Neuropsychiatric symptoms are common after traumatic brain injury (TBI) and often resolve within 3 months post-injury. However, the degree to which individual patients follow this course is unknown. We characterized trajectories of neuropsychiatric symptoms over 12 months post-TBI. We hypothesized that a substantial proportion of individuals would display trajectories distinct from the group-average course, with some exhibiting less favorable courses.

Participants were level 1 trauma center patients with TBI (n = 1943), orthopedic trauma controls (n = 257), and non-injured friend controls (n = 300). Trajectories of six symptom dimensions (Depression, Anxiety, Fear, Sleep, Physical, and Pain) were identified using growth mixture modeling from 2 weeks to 12 months post-injury.

Depression, Anxiety, Fear, and Physical symptoms displayed three trajectories: Stable-Low (86.2–88.6%), Worsening (5.6–10.9%), and Improving (2.6–6.4%). Among symptomatic trajectories (Worsening, Improving), lower-severity TBI was associated with higher prevalence of elevated symptoms at 2 weeks that steadily resolved over 12 months compared to all other groups, whereas higher-severity TBI was associated with higher prevalence of symptoms that gradually worsened from 3–12 months. Sleep and Pain displayed more variable recovery courses, and the most common trajectory entailed an average level of problems that remained stable over time (Stable-Average; 46.7–82.6%). Symptomatic Sleep and Pain trajectories (Stable-Average, Improving) were more common in traumatically injured groups.

Findings illustrate the nature and rates of distinct neuropsychiatric symptom trajectories and their relationship to traumatic injuries. Providers may use these results as a referent for gauging typical v. atypical recovery in the first 12 months post-injury.

Blood-based biomarkers represent a scalable and accessible approach for the detection and monitoring of Alzheimer’s disease (AD). Plasma phosphorylated tau (p-tau) and neurofilament light (NfL) are validated biomarkers for the detection of tau and neurodegenerative brain changes in AD, respectively. There is now emphasis to expand beyond these markers to detect and provide insight into the pathophysiological processes of AD. To this end, a reactive astrocytic marker, namely plasma glial fibrillary acidic protein (GFAP), has been of interest. Yet, little is known about the relationship between plasma GFAP and AD. Here, we examined the association between plasma GFAP, diagnostic status, and neuropsychological test performance. Diagnostic accuracy of plasma GFAP was compared with plasma measures of p-tau181 and NfL.

This sample included 567 participants from the Boston University (BU) Alzheimer’s Disease Research Center (ADRC) Longitudinal Clinical Core Registry, including individuals with normal cognition (n=234), mild cognitive impairment (MCI) (n=180), and AD dementia (n=153). The sample included all participants who had a blood draw. Participants completed a comprehensive neuropsychological battery (sample sizes across tests varied due to missingness). Diagnoses were adjudicated during multidisciplinary diagnostic consensus conferences. Plasma samples were analyzed using the Simoa platform. Binary logistic regression analyses tested the association between GFAP levels and diagnostic status (i.e., cognitively impaired due to AD versus unimpaired), controlling for age, sex, race, education, and APOE e4 status. Area under the curve (AUC) statistics from receiver operating characteristics (ROC) using predicted probabilities from binary logistic regression examined the ability of plasma GFAP to discriminate diagnostic groups compared with plasma p-tau181 and NfL. Linear regression models tested the association between plasma GFAP and neuropsychological test performance, accounting for the above covariates.

The mean (SD) age of the sample was 74.34 (7.54), 319 (56.3%) were female, 75 (13.2%) were Black, and 223 (39.3%) were APOE e4 carriers. Higher GFAP concentrations were associated with increased odds for having cognitive impairment (GFAP z-score transformed: OR=2.233, 95% CI [1.609, 3.099], p<0.001; non-z-transformed: OR=1.004, 95% CI [1.002, 1.006], p<0.001). ROC analyses, comprising of GFAP and the above covariates, showed plasma GFAP discriminated the cognitively impaired from unimpaired (AUC=0.75) and was similar, but slightly superior, to plasma p-tau181 (AUC=0.74) and plasma NfL (AUC=0.74). A joint panel of the plasma markers had greatest discrimination accuracy (AUC=0.76). Linear regression analyses showed that higher GFAP levels were associated with worse performance on neuropsychological tests assessing global cognition, attention, executive functioning, episodic memory, and language abilities (ps<0.001) as well as higher CDR Sum of Boxes (p<0.001).

Higher plasma GFAP levels differentiated participants with cognitive impairment from those with normal cognition and were associated with worse performance on all neuropsychological tests assessed. GFAP had similar accuracy in detecting those with cognitive impairment compared with p-tau181 and NfL, however, a panel of all three biomarkers was optimal. These results support the utility of plasma GFAP in AD detection and suggest the pathological processes it represents might play an integral role in the pathogenesis of AD.

Parkinsonism and Parkinson's disease (PD) have been described as consequences of repetitive head impacts (RHI) from boxing, since 1928. Autopsy studies have shown that RHI from other contact sports can also increase risk for neurodegenerative diseases, including chronic traumatic encephalopathy (CTE) and Lewy bodies. In vivo research on the relationship between American football play and PD is scarce, with small samples, and equivocal findings. This study leveraged the Fox Insight study to evaluate the association between American football and parkinsonism and/or PD Diagnosis and related clinical outcomes.

Fox Insight is an online study of people with and without PD who are 18+ years (>50,000 enrolled). Participants complete online questionnaires on motor function, cognitive function, and general health behaviors. Participants self-reported whether they "currently have a diagnosis of Parkinson's disease, or parkinsonism, by a physician or other health care professional." In November 2020, the Boston University Head Impact Exposure Assessment was launched in Fox Insight for large-scale data collection on exposure to RHI from contact sports and other sources. Data used in this abstract were obtained from the Fox Insight database https://foxinsight-info.michaeljfox.org/insight/explore/insight.jsp on 01/06/2022. The sample includes 2018 men who endorsed playing an organized sport. Because only 1.6% of football players were women, analyses are limited to men. Responses to questions regarding history of participation in organized football were examined. Other contact and/or non-contact sports served as the referent group. Outcomes included PD status (absence/presence of parkinsonism or PD) and Penn Parkinson's Daily Activities Questionnaire-15 (PDAQ-15) for assessment of cognitive symptoms. Binary logistic regression tested associations between history and years of football play with PD status, controlling for age, education, current heart disease or diabetes, and family history of PD. Linear regressions, controlling for these variables, were used for the PDAQ-15.

Of the 2018 men (mean age=67.67, SD=9.84; 10, 0.5% Black), 788 (39%) played football (mean years of play=4.29, SD=2.88), including 122 (16.3%) who played youth football, 494 (66.0%) played high school, 128 (17.1%) played college football, and 5 (0.7%) played at the semi-professional or professional level. 1738 (86.1%) reported being diagnosed with parkinsonism/PD, and 707 of these were football players (40.7%). History of playing any level of football was associated with increased odds of having a reported parkinsonism or PD diagnosis (OR=1.52, 95% CI=1.14-2.03, p=0.004). The OR remained similar among those age <69 (sample median age) (OR=1.45, 95% CI=0.97-2.17, p=0.07) and 69+ (OR=1.45, 95% CI=0.95-2.22, p=0.09). Among the football players, there was not a significant association between years of play and PD status (OR=1.09, 95% CI=1.00-1.20, p=0.063). History of football play was not associated with PDAQ-15 scores (n=1980) (beta=-0.78, 95% CI=-1.59-0.03, p=0.059) among the entire sample.

Among 2018 men from a data set enriched for PD, playing organized football was associated with increased odds of having a reported parkinsonism/PD diagnosis. Next steps include examination of the contribution of traumatic brain injury and other sources of RHI (e.g., soccer, military service).

Former professional American football players have a high relative risk for neurodegenerative diseases like chronic traumatic encephalopathy (CTE). Interpreting low cognitive test scores in this population occasionally is complicated by performance on validity testing. Neuroimaging biomarkers may help inform whether a neurodegenerative disease is present in these situations. We report three cases of retired professional American football players who completed comprehensive neuropsychological testing, but “failed” performance validity tests, and underwent multimodal neuroimaging (structural MRI, Aß-PET, and tau-PET).

Three cases were identified from the Focused Neuroimaging for the Neurodegenerative Disease Chronic Traumatic Encephalopathy (FIND-CTE) study, an ongoing multimodal imaging study of retired National Football League players with complaints of progressive cognitive decline conducted at Boston University and the UCSF Memory and Aging Center. Participants were relatively young (age range 55-65), had 16 or more years of education, and two identified as Black/African American. Raw neuropsychological test scores were converted to demographically-adjusted z-scores. Testing included standalone (Test of Memory Malingering; TOMM) and embedded (reliable digit span, RDS) performance validity measures. Validity cutoffs were TOMM Trial 2 < 45 and RDS < 7. Structural MRIs were interpreted by trained neurologists. Aß-PET with Florbetapir was used to quantify cortical Aß deposition as global Centiloids (0 = mean cortical signal for a young, cognitively normal, Aß negative individual in their 20s, 100 = mean cortical signal for a patient with mild-to-moderate Alzheimer’s disease dementia). Tau-PET was performed with MK-6240 and first quantified as standardized uptake value ratio (SUVR) map. The SUVR map was then converted to a w-score map representing signal intensity relative to a sample of demographically-matched healthy controls.

All performed in the average range on a word reading-based estimate of premorbid intellect. Contribution of Alzheimer’s disease pathology was ruled out in each case based on Centiloids quantifications < 0. All cases scored below cutoff on TOMM Trial 2 (Case #1=43, Case #2=42, Case #3=19) and Case #3 also scored well below RDS cutoff (2). Each case had multiple cognitive scores below expectations (z < -2.0) most consistently in memory, executive function, processing speed domains. For Case #1, MRI revealed mild atrophy in dorsal fronto-parietal and medial temporal lobe (MTL) regions and mild periventricular white matter disease. Tau-PET showed MTL tau burden modestly elevated relative to controls (regional w-score=0.59, 72nd%ile). For Case #2, MRI revealed cortical atrophy, mild hippocampal atrophy, and a microhemorrhage, with no evidence of meaningful tau-PET signal. For Case #3, MRI showed cortical atrophy and severe white matter disease, and tau-PET revealed significantly elevated MTL tau burden relative to controls (w-score=1.90, 97th%ile) as well as focal high signal in the dorsal frontal lobe (overall frontal region w-score=0.64, 74th%ile).

Low scores on performance validity tests complicate the interpretation of the severity of cognitive deficits, but do not negate the presence of true cognitive impairment or an underlying neurodegenerative disease. In the rapidly developing era of biomarkers, neuroimaging tools can supplement neuropsychological testing to help inform whether cognitive or behavioral changes are related to a neurodegenerative disease.

Blood-based biomarkers offer a more feasible alternative to Alzheimer’s disease (AD) detection, management, and study of disease mechanisms than current in vivo measures. Given their novelty, these plasma biomarkers must be assessed against postmortem neuropathological outcomes for validation. Research has shown utility in plasma markers of the proposed AT(N) framework, however recent studies have stressed the importance of expanding this framework to include other pathways. There is promising data supporting the usefulness of plasma glial fibrillary acidic protein (GFAP) in AD, but GFAP-to-autopsy studies are limited. Here, we tested the association between plasma GFAP and AD-related neuropathological outcomes in participants from the Boston University (BU) Alzheimer’s Disease Research Center (ADRC).

This sample included 45 participants from the BU ADRC who had a plasma sample within 5 years of death and donated their brain for neuropathological examination. Most recent plasma samples were analyzed using the Simoa platform. Neuropathological examinations followed the National Alzheimer’s Coordinating Center procedures and diagnostic criteria. The NIA-Reagan Institute criteria were used for the neuropathological diagnosis of AD. Measures of GFAP were log-transformed. Binary logistic regression analyses tested the association between GFAP and autopsy-confirmed AD status, as well as with semi-quantitative ratings of regional atrophy (none/mild versus moderate/severe) using binary logistic regression. Ordinal logistic regression analyses tested the association between plasma GFAP and Braak stage and CERAD neuritic plaque score. Area under the curve (AUC) statistics from receiver operating characteristics (ROC) using predicted probabilities from binary logistic regression examined the ability of plasma GFAP to discriminate autopsy-confirmed AD status. All analyses controlled for sex, age at death, years between last blood draw and death, and APOE e4 status.

Of the 45 brain donors, 29 (64.4%) had autopsy-confirmed AD. The mean (SD) age of the sample at the time of blood draw was 80.76 (8.58) and there were 2.80 (1.16) years between the last blood draw and death. The sample included 20 (44.4%) females, 41 (91.1%) were White, and 20 (44.4%) were APOE e4 carriers. Higher GFAP concentrations were associated with increased odds for having autopsy-confirmed AD (OR=14.12, 95% CI [2.00, 99.88], p=0.008). ROC analysis showed plasma GFAP accurately discriminated those with and without autopsy-confirmed AD on its own (AUC=0.75) and strengthened as the above covariates were added to the model (AUC=0.81). Increases in GFAP levels corresponded to increases in Braak stage (OR=2.39, 95% CI [0.71-4.07], p=0.005), but not CERAD ratings (OR=1.24, 95% CI [0.004, 2.49], p=0.051). Higher GFAP levels were associated with greater temporal lobe atrophy (OR=10.27, 95% CI [1.53,69.15], p=0.017), but this was not observed with any other regions.

The current results show that antemortem plasma GFAP is associated with non-specific AD neuropathological changes at autopsy. Plasma GFAP could be a useful and practical biomarker for assisting in the detection of AD-related changes, as well as for study of disease mechanisms.