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Application of linear mixed models to study genetic stability of height and body mass index across countries and time.

ABSTRACT: BACKGROUND: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? METHODS: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. RESULTS: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. CONCLUSIONS: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.

SUBMITTER: Trzaskowski M

PROVIDER: S-EPMC4864877 | biostudies-literature | 2016 Apr

REPOSITORIES: biostudies-literature

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Application of linear mixed models to study genetic stability of height and body mass index across countries and time.

Trzaskowski Maciej M Lichtenstein Paul P Magnusson Patrik K PK Pedersen Nancy L NL Plomin Robert R

International journal of epidemiology 20160127 2

<h4>Background</h4>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?<h4>Methods</h4>A sample of 3152 11-year-old c ...[more]

PMID: 26819444

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Project description:To determine whether height and body mass index (BMI) have a causal role in five measures of socioeconomic status.Mendelian randomisation study to test for causal effects of differences in stature and BMI on five measures of socioeconomic status. Mendelian randomisation exploits the fact that genotypes are randomly assigned at conception and thus not confounded by non-genetic factors.UK Biobank.119,669 men and women of British ancestry, aged between 37 and 73 years.Age completed full time education, degree level education, job class, annual household income, and Townsend deprivation index.In the UK Biobank study, shorter stature and higher BMI were observationally associated with several measures of lower socioeconomic status. The associations between shorter stature and lower socioeconomic status tended to be stronger in men, and the associations between higher BMI and lower socioeconomic status tended to be stronger in women. For example, a 1 standard deviation (SD) higher BMI was associated with a £210 (€276; $300; 95% confidence interval £84 to £420; P=6 × 10(-3)) lower annual household income in men and a £1890 (£1680 to £2100; P=6 × 10(-15)) lower annual household income in women. Genetic analysis provided evidence that these associations were partly causal. A genetically determined 1 SD (6.3 cm) taller stature caused a 0.06 (0.02 to 0.09) year older age of completing full time education (P=0.01), a 1.12 (1.07 to 1.18) times higher odds of working in a skilled profession (P=6 × 10(-7)), and a £1130 (£680 to £1580) higher annual household income (P=4 × 10(-8)). Associations were stronger in men. A genetically determined 1 SD higher BMI (4.6 kg/m(2)) caused a £2940 (£1680 to £4200; P=1 × 10(-5)) lower annual household income and a 0.10 (0.04 to 0.16) SD (P=0.001) higher level of deprivation in women only.These data support evidence that height and BMI play an important partial role in determining several aspects of a person's socioeconomic status, especially women's BMI for income and deprivation and men's height for education, income, and job class. These findings have important social and health implications, supporting evidence that overweight people, especially women, are at a disadvantage and that taller people, especially men, are at an advantage.

Project description:PURPOSE:Recent studies have suggested height as a risk factor for glioma, but less is known regarding body mass index (BMI) or other anthropomorphic measures. We evaluated the association between body habitus and risk of glioma. METHODS:We evaluated the association of measures of height, BMI, waist circumference, and somatotypes with risk of glioma in two prospective cohorts, the Nurses' Health Study and the Health Professionals Follow-Up Study. RESULTS:We documented 508 incident cases of glioma (321 glioblastoma [GBM]). In both cohorts, we found no significant association between adult BMI or waist circumference and risk of glioma, with pooled HR for BMI of 1.08 (95% CI 0.85-1.38 comparing???30 to <?25 kg/m2) and for waist circumference of 1.05 (95% CI 0.80-1.37 highest vs. lowest quintile). Higher young adult BMI (at age 18 in NHS and 21 in HPFS) was associated with modestly increased risk of glioma in the pooled cohorts (pooled HR 1.35, 95% CI 1.06-1.72 comparing???25 kg/m2 vs. less; HR 1.34 for women and 1.37 for men). Analysis of body somatotypes suggested reduced risk of glioma among women with heavier body types at all ages this measure was assessed (HRs ranging from 0.52 to 0.65 comparing highest tertile to lowest tertile), but no significant association among men. Height was associated with increased risk of glioma among women (HR?1.09, 95% CI 1.04-1.14 per inch), but not significantly among men. Within the 8 years prior to diagnosis, cases had no material weight loss compared to non-cases. All results were similar when limited to GBM. CONCLUSION:Adult BMI and waist circumference were not associated with glioma. Higher BMI at age 21 for men and at age 18 for women was modestly associated with risk in the pooled cohort. Based on body somatotypes, however, women with heavier body types during childhood and young adulthood may be at lower risk of glioma, although this association was not observed later in life with measurements of BMI. Greater height was associated with increased risk, and the trend was more pronounced in women.

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Application of linear mixed models to study genetic stability of height and body mass index across countries and time.

Publications

Application of linear mixed models to study genetic stability of height and body mass index across countries and time.

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