Fig 1.
Study volunteer numbers, health characteristics, groupings, and figure inclusions.
The number of patients available for recruitment, number of patients recruited, number of patients utilized, and the identification of the figures where these patients were utilized, are indicated.
Fig 2.
Experimental approach for discriminating sera from control individuals and patients with TBI and post- concussion syndrome (PCS) sequelae.
(A) Flow chart for serum sample handling and mass spectrometry for binary patient/subject group analysis. Distinguishing control samples from TBI “most affected” samples is exhibited. (B) Peak Scoring for LOOCV (leave [one serum sample] out cross validation) procedure to classify mass peaks either “most affect” or control from a “left out” sample, over a narrow range (600–660 m/Z is displayed) of significant group discriminatory mass peaks. The PCV (peak classification value) example is exhibited on peak 635 which is used to classify “left out” peaks as either most affected (peak area above this PCV) or control (peak area at or below this PCV).
Fig 3.
Distinguishing sera from TBI “most affected” patients versus controls using LOOCV and sample randomization analyses.
Male veterans of the United States Iraq and Afghanistan Wars were age-matched selected for these two different groups with similar war theater experiences but either having mild TBI and post-concussion sequelae PTSD and CM and SDep (most affected group) or lack of all these maladies (control group). (A) Serum discrimination of TBI most affected patients (dark circles) from controls (squares) by % of LOOCV classified mass peaks. A cut off value is present (- or + SDs from the most affected or control groups respectively) to determine test metric values (e.g. true positives). (B) Non-serum sample discrimination when the two different sample groups are mixed together randomly followed by the same LOOCV mass peak analysis. An * indicates a female volunteer and no experimental segregation is observed from the male volunteers in this analysis.
Fig 4.
Analysis of blinded sera samples: Comparing patients with TBI+PCS versus controls or TBI alone.
(A)Training set of serum discrimination of TBI most affected patients (triangles) from controls (circles) by % of LOOCV classified mass peaks; correct true positives and true negatives are observed. (B) Non-serum sample discrimination observed when the two different sample groups in panel A are mixed together randomly followed by the same LOOCV mass peak analysis. (C) Assessing the ability of the training set in panel A to correctly discriminate a blinded group of ten samples; 9 out of 10 samples were correctly identified. (D) Discrimination of sera from TBI most affected patients (dashes) from patients with TBI alone (dark squares), and assessment of 6 “left out” group of TBI most affected patients (triangles); 5 out of 6 blinded most affect patients were identified. An * indicates a female volunteer and no experimental segregation is observed from the male volunteers in this analysis.
Fig 5.
Distinguishing sera of TBI patients with and without chronic migraine (CM).
(A) Sera discrimination of patients with TBI alone (diamonds) versus sera from control individuals (dark squares) by % of LOOCV classified mass peak analysis. (B) Sera discrimination of patients with TBI plus CM (triangles) versus sera from control individuals (dark squares). (C) Non-serum sample discrimination observed when the two different sample groups in B are mixed together randomly followed by the same LOOCV mass peak analysis. (D) Sera discrimination of patients with TBI plus CM (dashes) versus TBI alone (dark squares) by % of LOOCV classified mass peak analysis. An * indicates a female volunteer and no experimental segregation is observed from the male volunteers in this analysis.
Table 1.
Patient characteristics.
Fig 6.
Physiological/cellular pathways of serum proteins found to distinguish TBI most affected patients from controls.
Affected physiological/cellular pathways and serum protein assignments from Table 3 (top panel) that were found to distinguish TBI most affected patients from control individuals. The next top 58 proteins for each group (TBI most affected or control) not exhibited in Table 3 were added to the 48 in this table for this analysis. Analysis performed by using Ingenuity Pathway Analysis (IPA) bioinformatics software (Qiagen, Inc.).
Fig 7.
Physiological/cellular pathways of serum proteins found to distinguish TBI with CM from TBI only patients.
Affected physiological/cellular pathways and serum protein assignments from Table 3 (bottom panel) that were found to distinguish patients with TBI alone versus patients with TBI plus CM. The next top 58 proteins for each group (TBI alone and TBI plus CM) not exhibited in Table 3 were added to the 48 in this table for this analysis. Analysis performed by using Ingenuity Pathway Analysis (IPA).
Table 2.
LOOCV serum mass profiling test metrics.
Table 3.
Peptides/proteins identified using LOOCV discriminatory mass peaks in TBI+PTSD+CM+SDep versus controls and TBI+CM versus TBI.