Skip to content
Licensed Unlicensed Requires Authentication Published by De Gruyter December 1, 2020

Down-regulation of SORL1 is associated with Alzheimer’s disease through activating ABC transporter pathway

  • Zhiqiang Wei EMAIL logo , Xingdi Qi , Shijun Zhai , Yan Chen , Xiaoshuang Xia , Boyu Zheng , Xugang Sun , Guangming Zhang , Ling Wang , Qi Zhang , Chen Xu , Shihe Jiang , Xiulian Li , Bingxin Xie , Xiaohui Liao , Zhu Ai and Xin Li

Abstract

Alzheimer’s disease (AD) is a common neurodegenerative disease with high morbidity among elderly people. A genetic attribution has been extensively proved. Here, we propose to further prioritize genes that harbor single nucleotide variation (SNV) or structural variation (SV) for AD and explore the underlying potential mechanisms through exploiting their expression and methylation spectra. A high-confidence AD-associated candidate gene list was obtained from the ClinVar and Human Gene Mutation Database (HGMD). Genome-wide methylation and expression profiles of AD and normal subjects were downloaded from the Gene Expression Omnibus (GEO). Through comprehensive comparison of expression and methylation levels between AD and normal samples, as well as different stages of AD samples, SORL1 was identified as the most plausible gene for AD incidence and progression. Gene Set Enrichment Analysis (GSEA) revealed significant activation of the ABC (ATP binding cassette) transporter with the aberrant up-regulation of SORL1 within AD samples. This study unfolds the expression and methylation spectra of previously probed genes with SNV or SV in AD for the first time, and reports an aberrant activation of the ABC transporter pathway that might contribute to AD progression. This should shed some light on AD diagnosis and precision treatment.


Corresponding author: Zhiqiang Wei, Department of Neurology, The Second Hospital of Tianjin Medical University, Pingjiang Road 23, Hexi district, Tianjin, 300211, P.R. China, E-mail:
Zhiqiang Wei and Xingdi Qi contributed equally to this work.

Funding source: Tianjin Natural Science Foundation of China

Award Identifier / Grant number: 16JCYBJC25500

Funding source: The key project in the Science and Technology Foundation of Tianjin Health and Family Planning

Award Identifier / Grant number: 15KG136

Funding source: Tianjin Science and Technology Commission Scientific Popularization Project

Award Identifier / Grant number: 17KPHDSF00170

  1. Author contributions: All authors have made contributions to this research and the authors’ contribution is below. WZQ, QXD and LX, put forward the ideas of this article, wrote this article and analyzed the data.CY, XXS, ZBY, SXG and ZGM, helped in the acquisition of data and put forward the ideas of the article.WL, ZQ, XC, JSH, LXL, XBX, LXH and AZ helped in the analysis and interpretation of data and in revising the manuscript. WZQ, ZSJ, LX, provided valuable instructions and suggestions for this paper and helped in revising the manuscript.

  2. Research funding: This study was funded by Tianjin Natural Science Foundation of China (Grant No. 16JCYBJC25500), the key project in the Science and Technology Foundation of Tianjin Health and Family Planning (Grant No. 15KG136) and Tianjin Science and Technology Commission Scientific Popularization Project (Grant No. 17KPHDSF00170).

  3. Conflict of interest: No competing financial interests exist.

References

1. James, SL, Abate, D, Abate, KH, Abay, SM, Abbafati, C, Abbasi, N. Global, regional, and national incidence, prevalence, and years lived with disability for 354 diseases and injuries for 195 countries and territories, 1990-2017: a systematic analysis for the Global Burden of Disease Study 2017. Lancet 2018;392:1789–858.10.1016/S0140-6736(18)32279-7Search in Google Scholar

2. Qiang, W, Yau, WM, Lu, JX, Collinge, J, Tycko, R. Structural variation in amyloid-beta fibrils from Alzheimer’s disease clinical subtypes. Nature 2017;541:217–21. https://doi.org/10.1038/nature20814.Search in Google Scholar

3. Chen, GF, Xu, TH, Yan, Y, Zhou, YR, Jiang, Y, Melcher, K. Amyloid beta: structure, biology and structure-based therapeutic development. Acta Pharmacol Sin 2017;38:1205–35. https://doi.org/10.1038/aps.2017.28.Search in Google Scholar

4. Palop, JJ, Chin, J, Mucke, L. A network dysfunction perspective on neurodegenerative diseases. Nature 2006;443:768–73. https://doi.org/10.1038/nature05289.Search in Google Scholar

5. Gatz, M, Reynolds, CA, Fratiglioni, L, Johansson, B, Mortimer, JA, Berg, S. Role of genes and environments for explaining Alzheimer disease. Arch Gen Psychiatr 2006;63:168–74. https://doi.org/10.1001/archpsyc.63.2.168.Search in Google Scholar

6. Ko, Y, Ament, SA, Eddy, JA, Caballero, J, Earls, JC, Hood, L, et al.. Cell type-specific genes show striking and distinct patterns of spatial expression in the mouse brain. Proc Natl Acad Sci USA 2013;110:3095–100. https://doi.org/10.1073/pnas.1222897110.Search in Google Scholar

7. Qureshi, IA, Mehler, MF. Advances in epigenetics and epigenomics for neurodegenerative diseases. Curr Neurol Neurosci Rep 2011;11:464–73. https://doi.org/10.1007/s11910-011-0210-2.Search in Google Scholar

8. Jackson, M, Marks, L, May, GHW, Wilson, JB. The genetic basis of disease. Essays Biochem 2018;62:643–723. https://doi.org/10.1042/ebc20170053.Search in Google Scholar

9. Alasmari, F, Ashby, CR, Hall, FS, Sari, Y, Tiwari, AK. Modulation of the ATP-binding cassette B1 transporter by neuro-inflammatory cytokines: role in the pathogenesis of Alzheimer’s disease. Front Pharmacol 2018;9:658. https://doi.org/10.3389/fphar.2018.00658.Search in Google Scholar

10. Mastroeni, D, Grover, A, Delvaux, E, Whiteside, C, Coleman, PD, Rogers, J. Epigenetic changes in Alzheimer’s disease: decrements in DNA methylation. Neurobiol Aging 2010;31:2025–37. https://doi.org/10.1016/j.neurobiolaging.2008.12.005.Search in Google Scholar

11. Yokoyama, AS, Rutledge, JC, Medici, V. DNA methylation alterations in Alzheimer’s disease. Environmental epigenetics 2017;3:dvx008. https://doi.org/10.1093/eep/dvx008.Search in Google Scholar

12. Jiang, Q, Lee, CY, Mandrekar, S, Wilkinson, B, Cramer, P, Zelcer, N. ApoE promotes the proteolytic degradation of Abeta. Neuron 2008;58:681–93. https://doi.org/10.1016/j.neuron.2008.04.010.Search in Google Scholar

13. Iwata, A, Nagata, K, Hatsuta, H, Takuma, H, Bundo, M. Altered CpG methylation in sporadic Alzheimer’s disease is associated with APP and MAPT dysregulation. Hum Mol Genet 2014;23:648–56. https://doi.org/10.1093/hmg/ddt451.Search in Google Scholar

14. Blalock, EM, Buechel, HM, Popovic, J, Geddes, JW, Landfield, PW. Landfield, Microarray analyses of laser-captured hippocampus reveal distinct gray and white matter signatures associated with incipient Alzheimer’s disease. J Chem Neuroanat 2011;42:118–26. https://doi.org/10.1016/j.jchemneu.2011.06.007.Search in Google Scholar

15. Sanchez-Mut, JV, Heyn, H, Vidal, E, Moran, S, Sayols, S, Delgado-Morales, R. Human DNA methylomes of neurodegenerative diseases show common epigenomic patterns. Transl Psychiatry 2016;6:e718. https://doi.org/10.1038/tp.2015.214.Search in Google Scholar

16. Diboun, I, Wernisch, L, Orengo, CA, Koltzenburg, M. Microarray analysis after RNA amplification can detect pronounced differences in gene expression using limma. BMC Genom 2006;7:252. https://doi.org/10.1186/1471-2164-7-252.Search in Google Scholar

17. Gautier, L, Cope, L, Bolstad, BM, Irizarry, RA. Affy--analysis of Affymetrix GeneChip data at the probe level. Bioinformatics 2004;20:307–15. https://doi.org/10.1093/bioinformatics/btg405.Search in Google Scholar

18. Pimenova, AA, Raj, T, Goate, AM. Untangling genetic risk for Alzheimer’s disease. Biol Psychiatr 2018;83:300–10. https://doi.org/10.1016/j.biopsych.2017.05.014.Search in Google Scholar

19. Arbor, SC, LaFontaine, M, Cumbay, M. Amyloid-beta Alzheimer targets - protein processing, lipid rafts, and amyloid-beta pores. Yale J Biol Med 2016;89:5–21.Search in Google Scholar

20. Quiroz, YT, Stern, CE, Reiman, EM, Brickhouse, M, Ruiz, A, Sperling, RA. Sperling, Cortical atrophy in presymptomatic Alzheimer’s disease presenilin 1 mutation carriers. J Neurol Neurosurg Psychiatr 2013;84:556–61. https://doi.org/10.1136/jnnp-2012-303299.Search in Google Scholar

21. Supnet, C, Bezprozvanny, I. Presenilins function in ER calcium leak and Alzheimer’s disease pathogenesis. Cell Calcium 2011;50:303–9. https://doi.org/10.1016/j.ceca.2011.05.013.Search in Google Scholar

22. Furuya, TK, da Silva, PN, Payão, SL, Rasmussen, LT, de Labio, RW, Bertolucci, PH. SORL1 and SIRT1 mRNA expression and promoter methylation levels in aging and Alzheimer’s Disease. Neurochem Int 2012;61:973–5. https://doi.org/10.1016/j.neuint.2012.07.014.Search in Google Scholar

23. Yu, L, Chibnik, LB, Srivastava, GP, Pochet, N, Yang, J, Xu, J. Association of Brain DNA methylation in SORL1, ABCA7, HLA-DRB5, SLC24A4, and BIN1 with pathological diagnosis of Alzheimer disease. JAMA neurology 2015;72:15–24. https://doi.org/10.1001/jamaneurol.2014.3049.Search in Google Scholar

24. KoLsch, H, Jessen, F, Wiltfang, J, Lewczuk, P, Dichgans, M, Teipel, SJ, et al.. Association of SORL1 gene variants with Alzheimer’s disease. Brain Res 2009;1264:1–6. https://doi.org/10.1016/j.brainres.2009.01.044.Search in Google Scholar

25. Grear, KE, Ling, IF, Simpson, JF, Furman, JL, Simmons, CR, Peterson, SL, et al.. Expression of SORL1 and a novel SORL1 splice variant in normal and Alzheimers disease brain. Mol Neurodegener 2009;4:46. https://doi.org/10.1186/1750-1326-4-46.Search in Google Scholar

26. Cellini, E, Tedde, A, Bagnoli, S, Pradella, S, Piacentini, S, Sorbi, S, et al.. Implication of sex and SORL1 variants in Italian patients with alzheimer disease. JAMA Neurology 2009;66:1260–6. https://doi.org/10.1001/archneurol.2009.101.Search in Google Scholar

27. Furuya, TK, da Silva, PN, Payão, SL, Rasmussen, LT, de Labio, RW, Bertolucci, PH, et al.. SORL1 and SIRT1 mRNA expression and promoter methylation levels in aging and Alzheimer’s Disease. Neurochem Int 2012;61:973–5. https://doi.org/10.1016/j.neuint.2012.07.014.Search in Google Scholar

28. Yang, Yu, Wang, M, Yang, X, Sui, M, Zhang, T, Liang, J, et al.. Association between DNA methylation of SORL1 5’-flanking region and mild cognitive impairment in type 2 diabetes mellitus. Ann Endocrinol 2016;77:625–32. https://doi.org/10.1016/j.ando.2016.02.008.Search in Google Scholar

29. Locher, KP. Mechanistic diversity in ATP-binding cassette (ABC) transporters. Nat Struct Mol Biol 2016;23:487–93. https://doi.org/10.1038/nsmb.3216.Search in Google Scholar

30. Kooij, G, van Horssen, J, Bandaru, VV, Haughey, NJ, de Vries, HE. The role of ATP-binding cassette transporters in neuro-inflammation: relevance for bioactive lipids. Front Pharmacol 2012;3:74. https://doi.org/10.3389/fphar.2012.00074.Search in Google Scholar

31. Zhong, X, Liu, MY, Sun, XH, Wei, MJ. Association between ABCB1 polymorphisms and haplotypes and Alzheimer’s disease: a meta-analysis. Sci Rep 2016;6:32708. https://doi.org/10.1038/srep32708.Search in Google Scholar

32. Hu, W, Lin, X, Zhang, H, Zhao, N. ATP binding cassette subfamily A member 2 (ABCA2) expression and methylation are associated with Alzheimer’s disease. Med Sci Mon Int Med J Exp Clin Res 2017;23:5851–61. https://doi.org/10.12659/msm.905524.Search in Google Scholar

33. Davis, W, Tew, KD. ATP-binding cassette transporter-2 (ABCA2) as a therapeutic target. Biochem Pharmacol 2018;151:188–200. https://doi.org/10.1016/j.bcp.2017.11.018.Search in Google Scholar

34. Van den Hove, DL, Kompotis, K, Lardenoije, R, Kenis, G, Mill, J, Steinbusch, HW. Epigenetically regulated microRNAs in Alzheimer’s disease. Neurobiol Aging 2014;35:731–45. https://doi.org/10.1016/j.neurobiolaging.2013.10.082.Search in Google Scholar


Supplementary material

The online version of this article offers supplementary material (https://doi.org/10.1515/znc-2019-0213).


Received: 2019-11-28
Accepted: 2020-10-31
Published Online: 2020-12-01
Published in Print: 2021-05-26

© 2020 Walter de Gruyter GmbH, Berlin/Boston

Downloaded on 25.4.2024 from https://www.degruyter.com/document/doi/10.1515/znc-2019-0213/html
Scroll to top button