title: Application of linear mixed models to study genetic stability of height and body mass index across countries and time.
abstract: It is now possible to estimate genetic correlations between two independent samples when there is no overlapping phenotypic information. We applied the latest bivariate genomic methods to children in the UK and older adults in Sweden to ask two questions. Are the same variants driving individual differences in anthropometric traits in these two populations, and are these variants as important in childhood as they are later in life?
  
  
  
  A sample of 3152 11-year-old children in the UK was compared with a sample of 6813 adults with an average age of 65 in Sweden. Genotypes were imputed from 1000 genomes with combined 9 767 136 single nucleotide polymorphisms meeting quality control criteria in both samples. Two cross-sample GCTA-GREML analyses and linkage disequilibrium (LD) score regressions were conducted to assess genetic correlations across more than 50 years: child versus adult height and child versus adult body mass index (BMI). Consistency of effects was tested using the recently proposed polygenic scoring method.
  
  
  
  For height, GCTA-GREML and LD score indicated strong genetic stability between children and adults, 0.58 (0.16) and 1.335 (1.09), respectively. For BMI, both methods produced similarly strong estimates of genetic stability 0.75 (0.26) and 0.855 (0.49), respectively. In height, adult polygenic score explained 60% of genetic variance in childhood and 10% of variance in BMI.
  
  
  
  Here we replicated and extended previous findings of longitudinal genetic stability in anthropometric traits to cross-cultural dimensions, and showed that for height but not BMI these variants are as important in childhood as they are in adulthood.
authors.affiliation: King's College London, Institute of Psychiatry, Psychology & Neuroscience, London, UK and maciej.trzaskowski@kcl.ac.uk.
authors.forename: Maciej
authors.initials: M
authors.lastname: Trzaskowski
authors.affiliation: Karolinska Institutet, Department of Medical Epidemiology and Biostatistics, Stockholm, Sweden.
authors.forename: Paul
authors.initials: P
authors.lastname: Lichtenstein
authors.affiliation: Karolinska Institutet, Department of Medical Epidemiology and Biostatistics, Stockholm, Sweden.
authors.forename: Patrik K
authors.initials: PK
authors.lastname: Magnusson
authors.affiliation: Karolinska Institutet, Department of Medical Epidemiology and Biostatistics, Stockholm, Sweden.
authors.forename: Nancy L
authors.initials: NL
authors.lastname: Pedersen
authors.affiliation: King's College London, Institute of Psychiatry, Psychology & Neuroscience, London, UK and.
authors.forename: Robert
authors.initials: R
authors.lastname: Plomin
keywords: BMI; GCTA; GREML; LD score regression; Unrelated samples; genetic stability; height; polygenic prediction; weight
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