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Integrating human brain proteomes with genome-wide association data implicates new proteins in Alzheimer’s disease pathogenesis

Nature Genetics volume 53, pages 143–146 (2021)Cite this article

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Abstract

Genome-wide association studies (GWAS) have identified many risk loci for Alzheimer’s disease (AD)1,2, but how these loci confer AD risk is unclear. Here, we aimed to identify loci that confer AD risk through their effects on brain protein abundance to provide new insights into AD pathogenesis. To that end, we integrated AD GWAS results with human brain proteomes to perform a proteome-wide association study (PWAS) of AD, followed by Mendelian randomization and colocalization analysis. We identified 11 genes that are consistent with being causal in AD, acting via their cis-regulated brain protein abundance. Nine replicated in a confirmation PWAS and eight represent new AD risk genes not identified before by AD GWAS. Furthermore, we demonstrated that our results were independent of APOE e4. Together, our findings provide new insights into AD pathogenesis and promising targets for further mechanistic and therapeutic studies.

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Fig. 1: Manhattan plot for the discovery AD PWAS.

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Data availability

Phenotypic, proteomic and transcriptomic data used in this manuscript are available via the AD Knowledge Portal (https://adknowledgeportal.org). The AD Knowledge Portal is a platform for accessing data, analyses and tools generated by the Accelerating Medicines Partnership (AMP-AD) Target Discovery Program and other National Institute on Aging (NIA)-supported programs to enable open-science practices and accelerate translational learning. The data, analyses and tools are shared early in the research cycle without a publication embargo on secondary use. Data are available for general research use according to the following requirements for data access and data attribution (https://adknowledgeportal.org/DataAccess/Instructions). Results of the pQTL analysis, protein weights and transcript weights described in this manuscript can be accessed at https://doi.org/10.7303/syn23627957.

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Acknowledgements

We thank the participants of the ROS, MAP, Mayo, Mount Sinai Brain Bank and Banner Sun Health Research Institute Brain and Body Donation Program for their time and participation. The following National Institutes of Health (NIH) grants supported this work: P30 AG066511 (A.I.L.); P30 AG10161 (D.A.B.); P30 NS055077 (A.I.L.); P50 AG025688 (A.I.L.); R01 AG015819 (D.A.B.); R01 AG017917 (D.A.B.); R01 AG053960 (N.T.S.); R01 AG056533 (T.S.W., A.P.W.); R01 AG057911 (N.T.S.); R01 AG061800 (N.T.S.); R56 AG060757 (T.S.W.); R56 AG062256 (T.S.W.); RC2 AG036547 (D.A.B.); RF1 AG057470 (T.S.W.); U01 AG046152 (P.L.D.); U01 AG046161 (A.I.L.); U01 AG061356 (P.L.D.); U01 AG061357 (A.I.L.); and U01 MH115484 (A.P.W.). NIH grants include those that supported the Accelerating Medicine Partnership for AD, the National Institute of Neurological Disorders and Stroke Emory Neuroscience Core and Goizueta Alzheimer’s Disease Research Center (ADRC) at Emory University, the Rush University ADRC and Arizona State University ADRC that made this work possible. The following Veterans Administration grants supported this work: I01 BX003853 (A.P.W.) and IK4 BX005219 (A.P.W.). The Brain and Body Donation Program has been supported by the NIH, the Arizona Department of Health Services, the Arizona Biomedical Research Commission and the Michael J. Fox Foundation for Parkinson’s Research. Additional support includes grants from the Alzheimer’s Association (N.T.S.), Alzheimer’s Research UK (N.T.S.), the Michael J. Fox Foundation for Parkinson’s Research (N.T.S.) and the Weston Brain Institute Biomarkers Across Neurodegenerative Diseases Grant 11060 (N.T.S.). The views expressed in this work do not necessarily represent the views of the Veterans Administration or the United States Government.

Author information

Authors and Affiliations

  1. Division of Mental Health, Atlanta VA Medical Center, Decatur, GA, USA

    Aliza P. Wingo

  2. Department of Psychiatry, Emory University School of Medicine, Atlanta, GA, USA

    Aliza P. Wingo

  3. Department of Neurology, Emory University School of Medicine, Atlanta, GA, USA

    Yue Liu, Ekaterina S. Gerasimov, Chloe Robins, James J. Lah, Allan I. Levey & Thomas S. Wingo

  4. Sage Bionetworks, Seattle, WA, USA

    Jake Gockley & Benjamin A. Logsdon

  5. Department of Biochemistry, Emory University School of Medicine, Atlanta, GA, USA

    Duc M. Duong, Eric B. Dammer & Nicholas T. Seyfried

  6. Banner Sun Health Research Institute, Sun City, AZ, USA

    Thomas G. Beach

  7. Banner Alzheimer’s Institute, Arizona State University and University of Arizona, Phoenix, AZ, USA

    Eric M. Reiman

  8. Department of Human Genetics, Emory University School of Medicine, Atlanta, GA, USA

    Michael P. Epstein & Thomas S. Wingo

  9. Center for Translational and Computational Neuroimmunology, Department of Neurology and the Taub Institute for Research on Alzheimer’s Disease and the Aging Brain, Columbia University Medical Center, New York, NY, USA

    Philip L. De Jager

  10. Rush Alzheimer’s Disease Center, Rush University Medical Center, Chicago, IL, USA

    David A. Bennett

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  1. Aliza P. Wingo
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Contributions

A.P.W. and T.S.W. conceptualized and designed the study. A.P.W., D.M.D., E.B.D., T.G.B., E.M.R., P.L.D., J.J.L., D.A.B., N.T.S., A.I.L. and T.S.W. acquired the data. A.P.W., Y.L., E.S.G., J.G., B.A.L. and T.S.W. conducted the analyses. A.P.W., Y.L., E.S.G., J.G., B.A.L., E.B.D., C.R., M.P.E., J.J.L., D.A.B., N.T.S., A.I.L. and T.S.W. interpreted the data. A.P.W. and T.S.W. wrote the first draft of the manuscript. All authors critically revised and reviewed the manuscript.

Corresponding authors

Correspondence to Aliza P. Wingo or Thomas S. Wingo.

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The authors declare no competing interests.

Additional information

Peer review information Nature Genetics thanks Towfique Raj and the other anonymous reviewer(s) for their contribution to the peer review of this work.

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data

Extended Data Fig. 1 Quantile-quantile plots for the discovery and replication PWAS of AD.

Quantile-quantile plot for a, the discovery PWAS of AD (λ = 1.36; λ1000 = 1.003) and b, confirmatory PWAS of AD (λ = 1.39; λ1000 = 1.003).

Extended Data Fig. 2 Overlap of significant genes between AD and other traits.

Overlap between results of the AD PWAS and PWAS for other traits. All the PWAS used the discovery ROS/MAP proteomic dataset (n = 376) and GWAS summary results from Caucasian individuals. The following outcomes were tested: clinical AD GWAS (N = 63,926), amyotrophic lateral sclerosis (ALS; N = 80,610), body mass index (BMI; N = 681,275), height (N = 693,529), neuroticism (N = 390,278), Parkinson’s disease (PD; N = 1,474,097), and waist-to-hip ratio adjusting for BMI (WHRadjBMI; N = 694,649). Significant genes considered for overlap are those with FDR p < 0.05.

Extended Data Fig. 3 Quantile-quantile plot for the TWAS of AD.

Quantile-quantile plot for the TWAS of AD (λ = 1.22; λ1000 = 1.002).

Extended Data Fig. 4 Single cell-type expression.

Single-cell type expression for AD PWAS-significant genes with evidence of causality in AD. Using human brain single-cell RNA-sequencing data profiled from the dPFC, we found that 6 genes (of the 11 genes) had evidence of enrichment in a cell type at FDR p < 0.05. Enrichment testing was performed using Wilcoxon rank sum test, as implemented by the Seurat package, and multiple testing was accounted for by FDR adjusted for 17,775 tested genes. CARHSP1 showed enrichment in oligodendrocytes. CTSH showed enrichment in astrocytes and microglia. DOC2A, ICA1L, PLEKHA1, and SNX32 were enriched in excitatory neurons.

Source data

Extended Data Fig. 5 Genetic principal components of genetic ancestry for each dataset.

Genetic principal components of genetic ancestry for each dataset. The first two genetic principal components for individuals in each dataset are plotted (grey boxes) with individuals from the 1000 Genomes CEU dataset (purple triangles) for a, the discovery proteomic dataset, b, the replication proteomic dataset, and c, the transcriptomic dataset.

Source data

Supplementary information

Supplementary Information

List of supplementary tables

Reporting Summary

Supplementary Tables

Supplementary Tables 1–20

Source data

Source Data Extended Data Fig. 4

Statistical source data

Source Data Extended Data Fig. 5

Statistical source data

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Wingo, A.P., Liu, Y., Gerasimov, E.S. et al. Integrating human brain proteomes with genome-wide association data implicates new proteins in Alzheimer’s disease pathogenesis. Nat Genet 53, 143–146 (2021). https://doi.org/10.1038/s41588-020-00773-z

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