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Nature Neuroscience
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Shared proteomic effects of cerebral atherosclerosis and Alzheimer’s disease on the human brain

Nature Neurosciencevolume 23, pages696–700 (2020)Cite this article

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APublisher Correction to this article was published on 23 June 2020

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Abstract

Cerebral atherosclerosis contributes to dementia via unclear processes. We performed proteomic sequencing of dorsolateral prefrontal cortex in 438 older individuals and found associations between cerebral atherosclerosis and reduced synaptic signaling and RNA splicing and increased oligodendrocyte development and myelination. Consistently, single-cell RNA sequencing showed cerebral atherosclerosis associated with higher oligodendrocyte abundance. A subset of proteins and modules associated with cerebral atherosclerosis was also associated with Alzheimer’s disease, suggesting shared mechanisms.

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Fig. 1: Differential protein expression in CA and AD.
Fig. 2: Enrichment analysis of proteins associated with CA.
Fig. 3: Protein co-expression network analysis for brain cell types and clinical and neuropathologic outcomes.

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Data availability

Phenotype data are available at:https://www.radc.rush.edu. Proteomic data from the discovery dataset (ROS/MAP cohorts) are available athttps://www.synapse.org/#!Synapse:syn17015098. Proteomic data from the replication dataset (BLSA cohort) are available athttps://www.synapse.org/#!Synapse:syn11209141.

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Acknowledgements

We thank the participants of the ROS and MAP studies and participants in the Baltimore Longitudinal Study of Aging for their time, participation and invaluable contributions. Support was provided by NIH grant no. R01 AG056533, grant no. R01 AG053960, the Accelerating Medicine Partnership for AD (grant nos. U01 AG046152, U01 AG046161, U01 AG061356 and U01 AG061357), the Emory Alzheimer’s Disease Research Center (grant no. P50 AG025688), the NINDS Emory Neuroscience Core (grant no. P30 NS055077), the Johns Hopkins Alzheimer’s Disease Research Center (grant no. P50 AG005146), and NIH grant nos. R01 AG017917 (D.A.B.), R01 AG015819 (D.A.B.), RC2 AG036547 (D.A.B.), P30 AG10161 (D.A.B.), R01 AG042210 (J.A.S.), R01 AG064233 (J.A.S), UH2-3 NS100599 (J.A.S.), U19 AG033655, R21 AG055844 (J.C.T.), and in part by the intramural program of the NIH, National Institute on Aging. A.P.W. is also supported by grant nos. U01 MH115484 and I01 BX003853. T.S.W. is also supported by NIH grant nos. RF1 AG057470, R56 AG062256, R56 AG060757 and R56 AG062633. N.T.S. is also supported by the Alzheimer’s Association, Alzheimer’s Research UK, The Michael J. Fox Foundation for Parkinson’s Research, the Weston Brain Institute Biomarkers Across Neurodegenerative Diseases (grant no. 11060), NIH grant no. R01 AG061800 and NIH grant no. R01 AG057911.

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

    Wen Fan, Ekaterina S. Gerasimov, Yue Liu, Nadia V. Harerimana, Ihab M. Hajjar, James J. Lah, Allan I. Levey & Thomas S. Wingo

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

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

  5. Department of Pathology, Johns Hopkins School of Medicine, Baltimore, MD, USA

    Bartholomew White & Juan C. Troncoso

  6. Clinical and Translational Neuroscience Section, Laboratory of Behavioral Neuroscience, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA

    Madhav Thambisetty

  7. Rush Alzheimer’s Disease Center, Rush University Medical Center, Chicago, Illinois, USA

    Namhee Kim, Julie A. Schneider & David A. Bennett

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

    Thomas S. Wingo

Authors
  1. Aliza P. Wingo
  2. Wen Fan
  3. Duc M. Duong
  4. Ekaterina S. Gerasimov
  5. Eric B. Dammer
  6. Yue Liu
  7. Nadia V. Harerimana
  8. Bartholomew White
  9. Madhav Thambisetty
  10. Juan C. Troncoso
  11. Namhee Kim
  12. Julie A. Schneider
  13. Ihab M. Hajjar
  14. James J. Lah
  15. David A. Bennett
  16. Nicholas T. Seyfried
  17. Allan I. Levey
  18. Thomas S. Wingo

Contributions

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

Corresponding authors

Correspondence toAliza P. Wingo,Nicholas T. Seyfried,Allan I. Levey orThomas S. Wingo.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

Peer review informationNature Neuroscience thanks Costantino Iadecola 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 Association between cerebral atherosclerosis and oligodendrocyte abundance.

This figure summarizes the association between CA and oligodendrocyte abundance estimated from single-cell nuclear RNA sequencing of human dorsolateral prefrontal cortex in an independent dataset. Higher cerebral atherosclerosis was associated with higher oligodendrocyte abundance in the dorsolateral prefrontal cortex after adjusting for sex, age, and 8 other measured pathologies using linear regression (p = 0.003, β = 0.077, N = 48). For each box plot, the box reflects the first and third quartile, the dark horizontal line reflects the median, the vertical lines extending from the boxes show the 1.5x the interquartile range, and points beyond the lines are outliers.

Source data

Extended Data Fig. 2 Association between NEFL or NEFM brain protein and cerebral atherosclerosis, AD.

(a) Boxplot of dorsolateral prefrontal cortex NEFL protein level for each level of CA (that is, none to severe). NEFL protein levels were identified as associated with CA using linear regression adjusted for relevant covariates and 8 other pathologies (N = 375; p = 0.0002; adjusted p = 0.034; Fig.1). (b) Boxplot of dorsolateral prefrontal cortex NEFL protein level by clinical diagnosis (that is, cognitive normal control [control], mild cognitive impairment [MCI], and AD). MCI is generally regarded as an intermediate stage between cognitively normal and AD. NEFL protein levels were identified as associated with AD by logistic regression adjusted for relevant covariates (N = 383; p = 0.0025; adjusted p = 0.0322; Fig.1).(c) Boxplot of dorsolateral prefrontal cortex NEFM protein level for each level of CA (that is, none to severe). NEFM protein levels were identified as associated with CA using linear regression adjusted for relevant covariates and 8 other pathologies (N = 375; p = 0.0006; adjusted p = 0.045). (d) Boxplot of dorsolateral prefrontal cortex NEFM protein level by clinical diagnosis (that is, cognitive normal control [control], mild cognitive impairment [MCI], and AD). NEFM protein levels were identified as associated with AD by logistic regression adjusted for relevant covariates (N = 383; p = 0.0019; adjusted p = 0.028). For each boxplot, the box reflects the first and third quartile, the dark horizontal line reflects the median, the vertical lines extending from the boxes show the 1.5x the interquartile range, and points beyond the lines are outliers. (e) Proteome-wide adjusted p-values for associations between NEFL and NEFM brain protein levels and each of the 9 measured pathologies adjusting for the remaining 8 measured pathologies. Associations were tested with regression and the provided p-values were adjusted for multiple testing using Benjamin-Hochberg false discovery rate.

Source data

Supplementary information

Supplementary Information

Supplementary Figs. 1–7 and Supplementary Tables 1–3.

Supplementary Table 1

Supplementary Tables 4–16.

Source data

Source Data Fig. 1

Statistical source data.

Source Data Fig. 2

Statistical source data.

Source Data Fig. 3

Underlying data and statistical source data.

Source Data Extended Data Fig. 1

Underlying data and statistical source data.

Source Data Extended Data Fig. 2

Underlying data and statistical source data.

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Wingo, A.P., Fan, W., Duong, D.M.et al. Shared proteomic effects of cerebral atherosclerosis and Alzheimer’s disease on the human brain.Nat Neurosci23, 696–700 (2020). https://doi.org/10.1038/s41593-020-0635-5

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