Smith, G.D. & Ebrahim, S. Mendelian randomization: can genetic epidemiology contribute to understanding environmental determinants of disease? Int. J. Epidemiol. 32, 1–22 (2003).
Smith, G.D. & Hemani, G. Mendelian randomization: genetic anchors for causal inference in epidemiological studies. Hum. Mol. Genet. 23 (R1), R89–R98 (2014).
Vandenberg, S.G. in Methods and Goals in Human Behavior Genetics 29–43 (cademic Press, 1965).
Kempthorne, O. & Osborne, R.H. The interpretation of twin data. Am. J. Hum. Genet. 13, 320–339 (1961).
Loehlin, J.C. & Vandenberg, S.G. in Progress in Human Behavior Genetics (ed. Vandenberg, S.G.) 261–285 (Johns Hopkins Univ. Press, 1968).
Neale, M. & Cardon, L. Methodology for Genetic Studies of Twins and Families Number 67 (Springer, 1992).
Lichtenstein, P. et al. Common genetic determinants of schizophrenia and bipolar disorder in Swedish families: a population-based study. Lancet 373, 234–239 (2009).
Voight, B.F. et al. Plasma HDL cholesterol and risk of myocardial infarction: a Mendelian randomisation study. Lancet 380, 572–580 (2012).
Do, R. et al. Common variants associated with plasma triglycerides and risk for coronary artery disease. Nat. Genet. 45, 1345–1352 (2013).
Visscher, P.M., Brown, M.A., McCarthy, M.I. & Yang, J. Five years of GWAS discovery. Am. J. Hum. Genet. 90, 7–24 (2012).
Yang, J. et al. Common SNPs explain a large proportion of the heritability for human height. Nat. Genet. 42, 565–569 (2010).
Yang, J., Lee, S.H., Goddard, M.E. & Visscher, P.M. GCTA: a tool for genome-wide complex trait analysis. Am. J. Hum. Genet. 88, 76–82 (2011).
Lee, S.H., Yang, J., Goddard, M.E., Visscher, P.M. & Wray, N.R. Estimation of pleiotropy between complex diseases using single-nucleotide polymorphism–derived genomic relationships and restricted maximum likelihood. Bioinformatics 28, 2540–2542 (2012).
Cross-Disorder Group of the Psychiatric Genomics Consortium. Genetic relationship between five psychiatric disorders estimated from genome-wide SNPs. Nat. Genet. 45, 984–994 (2013).
Vattikuti, S., Guo, J. & Chow, C.C. Heritability and genetic correlations explained by common SNPs for metabolic syndrome traits. PLoS Genet. 8, e1002637 (2012).
Chen, G.-B. et al. Estimation and partitioning of (co) heritability of inflammatory bowel disease from GWAS and Immunochip data. Hum. Mol. Genet. 23, 4710–4720 (2014).
Purcell, S.M. et al. Common polygenic variation contributes to risk of schizophrenia and bipolar disorder. Nature 460, 748–752 (2009).
Dudbridge, F. Power and predictive accuracy of polygenic risk scores. PLoS Genet. 9, e1003348 (2013).
Bulik-Sullivan, B.K. et al. LD score regression distinguishes confounding from polygenicity in genome-wide association studies. Nat. Genet. 47, 291–295 (2015).
Yang, J. et al. Genomic inflation factors under polygenic inheritance. Eur. J. Hum. Genet. 19, 807–812 (2011).
Speed, D., Hemani, G., Johnson, M.R. & Balding, D.J. Improved heritability estimation from genome-wide SNPs. Am. J. Hum. Genet. 91, 1011–1021 (2012).
Cross-Disorder Group of the Psychiatric Genomics Consortium. et al. Identification of risk loci with shared effects on five major psychiatric disorders: a genome-wide analysis. Lancet 381, 1371–1379 (2013).
Perry, J.R. et al. Parent-of-origin-specific allelic associations among 106 genomic loci for age at menarche. Nature 514, 92–97 (2014).
Morris, A.P. et al. Large-scale association analysis provides insights into the genetic architecture and pathophysiology of type 2 diabetes. Nat. Genet. 44, 981–990 (2012).
Horikoshi, M. et al. New loci associated with birth weight identify genetic links between intrauterine growth and adult height and metabolism. Nat. Genet. 45, 76–82 (2013).
Freathy, R.M. et al. Type 2 diabetes risk alleles are associated with reduced size at birth. Diabetes 58, 1428–1433 (2009).
Early Growth Genetics (EGG) Consortium. A genome-wide association meta-analysis identifies new childhood obesity loci. Nat. Genet. 44, 526–531 (2012).
Taal, H.R. et al. Common variants at 12q15 and 12q24 are associated with infant head circumference. Nat. Genet. 44, 532–538 (2012).
Onland-Moret, N.C. et al. Age at menarche in relation to adult height: the EPIC study. Am. J. Epidemiol. 162, 623–632 (2005).
Day, F. et al. Puberty timing associated with diabetes, cardiovascular disease and also diverse health outcomes in men and women: the UK Biobank study. Sci. Rep. 5, 11208 (2014).
Elks, C.E. et al. Age at menarche and type 2 diabetes risk: the EPIC-InterAct study. Diabetes Care 36, 3526–3534 (2013).
Finucane, H.K. et al. Partitioning heritability by functional category using genome-wide association study summary statistics. Nat. Genet. doi:10.1038/ng.3404 (28 September 2015).
Farooqi, I.S. Defining the neural basis of appetite and obesity: from genes to behaviour. Clin. Med. 14, 286–289 (2014).
Wang, N. et al. Associations of adult height and its components with mortality: a report from cohort studies of 135,000 Chinese women and men. Int. J. Epidemiol. 40, 1715–1726 (2011).
Hebert, P.R. et al. Height and incidence of cardiovascular disease in male physicians. Circulation 88, 1437–1443 (1993).
Rich-Edwards, J.W. et al. Height and the risk of cardiovascular disease in women. Am. J. Epidemiol. 142, 909–917 (1995).
Rietveld, C.A. et al. GWAS of 126,559 individuals identifies genetic variants associated with educational attainment. Science 340, 1467–1471 (2013).
Barnes, D.E. & Yaffe, K. The projected effect of risk factor reduction on Alzheimer's disease prevalence. Lancet Neurol. 10, 819–828 (2011).
Norton, S., Matthews, F.E., Barnes, D.E., Yaffe, K. & Brayne, C. Potential for primary prevention of Alzheimer's disease: an analysis of population-based data. Lancet Neurol. 13, 788–794 (2014).
MacCabe, J.H. et al. Excellent school performance at age 16 and risk of adult bipolar disorder: national cohort study. Br. J. Psychiatry 196, 109–115 (2010).
Tiihonen, J. et al. Premorbid intellectual functioning in bipolar disorder and schizophrenia: results from a cohort study of male conscripts. Am. J. Psychiatry 162, 1904–1910 (2005).
Pierce, J.P., Fiore, M.C., Novotny, T.E., Hatziandreu, E.J. & Davis, R.M. Trends in cigarette smoking in the United States: educational differences are increasing. J. Am. Med. Assoc. 261, 56–60 (1989).
Striegel-Moore, R.H., Garvin, V., Dohm, F.-A. & Rosenheck, R.A. Psychiatric comorbidity of eating disorders in men: a national study of hospitalized veterans. Int. J. Eat. Disord. 25, 399–404 (1999).
Blinder, B.J., Cumella, E.J. & Sanathara, V.A. Psychiatric comorbidities of female inpatients with eating disorders. Psychosom. Med. 68, 454–462 (2006).
Deary, I.J., Strand, S., Smith, P. & Fernandes, C. Intelligence and educational achievement. Intelligence 35, 13–21 (2007).
Calvin, C.M., Fernandes, C., Smith, P., Visscher, P.M. & Deary, I.J. Sex, intelligence and educational achievement in a national cohort of over 175,000 11-year-old schoolchildren in England. Intelligence 38, 424–432 (2010).
Durkin, M.S. et al. Socioeconomic inequality in the prevalence of autism spectrum disorder: evidence from a US cross-sectional study. PLoS ONE 5, e11551 (2010).
Robinson, E.B. et al. Autism spectrum disorder severity reflects the average contribution of de novo and familial influences. Proc. Natl. Acad. Sci. USA 111, 15161–15165 (2014).
Samocha, K.E. et al. A framework for the interpretation of de novo mutation in human disease. Nat. Genet. 46, 944–950 (2014).
Silman, A.J. & Pearson, J.E. Epidemiology and genetics of rheumatoid arthritis. Arthritis Res. 4 (suppl 3), S265–S272 (2002).
de Leon, J. & Diaz, F.J. A meta-analysis of worldwide studies demonstrates an association between schizophrenia and tobacco smoking behaviors. Schizophr. Res. 76, 135–157 (2005).
Andreassen, O.A. et al. Improved detection of common variants associated with schizophrenia by leveraging pleiotropy with cardiovascular-disease risk factors. Am. J. Hum. Genet. 92, 197–209 (2013).
Cotsapas, C. et al. Pervasive sharing of genetic effects in autoimmune disease. PLoS Genet. 7, e1002254 (2011).
Farh, K.K. et al. Genetic and epigenetic fine mapping of causal autoimmune disease variants. Nature 518, 337–343 (2015).
Wurtz, P. et al. Metabolic signatures of adiposity in young adults: Mendelian randomization analysis and effects of weight change. PLoS Med. 11, e1001765 (2014).
Burgess, S., Freitag, D.F., Khan, H., Gorman, D.N. & Thompson, S.G. Using multivariable Mendelian randomization to disentangle the causal effects of lipid fractions. PLoS ONE 9, e108891 (2014).
Greenland, S., Pearl, J. & Robins, J.M. Causal diagrams for epidemiologic research. Epidemiology 10, 37–48 (1999).
Dahl, A., Hore, V., Iotchkova, V. & Marchini, J. Network inference in matrix-variate Gaussian models with non-independent noise. arXiv http://arxiv.org/abs/1312.1622 (2013).
Angrist, J.D. & Pischke, J-S. Mostly Harmless Econometrics: An Empiricist's Companion (Princeton Univ. Press, 2008).
Aschard, H., Vilhjálmsson, B.J., Joshi, A.D., Price, A.L. & Kraft, P. Adjusting for heritable covariates can bias effect estimates in genome-wide association studies. Am. J. Hum. Genet. 96, 329–339 (2015).
International HapMap 3 Consortium. Integrating common and rare genetic variation in diverse human populations. Nature 467, 52–58 (2010).