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Shared genetic architecture between metabolic traits and Alzheimer’s disease: a large-scale genome-wide cross-trait analysis

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A Correction to this article was published on 10 November 2020

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Abstract

A growing number of studies clearly demonstrate a substantial link between metabolic dysfunction and the risk of Alzheimer’s disease (AD), especially glucose-related dysfunction; one hypothesis for this comorbidity is the presence of a common genetic etiology. We conducted a large-scale cross-trait GWAS to investigate the genetic overlap between AD and ten metabolic traits. Among all the metabolic traits, fasting glucose, fasting insulin and HDL were found to be genetically associated with AD. Local genetic covariance analysis found that 19q13 region had strong local genetic correlation between AD and T2D (P = 6.78 × 10− 22), LDL (P = 1.74 × 10− 253) and HDL (P = 7.94 × 10− 18). Cross-trait meta-analysis identified 4 loci that were associated with AD and fasting glucose, 3 loci that were associated with AD and fasting insulin, and 20 loci that were associated with AD and HDL (Pmeta < 1.6 × 10− 8, single trait P < 0.05). Functional analysis revealed that the shared genes are enriched in amyloid metabolic process, lipoprotein remodeling and other related biological pathways; also in pancreas, liver, blood and other tissues. Our work identifies common genetic architectures shared between AD and fasting glucose, fasting insulin and HDL, and sheds light on molecular mechanisms underlying the association between metabolic dysregulation and AD.

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Change history

  • 10 November 2020

    Page 4: In the “Results-Genetic correlation between AD and metabolic traits” section, the sentence “We also observed that HDL had a significant genetic correlation with AD (Rg = -0.137, P = 0.0436)” should be “We also observed that HDL had a significant genetic correlation with AD (Rg = 0.322, P = 0.017)”.

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Acknowledgements

We thank IGAP consortium, GIANT consortium, DIAGRAM consortium, MAGIC Consortium and ENGAGE Consortium for providing GWAS summary statistic data. We also thank Dr. Huwenbo Shi for statistical advice. This study was supported by grants from National Institute of Environmental Health Sciences (NIEHS) P30ES000002 (Zhu), A Merit Review Award Clinical Science R&D I01CX000934-01A1 (Driver) and Dr. Liang is a collaborator funded by this award.

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  1. Jane A. Driver and Liming Liang contributed equally to this work.

Authors and Affiliations

  1. Program in Genetic Epidemiology and Statistical Genetics, Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA

    Zhaozhong Zhu, Yifei Lin & Liming Liang

  2. Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA, USA

    Zhaozhong Zhu

  3. Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA

    Xihao Li & Liming Liang

  4. Geriatric Research Education and Clinical Center and Massachusetts Veterans Epidemiology Research and Information Center, VA Medical Center, Boston, MA, USA

    Jane A. Driver

  5. Division of Aging, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA

    Jane A. Driver

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  1. Zhaozhong Zhu
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  3. Xihao Li
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Contributions

ZZ, JAD, and LL designed the study. ZZ and XL performed the statistical analysis. ZZ, YL, JAD, and LL wrote the manuscript. All authors helped interpret the data, reviewed and edited the final paper, and approved the submission.

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Correspondence to Liming Liang.

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Zhu, Z., Lin, Y., Li, X. et al. Shared genetic architecture between metabolic traits and Alzheimer’s disease: a large-scale genome-wide cross-trait analysis. Hum Genet 138, 271–285 (2019). https://doi.org/10.1007/s00439-019-01988-9

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