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CD33 modulates TREM2: convergence of Alzheimer loci

Nature Neuroscience volume 18, pages 1556–1558 (2015)Cite this article

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Abstract

We used a protein quantitative trait analysis in monocytes from 226 individuals to evaluate cross-talk between Alzheimer loci. The NME8 locus influenced PTK2B and the CD33 risk allele led to greater TREM2 expression. There was also a decreased TREM1/TREM2 ratio with a TREM1 risk allele, decreased TREM2 expression with CD33 suppression and elevated cortical TREM2 mRNA expression with amyloid pathology.

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Figure 1: TREM1 association with AD may not be mediated by a simple reduction of TREM1 expression but by a balance of TREM1 and TREM2.
Figure 2: CD33 modulates TREM2 surface expression.

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Change history

  • 08 October 2015

    In the version of this article initially published online, the up- and down-arrows were switched in the second row of Table 1: the G allele of rs3826656 confers a decreased risk, the A allele an increased. In the first sentence of paragraph 6, the degrees of freedom for the ROS-MAP data t value should have been 142 rather than 153. And in paragraphs 7 and 8, both instances of zdisc_meta should have read zdisc, both instances of Pdisc_meta should have read Pdisc, and both instances of zmeta should have read zjoint. The errors have been corrected for the print, PDF and HTML versions of this article.

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Acknowledgements

The authors are grateful to the participants of PGP, HABS, ROS and MAP for the time and specimens that they contributed. This work was supported by US National Institutes of Health grants R01 AG036836, R01 AG048015, R01 AG043617, P01 AG036694, P30 AG10161, R01 AG15819, R01 AG17917 and U01 AG46152.

Author information

Author notes

  1. Elizabeth M Bradshaw and Philip L De Jager: These authors contributed equally to this work.

Authors and Affiliations

  1. Ann Romney Center for Neurologic Diseases, Brigham and Women's Hospital, Boston, Massachusetts, USA

    Gail Chan, Charles C White, Phoebe A Winn, Maria Cimpean, Joseph M Replogle, Laura R Glick, Nicole E Cuerdon, Katie J Ryan, Lori B Chibnik, Elizabeth M Bradshaw & Philip L De Jager

  2. Department of Neurology, Program in Translational NeuroPsychiatric Genomics, Institute for the Neurosciences, Brigham and Women's Hospital, Boston, Massachusetts, USA

    Gail Chan, Charles C White, Phoebe A Winn, Maria Cimpean, Joseph M Replogle, Laura R Glick, Nicole E Cuerdon, Katie J Ryan, Lori B Chibnik, Elizabeth M Bradshaw & Philip L De Jager

  3. Department of Psychiatry, Program in Translational NeuroPsychiatric Genomics, Institute for the Neurosciences, Brigham and Women's Hospital, Boston, Massachusetts, USA

    Gail Chan, Charles C White, Phoebe A Winn, Maria Cimpean, Joseph M Replogle, Laura R Glick, Nicole E Cuerdon, Katie J Ryan, Lori B Chibnik, Elizabeth M Bradshaw & Philip L De Jager

  4. Program in Medical and Population Genetics, Broad Institute, Cambridge, Massachusetts, USA

    Gail Chan, Charles C White, Phoebe A Winn, Maria Cimpean, Joseph M Replogle, Laura R Glick, Nicole E Cuerdon, Katie J Ryan, Lori B Chibnik, Elizabeth M Bradshaw & Philip L De Jager

  5. Harvard Medical School, Boston, Massachusetts, USA

    Gail Chan, Joseph M Replogle, Katie J Ryan, Keith A Johnson, Lori B Chibnik, Reisa A Sperling, Elizabeth M Bradshaw & Philip L De Jager

  6. Department of Neurology, Center for Alzheimer's Research and Treatment, Brigham and Women's Hospital, Boston, Massachusetts, USA

    Keith A Johnson & Reisa A Sperling

  7. Department of Neurology, Massachusetts General Hospital, Boston, Massachusetts, USA

    Keith A Johnson & Reisa A Sperling

  8. Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, Illinois, USA

    Julie A Schneider & David A Bennett

Authors
  1. Gail Chan
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  2. Charles C White
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Contributions

G.C., P.L.D. and E.M.B. designed and implemented the study and wrote the manuscript. G.C. planned and conducted the experiments with technical assistance from P.A.W., M.C. and K.J.R. C.C.W., J.M.R., L.B.C. and G.C. performed statistical analyses and assisted with the interpretation of results. P.L.D., L.R.G. and N.E.C. coordinated the collection of blood from PGP. R.A.S. and K.A.J. provided blood samples and genetic data from HABS. J.A.S. and D.A.B. contributed clinical, genetic and post-mortem data from ROS-MAP. P.L.D. coordinated access to all of the cohorts. All of the authors contributed to the review of the manuscript.

Corresponding author

Correspondence to Philip L De Jager.

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Competing interests

The authors declare no competing financial interests.

Integrated supplementary information

Supplementary Figure 1 Genes of interest are preferentially expressed by monocytes.

(a) Flow cytometry gating scheme of peripheral blood mononuclear cells shows that CD33, TYROBP, TREM1, TREM2 and TREML2 are expressed predominantly by monocytes, whereas PTK2B is expressed highly by both lymphocytes and monocytes. Patterns in protein expression are consistent with (b) mRNA expression in T cells (n = 213) and monocytes (n = 211) from ImmVar. The y axis represents mRNA expression values log2 transformed and normalized.

Supplementary Figure 2 Pairwise correlations of measured proteins.

(a) Correlation matrix showing strong positive correlations between CD33 and TREM2 as well as PTK2B and TYROBP. No dot indicates P < 0.05 (after corrected for multiple comparisons) for correlation between each protein pair. Uncorrected P values and correlation coefficients are indicated in (b) and (c), respectively.

Supplementary Figure 3 TREM1 association with AD may not be mediated by a simple reduction of TREM1 expression but by a balance of TREM1 and TREM2.

(a) Table showing effect sizes (β) and P values for the association of rs2627567 and rs6910730 with TREM1, TREM2 and the TREM1/TREM2 ratio in PGP (discovery and validation subjects (PGPmeta)) and HABS. (b) In the PGP subjects, rs2627567A (the reference allele of the non-AD SNP) is associated with decreases in both TREM1 and TREM2, whereas the AD risk allele rs6910730G is associated with a decrease in TREM1 but an increase in TREM2. This leads to a more significant reduction in TREM1/TREM2 ratio for rs6910730G than the simple effect of reduced TREM1 expression alone. TREM1 and TREM2 surface expression on monocytes was quantified via flow cytometry; the y axis represents normalized median fluorescence intensity (MFI) and the horizontal line denotes mean MFI.

Supplementary Figure 4 Summary of the effects of AD risk variants in monocytes.

(a) The CD33 risk allele rs3865444C is associated with increased expression of the full-length CD33 isoform, which mediates increased TREM2 surface expression. While CD33 suppression with anti-CD33 antibody leads to reduced TREM2 surface expression, there is no effect of CD33 on TREM2 mRNA. The TREM1 risk allele rs6910730G is associated with decreased TREM1 surface expression and a decreased TREM1/TREM2 ratio. The “?” denotes a possible role of this TREM1 SNP in raising TREM2 surface expression in younger individuals. Dashed lines indicate a reduction in protein. (b) The PTK2B risk allele rs28834970C and the NME8 risk allele rs2718058A are associated with increased PTK2B and NME8 mRNA expression, respectively, as well as increased PTK2B protein expression. The effect of rs2718058A on PTK2B protein is likely mediated through increased NME8 protein expression. Together, this suggests that an increase in PTK2B contributes to increased AD risk.

Supplementary information

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Supplementary Figures 1–4 and Supplementary Tables 1–4 (PDF 2281 kb)

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Chan, G., White, C., Winn, P. et al. CD33 modulates TREM2: convergence of Alzheimer loci. Nat Neurosci 18, 1556–1558 (2015). https://doi.org/10.1038/nn.4126

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