K. et al. LD Score regression distinguishes confounding from polygenicity in genome-wide association studies. Nat. Genet. 47, 291–295 (2015).
Loh, P.R. et al. Efficient Bayesian mixed-model analysis increases association power in large cohorts. Nat. Genet. 47, 284–290 (2015).
Bulik-Sullivan, B. et al. An atlas of genetic correlations across human diseases and traits. Nat. Genet. 47, 1236–1241 (2015).
Bowden, J., Davey Smith, G. & Burgess, S. Mendelian randomization with invalid instruments: effect estimation and bias detection through Egger regression. Int. J. Epidemiol. 44, 512–525 (2015).
Segrè, A.V., Groop, L., Mootha, V.K., Daly, M.J. & Altshuler, D. Common inherited variation in mitochondrial genes is not enriched for associations with type 2 diabetes or related glycemic traits. PLoS Genet. 6, e1001058 (2010).
Finucane, H.K. et al. Partitioning heritability by functional annotation using genome-wide association summary statistics. Nat. Genet. 47, 1228–1235 (2015).
Gamazon, E.R. et al. A gene-based association method for mapping traits using reference transcriptome data. Nat. Genet. 47, 1091–1098 (2015).
GTEx Consortium. The Genotype-Tissue Expression (GTEx) project. Nat. Genet. 45, 580–585 (2013).
Sarkar, A., Ward, L.D. & Kellis, M. Functional enrichments of disease variants across thousands of independent loci in eight diseases. Preprint at bioRxiv http://dx.doi.org/10.1101/048066 (2016).
Ernst, J. et al. Mapping and analysis of chromatin state dynamics in nine human cell types. Nature 473, 43–49 (2011).
Kundaje, A. et al. Integrative analysis of 111 reference human epigenomes. Nature 518, 317–330 (2015).