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Genetically-Predicted Adult Height and Alzheimer's Disease

Accepted version
Peer-reviewed

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Article

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Authors

Larsson, SC 
Markus, HS 

Abstract

BACKGROUND: Observational studies have linked increased adult height with better cognitive performance and reduced risk of Alzheimer's disease (AD). It is unclear whether the associations are due to shared biological processes that influence height and AD or due to confounding by early life exposures or environmental factors. OBJECTIVE: To use a genetic approach to investigate the association between adult height and AD. METHODS: We selected 682 single nucleotide polymorphisms (SNPs) associated with height at genome-wide significance (p < 5×10-8) in the Genetic Investigation of ANthropometric Traits (GIANT) consortium. Summary statistics for each of these SNPs on AD were obtained from the International Genomics of Alzheimer's Project (IGAP) of 17,008 individuals with AD and 37,154 controls. The estimate of the association between genetically predicted height and AD was calculated using the inverse-variance weighted method. RESULTS: The odds ratio of AD was 0.91 (95% confidence interval, 0.86-0.95; p = 9.8×10-5) per one standard deviation increase (about 6.5 cm) in genetically predicted height based on 682 SNPs, which were clustered in 419 loci. In an analysis restricted to one SNP from each height-associated locus (n = 419 SNPs), the corresponding OR was 0.92 (95% confidence interval, 0.86-0.97; p = 4.8×10-3). CONCLUSIONS: This finding suggests that biological processes that influence adult height may have a role in the etiology of AD.

Description

Keywords

Alzheimer’s disease, anthropometry, genetics, polymorphism, single nucleotide

Journal Title

Journal of Alzheimer's Disease

Conference Name

Journal ISSN

1387-2877
1875-8908

Volume Title

60

Publisher

IOS Press
Sponsorship
Medical Research Council (MR/L003120/1)
British Heart Foundation (None)
Medical Research Council (MC_UU_00002/7)
Wellcome Trust (204623/Z/16/Z)
This work was supported by a Young Scholar Award (to Susanna C. Larsson) from the Karolinska Institutet’s Strategic Research Program in Epidemiology (SFO-EPI). Hugh S. Markus and Matthew Traylor have infrastructural support from the Cambridge University Trusts NIHR Biomedical Research Centre. Hugh S. Markus is supported by a NIHR Senior Investigator award. The authors thank the International Genomics of Alzheimer’s Project (IGAP) for providing summary-level data for these analyses. The investigators within IGAP contributed to the design and implementation of IGAP and/or provided data but did not participate in analysis or writing of this report. IGAP was made possible by the generous participation of the control subjects, the patients, and their families. The i– Select chips was funded by the French National Foundation on Alzheimer’s disease and related disorders. EADI was supported by the LABEX (laboratory of excellence program investment for the future) DISTALZ grant, Inserm, Institut Pasteur de Lille, Université de Lille 2 and the Lille University Hospital. GERAD was supported by the Medical Research Council (Grant n° 503480), Alzheimer’s Research UK (Grant n° 503176), the Wellcome Trust (Grant n° 082604/2/07/Z) and German Federal Ministry of Education and Research (BMBF): Competence Network Dementia (CND) grant n° 01GI0102, 01GI0711, 01GI0420. CHARGE was partly supported by the NIH/NIA grant R01 AG033193 and the NIA AG081220 and AGES contract N01–AG–12100, the NHLBI grant R01 HL105756, the Icelandic Heart Association, and the Erasmus Medical Center and Erasmus University. ADGC was supported by the NIH/NIA grants: U01 AG032984, U24 AG021886, U01 AG016976, and the Alzheimer’s Association grant ADGC–10–196728.