Stephanie M Williams1, Carrie Peltz1, Kristine Yaffe1, Philip Schulz1, Michael R Sierks2. 1. From the School for Engineering of Matter, Transport and Energy (S.M.W., P.S., M.R.S.), Arizona State University, Tempe; Northern California Institute for Research and Education (C.P.); San Francisco Veterans Affairs Medical Center (C.P., K.Y.); and Departments of Psychiatry, Neurology, and Epidemiology and Biostatistics (K.Y.), University of California, San Francisco. 2. From the School for Engineering of Matter, Transport and Energy (S.M.W., P.S., M.R.S.), Arizona State University, Tempe; Northern California Institute for Research and Education (C.P.); San Francisco Veterans Affairs Medical Center (C.P., K.Y.); and Departments of Psychiatry, Neurology, and Epidemiology and Biostatistics (K.Y.), University of California, San Francisco. sierks@asu.edu.
Abstract
OBJECTIVE: To utilize a panel of 11 single chain variable fragments (scFvs) that selectively bind disease-related variants of TAR DNA-binding protein (TDP)-43, β-amyloid, tau, and α-synuclein to assess damage following traumatic brain injury (TBI), and determine if the presence of protein variants could account for the increased risk of various neurodegenerative diseases following TBI. METHODS: We utilized the panel of 11 scFvs in a sensitive ELISA format to analyze sera from 43 older veterans, 25 who had experienced at least 1 TBI incident during their lifetime (∼29.4 years after TBI), and 18 controls who did not incur TBI, in a cross-sectional study. RESULTS: Each of the 11 scFvs individually could significantly distinguish between TBI and control samples, though they did not detect each TBI sample. Comparing the levels of all 11 variants, all 25 TBI cases displayed higher reactivity compared to the controls and receiver operating characteristic analysis revealed 100% sensitivity and specificity. Higher total protein variants levels correlated with TBI severity and with loss of consciousness. Oligomeric tau levels distinguished between single and multiple TBI incidents. While all TBI cases were readily selected with the panel, the binding pattern varied from patient to patient, suggesting subgroups that are at increased risk for different neurodegenerative diseases. CONCLUSION: The panel of protein variants-specific scFvs can be used to identify blood-based biomarkers indicative of TBI even 20 years or more after the initial TBI. Being able to identify subgroups of biomarker profiles allows for the possibility of individually targeted treatments.
OBJECTIVE: To utilize a panel of 11 single chain variable fragments (scFvs) that selectively bind disease-related variants of TAR DNA-binding protein (TDP)-43, β-amyloid, tau, and α-synuclein to assess damage following traumatic brain injury (TBI), and determine if the presence of protein variants could account for the increased risk of various neurodegenerative diseases following TBI. METHODS: We utilized the panel of 11 scFvs in a sensitive ELISA format to analyze sera from 43 older veterans, 25 who had experienced at least 1 TBI incident during their lifetime (∼29.4 years after TBI), and 18 controls who did not incur TBI, in a cross-sectional study. RESULTS: Each of the 11 scFvs individually could significantly distinguish between TBI and control samples, though they did not detect each TBI sample. Comparing the levels of all 11 variants, all 25 TBI cases displayed higher reactivity compared to the controls and receiver operating characteristic analysis revealed 100% sensitivity and specificity. Higher total protein variants levels correlated with TBI severity and with loss of consciousness. Oligomeric tau levels distinguished between single and multiple TBI incidents. While all TBI cases were readily selected with the panel, the binding pattern varied from patient to patient, suggesting subgroups that are at increased risk for different neurodegenerative diseases. CONCLUSION: The panel of protein variants-specific scFvs can be used to identify blood-based biomarkers indicative of TBI even 20 years or more after the initial TBI. Being able to identify subgroups of biomarker profiles allows for the possibility of individually targeted treatments.
Authors: Stephanie M Williams; Lalitha Venkataraman; Huilai Tian; Galam Khan; Brent T Harris; Michael R Sierks Journal: J Vis Exp Date: 2015-02-12 Impact factor: 1.355
Authors: Emily L Dennis; David Baron; Brenda Bartnik-Olson; Karen Caeyenberghs; Carrie Esopenko; Frank G Hillary; Kimbra Kenney; Inga K Koerte; Alexander P Lin; Andrew R Mayer; Stefania Mondello; Alexander Olsen; Paul M Thompson; David F Tate; Elisabeth A Wilde Journal: Hum Brain Mapp Date: 2020-06-01 Impact factor: 5.038