Faculty Bibliography

Effective mild cognitive impairment (MCI) screening requires accessible testing. This study compared two tests for distinguishing MCI patients from controls: Rapid Automatized Naming (RAN) for naming speed and Low Contrast Letter Acuity (LCLA) for sensitivity to low contrast letters. Two RAN tasks were used: the Mobile Universal Lexicon Evaluation System (MULES, picture naming) and Staggered Uneven Number test (SUN, number naming). Both RAN tasks were administered on a tablet and in a paper/pencil format. The tablet format was administered using the Mobile Integrated Cognitive Kit (MICK) application. LCLA was tested at 2.5% and 1.25% contrast. Sixty-four participants (31 MCI, 34 controls; mean age 73.2 ± 6.8 years) were included. MCI patients were slower than controls for paper/pencil (75.0 vs. 53.6 sec, p < 0.001), and tablet MULES (69.0 sec vs. 50.2 sec, p = 0.01). The paper/pencil SUN showed no significant difference (MCI: 59.5 sec vs. controls: 59.9 sec, p = 0.07), nor did tablet SUN (MCI: 59.3 sec vs. controls: 55.7 sec, p = 0.36). MCI patients had worse performance on LCLA testing at 2.5% contrast (33 letters vs. 36, p = 0.04*) and 1.25% (0 letters vs. 14. letters, p < 0.001). Receiver operating characteristic (ROC) analysis showed similar performance of paper/pencil and tablet MULES in distinguishing MCI from controls (AUC = 0.77), outperforming both SUN (AUC = 0.63 paper, 0.59 tablet) and LCLA (2.5% contrast: AUC = 0.65, 1.25% contrast: AUC = 0.72). The MULES, in both formats, may be a valuable screening tool for MCI.

BACKGROUND AND OBJECTIVES/OBJECTIVE:Disturbances in brain catecholamine activity may be associated with symptoms after exposure to repetitive head impacts (RHIs) or related chronic traumatic encephalopathy (CTE). In this article, we studied CSF catecholamines in former professional and college American football players and examined the relationship with football proxies of RHI exposure, CTE probability, cognitive performance, neuropsychiatric symptoms, and parkinsonism. METHODS:In this observational cross-sectional study, we examined male former American football players, professional ("PRO") or college ("COL") level, and asymptomatic unexposed male ("UE") individuals from the DIAGNOSE CTE Research Project. Catecholamines-norepinephrine (NE) and its metabolite, 3,4-dihydroxyphenylglycol (DHPG), and dopamine (DA) and its precursor, 3,4-dihydroxyphenylalanine (l-DOPA), and metabolite, 3,4-dihydroxyphenylacetic acid (DOPAC)-were measured in CSF with high-performance liquid chromatography and compared across groups with analysis of covariance. Multivariable linear regression models tested the relationship between CSF catecholamines and proxies of RHI exposure (e.g., total years of playing American football), factor scores for cognition, and neurobehavioral dysregulation (explosivity, emotional dyscontrol, impulsivity, affective lability), as well as depressive/anxiety symptoms, measured with the Beck Depression/Anxiety Inventories. CTE probability and parkinsonism were assessed using the National Institute of Neurological Disorders and Stroke consensus diagnostic criteria for traumatic encephalopathy syndrome (TES), and biomarkers were compared among different diagnostic groups. RESULTS:The cohort consisted of 120 former American football players (85 PRO players, 35 COL players) and 35 UE participants (age 45-75). Former players had significantly lower levels of NE (mean difference = -0.114, 95% CI -0.190 to -0.038), l-DOPA (-0.121, 95% CI -0.109 to -0.027), and DOPAC (-0.116, 95% CI -0.177 to -0.054) than UE participants. For NE and DOPAC, these overall group differences were primarily due to differences between the PRO and UE cohorts. No significant differences were found across TES-CTE probability subgroups or TES-parkinsonism diagnostic groups. Within the COL cohort, tested as post hoc analyses, higher CSF NE and l-DOPA were associated with higher neurobehavioral dysregulation factor scores, BAI total score, and worse executive functioning and processing speed. CSF DHPG and DOPAC were associated with impulsivity only in this subgroup. DISCUSSION/CONCLUSIONS:We observed reduced CSF catecholamine concentrations in former elite American football players, although the relationship with degree of RHI exposure and the clinical impact needs further study.

BACKGROUND:Visual symptoms are common after concussion. Rapid automatized naming (RAN) tasks are simple performance measures that demonstrate worse time scores in the setting of acute or more remote injury. METHODS:We evaluated the capacity for the Mobile Universal Lexicon Evaluation System (MULES) and Staggered Uneven Number (SUN) testing to be feasibly administered during preseason testing in a cohort of youth ice hockey athletes using a novel computerized app, the Mobile Integrated Cognitive Kit (MICK). Participants from a youth hockey league underwent preseason testing. RESULTS:Among 60 participants, the median age was 13 years (range 6-17). The median best time for the MULES was 49.8 seconds (range = 34.2-141.0) and the median best time for the SUN was 70.1 (range = 36.6-200.0). As is characteristic of timed performance measures, there were learning effects between the first and second trials for both the MULES (median improvement = 10.6 seconds, range = -32.3 to 92.0, P < 0.001, Wilcoxon signed-rank test) and SUN (median improvement = 2.4 seconds, range= -8.0 to 15.1, P = 0.001, Wilcoxon signed-rank test). Age was a predictor of best baseline times, with longer (worse) times for younger participants for MULES (P < 0.001, rs = -0.67) and SUN (P < 0.001, rs = -0.54 Spearman rank correlation). Degrees of learning effect did not vary with age (P > 0.05, rs = -0.2). CONCLUSIONS:Vision-based RAN tasks, such as the MULES and SUN, can be feasibly administered using the MICK app during preseason baseline testing in youth sports teams. The results suggest that more frequent baseline tests are necessary for preadolescent athletes because of the relation of RAN task performance to age.

BACKGROUND:In many parts of the world including India, the prevalence of autoimmune inflammatory diseases such as neuromyelitis optica spectrum disorders (NMOSD), myelin oligodendrocyte glycoprotein antibody-associated disease (MOGAD), and multiple sclerosis (MS) is rising. A diagnosis is often delayed due to insufficient diagnostic tools. Machine learning (ML) models have accurately differentiated eyes of patients with MS from those of healthy controls (HCs) using optical coherence tomography (OCT)-based retinal images. Examining OCT characteristics may allow for early differentiation of these conditions. The objective of this study was to determine feasibility of ML analyses to distinguish between patients with different autoimmune inflammatory diseases, other ocular diseases, and HCs based on OCT measurements of the peripapillary retinal nerve fiber layer (pRNFL), ganglion cell-inner plexiform layer (GCIPL), and inner nuclear layers (INLs). METHODS:Eyes of people with MS (n = 99 patients), NMOSD (n = 40), MOGAD (n = 74), other ocular diseases (OTHER, n = 16), and HCs (n = 54) from the Mangalore Demyelinating Disease Registry were included. Support vector machine (SVM) classification models incorporating age, pRNFL, GCIPL, and INL were performed. Data were split into training (70%) and testing (30%) data and accounted for within-patient correlations. Cross-validation was used in training to choose the best parameters for the SVM model. Accuracy and area under receiver operating characteristic curves (AUROCs) were used to assess model performance. RESULTS:The SVM models distinguished between eyes of patients with each condition (i.e., MOGAD vs NMOSD, NMOSD vs HC, MS vs OTHER, etc) with strong discriminatory power demonstrated from the AUROCs for these comparisons ranging from 0.81 to 1.00. These models also performed with moderate to high accuracy, ranging from 0.66 to 0.81, with the exception of the MS vs NMOSD comparison, which had an accuracy of 0.53. CONCLUSIONS:ML models are useful for distinguishing between autoimmune inflammatory diseases and for distinguishing these from HCs and other ocular diseases based on OCT measures. This study lays the groundwork for future deep learning studies that use analyses of raw OCT images for identifying eyes of patients with such disorders and other etiologies of optic neuropathy.

BACKGROUND:The randomized, phase 2 RENEW trial (NCT01721161) evaluated efficacy/safety of opicinumab (anti-LINGO-1) versus placebo in patients with first-episode unilateral acute optic neuritis (AON). Although no significant differences in the latency recovery of visual evoked potential (VEP) were observed between opicinumab and placebo groups in the intention to treat (ITT) population, the prespecified per-protocol (PP) population showed better recovery with opicinumab than with placebo. RENEWED (NCT02657915) was a one-visit, follow-up study 2 years after the last RENEW study visit (Week 32) designed to assess the long-term electrophysiological and clinical outcomes for participants previously enrolled and having received study treatment in RENEW. METHODS:In the original study (RENEW), participants (aged 18-55 years) with a first unilateral AON episode were enrolled ≤28 days from first symptom onset and after treatment with methylprednisolone 1 g/day intravenously for 3-5 days; these participants were randomized to receive opicinumab 100 mg/kg or placebo intravenously once every 4 weeks from baseline to Week 20, assessed up to Week 32. Participants who received ≥1 dose of opicinumab 100 mg/kg or placebo in RENEW were eligible for the RENEWED follow-up study. Participants enrolled in RENEWED at 2 years (with an additional up to 12-month window) after the last RENEW study visit (Week 32) in both ITT and PP populations. The primary endpoint was change in full-field VEP (FF-VEP) latency of the affected eye at RENEWED study visit versus baseline of the fellow eye in RENEW, comparing between participants who received opicinumab and placebo in RENEW. Clinical progression and severity of multiple sclerosis (MS) were assessed. A substudy evaluated latency recovery using multifocal VEP (mfVEP) as an exploratory endpoint. RESULTS:Of 82 RENEW participants, 52 (63.4 %; opicinumab n = 28, placebo n = 24) enrolled in and completed RENEWED. The adjusted mean (95 % CI) difference in FF-VEP latency delay between opicinumab and placebo groups was -6.0 (-14.6, 2.6) msec (p = 0.165) for the PP population and -4.5 (-12.6, 3.7) msec (p = 0.274) for the ITT population at the RENEWED study visit. Nominally significant improvement on mfVEP latency in the opicinumab group versus placebo was observed in participants of the mfVEP substudy (p = 0.009). In participants from the PP population without clinically definite MS (CDMS) at RENEW baseline,12 (55 %) in the opicinumab group and 12 (67 %) in the placebo group developed CDMS from enrollment in the RENEW study up to RENEWED Day 1; the estimated proportion of participants with CDMS at 2 years after the last study visit assessment in RENEW was lower when treated with opicinumab (0.50) than when treated with placebo (0.61) (hazard ratio p-value = 0.23). No benefit on visual acuity or other neurological functions was observed in the opicinumab group vs placebo in RENEWED. CONCLUSION/CONCLUSIONS:The numerically increased VEP latency recovery with opicinumab treatment in RENEWED was consistent with those observed in the parent study RENEW. However, the VEP latency and clinical data in RENEWED should be interpreted with caution, given the nature of the follow-up study, the small sample size and the limitation in study design.

INTRODUCTION/BACKGROUND:Blood-based biomarkers offer a promising approach for the detection of neuropathologies from repetitive head impacts (RHI). We evaluated plasma biomarkers of amyloid, tau, neurodegeneration, and inflammation in former football players. METHODS:The sample included 180 former football players and 60 asymptomatic, unexposed male participants (aged 45-74). Plasma assays were conducted for beta-amyloid (Aβ) 40, Aβ42, hyper-phosphorylated tau (p-tau) 181+231, total tau (t-tau), neurofilament light (NfL), glial fibrillary acidic protein (GFAP), interleukin-6 (IL-6), Aβ42/p-tau181 and Aβ42/Aβ40 ratios. We evaluated their ability to differentiate the groups and associations with RHI proxies and traumatic encephalopathy syndrome (TES). RESULTS:= 0.008). DISCUSSION/CONCLUSIONS:Plasma p-tau181 and p-tau231, GFAP, and NfL may offer some usefulness for the characterization of RHI-related neuropathologies. HIGHLIGHTS/CONCLUSIONS:Former football players had higher plasma p-tau181 and p-tau231 and lower Aβ42/ptau-181 compared to asymptomatic, unexposed men. Younger age of first exposure was associated with increased plasma NfL and GFAP in older but not younger participants. Plasma GFAP was higher in participants with TES-CTE possible/probable compared to TES-CTE no/suggestive.