Behavioural Science Section / The Berlin Aging Study II - An Overview
Genetic Burden Analyses of Phenotypes Relevant to Aging in the Berlin Aging Study II (BASE-II)Lill C.M.a · Liu T.b · Norman K.c · Meyer A.c · Steinhagen-Thiessen E.c · Demuth I.c, d · Bertram L.a, e
aLübeck Interdisciplinary Platform for Genome Analytics (LIGA), Institutes of Neurogenetics and Integrative and Experimental Genomics, University of Lübeck, Lübeck, bMax Planck Institute for Human Development, cResearch Group on Geriatrics and dInstitute of Medical and Human Genetics, Charité - Universitätsmedizin Berlin, Berlin, Germany; eNeuroepidemiology and Ageing Research Unit, School of Public Health, Faculty of Medicine, The Imperial College of Science, Technology, and Medicine, London, UK
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Article / Publication Details
Background: Body mass index (BMI), bone mineral density (BMD), and telomere length are phenotypes that modulate the course of aging. Over 40% of their phenotypic variance is determined by genetics. Genome-wide association studies (GWAS) have recently uncovered >100 independent single-nucleotide polymorphisms (SNPs) showing genome-wide significant (p < 5 × 10-8) association with these traits. Objective: To test the individual and combined impact of previously reported GWAS SNPs on BMI, BMD, and relative leukocyte telomere length (rLTL) in ∼1,750 participants of the Berlin Aging Study II (BASE-II), a cohort consisting predominantly of individuals >60 years of age. Methods: Linear regression analyses were performed on a total of 101 SNPs and BMI, BMD measurements of the femoral neck (FN) and lumbar spine (LS), and rLTL. The combined effect of all trait-specific SNPs was evaluated by generating a weighted genomic profile score (wGPS) used in the association analyses. The predictive capability of the wGPS was estimated by determining the area under the receiver operating curve (AUC) for osteoporosis status (determined by BMD) with and without the wGPS. Results: Five loci showed experiment-wide significant association with BMI (FTO rs1558902, p = 1.80 × 10-5) or BMD (MEPE rs6532023, pFN = 5.40 × 10-4, pLS = 1.09 × 10-4; TNFRSF11B rs2062377, pLS = 8.70 × 10-4; AKAP11 rs9533090, pLS = 1.05 × 10-3; SMG6 rs4790881, pFN = 3.41 × 10-4) after correction for multiple testing. Several additional loci showed nominally significant (p < 0.05) association with BMI and BMD. The trait-specific wGPS was highly significantly associated with BMD (p < 2 × 10-16) and BMI (p = 1.10 × 10-6). No significant association was detected for rLTL in either single-SNP or wGPS-based analyses. The AUC for osteoporosis improved modestly from 0.762 (95% CI 0.733-0.800) to 0.786 (95% CI 0.756-0.823) and 0.785 (95% CI 0.757-0.824) upon inclusion of the FN- and LS-BMD wGPS, respectively. Conclusion: Our study provides an independent validation of previously reported genetic association signals for BMI and BMD in the BASE-II cohort. Additional studies are needed to pinpoint the factors underlying the proportion of phenotypic variance that remains unexplained by the current models.
© 2016 S. Karger AG, Basel
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