Amyloid, Tau, and APOE in Alzheimer's Disease: Impact on White Matter Tracts.

Alzheimer's disease (AD) is characterized by cognitive decline and memory loss due to the abnormal accumulation of amyloid-beta (Aß) plaques and tau tangles in the brain; its onset and progression also depend on genetic factors such as the apolipoprotein E (APOE) genotype. Understanding how these factors affect the brain's neural pathways is important for early diagnostics and interventions. Tractometry is an advanced technique for 3D quantitative assessment of white matter tracts, localizing microstructural abnormalities in diseased populations in vivo. In this work, we applied BUAN (Bundle Analytics) tractometry to 3D diffusion MRI data from 730 participants in ADNI3 (phase 3 of the Alzheimer's Disease Neuroimaging Initiative; age range: 55-95 years, 349M/381F, 214 with mild cognitive impairment, 69 with AD, and 447 cognitively healthy controls). Using along-tract statistical analysis, we assessed the localized impact of amyloid, tau, and APOE genetic variants on the brain's neural pathways. BUAN quantifies microstructural properties of white matter tracts, supporting along-tract statistical analyses that identify factors associated with brain microstructure. We visualize the 3D profile of white matter tract associations with tau and amyloid burden in Alzheimer's disease; strong associations near the cortex may support models of disease propagation along neural pathways. Relative to the neutral genotype, APOE ϵ3/ϵ3, carriers of the AD-risk conferring APOE ϵ4 genotype show microstructural abnormalities, while carriers of the protective ϵ2 genotype also show subtle differences. Of all the microstructural metrics, mean diffusivity (MD) generally shows the strongest associations with AD pathology, followed by axial diffusivity (AxD) and radial diffusivity (RD), while fractional anisotropy (FA) is typically the least sensitive metric. Along-tract microstructural metrics are sensitive to tau and amyloid accumulation, showing the potential of diffusion MRI to track AD pathology and map its impact on neural pathways.

Sex differences in body composition and shock attenuation during running.

Running-related impact shock is absorbed via biological tissue deformation. Given known sex differences in body composition, shock attenuation may also differ between sexes thereby influencing sex-specific running-related injury risk. This study examined sex differences in body composition and shock attenuation during running. Seventeen female (mean ± 1SD age: 34.7 ± 16.1) and twenty-one male runners (age: 29.0 ± 13.8) ran overground as inertial measurement units with triaxial accelerometers measured impact shock at the distal tibia and low-back. Frequency-domain axial and resultant shock attenuation were calculated between the low-back relative to the tibia using a transfer function of the power spectral density within 9-20, 21-35, and 36-50 Hz. Bone mineral density and content, fat and lean mass were measured in the lower extremity and pelvis/gynoid regions using dual x-ray absorptiometry. The association between sex and shock attenuation was tested using age-adjusted linear regression models, adjusted and unadjusted for body composition as a post-hoc analysis (α = 0.05). Body composition variables normalized to body mass were compared between sexes using independent samples t-tests (α = 0.05). Body composition differed between sexes (p-range: <0.001-0.01, Cohen's d range: 0.17-2.41). Before adjusting for body composition, sex was not significantly associated with axial or resultant shock attenuation (p > 0.05), but adjusting for select body composition variables like lower extremity lean and bone mass revealed greater attenuation in females than males (ß-range: -124.76 to -46.42, negative indicates greater attenuation; p-range = 0.004-0.04). Sex may not influence shock attenuation during running, but body composition must be accounted for to better understand this association and consequently sex-specific tissue capacities relative to applied loads.

Extracting actigraphy-based walking features with structured functional principal components.

Objective.We extract walking features from raw accelerometry data while accounting for varying cadence and commonality of features among subjects. Walking is the most performed type of physical activity. Thus, we explore if an individual's physical health is related to these walking features.Approach.We use data collected using ActiGraph GT3X+ devices (sampling rate = 80 Hz) as part of the developmental epidemiologic cohort study,I= 48, age =78.7±5.7years, 45.8% women. We apply structured functional principal component analysis (SFPCA) to extract features from walking signals on both, the subject-specific and the subject-spectrum-specific level of a fast-paced 400 m walk, an indicator of aerobic fitness in older adults. We also use the subject-specific level feature scores to study their associations with age and physical performance measures. Specifically, we transform the raw data into the frequency domain by applying local Fast Fourier Transform to obtain the walking spectra. SFPCA decomposes these spectra into easily interpretable walking features expressed as cadence and acceleration, which can be related to physical performance.Main results.We found that five subject-specific and 19 subject-spectrum-specific level features explained more than 85% of their respective level variation, thus significantly reducing the complexity of the data. Our results show that 54% of the total data variation arises at the subject-specific and 46% at the subject-spectrum-specific level. Moreover, we found that higher acceleration magnitude at the cadence was associated with younger age, lower BMI, faster average cadence and higher short physical performance battery scores. Lower acceleration magnitude at the cadence and higher acceleration magnitude at cadence multiples 2.5 and 3.5 are related to older age and higher blood pressure.Significance.SFPCA extracted subject-specific level empirical walking features which were meaningfully associated with several health indicators and younger age. Thus, an individual's walking pattern could shed light on subclinical stages of somatic diseases.

Tangent space functional reconfigurations in individuals at risk for alcohol use disorder.

Human brain function dynamically adjusts to ever-changing stimuli from the external environment. Studies characterizing brain functional reconfiguration are nevertheless scarce. Here we present a principled mathematical framework to quantify brain functional reconfiguration when engaging and disengaging from a stop signal task (SST). We apply tangent space projection (a Riemannian geometry mapping technique) to transform functional connectomes (FCs) and quantify functional reconfiguration using the correlation distance of the resulting tangent-FCs. Our goal was to compare functional reconfigurations in individuals at risk for alcohol use disorder (AUD). We hypothesized that functional reconfigurations when transitioning in/from a task would be influenced by family history of alcohol use disorder (FHA) and other AUD risk factors. Multilinear regression model results showed that engaging and disengaging functional reconfiguration were driven by different AUD risk factors. Functional reconfiguration when engaging in the SST was negatively associated with recent drinking. When disengaging from the SST, however, functional reconfiguration was negatively associated with FHA. In both models, several other factors contributed to the explanation of functional reconfiguration. This study demonstrates that tangent-FCs can characterize task-induced functional reconfiguration, and that it is related to AUD risk.

Research Letter: Relationship of Blood Biomarkers of Inflammation With Acute Concussion Symptoms and Recovery in the CARE Consortium.

OBJECTIVE: Determine the association of inflammatory biomarkers with clinical measures and recovery in participants with concussion. SETTING: Multicenter study in National Collegiate Athletic Association member institutions including military service academies. PARTICIPANTS: Four hundred twenty-two participants with acute concussion. DESIGN: Clinical visits and blood draws were completed preinjury and at multiple visits postconcussion (0-12 hours, 12-36 hours, and 36-60 hours postinjury). Clinical measures included Sport Concussion Assessment Tool (SCAT) symptom severity, Balance Error Scoring System, Standardized Assessment of Concussion (SAC), Brief Symptom Inventory-18 (BSI-18) scores, time to initiation of graduated return-to-play (RTP) protocol, and time to RTP. Interleukin (IL)-6, IL-10, IL-8, IL-1 receptor antagonist (RA), tumor necrosis factor (TNF), c-reactive protein, and vascular endothelial growth factor (VEGF) were measured in serum. Prespecified analyses focused on IL-6 and IL-1RA at 0 to 12 hours; exploratory analyses were conducted with false discovery rate correction. RESULTS: For prespecified analyses, IL-1RA at 0 to 12 hours in female participants was positively associated with more errors on the SAC (B(standard error, SE) = 0.58(0.27), P < .05) and worse SCAT symptom severity (B(SE) = 0.96(0.44), P < .05). For exploratory analyses, higher levels of IL-1RA at 12 to 36 hours were associated with higher global (B(SE) = 0.55(0.14), q < 0.01), depression (B(SE) = 0.45(0.10), q < 0.005), and somatization scores on the BSI (B(SE) = 0.46(0.12), q < 0.01) in participants with concussion; Higher TNF at 12 to 36 hours was associated with fewer errors on the SAC (B(SE) = - 0.46(0.14), q < 0.05). Subanalyses showed similar results for male participants and participants who were athletes. No associations were discovered in nonathlete cadets. Higher IL-8 at 0 to 12 hours was associated with slower RTP in female participants (OR = 14.47; 95% confidence interval, 2.96-70.66, q < 0.05); no other associations with recovery were observed. CONCLUSIONS: Peripheral inflammatory markers are associated with clinical symptoms following concussion and potentially represent one mechanism for psychological symptoms observed postinjury. Current results do not provide strong support for a potential prognostic role for these markers.

Are Gait Patterns during In-Lab Running Representative of Gait Patterns during Real-World Training? An Experimental Study.

Biomechanical assessments of running typically take place inside motion capture laboratories. However, it is unclear whether data from these in-lab gait assessments are representative of gait during real-world running. This study sought to test how well real-world gait patterns are represented by in-lab gait data in two cohorts of runners equipped with consumer-grade wearable sensors measuring speed, step length, vertical oscillation, stance time, and leg stiffness. Cohort 1 (N = 49) completed an in-lab treadmill run plus five real-world runs of self-selected distances on self-selected courses. Cohort 2 (N = 19) completed a 2.4 km outdoor run on a known course plus five real-world runs of self-selected distances on self-selected courses. The degree to which in-lab gait reflected real-world gait was quantified using univariate overlap and multivariate depth overlap statistics, both for all real-world running and for real-world running on flat, straight segments only. When comparing in-lab and real-world data from the same subject, univariate overlap ranged from 65.7% (leg stiffness) to 95.2% (speed). When considering all gait metrics together, only 32.5% of real-world data were well-represented by in-lab data from the same subject. Pooling in-lab gait data across multiple subjects led to greater distributional overlap between in-lab and real-world data (depth overlap 89.3-90.3%) due to the broader variability in gait seen across (as opposed to within) subjects. Stratifying real-world running to only include flat, straight segments did not meaningfully increase the overlap between in-lab and real-world running (changes of <1%). Individual gait patterns during real-world running, as characterized by consumer-grade wearable sensors, are not well-represented by the same runner's in-lab data. Researchers and clinicians should consider "borrowing" information from a pool of many runners to predict individual gait behavior when using biomechanical data to make clinical or sports performance decisions.

Profile of brief symptom inventory-18 (BSI-18) scores in collegiate athletes: A CARE Consortium study.

Objective: The goal of this study was to characterize normative scores for the Brief Symptom Inventory (BSI-18) in collegiate athletes to inform decision making about the need for psychological health services in this group. Methods: Collegiate student-athletes (N = 20,034) from 25 universities completed the BSI-18 at their preseason baseline assessment. A subgroup (n = 5,387) underwent multiple baseline assessments. Global Severity Index (GSI) scores were compared to community norms and across multiple timepoints. Results: Collegiate athletes reported significantly lower GSI scores than published community norms (p<.001). Published GSI threshold scores for "caseness", identified only 2 per 100 athletes (≥ the 98th percentile) as needing further evaluation. Using a GSI score ≥ than the cohort's 90th percentile, 11.4 per 100 athletes would merit additional evaluation. These individuals were more likely to report a history of psychiatric diagnosis (Odds ratio [95% CI] 2.745 [2.480, 3.039]), as well as ≥ 2 prior concussions (p<.001). GSI scores were not highly correlated across timepoints. Suicidal ideation was rare (n = 230; 1.15%). Conclusions: For collegiate student-athletes, published BSI-18 threshold scores identify only extreme outliers who might benefit from additional behavioral health evaluation. Alternatively, use of threshold scores ≥ the 90th percentile identifies a more realistic 11.4% of the population, with higher likelihood of prior concussion and/or psychiatric disorders.

Association of Blood Biomarkers of Inflammation With Acute Concussion in Collegiate Athletes and Military Service Academy Cadets.

BACKGROUND AND OBJECTIVES: The objective was to characterize the acute effects of concussion (a subset of mild traumatic brain injury) on serum interleukin (IL)-6 and IL-1 receptor antagonist (RA) and 5 additional inflammatory markers in athletes and military service academy members from the Concussion Assessment, Research, and Education Consortium and to determine whether these markers aid in discrimination of concussed participants from controls. METHODS: Athletes and cadets with concussion and matched controls provided blood at baseline and postinjury visits between January 2015 and March 2020. Linear models investigated changes in inflammatory markers measured using Meso Scale Discovery assays across time points (baseline and 0-12, 12-36, 36-60 hours). Subanalyses were conducted in participants split by sex and injury population. Logistic regression analyses tested whether acute levels of IL-6 and IL-1RA improved discrimination of concussed participants relative to brain injury markers (glial fibrillary acidic protein, tau, neurofilament light, ubiquitin c-terminal hydrolase-L1) or clinical data (Sport Concussion Assessment Tool-Third Edition, Standardized Assessment of Concussion, Balance Error Scoring System). RESULTS: Participants with concussion (total, N = 422) had elevated IL-6 and IL-1RA at 0-12 hours vs controls (n = 345; IL-6: mean difference [MD] (standard error) = 0.701 (0.091), p < 0.0001; IL-1RA: MD = 0.283 (0.042), p < 0.0001) and relative to baseline (IL-6: MD = 0.656 (0.078), p < 0.0001; IL-1RA: MD = 0.242 (0.038), p < 0.0001), 12-36 hours (IL-6: MD = 0.609 (0.086), p < 0.0001; IL-1RA: MD = 0.322 (0.041), p < 0.0001), and 36-60 hours (IL-6: MD = 0.818 (0.084), p < 0.0001; IL-1RA: MD = 0.317 (0.040), p < 0.0001). IL-6 and IL-1RA were elevated in participants with sport (IL-6: MD = 0.748 (0.115), p < 0.0001; IL-1RA: MD = 0.304 (0.055), p < 0.0001) and combative-related concussions (IL-6: MD = 0.583 (0.178), p = 0.001; IL-1RA: MD = 0.312 (0.081), p = 0.0001). IL-6 was elevated in male (MD = 0.734 (0.105), p < 0.0001) and female participants (MD = 0.600 (0.177), p = 0.0008); IL-1RA was only elevated in male participants (MD = 0.356 (0.047), p < 0.0001). Logistic regression showed the inclusion of IL-6 and IL-1RA at 0-12 hours improved the discrimination of participants with concussion from controls relative to brain injury markers (χ2(2) = 17.855, p = 0.0001; area under the receiver operating characteristic curve [AUC] 0.73 [0.66-0.80] to 0.78 [0.71-0.84]), objective clinical measures (balance and cognition; χ2(2) = 40.661, p < 0.0001; AUC 0.81 [0.76-0.86] to 0.87 [0.83-0.91]), and objective and subjective measures combined (χ2(2) = 13.456, p = 0.001; AUC 0.97 [0.95-0.99] to 0.98 [0.96-0.99]), although improvement in AUC was only significantly relative to objective clinical measures. DISCUSSION: IL-6 and IL-1RA (male participants only) are elevated in the early-acute window postconcussion and may aid in diagnostic decisions beyond traditional blood markers and common clinical measures. IL-1RA results highlight sex differences in the immune response to concussion which should be considered in future biomarker work.

Concordance Between Accelerometer-Measured and Self-Reported Physical Activity and Sedentary Time in Adults with Autism.

This study examined the concordance between accelerometry-measured and self-reported physical activity (PA) and sedentary time in adults with autism. Twenty-four participants wore an ActiGraph GT3X + accelerometer for seven consecutive days and completed the International Physical Activity Questionnaire-Short Form (IPAQ-SF) on the last day of their study participation. Bland-Altman plots assessed the magnitude of agreement between the two measures. Nearly 80% of the participants accumulated the recommended ≥ 150 min of moderate to vigorous PA (MVPA)/week, but were also sedentary for over nine hours/day according to accelerometry data. Findings showed that adults with autism tended to overreport MVPA (b = 1.606, p < 0.01) and underreport sedentary time (b = 1.161, p = 0.03) via the IPAQ-SF, as compared to objective measurements.

Matrix-Variate Regression for Sparse, Low-Rank Estimation of Brain Connectivities Associated With a Clinical Outcome.

OBJECTIVE: We address the problem of finding brain connectivities that are associated with a clinical outcome or phenotype. METHODS: The proposed framework regresses a (scalar) clinical outcome on matrix-variate predictors which arise in the form of brain connectivity matrices. For example, in a large cohort of subjects we estimate those regions of functional connectivities that are associated with neurocognitive scores. We approach this high-dimensional yet highly structured estimation problem by formulating a regularized estimation process that results in a low-rank coefficient matrix having a sparse set of nonzero entries which represent regions of biologically relevant connectivities. In contrast to the recent literature on estimating a sparse, low-rank matrix from a single noisy observation, our scalar-on-matrix regression framework produces a data-driven extraction of structures that are associated with a clinical response. The method, called Sparsity Inducing Nuclear-Norm Estimator (SpINNEr), simultaneously constrains the regression coefficient matrix in two ways: a nuclear norm penalty encourages low-rank structure while an l1 norm encourages entry-wise sparsity. RESULTS: Our simulations show that SpINNEr outperforms other methods in estimation accuracy when the response-related entries (representing the brain's functional connectivity) are arranged in well-connected communities. SpINNEr is applied to investigate associations between HIV-related outcomes and functional connectivity in the human brain. CONCLUSION AND SIGNIFICANCE: Overall, this work demonstrates the potential of SpINNEr to recover sparse and low-rank estimates under scalar-on-matrix regression framework.

High-intensity sweet taste as a predictor of subjective alcohol responses to the ascending limb of an intravenous alcohol prime: an fMRI study.

High-intensity sweet-liking has been linked to alcohol use disorder (AUD) risk. However, the neural underpinning of this association is poorly understood. To find a biomarker predictive of AUD, 140 participants (social and heavy drinkers, ages 21-26) underwent functional magnetic resonance imaging (fMRI) during a monetary incentive delay (MID) task and stimulation with high (SucroseHigh)- and low-concentration sucrose, as well as viscosity-matched water. On another day after imaging, and just before free-access intravenous alcohol self-administration, participants experienced a 30 mg% alcohol prime (10 min ascent) using the Computerized Alcohol Infusion System. Principal component analysis (PCA) of subjective responses (SR) to the prime's ascending limb generated enjoyable (SRenjoy) and sedative (SRsed) intoxication components. Another PCA created one component reflective of self-administered alcohol exposure (AE) over 90 min. Component loadings were entered as regressors in a voxel-wise general linear fMRI model, with reward type as a fixed factor. By design, peak prime breath alcohol concentration was similar across participants (29 ± 3.4 mg%). SRenjoy on the prime's ascending limb correlated positively with [SucroseHigh > Water] in the supplementary motor area and right dorsal anterior insula, implicating the salience network. Neither SR component correlated with the brain's response to MID. AE was unrelated to brain reward activation. While these findings do not support a relationship between alcohol self-administration and (1) subjective liking of or (2) regional brain response to an intensely sweet taste, they show that alcohol's enjoyable intoxicating effects on the rising limb correspond with anterior insular and supplementary motor area responses to high-concentration sucrose taste. No such associations were observed with MID despite robust activation in those regions. Insula and supplementary motor area responses to intense sensations relate to a known risk factor for AUD in a way that is not apparent with a secondary (monetary) reward.

Gene Expression Alterations in Peripheral Blood Following Sport-Related Concussion in a Prospective Cohort of Collegiate Athletes: A Concussion Assessment, Research and Education (CARE) Consortium Study.

BACKGROUND: Molecular-based approaches to understanding concussion pathophysiology provide complex biological information that can advance concussion research and identify potential diagnostic and/or prognostic biomarkers of injury. OBJECTIVE: The aim of this study was to identify gene expression changes in peripheral blood that are initiated following concussion and are relevant to concussion response and recovery. METHODS: We analyzed whole blood transcriptomes in a large cohort of concussed and control collegiate athletes who were participating in the multicenter prospective cohort Concussion Assessment, Research, and Education (CARE) Consortium study. Blood samples were collected from collegiate athletes at preseason (baseline), within 6 h of concussion injury, and at four additional prescribed time points spanning 24 h to 6 months post-injury. RNA sequencing was performed on samples from 230 concussed, 130 contact control, and 102 non-contact control athletes. Differential gene expression and deconvolution analysis were performed at each time point relative to baseline. RESULTS: Cytokine and immune response signaling pathways were activated immediately after concussion, but at later time points these pathways appeared to be suppressed relative to the contact control group. We also found that the proportion of neutrophils increased and natural killer cells decreased in the blood following concussion. CONCLUSIONS: Transcriptome signatures in the blood reflect the known pathophysiology of concussion and may be useful for defining the immediate biological response and the time course for recovery. In addition, the identified immune response pathways and changes in immune cell type proportions following a concussion may inform future treatment strategies.

Associations between skeletal muscle energetics and accelerometry-based performance fatigability: Study of Muscle, Mobility and Aging.

Performance fatigability is typically experienced as insufficient energy to complete daily physical tasks, particularly with advancing age, often progressing toward dependency. Thus, understanding the etiology of performance fatigability, especially cellular-level biological mechanisms, may help to delay the onset of mobility disability. We hypothesized that skeletal muscle energetics may be important contributors to performance fatigability. Participants in the Study of Muscle, Mobility and Aging completed a usual-paced 400-m walk wearing a wrist-worn ActiGraph GT9X to derive the Pittsburgh Performance Fatigability Index (PPFI, higher scores = more severe fatigability) that quantifies percent decline in individual cadence-versus-time trajectory from their maximal cadence. Complex I&II-supported maximal oxidative phosphorylation (max OXPHOS) and complex I&II-supported electron transfer system (max ETS) were quantified ex vivo using high-resolution respirometry in permeabilized fiber bundles from vastus lateralis muscle biopsies. Maximal adenosine triphosphate production (ATPmax ) was assessed in vivo by 31 P magnetic resonance spectroscopy. We conducted tobit regressions to examine associations of max OXPHOS, max ETS, and ATPmax with PPFI, adjusting for technician/site, demographic characteristics, and total activity count over 7-day free-living among older adults (N = 795, 70-94 years, 58% women) with complete PPFI scores and ≥1 energetics measure. Median PPFI score was 1.4% [25th-75th percentile: 0%-2.9%]. After full adjustment, each 1 standard deviation lower max OXPHOS, max ETS, and ATPmax were associated with 0.55 (95% CI: 0.26-0.84), 0.39 (95% CI: 0.09-0.70), and 0.54 (95% CI: 0.27-0.81) higher PPFI score, respectively. Our findings suggested that therapeutics targeting muscle energetics may potentially mitigate fatigability and lessen susceptibility to disability among older adults.

Tangent functional connectomes uncover more unique phenotypic traits.

Functional connectomes (FCs) containing pairwise estimations of functional couplings between pairs of brain regions are commonly represented by correlation matrices. As symmetric positive definite matrices, FCs can be transformed via tangent space projections, resulting into tangent-FCs. Tangent-FCs have led to more accurate models predicting brain conditions or aging. Motivated by the fact that tangent-FCs seem to be better biomarkers than FCs, we hypothesized that tangent-FCs have also a higher fingerprint. We explored the effects of six factors: fMRI condition, scan length, parcellation granularity, reference matrix, main-diagonal regularization, and distance metric. Our results showed that identification rates are systematically higher when using tangent-FCs across the "fingerprint gradient" (here including test-retest, monozygotic and dizygotic twins). Highest identification rates were achieved when minimally (0.01) regularizing FCs while performing tangent space projection using Riemann reference matrix and using correlation distance to compare the resulting tangent-FCs. Such configuration was validated in a second dataset (resting-state).

Plasma phosphorylated tau181 as a biomarker of mild traumatic brain injury: findings from THINC and NCAA-DoD CARE Consortium prospective cohorts.

Objective: The aim of this study was to investigate phosphorylated tau (p-tau181) protein in plasma in a cohort of mild traumatic brain injury (mTBI) patients and a cohort of concussed athletes. Methods: This pilot study comprised two independent cohorts. The first cohort-part of a Traumatic Head Injury Neuroimaging Classification (THINC) study-with a mean age of 46 years was composed of uninjured controls (UIC, n = 30) and mTBI patients (n = 288) recruited from the emergency department with clinical computed tomography (CT) and research magnetic resonance imaging (MRI) findings. The second cohort-with a mean age of 19 years-comprised 133 collegiate athletes with (n = 112) and without (n = 21) concussions. The participants enrolled in the second cohort were a part of a multicenter, prospective, case-control study conducted by the NCAA-DoD Concussion Assessment, Research and Education (CARE) Consortium at six CARE Advanced Research Core (ARC) sites between 2015 and 2019. Blood was collected within 48 h of injury for both cohorts. Plasma concentration (pg/ml) of p-tau181 was measured using the Single Molecule Array ultrasensitive assay. Results: Concentrations of plasma p-tau181 in both cohorts were significantly elevated compared to controls within 48 h of injury, with the highest concentrations of p-tau181 within 18 h of injury, with an area under the curve (AUC) of 0.690-0.748, respectively, in distinguishing mTBI patients and concussed athletes from controls. Among the mTBI patients, the levels of plasma p-tau181 were significantly higher in patients with positive neuroimaging (either CT+/MRI+, n = 74 or CT-/MRI+, n = 89) compared to mTBI patients with negative neuroimaging (CT-/MRI-, n = 111) findings and UIC (P-values < 0.05). Conclusion: These findings indicate that plasma p-tau181 concentrations likely relate to brain injury, with the highest levels in patients with neuroimaging evidence of injury. Future research is needed to replicate and validate this protein assay's performance as a possible early diagnostic biomarker for mTBI/concussions.

Validation of the Pittsburgh Performance Fatigability Index in the Study of Muscle, Mobility and Aging.

BACKGROUND: The Pittsburgh Performance Fatigability Index (PPFI) quantifies the percent decline in cadence using accelerometry during standardized walking tasks. Although PPFI has shown strong correlations with physical performance, the developmental sample was relatively homogenous and small, necessitating further validation. METHODS: Participants from the Study of Muscle, Mobility and Aging (N = 805, age = 76.4 ±â€…5.0 years, 58% women, 85% White) wore an ActiGraph GT9X on the nondominant wrist during usual-paced 400 m walk. Tri-axial accelerations were analyzed to compute PPFI (higher score = greater fatigability). To evaluate construct and discriminant validity, Spearman correlations (rs) between PPFI and gait speed, Short Physical Performance Battery (SPPB), chair stand speed, leg peak power, VO2peak, perceived fatigability, and mood were examined. Sex-specific PPFI cut-points that optimally discriminated gait speed using classification and regression tree were then generated. Their discriminate power in relation to aforementioned physical performance were further evaluated. RESULTS: Median PPFI score was 1.4% (25th-75th percentile range: 0%-21.7%), higher among women than men (p < .001). PPFI score was moderate-to-strongly correlated with gait speed (rs = -0.75), SPPB score (rs = -0.38), chair stand speed (rs = -0.36), leg peak power (rs = -0.34) and VO2peak (rs = -0.40), and less strongly with perceived fatigability (rs = 0.28-0.29), all p < .001. PPFI score was not correlated with mood (|rs| < 0.08). Sex-specific PPFI cut-points (no performance fatigability: PPFI = 0%; mild performance fatigability: 0% < PPFI < 3.5% [women], 0% < PPFI < 5.4% [men]; moderate-to-severe performance fatigability: PPFI ≥ 3.5% [women], PPFI ≥ 5.4% [men]) discriminated physical performance (all p < .001), adjusted for demographics and smoking status. CONCLUSION: Our work underscores the utility of PPFI as a valid measure to quantify performance fatigability in future longitudinal epidemiologic studies and clinical/pharmaceutical trials.

The modulatory role of cannabis use in subconcussive neural injury.

Cannabis use has become popular among athletes, many of whom are exposed to repetitive subconcussive head impacts. We aimed to test whether chronic cannabis use would be neuroprotective or exacerbating against acute subconcussive head impacts. This trial included 43 adult soccer players (Cannabis group using cannabis at least once a week for the past 6 months, n = 24; non-cannabis control group, n = 19). Twenty soccer headings, induced by our controlled heading model, significantly impaired ocular-motor function, but the degrees of impairments were less in the cannabis group compared to controls. The control group significantly increased its serum S100B level after heading, whereas no change was observed in the cannabis group. There was no group difference in serum neurofilament light levels at any time point. Our data suggest that chronic cannabis use may be associated with an enhancement of oculomotor functional resiliency and suppression of the neuroinflammatory response following 20 soccer headings.

Longitudinal Associations Between Blood Biomarkers and White Matter MRI in Sport-Related Concussion: A Study of the NCAA-DoD CARE Consortium.

BACKGROUND AND OBJECTIVES: To study longitudinal associations between blood-based neural biomarkers (including total tau, neurofilament light [NfL], glial fibrillary acidic protein [GFAP], and ubiquitin C-terminal hydrolase-L1) and white matter neuroimaging biomarkers in collegiate athletes with sport-related concussion (SRC) from 24 hours postinjury to 1 week after return to play. METHODS: We analyzed clinical and imaging data of concussed collegiate athletes in the Concussion Assessment, Research, and Education (CARE) Consortium. The CARE participants completed same-day clinical assessments, blood draws, and diffusion tensor imaging (DTI) at 3 time points: 24-48 hours postinjury, point of becoming asymptomatic, and 7 days after return to play. DTI probabilistic tractography was performed for each participant at each time point to render 27 participant-specific major white matter tracts. The microstructural organization of these tracts was characterized by 4 DTI metrics. Mixed-effects models with random intercepts were applied to test whether white matter microstructural abnormalities are associated with the blood-based biomarkers at the same time point. An interaction model was used to test whether the association varies across time points. A lagged model was used to test whether early blood-based biomarkers predict later microstructural changes. RESULTS: Data from 77 collegiate athletes were included in the following analyses. Among the 4 blood-based biomarkers, total tau had significant associations with the DTI metrics across the 3 time points. In particular, high tau level was associated with high radial diffusivity (RD) in the right corticospinal tract (ß = 0.25, SE = 0.07, p FDR-adjusted = 0.016) and superior thalamic radiation (ß = 0.21, SE = 0.07, p FDR-adjusted = 0.042). NfL and GFAP had time-dependent associations with the DTI metrics. NfL showed significant associations only at the asymptomatic time point (|ß|s > 0.12, SEs <0.09, psFDR-adjusted < 0.05) and GFAP showed a significant association only at 7 days after return to play (ßs > 0.14, SEs <0.06, psFDR-adjusted < 0.05). The p values for the associations of early tau and later RD were not significant after multiple comparison adjustment, but were less than 0.1 in 7 white matter tracts. DISCUSSION: This prospective study using data from the CARE Consortium demonstrated that in the early phase of SRC, white matter microstructural integrity detected by DTI neuroimaging was associated with elevated levels of blood-based biomarkers of traumatic brain injury. Total tau in the blood showed the strongest association with white matter microstructural changes.

Fingerprinting walking using wrist-worn accelerometers.

BACKGROUND: Identifying an individual from accelerometry data collected during walking without reliance on step-cycle detection has not been achieved with high accuracy. RESEARCH QUESTION: We propose an open-source reproducible method to: (1) create a unique, person-specific "walking fingerprint" from a sample of un-landmarked high-resolution data collected by a wrist-worn accelerometer; and (2) predict who an individual is from their walking fingerprint. METHODS: Accelerometry data were collected during walking from 32 individuals (23-52 y.o., 19 females) for at least 380 s each. For this study's purpose, data are not landmarked, nor synchronized. Individual walking fingerprints were created by: (1) partitioning the accelerometer time series in adjacent, non-overlapping one-second intervals; (2) transforming all one-second interval data for a given individual into a three-dimensional (3D) image obtained by plotting each one-second interval time series by the lagged time series for a series of lags; (3) partitioning these resulting participant-specific 3D images into a grid of cells; and (4) identifying the combinations of cells (areas in the 3D image) that best predict the individual. For every participant, the first 200 s of data were used as training and the last 180 s as testing. This approach does not use segmentation methods for individual strides, which reduces dependence on complementary algorithms and increases its generalizability. RESULTS: The method correctly identified 100 % of the participants in the test data and highlighted unique features of walking that characterize the individuals. SIGNIFICANCE: Predicting the identity of an individual from their walking pattern has immediate implications that can complement or replace those of actual fingerprinting, voice, and image recognition. Furthermore, as walking may change with age or disease burden, individual walking fingerprints may be used as biomarkers of change in health status with potential clinical and epidemiologic implications.