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Lower White Matter Volume and Worse Executive Functioning Reflected in Higher Levels of Plasma GFAP among Older Adults with and Without Cognitive Impairment

Published online by Cambridge University Press:  22 June 2021

Breton M. Asken*
Affiliation:
Department of Neurology, Memory and Aging Center, Weill Institute for Neurosciences, University of California, San Francisco, CA, USA
Lawren VandeVrede
Affiliation:
Department of Neurology, Memory and Aging Center, Weill Institute for Neurosciences, University of California, San Francisco, CA, USA
Julio C. Rojas
Affiliation:
Department of Neurology, Memory and Aging Center, Weill Institute for Neurosciences, University of California, San Francisco, CA, USA
Corrina Fonseca
Affiliation:
Department of Neurology, Memory and Aging Center, Weill Institute for Neurosciences, University of California, San Francisco, CA, USA
Adam M. Staffaroni
Affiliation:
Department of Neurology, Memory and Aging Center, Weill Institute for Neurosciences, University of California, San Francisco, CA, USA
Fanny M. Elahi
Affiliation:
Department of Neurology, Memory and Aging Center, Weill Institute for Neurosciences, University of California, San Francisco, CA, USA
Cutter A. Lindbergh
Affiliation:
Department of Neurology, Memory and Aging Center, Weill Institute for Neurosciences, University of California, San Francisco, CA, USA
Alexandra C. Apple
Affiliation:
Department of Neurology, Memory and Aging Center, Weill Institute for Neurosciences, University of California, San Francisco, CA, USA
Michelle You
Affiliation:
Department of Neurology, Memory and Aging Center, Weill Institute for Neurosciences, University of California, San Francisco, CA, USA
Sophia Weiner-Light
Affiliation:
Department of Neurology, Memory and Aging Center, Weill Institute for Neurosciences, University of California, San Francisco, CA, USA
Nivetha Brathaban
Affiliation:
Department of Neurology, Memory and Aging Center, Weill Institute for Neurosciences, University of California, San Francisco, CA, USA
Nicole Fernandes
Affiliation:
Department of Neurology, Memory and Aging Center, Weill Institute for Neurosciences, University of California, San Francisco, CA, USA
Adam L. Boxer
Affiliation:
Department of Neurology, Memory and Aging Center, Weill Institute for Neurosciences, University of California, San Francisco, CA, USA
Bruce L. Miller
Affiliation:
Department of Neurology, Memory and Aging Center, Weill Institute for Neurosciences, University of California, San Francisco, CA, USA
Howie J. Rosen
Affiliation:
Department of Neurology, Memory and Aging Center, Weill Institute for Neurosciences, University of California, San Francisco, CA, USA
Joel H. Kramer
Affiliation:
Department of Neurology, Memory and Aging Center, Weill Institute for Neurosciences, University of California, San Francisco, CA, USA
Kaitlin B. Casaletto
Affiliation:
Department of Neurology, Memory and Aging Center, Weill Institute for Neurosciences, University of California, San Francisco, CA, USA
*
*Correspondence and reprint requests to: Breton M. Asken, 675 Nelson Rising Lane, Suite 190, San Francisco, CA 94158, USA. E-mail: [email protected]

Abstract

Objective:

There are minimal data directly comparing plasma neurofilament light (NfL) and glial fibrillary acidic protein (GFAP) in aging and neurodegenerative disease research. We evaluated associations of plasma NfL and plasma GFAP with brain volume and cognition in two independent cohorts of older adults diagnosed as clinically normal (CN), mild cognitive impairment (MCI), or Alzheimer’s dementia.

Methods:

We studied 121 total participants (Cohort 1: n = 50, age 71.6 ± 6.9 years, 78% CN, 22% MCI; Cohort 2: n = 71, age 72.2 ± 9.2 years, 45% CN, 25% MCI, 30% dementia). Gray and white matter volumes were obtained for total brain and broad subregions of interest (ROIs). Neuropsychological testing evaluated memory, executive functioning, language, and visuospatial abilities. Plasma samples were analyzed in duplicate for NfL and GFAP using single molecule array assays (Quanterix Simoa). Linear regression models with structural MRI and cognitive outcomes included plasma NfL and GFAP simultaneously along with relevant covariates.

Results:

Higher plasma GFAP was associated with lower white matter volume in both cohorts for temporal (Cohort 1: β = −0.33, p = .002; Cohort 2: β = −0.36, p = .03) and parietal ROIs (Cohort 1: β = −0.31, p = .01; Cohort 2: β = −0.35, p = .04). No consistent findings emerged for gray matter volumes. Higher plasma GFAP was associated with lower executive function scores (Cohort 1: β = −0.38, p = .01; Cohort 2: β = −0.36, p = .007). Plasma NfL was not associated with gray or white matter volumes, or cognition after adjusting for plasma GFAP.

Conclusions:

Plasma GFAP may be more sensitive to white matter and cognitive changes than plasma NfL. Biomarkers reflecting astroglial pathophysiology may capture complex dynamics of aging and neurodegenerative disease.

Type
Research Article
Copyright
Copyright © INS. Published by Cambridge University Press, 2021

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References

REFERENCES

Albert, M. S., DeKosky, S. T., Dickson, D., Dubois, B., Feldman, H. H., Fox, N. C., … Phelps, C. H. (2011). The diagnosis of mild cognitive impairment due to Alzheimer’s disease: recommendations from the National Institute on Aging-Alzheimer’s Association workgroups on diagnostic guidelines for Alzheimer’s disease. Alzheimers Dement, 7(3), 270279. doi: 10.1016/j.jalz.2011.03.008 CrossRefGoogle Scholar
Armstrong, N. M., An, Y., Shin, J. J., Williams, O. A., Doshi, J., Erus, G., … Resnick, S. M. (2020). Associations between cognitive and brain volume changes in cognitively normal older adults. Neuroimage, 223, 117289. doi: 10.1016/j.neuroimage.2020.117289 CrossRefGoogle ScholarPubMed
Ashburner, J. (2007). A fast diffeomorphic image registration algorithm. Neuroimage, 38(1), 95113.Google ScholarPubMed
Ashburner, J., & Friston, K. J. (2005). Unified segmentation. Neuroimage, 26(3), 839851.CrossRefGoogle ScholarPubMed
Asken, B. M., Elahi, F. M., La Joie, R., Strom, A., Staffaroni, A. M., Lindbergh, C. A., … Casaletto, K. B. (2020). Plasma Glial Fibrillary Acidic Protein Levels Differ Along the Spectra of Amyloid Burden and Clinical Disease Stage. J Alzheimers Dis. doi: 10.3233/jad-200755 CrossRefGoogle ScholarPubMed
Bettcher, B. M., Mungas, D., Patel, N., Elofson, J., Dutt, S., Wynn, M., … Kramer, J. H. (2016). Neuroanatomical substrates of executive functions: beyond prefrontal structures. Neuropsychologia, 85, 100109.CrossRefGoogle ScholarPubMed
Bettcher, B. M., Olson, K. E., Carlson, N. E., McConnell, B. V., Boyd, T., Adame, V., … Thaker, A. A. (2021). Astrogliosis and Episodic Memory in Late Life: Higher GFAP is Related to Worse Memory and White Matter Microstructure in Healthy Aging and Alzheimer’s Disease. Neurobiology of aging, Pre-Proof Online Ahead of Print.CrossRefGoogle Scholar
Braun, M., & Iliff, J. J. (2020). The impact of neurovascular, blood-brain barrier, and glymphatic dysfunction in neurodegenerative and metabolic diseases. Int Rev Neurobiol, 154, 413436. doi: 10.1016/bs.irn.2020.02.006 CrossRefGoogle ScholarPubMed
Carter, S. F., Herholz, K., Rosa-Neto, P., Pellerin, L., Nordberg, A., & Zimmer, E. R. (2019). Astrocyte biomarkers in Alzheimer’s disease. Trends in molecular medicine, 25(2), 7795.CrossRefGoogle ScholarPubMed
Casaletto, K., Elahi, F., Fitch, R., Walters, S., Fox, E., Staffaroni, A., … Rojas, J. (2018). A comparison of biofluid cytokine markers across platform technologies: Correspondence or divergence? Cytokine, 111, 481489.CrossRefGoogle ScholarPubMed
Casaletto, K. B., Rentería, M. A., Pa, J., Tom, S. E., Harrati, A., Armstrong, N. M., … Zahodne, L. B. (2020). Late-Life Physical and Cognitive Activities Independently Contribute to Brain and Cognitive Resilience. J Alzheimers Dis, 74(1), 363376. doi: 10.3233/jad-191114 CrossRefGoogle ScholarPubMed
Delis, D. C., Kramer, J. H., Kaplan, E., & Holdnack, J. (2004). Reliability and validity of the Delis-Kaplan Executive Function System: an update. J Int Neuropsychol Soc, 10(2), 301303. doi: 10.1017/s1355617704102191 CrossRefGoogle ScholarPubMed
Desikan, R. S., Ségonne, F., Fischl, B., Quinn, B. T., Dickerson, B. C., Blacker, D., … Hyman, B. T. (2006). An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest. Neuroimage, 31(3), 968980.CrossRefGoogle ScholarPubMed
Elahi, F. M., Casaletto, K. B., La Joie, R., Walters, S. M., Harvey, D., Wolf, A., … Cobigo, Y. (2019). Plasma biomarkers of astrocytic and neuronal dysfunction in early-and late-onset Alzheimer’s disease. Alzheimer’s & Dementia.Google Scholar
Gaetani, L., Blennow, K., Calabresi, P., Di Filippo, M., Parnetti, L., & Zetterberg, H. (2019). Neurofilament light chain as a biomarker in neurological disorders. Journal of Neurology, Neurosurgery & Psychiatry, 90(8), 870881.CrossRefGoogle Scholar
Hu, H., Chen, K. L., Ou, Y. N., Cao, X. P., Chen, S. D., Cui, M., … Yu, J. T. (2019). Neurofilament light chain plasma concentration predicts neurodegeneration and clinical progression in nondemented elderly adults. Aging (Albany NY), 11(17), 69046914. doi: 10.18632/aging.102220 CrossRefGoogle ScholarPubMed
Jessen, N. A., Munk, A. S., Lundgaard, I., & Nedergaard, M. (2015). The Glymphatic System: A Beginner’s Guide. Neurochem Res, 40(12), 25832599. doi: 10.1007/s11064-015-1581-6 CrossRefGoogle ScholarPubMed
Kapasi, A., Yu, L., Boyle, P. A., Barnes, L. L., Bennett, D. A., & Schneider, J. A. (2020). Limbic-predominant age-related TDP-43 encephalopathy, ADNC pathology, and cognitive decline in aging. Neurology, 95(14), e1951-e1962. doi: 10.1212/wnl.0000000000010454 CrossRefGoogle Scholar
Kennedy, K. M., & Raz, N. (2009). Aging white matter and cognition: differential effects of regional variations in diffusion properties on memory, executive functions, and speed. Neuropsychologia, 47(3), 916927. doi: 10.1016/j.neuropsychologia.2009.01.001 CrossRefGoogle ScholarPubMed
Kramer, J. H., Jurik, J., Sharon, J. S., Rankin, K. P., Rosen, H. J., Johnson, J. K., & Miller, B. L. (2003). Distinctive neuropsychological patterns in frontotemporal dementia, semantic dementia, and Alzheimer disease. Cognitive and Behavioral Neurology, 16(4), 211218.CrossRefGoogle ScholarPubMed
Lezak, M. D., Howieson, D. B., Loring, D. W., & Fischer, J. S. (2004). Neuropsychological assessment: Oxford University Press, USA.Google Scholar
Mack, W. J., Freed, D. M., Williams, B. W., & Henderson, V. W. (1992). Boston Naming Test: shortened versions for use in Alzheimer’s disease. J Gerontol, 47(3), P154158. doi: 10.1093/geronj/47.3.p154 CrossRefGoogle ScholarPubMed
Mattsson, N., Andreasson, U., Zetterberg, H., & Blennow, K. (2017). Association of Plasma Neurofilament Light With Neurodegeneration in Patients With Alzheimer Disease. JAMA Neurol, 74(5), 557566. doi: 10.1001/jamaneurol.2016.6117 CrossRefGoogle ScholarPubMed
Mazziotta, J. C., Toga, A. W., Evans, A., Fox, P., & Lancaster, J. (1995). A probabilistic atlas of the human brain: theory and rationale for its development. Neuroimage, 2(2), 89101.CrossRefGoogle ScholarPubMed
McKhann, G. M., Knopman, D. S., Chertkow, H., Hyman, B. T., Jack, C. R. Jr, Kawas, C. H., … Phelps, C. H. (2011). The diagnosis of dementia due to Alzheimer’s disease: recommendations from the National Institute on Aging-Alzheimer’s Association workgroups on diagnostic guidelines for Alzheimer’s disease. Alzheimers Dement, 7(3), 263269. doi: 10.1016/j.jalz.2011.03.005 CrossRefGoogle Scholar
Miyake, A., Friedman, N. P., Emerson, M. J., Witzki, A. H., Howerter, A., & Wager, T. D. (2000). The unity and diversity of executive functions and their contributions to complex “frontal lobe” tasks: A latent variable analysis. Cognitive psychology, 41(1), 49100.Google ScholarPubMed
Moore, E. E., Hohman, T. J., Badami, F. S., Pechman, K. R., Osborn, K. E., Acosta, L. M. Y., … Jefferson, A. L. (2018). Neurofilament relates to white matter microstructure in older adults. Neurobiol Aging, 70, 233241. doi: 10.1016/j.neurobiolaging.2018.06.023 CrossRefGoogle ScholarPubMed
Nolan, A., De Paula Franca Resende, E., Petersen, C., Neylan, K., Spina, S., Huang, E., … Grinberg, L. T. (2019). Astrocytic Tau Deposition Is Frequent in Typical and Atypical Alzheimer Disease Presentations. J Neuropathol Exp Neurol, 78(12), 11121123. doi: 10.1093/jnen/nlz094 CrossRefGoogle ScholarPubMed
Nyberg, L., Lundquist, A., Nordin Adolfsson, A., Andersson, M., Zetterberg, H., Blennow, K., & Adolfsson, R. (2020). Elevated plasma neurofilament light in aging reflects brain white-matter alterations but does not predict cognitive decline or Alzheimer’s disease. Alzheimers Dement (Amst), 12(1), e12050. doi: 10.1002/dad2.12050 Google ScholarPubMed
Oeckl, P., Halbgebauer, S., Anderl Straub, S., Steinacker, P., Huss, A. M., Neugebauer, H., … Kornhuber, J. (2019). Glial Fibrillary Acidic Protein in Serum Is Increased in Alzheimer’s Disease and Correlates with Cognitive Impairment. Journal of Alzheimer’s Disease (Preprint), 17.CrossRefGoogle Scholar
Possin, K. L., Laluz, V. R., Alcantar, O. Z., Miller, B. L., & Kramer, J. H. (2011). Distinct neuroanatomical substrates and cognitive mechanisms of figure copy performance in Alzheimer’s disease and behavioral variant frontotemporal dementia. Neuropsychologia, 49(1), 4348. doi: 10.1016/j.neuropsychologia.2010.10.026 Google ScholarPubMed
Rajan, K. B., Aggarwal, N. T., McAninch, E. A., Weuve, J., Barnes, L. L., Wilson, R. S., … Evans, D. A. (2020). Remote Blood Biomarkers of Longitudinal Cognitive Outcomes in a Population Study. Ann Neurol. doi: 10.1002/ana.25874 CrossRefGoogle ScholarPubMed
Schultz, S. A., Strain, J. F., Adedokun, A., Wang, Q., Preische, O., Kuhle, J., … Gordon, B. A. (2020). Serum neurofilament light chain levels are associated with white matter integrity in autosomal dominant Alzheimer’s disease. Neurobiol Dis, 142, 104960. doi: 10.1016/j.nbd.2020.104960 CrossRefGoogle ScholarPubMed
Sled, J. G., Zijdenbos, A. P., & Evans, A. C. (1998). A nonparametric method for automatic correction of intensity nonuniformity in MRI data. IEEE transactions on medical imaging, 17(1), 8797.CrossRefGoogle ScholarPubMed
Staffaroni, A. M., Asken, B. M., Casaletto, K. B., Fonseca, C., You, M., Rosen, H. J., … Kramer, J. H. (2020). Development and validation of the Uniform Data Set (v3.0) executive function composite score (UDS3-EF). Alzheimers Dement. doi: 10.1002/alz.12214 Google Scholar
Sudre, C. H., Bocchetta, M., Heller, C., Convery, R., Neason, M., Moore, K. M., … Rohrer, J. D. (2019). White matter hyperintensities in progranulin-associated frontotemporal dementia: A longitudinal GENFI study. Neuroimage Clin, 24, 102077. doi: 10.1016/j.nicl.2019.102077 Google ScholarPubMed
Sun, Y., Tan, L., Xu, W., Wang, Z. T., Hu, H., Li, J. Q., … Yu, J. T. (2020). Plasma Neurofilament Light and Longitudinal Progression of White Matter Hyperintensity in Elderly Persons Without Dementia. J Alzheimers Dis, 75(3), 729737. doi: 10.3233/jad-200022 CrossRefGoogle ScholarPubMed
Vatcheva, K. P., Lee, M., McCormick, J. B., & Rahbar, M. H. (2016). Multicollinearity in Regression Analyses Conducted in Epidemiologic Studies. Epidemiology (Sunnyvale), 6(2). doi: 10.4172/2161-1165.1000227 CrossRefGoogle ScholarPubMed
Verberk, I. M. W., Thijssen, E., Koelewijn, J., Mauroo, K., Vanbrabant, J., de Wilde, A., … Teunissen, C. E. (2020). Combination of plasma amyloid beta((1–42/1–40)) and glial fibrillary acidic protein strongly associates with cerebral amyloid pathology. Alzheimers Res Ther, 12(1), 118. doi: 10.1186/s13195-020-00682-7 CrossRefGoogle ScholarPubMed
Wang, S.-Y., Chen, W., Xu, W., Li, J.-Q., Hou, X.-H., Ou, Y.-N., … Tan, L. (2019). Neurofilament Light Chain in Cerebrospinal Fluid and Blood as a Biomarker for Neurodegenerative Diseases: A Systematic Review and Meta-Analysis. Journal of Alzheimer’s Disease (Preprint), 19.Google Scholar
Warrington, E. K., & James, M. (1991). The Visual Object and Space Perception Battery : Bury St. Edmunds: Thames Valley Test Company.Google Scholar
Weintraub, S., Besser, L., Dodge, H. H., Teylan, M., Ferris, S., Goldstein, F. C., … Morris, J. C. (2018). Version 3 of the Alzheimer Disease Centers’ Neuropsychological Test Battery in the Uniform Data Set (UDS). Alzheimer Dis Assoc Disord, 32(1), 1017. doi: 10.1097/wad.0000000000000223 CrossRefGoogle Scholar
Yang, Z., & Wang, K. K. (2015). Glial fibrillary acidic protein: from intermediate filament assembly and gliosis to neurobiomarker. Trends Neurosci, 38(6), 364374. doi: 10.1016/j.tins.2015.04.003 CrossRefGoogle ScholarPubMed
Zetterberg, H. (2016). Neurofilament light: a dynamic cross-disease fluid biomarker for neurodegeneration. Neuron, 91(1), 13.CrossRefGoogle ScholarPubMed
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