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Association of the CX3CR1-V249I Variant with Neurofibrillary Pathology Progression in Late-Onset Alzheimer’s Disease

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Abstract

Neuroinflammation and microglial dysfunction have a prominent role in the pathogenesis of late-onset Alzheimer’s disease (LOAD). CX3CR1 is a microglia-specific gene involved in microglia-neuron crosstalk and neuroinflammation. Numerous evidence show the involvement of CX3CR1 in AD. The aim of this study was to investigate if some functional genetic variants of this gene could influence on LOAD’s outcome, in a neuropathologically confirmed Spanish cohort. We designed an open, pragmatic, case-control retrospective study including a total of 475 subjects (205 pathologically confirmed AD cases and 270 controls). We analyzed the association of the two CX3CR1 functional variants (V249I, rs3732379; and T280M, rs3732378) with neurofibrillary pathology progression rate according to Braak’s staging system, age at onset (AAO), survival time, and risk of suffering LOAD. We found that individuals heterozygous for CX3CR1-V249I presented a lower neurofibrillary pathology stage at death (OR = 0.42, 95%CI [0.23, 0.74], p = 0.003, adj-p = 0.013) than the other genotypes. Eighty percent of the subjects homozygous for 249I had higher neurofibrillary pathology progression (Braak’s stage VI). Moreover, homozygosis for 280M and 249I could be associated with a higher AAO in the subgroups of AD with Lewy bodies and without Lewy bodies. These CX3CR1 genetic variants could represent new modifying factors of pathology progression and age at onset in LOAD. These results provide further evidence of the involvement of CX3CR1 pathway and microglia/macrophages in the pathogenesis of LOAD.

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References

  1. Querfurth HW, LaFerla FM (2010) Alzheimer’s disease. N Engl J Med 362:329–344. doi:10.1056/NEJMra0909142

    Article  CAS  PubMed  Google Scholar 

  2. Glass CK, Saijo K, Winner B et al (2010) Mechanisms underlying inflammation in neurodegeneration. Cell 140:918–934. doi:10.1016/j.cell.2010.02.016

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. Parkkinen L, Soininen H, Alafuzoff I (2003) Regional distribution of alpha-synuclein pathology in unimpaired aging and Alzheimer disease. J Neuropathol Exp Neurol 62:363–367

    Article  CAS  PubMed  Google Scholar 

  4. Hansen LA (1997) The Lewy body variant of Alzheimer disease. J Neural Transm Suppl 51:83–93

    Article  CAS  PubMed  Google Scholar 

  5. Rao JS, Kellom M, Kim H-W, Rapoport SI (2012) Neuroinflammation and synaptic loss. Neurochem Res 37:903–910. doi:10.1007/s11064-012-0708-2

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Fan Z, Okello AA, Brooks DJ, Edison P (2015) Longitudinal influence of microglial activation and amyloid on neuronal function in Alzheimer’s disease. Brain J Neurol 138:3685–3698. doi:10.1093/brain/awv288

    Article  Google Scholar 

  7. Chen P, Zhao W, Guo Y et al (2016) CX3CL1/CX3CR1 in Alzheimer’s disease: A target for Neuroprotection. Biomed Res Int 2016:8090918. doi:10.1155/2016/8090918

    PubMed  PubMed Central  Google Scholar 

  8. Simard AR, Soulet D, Gowing G et al (2006) Bone marrow-derived microglia play a critical role in restricting senile plaque formation in Alzheimer’s disease. Neuron 49:489–502. doi:10.1016/j.neuron.2006.01.022

    Article  CAS  PubMed  Google Scholar 

  9. Perry VH, Teeling J (2013) Microglia and macrophages of the central nervous system: The contribution of microglia priming and systemic inflammation to chronic neurodegeneration. Semin Immunopathol 35:601–612. doi:10.1007/s00281-013-0382-8

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Heneka MT, Carson MJ, El Khoury J et al (2015) Neuroinflammation in Alzheimer’s disease. Lancet Neurol 14:388–405. doi:10.1016/S1474-4422(15)70016-5

    Article  CAS  PubMed  Google Scholar 

  11. Meyer-Luehmann M, Prinz M (2015) Myeloid cells in Alzheimer’s disease: Culprits, victims or innocent bystanders? Trends Neurosci 38:659–668. doi:10.1016/j.tins.2015.08.011

    Article  CAS  PubMed  Google Scholar 

  12. Naj AC, Jun G, Beecham GW et al (2011) Common variants at MS4A4/MS4A6E, CD2AP, CD33 and EPHA1 are associated with late-onset Alzheimer’s disease. Nat Genet 43:436–441. doi:10.1038/ng.801

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Chouraki V, Seshadri S (2014) Genetics of Alzheimer’s disease. Adv Genet 87:245–294. doi:10.1016/B978-0-12-800149-3.00005-6

    CAS  PubMed  Google Scholar 

  14. Karch CM, Goate AM (2015) Alzheimer’s disease risk genes and mechanisms of disease pathogenesis. Biol Psychiatry 77:43–51. doi:10.1016/j.biopsych.2014.05.006

    Article  CAS  PubMed  Google Scholar 

  15. Wang Z, Lei H, Zheng M et al (2016) Meta-analysis of the association between Alzheimer disease and variants in GAB2, PICALM, and SORL1. Mol Neurobiol 53:6501–6510. doi:10.1007/s12035-015-9546-y

    Article  CAS  PubMed  Google Scholar 

  16. Rai V (2016) Methylenetetrahydrofolate Reductase (MTHFR) C677T polymorphism and Alzheimer disease risk: A meta-analysis. Mol Neurobiol:1–14. doi:10.1007/s12035-016-9722-8

  17. Morgan K (2011) The three new pathways leading to Alzheimer’s disease. Neuropathol Appl Neurobiol 37:353–357. doi:10.1111/j.1365-2990.2011.01181.x

    Article  CAS  PubMed  Google Scholar 

  18. Schellenberg GD, Montine TJ (2012) The genetics and neuropathology of Alzheimer’s disease. Acta Neuropathol (Berl) 124:305–323. doi:10.1007/s00401-012-0996-2

    Article  CAS  Google Scholar 

  19. Dong X, Zhang L, Meng Q, Gao Q (2016) Association between interleukin-1A, interleukin-1B, and bridging integrator 1 polymorphisms and Alzheimer’s disease: A standard and cumulative meta-analysis. Mol Neurobiol. doi:10.1007/s12035-015-9683-3

    Google Scholar 

  20. Linnertz C, Lutz MW, Ervin JF et al (2014) The genetic contributions of SNCA and LRRK2 genes to Lewy body pathology in Alzheimer’s disease. Hum Mol Genet 23:4814–4821. doi:10.1093/hmg/ddu196

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Guerreiro R, Wojtas A, Bras J et al (2013) TREM2 variants in Alzheimer’s disease. N Engl J Med 368:117–127. doi:10.1056/NEJMoa1211851

    Article  CAS  PubMed  Google Scholar 

  22. Lu Y, Liu W, Wang X (2015) TREM2 variants and risk of Alzheimer’s disease: A meta-analysis. Neurol Sci Off J Ital Neurol Soc Ital Soc Clin Neurophysiol. doi:10.1007/s10072-015-2274-2

    Google Scholar 

  23. Bradshaw EM, Chibnik LB, Keenan BT et al (2013) CD33 Alzheimer’s disease locus: Altered monocyte function and amyloid biology. Nat Neurosci 16:848–850. doi:10.1038/nn.3435

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Griciuc A, Serrano-Pozo A, Parrado AR et al (2013) Alzheimer’s disease risk gene CD33 inhibits microglial uptake of amyloid beta. Neuron 78:631–643. doi:10.1016/j.neuron.2013.04.014

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Wolf Y, Yona S, Kim K-W, Jung S (2013) Microglia, seen from the CX3CR1 angle. Front Cell Neurosci 7:26. doi:10.3389/fncel.2013.00026

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Sheridan GK, Murphy KJ (2013) Neuron-glia crosstalk in health and disease: Fractalkine and CX3CR1 take centre stage. Open Biol 3:130181. doi:10.1098/rsob.130181

    Article  PubMed  PubMed Central  Google Scholar 

  27. Cardona AE, Pioro EP, Sasse ME et al (2006) Control of microglial neurotoxicity by the fractalkine receptor. Nat Neurosci 9:917–924. doi:10.1038/nn1715

    Article  CAS  PubMed  Google Scholar 

  28. Lee S, Varvel NH, Konerth ME et al (2010) CX3CR1 deficiency alters microglial activation and reduces beta-amyloid deposition in two Alzheimer’s disease mouse models. Am J Pathol 177:2549–2562. doi:10.2353/ajpath.2010.100265

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Lastres-Becker I, Innamorato NG, Jaworski T et al (2014) Fractalkine activates NRF2/NFE2L2 and heme oxygenase 1 to restrain tauopathy-induced microgliosis. Brain J Neurol 137:78–91. doi:10.1093/brain/awt323

    Article  Google Scholar 

  30. McDermott DH, Fong AM, Yang Q et al (2003) Chemokine receptor mutant CX3CR1-M280 has impaired adhesive function and correlates with protection from cardiovascular disease in humans. J Clin Invest 111:1241–1250. doi:10.1172/JCI16790

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Daoudi M, Lavergne E, Garin A et al (2004) Enhanced adhesive capacities of the naturally occurring Ile249–Met280 variant of the chemokine receptor CX3CR1. J Biol Chem 279:19649–19657. doi:10.1074/jbc.M313457200

    Article  CAS  PubMed  Google Scholar 

  32. Lopez-Lopez A, Gamez J, Syriani E et al (2014) CX3CR1 is a modifying gene of survival and progression in amyotrophic lateral sclerosis. PLoS One 9:e96528. doi:10.1371/journal.pone.0096528

    Article  PubMed  PubMed Central  Google Scholar 

  33. Arli B, Irkec C, Menevse S et al (2013) Fractalkine gene receptor polymorphism in patients with multiple sclerosis. Int J Neurosci 123:31–37. doi:10.3109/00207454.2012.723079

    Article  CAS  PubMed  Google Scholar 

  34. Brand S, Hofbauer K, Dambacher J et al (2006) Increased expression of the chemokine Fractalkine in Crohn’s disease and association of the Fractalkine receptor T280M polymorphism with a Fibrostenosing disease phenotype. Am J Gastroenterol 101:99–106

    Article  CAS  PubMed  Google Scholar 

  35. Faure S, Meyer L, Costagliola D et al (2000) Rapid progression to AIDS in HIV+ individuals with a structural variant of the chemokine receptor CX3CR1. Science 287:2274–2277. doi:10.1126/science.287.5461.2274

    Article  CAS  PubMed  Google Scholar 

  36. Zhang R, Wang L-Y, Wang Y-F et al (2015) Associations between the T280M and V249I SNPs in CX3CR1 and the risk of age-related macular degeneration. Invest Ophthalmol Vis Sci 56:5590–5598. doi:10.1167/iovs.15-16830

    Article  CAS  PubMed  Google Scholar 

  37. Montine TJ, Phelps CH, Beach TG et al (2012) National Institute on Aging-Alzheimer’s association guidelines for the neuropathologic assessment of Alzheimer’s disease: A practical approach. Acta Neuropathol (Berl) 123:1–11. doi:10.1007/s00401-011-0910-3

    Article  CAS  Google Scholar 

  38. Braak H, Alafuzoff I, Arzberger T et al (2006) Staging of Alzheimer disease-associated neurofibrillary pathology using paraffin sections and immunocytochemistry. Acta Neuropathol (Berl) 112:389–404. doi:10.1007/s00401-006-0127-z

    Article  Google Scholar 

  39. González JR, Armengol L, Solé X et al (2007) SNPassoc: An R package to perform whole genome association studies. Bioinforma Oxf Engl 23:644–645. doi:10.1093/bioinformatics/btm025

    Google Scholar 

  40. Vidal-Taboada JM, Lopez-Lopez A, Salvado M et al (2015) UNC13A confers risk for sporadic ALS and influences survival in a Spanish cohort. J Neurol 262:2285–2292. doi:10.1007/s00415-015-7843-z

    Article  CAS  PubMed  Google Scholar 

  41. Maphis N, Xu G, Kokiko-Cochran ON et al (2015) Reactive microglia drive tau pathology and contribute to the spreading of pathological tau in the brain. Brain J Neurol 138:1738–1755. doi:10.1093/brain/awv081

    Article  Google Scholar 

  42. Moatti D, Faure S, Fumeron F et al (2001) Polymorphism in the fractalkine receptor CX3CR1 as a genetic risk factor for coronary artery disease. Blood 97:1925–1928. doi:10.1182/blood.V97.7.1925

    Article  CAS  PubMed  Google Scholar 

  43. Colom-Cadena M, Gelpi E, Charif S et al (2013) Confluence of α-synuclein, tau, and β-amyloid pathologies in dementia with Lewy bodies. J Neuropathol Exp Neurol 72:1203–1212. doi:10.1097/NEN.0000000000000018

    Article  CAS  PubMed  Google Scholar 

  44. Compta Y, Parkkinen L, O’Sullivan SS et al (2011) Lewy- and Alzheimer-type pathologies in Parkinson’s disease dementia: Which is more important? Brain J Neurol 134:1493–1505. doi:10.1093/brain/awr031

    Article  Google Scholar 

  45. Sierra M, Gelpi E, Martí MJ, Compta Y (2016) Lewy- and alzheimer-type pathologies in midbrain and cerebellum across the Lewy body disorders spectrum. Neuropathol Appl Neurobiol. doi:10.1111/nan.12308

    PubMed  Google Scholar 

  46. Singh N, Rai H, Sinha N et al (2012) Association of V249I and T280M polymorphisms in the chemokine receptor CX3CR1 gene with early onset of coronary artery disease among north Indians. Genet Test Mol Biomark 16:756–760. doi:10.1089/gtmb.2011.0256

    Article  CAS  Google Scholar 

  47. Niessner A, Marculescu R, Haschemi A et al (2005) Opposite effects of CX3CR1 receptor polymorphisms V2491 and T280M on the development of acute coronary syndrome. A possible implication of fractalkine in inflammatory activation Thromb Haemost doi. doi:10.1160/TH04-11-0735

    Google Scholar 

  48. Murphy PM (1994) The molecular biology of leukocyte chemoattractant receptors. Annu Rev Immunol 12:593–633. doi:10.1146/annurev.iy.12.040194.003113

    Article  CAS  PubMed  Google Scholar 

  49. Corder EH, Saunders AM, Strittmatter WJ et al (1993) Gene dose of apolipoprotein E type 4 allele and the risk of Alzheimer’s disease in late onset families. Science 261:921–923

    Article  CAS  PubMed  Google Scholar 

  50. Blacker D, Haines JL, Rodes L et al (1997) ApoE-4 and age at onset of Alzheimer’s disease: The NIMH genetics initiative. Neurology 48:139–147

    Article  CAS  PubMed  Google Scholar 

  51. Sando SB, Melquist S, Cannon A et al (2008) APOE ε4 lowers age at onset and is a high risk factor for Alzheimer’s disease; a case control study from central Norway. BMC Neurol 8:9. doi:10.1186/1471-2377-8-9

    Article  PubMed  PubMed Central  Google Scholar 

  52. Lee JH, Cheng R, Schupf N et al (2007) The association between genetic variants in SORL1 and Alzheimer disease in an urban, multiethnic, community-based cohort. Arch Neurol 64:501–506. doi:10.1001/archneur.64.4.501

    Article  PubMed  PubMed Central  Google Scholar 

  53. Leduc V, De Beaumont L, Théroux L et al (2015) HMGCR is a genetic modifier for risk, age of onset and MCI conversion to Alzheimer’s disease in a three cohorts study. Mol Psychiatry 20:867–873. doi:10.1038/mp.2014.81

    Article  CAS  PubMed  Google Scholar 

  54. Naj AC, Jun G, Reitz C et al (2014) Effects of multiple genetic loci on age at onset in late-onset Alzheimer disease: A genome-wide association study. JAMA Neurol 71:1394–1404. doi:10.1001/jamaneurol.2014.1491

    Article  PubMed  PubMed Central  Google Scholar 

  55. Li Y-J, Scott WK, Hedges DJ et al (2002) Age at onset in two common neurodegenerative diseases is genetically controlled. Am J Hum Genet 70:985–993. doi:10.1086/339815

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  56. Lee JH, Barral S, Cheng R et al (2008) Age-at-onset linkage analysis in Caribbean Hispanics with familial late-onset Alzheimer’s disease. Neurogenetics 9:51–60. doi:10.1007/s10048-007-0103-3

    Article  PubMed  Google Scholar 

  57. Zhao W, Marchani EE, Cheung CYK et al (2013) Genome scan in familial late-onset Alzheimer’s disease: A locus on chromosome 6 contributes to age at onset. Am J Med Genet Part B Neuropsychiatr Genet Off Publ Int Soc Psychiatr Genet. doi:10.1002/ajmg.b.32133

    Google Scholar 

  58. Manolio TA (2010) Genomewide association studies and assessment of the risk of disease. N Engl J Med 363:166–176. doi:10.1056/NEJMra0905980

    Article  CAS  PubMed  Google Scholar 

  59. Balasa M, Gelpi E, Antonell A et al (2011) Clinical features and APOE genotype of pathologically proven early-onset Alzheimer disease. Neurology 76:1720–1725. doi:10.1212/WNL.0b013e31821a44dd

    Article  CAS  PubMed  Google Scholar 

  60. Crean S, Ward A, Mercaldi CJ et al (2011) Apolipoprotein E ε4 prevalence in Alzheimer’s disease patients varies across global populations: A systematic literature review and meta-analysis. Dement Geriatr Cogn Disord 31:20–30. doi:10.1159/000321984

    Article  CAS  PubMed  Google Scholar 

  61. Jin SC, Benitez BA, Karch CM et al (2014) Coding variants in TREM2 increase risk for Alzheimer’s disease. Hum Mol Genet 23:5838–5846. doi:10.1093/hmg/ddu277

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  62. Strobel S, Grünblatt E, Riederer P et al (1996) (2015) changes in the expression of genes related to neuroinflammation over the course of sporadic Alzheimer’s disease progression: CX3CL1, TREM2, and PPARγ. J Neural Transm Vienna Austria 122:1069–1076. doi:10.1007/s00702-015-1369-5

    Article  Google Scholar 

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Acknowledgements

The authors are indebted to the patients and their relatives for their cooperation. Authors acknowledge the Spanish National DNA Bank (Salamanca, Spain) and Neurological Tissue Bank of the Biobank-Hospital Clinic-IDIBAPS (Barcelona, Spain) for the data and sample procurement.

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Authors and Affiliations

  1. Biochemistry and Molecular Biology Unit, Department of Biomedical Sciences, Faculty of Medicine–IDIBAPS, University of Barcelona, Barcelona, Spain

    Alan López-López, Diana Maria Lopategui & Jose M. Vidal-Taboada

  2. Neurological Tissue Bank of the Biobank, Hospital Clinic, IDIBAPS, Barcelona, Spain

    Ellen Gelpi

  3. Miami Clinical and Translational Science Institute, University of Miami, Miami, Florida, USA

    Diana Maria Lopategui

  4. Institut de Neurociencies, University of Barcelona, Barcelona, Spain

    Jose M. Vidal-Taboada

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  1. Alan López-López
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  2. Ellen Gelpi
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  3. Diana Maria Lopategui
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  4. Jose M. Vidal-Taboada
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Corresponding author

Correspondence to Jose M. Vidal-Taboada.

Ethics declarations

The protocol of this study was approved by the IRB from the Hospital Clinic of Barcelona, the Spanish National DNA Bank, and the IDIBAPS Biobank Ethics and Scientific Committees. All procedures performed in this study involving human participants were in accordance with the ethical standards of the institutional and national research committee and with the 1964 Helsinki declaration. All patients and/or close relatives, in case of brain donors, gave their informed written consent for the use of brain tissue for research purposes. This article does not contain any studies with animals performed by any of the authors.

Funding

This study was funded by Ministerio de Economia y Competitividad (grant IPT-2012-0614-010000) and by Generalitat de Catalunya (grant 2014SGR1115). ALL held a fellowship from the Institut d’Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS).

Conflict of Interest

The authors declare that they have no conflict of interest.

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Table: CX3CR1 V249I marker analysis for Braak neurofibrillary pathology progression in LOAD without LB (LB−/AD) patients assuming a co-dominant, over-dominant, and recessive models. (DOC 45 kb)

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López-López, A., Gelpi, E., Lopategui, D.M. et al. Association of the CX3CR1-V249I Variant with Neurofibrillary Pathology Progression in Late-Onset Alzheimer’s Disease. Mol Neurobiol 55, 2340–2349 (2018). https://doi.org/10.1007/s12035-017-0489-3

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