Audrey Herrald ’23, Medical Sciences, 4/18/2020
Microglia cluster around amyloid-beta plaques in Alzheimer’s Disease; Microglia (red, Iba1 for mouse and CD11b for human) can be found closely associated with amyloid-beta plaques (methoxy, blue) in APP/PS1 mice as well human AD patients (scale bars = 10 μm)[i]
Although no single gene guarantees the development of Alzheimer’s Disease, there is a wide array of genes associated with an increased risk of developing the disease. Recently, a research team led by Professor Bart De Strooper and Dr. Mark Fiers found connections between eleven of these “risk genes” and the amyloid-β (AB) plaques found in the brains of Alzheimer’s Disease patients.[ii] Better understanding the relationship between AB plaques and risk genes may help guide future treatment patterns in genetically predisposed individuals.
Previous studies have indicated that both the intracellular formation of TAU neurofibrillary tangles and the extracellular aggregation of toxic AB protein segments causes Alzheimer’s Disease symptoms.[iii] De Strooper and Fiers’s team used mouse models to determine whether the many genetic risk factors for Alzheimer’s Disease interact more directly with the Tau tangles or the AB plaques. The researchers used mice in this study due to their early-stage modeling capacity; in a human, a thorough analysis of the hippocampus can only be performed in a postmortem state (usually after extensive disease progression).[iv] The APPtg mice models would develop the toxic AB plaques, while the TAUtg mice models would develop Tau tangles. In these models, the onset and initial progression of Alzheimer’s Disease via two different mechanisms could be observed—a crucial element of the risk-gene analysis that the team performed next.[v]
As the researchers observed the aggregation of AB and TAU in their two mouse models, they carefully monitored the expression of many Alzheimer’s Disease risk genes. Many of these genes showed common characteristics; for example, in the AB models, the observed risk genes tended to converge into an inflammatory “multicellular network.” These AB mice showed severe transcriptional deregulation and neuroinflammation as they aged. However, in the Tau models, aging simply revealed a relatively stable molecular phenotype. The same risk genes did not exhibit nearly as strong of a response to the Tau tangles as they did to the presence of AB fragments.
The deregulation of risk genes is another risk-generating factor in Alzheimer’s Disease, and the observed risk genes also tended to be deregulated in aging AB mice to a much greater extent than in Tau mice. The researchers examined numerous sets of these risk genes, ranging in size from 92 genes to 1,799 genes. De Strooper and Fiers’s team found that, independent of set size, genes that enhance the risk of Alzheimer’s Disease consistently and significantly generated adverse effects when exposed to increasing AB. They did not find a similar effect as they increased Tau in the respective model.
De Strooper and Fiers’s team also determined the location of expression for many of these AB-responsive risk genes. Many were found to be expressed in, or related to, microglia—the primary immune cells of the central nervous system.[vi] [vii] [viii]When microglia-related risk genes and AB fragments interacted, microglial cell activation significantly increased. The researchers propose that this increased activation may indicate increased macrophage-like “tagging” activity that causes the inflammatory biological symptoms of Alzheimer’s Disease.
In general, these results establish clear connections between the genetic risk of Alzheimer’s Disease, AB plaques, and microglial cells. Specifically, genetic risk appears to be downstream of AB presence but upstream of Tau protein tangles. This strengthens the current hypothesis that AB pathology alone is sufficient to induce a harmful immune reaction and that neuroinflammation is an integral—and perhaps even the driving—component of Alzheimer’s Disease.[ix] [x] The team found that the transition from an early, asymptomatic phase of Alzheimer’s Disease to a clinical, symptomatic phase is likely determined by the inheritance of multiple microglia-related risk genes. It is the genetic make‐up of microglia, in other words, which determines whether a pathological response to AB is induced. Knowledge of early association between risk genes and amyloid-ß plaques, as well as the microglial origin of these interactions, provides an important base for future research. Now, the identification of risk genes and early development of amyloid-ß plaques can serve as helpful signposts during investigation of disease-causing mechanisms.
Sources:
[i] Ising, C., & Heneka, M. (2018). Functional and structural damage of neurons by innate immune mechanisms during neurodegeneration. Cell Death & Disease, 9. https://doi.org/10.1038/s41419-017-0153-x
[ii] Fiers, M., De Strooper, B., & Buee, L. (2020). Novel Alzheimer risk genes determine the microglia response to amyloid‐β but not to TAU pathology. EMBO Molecular Medicine, 12(3). https://doi.org/10.15252/emmm.201910606
[iii] Gatz, M., Reynolds, C. A., Fratiglioni, L., Johansson, B., Mortimer, J. A., Berg, S., Fiske, A., & Pedersen, N. L. (2006). Role of Genes and Environments for Explaining Alzheimer Disease. Archives of General Psychiatry, 63(2), 168–174. https://doi.org/10.1001/archpsyc.63.2.168
[iv] Zhang, B., Gaiteri, C., Bodea, L.-G., Wang, Z., McElwee, J., Podtelezhnikov, A. A., Zhang, C., Xie, T., Tran, L., Dobrin, R., Fluder, E., Clurman, B., Melquist, S., Narayanan, M., Suver, C., Shah, H., Mahajan, M., Gillis, T., Mysore, J., … Emilsson, V. (2013). Integrated Systems Approach Identifies Genetic Nodes and Networks in Late-Onset Alzheimer’s Disease. Cell, 153(3), 707–720. https://doi.org/10.1016/j.cell.2013.03.030
[v] Zahs, K. R., & Ashe, K. H. (2010). ‘Too much good news’ – are Alzheimer mouse models trying to tell us how to prevent, not cure, Alzheimer’s disease? Trends in Neurosciences, 33(8), 381–389. https://doi.org/10.1016/j.tins.2010.05.004
[vi] Sala Frigerio, C., Wolfs, L., Fattorelli, N., Thrupp, N., Voytyuk, I., Schmidt, I., Mancuso, R., Chen, W.-T., Woodbury, M. E., Srivastava, G., Möller, T., Hudry, E., Das, S., Saido, T., Karran, E., Hyman, B., Perry, V. H., Fiers, M., & De Strooper, B. (2019). The Major Risk Factors for Alzheimer’s Disease: Age, Sex, and Genes Modulate the Microglia Response to Aβ Plaques. Cell Reports, 27(4), 1293-1306.e6. https://doi.org/10.1016/j.celrep.2019.03.099
[vii] Keren-Shaul, H., Spinrad, A., Weiner, A., Matcovitch-Natan, O., Dvir-Szternfeld, R., Ulland, T. K., David, E., Baruch, K., Lara-Astaiso, D., Toth, B., Itzkovitz, S., Colonna, M., Schwartz, M., & Amit, I. (2017). A Unique Microglia Type Associated with Restricting Development of Alzheimer’s Disease. Cell, 169(7), 1276-1290.e17. https://doi.org/10.1016/j.cell.2017.05.018
[viii] Sala Frigerio, C., Wolfs, L., Fattorelli, N., Thrupp, N., Voytyuk, I., Schmidt, I., Mancuso, R., Chen, W.-T., Woodbury, M. E., Srivastava, G., Möller, T., Hudry, E., Das, S., Saido, T., Karran, E., Hyman, B., Perry, V. H., Fiers, M., & De Strooper, B. (2019). The Major Risk Factors for Alzheimer’s Disease: Age, Sex, and Genes Modulate the Microglia Response to Aβ Plaques. Cell Reports, 27(4), 1293-1306.e6. https://doi.org/10.1016/j.celrep.2019.03.099
[ix] Wirz, K. T. S., Bossers, K., Stargardt, A., Kamphuis, W., Swaab, D. F., Hol, E. M., & Verhaagen, J. (2013). Cortical beta amyloid protein triggers an immune response, but no synaptic changes in the APPswe/PS1dE9 Alzheimer’s disease mouse model. Neurobiology of Aging, 34(5), 1328–1342. https://doi.org/10.1016/j.neurobiolaging.2012.11.008
[x] Matarin, M., Salih, D. A., Yasvoina, M., Cummings, D. M., Guelfi, S., Liu, W., Nahaboo Solim, M. A., Moens, T. G., Paublete, R. M., Ali, S. S., Perona, M., Desai, R., Smith, K. J., Latcham, J., Fulleylove, M., Richardson, J. C., Hardy, J., & Edwards, F. A. (2015). A Genome-wide Gene-Expression Analysis and Database in Transgenic Mice during Development of Amyloid or Tau Pathology. Cell Reports, 10(4), 633–644. https://doi.org/10.1016/j.celrep.2014.12.041