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Blood Biomarkers Relate to Cognitive Performance Years after Traumatic Brain Injury in Service Members and Veterans

Published online by Cambridge University Press:  09 November 2020

Sara M. Lippa Open the ORCID record for Sara M. Lippa [Opens in a new window] ,
Jessica Gill ,
Tracey A. Brickell ,
Louis M. French  and
Rael T. Lange
Sara M. Lippa*
Affiliation:
National Intrepid Center of Excellence, Walter Reed National Military Medical Center, Bethesda, MD, USA
Jessica Gill
Affiliation:
National Institutes of Health, National Institute of Nursing Research, Bethesda, MD, USA
Tracey A. Brickell
Affiliation:
National Intrepid Center of Excellence, Walter Reed National Military Medical Center, Bethesda, MD, USA Defense and Veterans Brain Injury Center, Walter Reed National Military Medical Center, Bethesda, MD, USA Uniformed Services University of the Health Sciences, Bethesda, MD, USA Defense and Veterans Brain Injury Center, Falls Church, VA, USA
Louis M. French
Affiliation:
National Intrepid Center of Excellence, Walter Reed National Military Medical Center, Bethesda, MD, USA Defense and Veterans Brain Injury Center, Walter Reed National Military Medical Center, Bethesda, MD, USA Uniformed Services University of the Health Sciences, Bethesda, MD, USA
Rael T. Lange
Affiliation:
National Intrepid Center of Excellence, Walter Reed National Military Medical Center, Bethesda, MD, USA Defense and Veterans Brain Injury Center, Walter Reed National Military Medical Center, Bethesda, MD, USA Defense and Veterans Brain Injury Center, Falls Church, VA, USA Department of Psychiatry, University of British Columbia, Vancouver, BC, Canada
*
*Correspondence and reprint requests to: Sara M. Lippa, Ph.D., National Intrepid Center of Excellence, Walter Reed National Military Medical Center, Room 1121, Building 51, 8901 Wisconsin Avenue, Bethesda, MD 20814, USA. Tel.: +1 301 319 3671. Email: [email protected]
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Abstract

Objective:

This study examines the relationship of serum total tau, neurofilament light (NFL), ubiquitin carboxyl-terminal hydrolase L1 (UCH-L1), and glial fibrillary acidic protein (GFAP) with neurocognitive performance in service members and veterans with a history of traumatic brain injury (TBI).

Method:

Service members (n = 488) with a history of uncomplicated mild (n = 172), complicated mild, moderate, severe, or penetrating TBI (sTBI; n = 126), injured controls (n = 116), and non-injured controls (n = 74) prospectively enrolled from Military Treatment Facilities. Participants completed a blood draw and neuropsychological assessment a year or more post-injury. Six neuropsychological composite scores and presence/absence of mild neurocognitive disorder (MNCD) were evaluated. Within each group, stepwise hierarchical regression models were conducted.

Results:

Within the sTBI group, increased serum UCH-L1 was related to worse immediate memory and delayed memory (R2Δ = .065–.084, ps < .05) performance, while increased GFAP was related to worse perceptual reasoning (R2Δ = .030, p = .036). Unexpectedly, within injured controls, UCH-L1 and GFAP were inversely related to working memory (R2Δ = .052–.071, ps < .05), and NFL was related to executive functioning (R2Δ = .039, p = .021) and MNCD (Exp(B) = 1.119, p = .029).

Conclusions:

Results suggest GFAP and UCH-L1 could play a role in predicting poor cognitive outcome following complicated mild and more severe TBI. Further investigation of blood biomarkers and cognition is warranted.

Keywords

UCH-L1GFAPTauNFLMilitaryMild neurocognitive disorder
Type
Brief Communication
Information
Journal of the International Neuropsychological Society , Volume 27 , Issue 5 , May 2021 , pp. 508 - 514
Copyright
Copyright © INS. Published by Cambridge University Press, 2020

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References

REFERENCES

Belanger, H.G., Tate, D.F., & Vanderploeg, R.D. (2018). Concussion and mild traumatic brain injury. In Morgan, J.E. & Ricker, J.H. (Eds.), Textbook of clinical neuropsychology (2nd ed., pp. 411–448). New York: Routledge.Google Scholar
Ben-Porath, Y.S. & Tellegen, A. (2011). MMPI-2-RF (Minnesota Multiphasic Personality Inventory-2 Restructured Form): Manual for administration, scoring, and interpretation.. Minneapolis, MN: University of Minnesota Press.Google Scholar
Blanchard, E.B., Jones-Alexander, J., Buckley, T.C., & Forneris, C.A. (1996). Psychometric properties of the PTSD checklist (PCL). Behaviour Research and Therapy, 34(8), 669–673.CrossRefGoogle Scholar
Dadas, A., Washington, J., Diaz-Arrastia, R., & Janigro, D. (2018). Biomarkers in traumatic brain injury (TBI): A review. Neuropsychiatric Disease and Treatment, 14, 2989–3000. doi: 10.2147/NDT.S125620 CrossRefGoogle ScholarPubMed
Defense and Veterans Brain Injury Center (DVBIC). (2019). Retrieved from http://www.dvbic.org/TBI-Numbers.aspx Google Scholar
Delis, D.C., Kaplan, E., & Kramer, J.H. (2001). Delis-Kaplan Executive Functioning System (D-KEFS): Examiner’s Manual. San Antonio, TX: The Psychological Corporation.Google Scholar
Delis, D.C., Kramer, J.H., Kaplan, E., & Ober, B.A. (2000). California Verbal Learning Test (2nd ed.). San Antonio, TX: Psychological Corporation.Google Scholar
Gan, Z.S., Stein, S.C., Swanson, R., Guan, S., Garcia, L., Mehta, D., & Smith, D.H. (2019). Blood biomarkers for traumatic brain injury: A quantitative assessment of diagnostic and prognostic accuracy. Frontiers in Neurology, 10, 446. doi: 10.3389/fneur.2019.00446 CrossRefGoogle ScholarPubMed
Green, P. (2004). Green’s Medical Symptom Validity Test (MSVT) for Microsoft Windows: User’s Manual. Edmonton: Green’s Publishing.Google Scholar
Guglielmotto, M., Monteleone, D., Vasciaveo, V., Repetto, I.E., Manassero, G., Tabaton, M., & Tamagno, E. (2017). The decrease of Uch-L1 activity is a common mechanism responsible for a beta 42 accumulation in Alzheimer’s and Vascular disease. Frontiers in Aging Neuroscience, 9, 320. doi: 10.3389/fnagi.2017.00320 CrossRefGoogle ScholarPubMed
Heaton, R.K., Miller, S.W., Taylor, M.J., & Grant, I. (2004). Revised Comprehensive Norms for an Expanded Halstead Reitan Battery: Demographically Adjusted Neuropsychological Norms for African American and Caucasian Adults. Lutz, FL: Psychological Assessment Resources, Inc.Google Scholar
Keane, T., Fairbank, J., Caddell, J., Zimering, R., Taylor, K., & Mora, C. (1989). The Combat Exposure Scale (CES). Available from http://www.ptsd.va.gov Google Scholar
Lippa, S.M., French, L.M., Bell, R.S., Brickell, T.A., & Lange, R.T. (2020). United States Military Service members demonstrate substantial and heterogeneous long-term neuropsychological dysfunction after moderate, severe, and penetrating traumatic brain injury. Journal of Neurotrauma, 37(4), 608–617. doi: 10.1089/neu.2019.6696 CrossRefGoogle ScholarPubMed
Lippa, S.M., Yeh, P.H., Gill, J., French, L.M., Brickell, T.A., & Lange, R.T. (2019). Plasma tau and amyloid are not reliably related to injury characteristics, neuropsychological performance, or white matter integrity in service members with a history of traumatic brain injury. Journal of Neurotrauma, 36(14), 2190–2199. doi: 10.1089/neu.2018.6269 CrossRefGoogle ScholarPubMed
Oeckl, P., Halbgebauer, S., Anderl-Straub, S., Steinacker, P., Huss, A.M., Neugebauer, H., … Consortium for Frontotemporal Lobar Degeneration German. (2019). Glial fibrillary acidic protein in serum is increased in Alzheimer’s disease and correlates with cognitive impairment. Journal of Alzheimers disease, 67(2), 481–488. doi: 10.3233/JAD-180325 CrossRefGoogle ScholarPubMed
Pearson. (2009). Advanced Clinical Solutions for Use with WAIS-IV and WMS-IV. San Antonio, TX: Pearson Education.Google Scholar
Reitan, R.M. (1958). Validity of the Trail Making Test as an indicator of organic brain damage. Perceptual and Motor Skills, 8, 271–276.CrossRefGoogle Scholar
Tombaugh, T.N. (1996). TOMM: Test of Memory Malingering. Tonawanda, NY: Multi-Health Systems.Google Scholar
Wang, K.K., Yang, Z., Sarkis, G., Torres, I., & Raghavan, V. (2017). Ubiquitin C-terminal hydrolase-L1 (UCH-L1) as a therapeutic and diagnostic target in neurodegeneration, neurotrauma and neuro-injuries. Expert Opinion on Therapeutic Targets, 21(6), 627–638. doi: 10.1080/14728222.2017.1321635 CrossRefGoogle ScholarPubMed
Wang, K.K., Yang, Z., Zhu, T., Shi, Y., Rubenstein, R., Tyndall, J.A., & Manley, G.T. (2018). An update on diagnostic and prognostic biomarkers for traumatic brain injury. Expert Review of Molecular Diagnostics, 18(2), 165–180. doi: 10.1080/14737159.2018.1428089 CrossRefGoogle ScholarPubMed
Wechsler, D. (2008). Wechsler Adult Intelligence Scale-Fourth Edition: Technical and interpretive manual. San Antonio, TX: Pearson.Google Scholar
Wechsler, D. (2009). Wechsler Memory Scale-Fourth Edition: Technical and Interpretive Manual. San Antonio, TX: Pearson.Google Scholar