Faculty Bibliography

BACKGROUND:Clinical evaluation of distal symmetric polyneuropathy (DSP), which can include small fiber neuropathy (SFN), differs among neurologists, neuromuscular specialists, and internists. The American Academy of Neurology (AAN) 2009 Practice Parameter guides evaluation of DSP, but there are no guidelines or AAN practice parameters for the evaluation of SFN. OBJECTIVE:Determine how neurologists evaluate and test for SFN in their clinical practice and compare responses between neuromuscular (NM) and non-neuromuscular specialists (non-NM). DESIGN/METHODS/METHODS:Eight hundred randomly selected AAN members, which included 400 members who indicated NM medicine to be a primary or secondary specialty, were selected to answer a survey about SFN. Respondents answered a survey instrument with a list of 44 serum tests and procedures for different neuropathy clinical scenarios. RESULTS:The survey response rate was 29.3% (234/798), with 48.8% (N = 114) indicating that their primary specialty was neuromuscular. For an initial evaluation of distal symmetric SFN, respondents ordered a mean of 12 tests (SD 5.8) with a range of 0-26 tests. There was no statistically significant difference between the mean number of tests ordered by neuromuscular versus non-neuromuscular specialists. The 5 most common overall responses were complete blood count (87%), vitamin B12 (86%), basic metabolic panel (84%), thyroid stimulating hormone (78%), and hemoglobin A1c (77%). For a secondary evaluation of etiologies of distal symmetric SFN, 52% of non-neuromuscular specialists (95% CI, 42%-61%) versus 35% of neuromuscular specialists (95% CI, 26%-45%) would order a paraneoplastic panel. There was significant disparity in ordering a skin biopsy for intraepidermal nerve fiber density, with 65% of neuromuscular specialists (95% CI, 55%-74%) indicating that they would order this test compared with 38% of non-neuromuscular specialists (95% CI, 29%-48%). CONCLUSIONS:The recommended studies with the highest yield for finding a cause of DSP were not universally ordered. There is variability in approaches to diagnosing SFN and searching for a possible etiology. The development of an AAN practice parameter for SFN may help promote consistent practice among neurologists of all subspecialties.

Neuronal oscillations at about 10 Hz, called alpha oscillations, are often thought to arise from synchronous activity across the occipital cortex and are usually largest when the cortex is inactive. However, recent studies measuring visual receptive fields have reported that local alpha power increases when cortex is excited by visual stimulation. This contrasts with the expectation that alpha oscillations are associated with cortical inactivity. Here, we used intracranial electrodes in human patients to measure alpha oscillations in response to visual stimuli whose location varied systematically across the visual field. We hypothesized that stimulus-driven local increases in alpha power result from a mixture of two effects: a reduction in alpha oscillatory power and a simultaneous increase in broadband power. To test this, we implemented a model to separate these components. The two components were then independently fit by population receptive field (pRF) models. We find that the alpha pRFs have similar center locations to pRFs estimated from broadband power but are several times larger and exhibit the opposite effect: alpha oscillatory power decreases in response to stimuli within the receptive field, reinforcing the link between alpha oscillations and cortical inactivity, whereas broadband power increases. The results demonstrate that alpha suppression in the human visual cortex can be precisely tuned, but that to measure these effects, it is essential to separate the oscillatory signal from broadband power changes. Finally, we show how the large size and the negative valence of alpha pRFs can explain key features of exogenous visual attention.

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:Neuropsychiatric symptoms (NPS) are common in older people with cognitive impairment and Alzheimer's disease (AD). No biomarkers to detect the related pathology or predict the clinical evolution of NPS are available yet. This study aimed to identify plasma proteins that may serve as biomarkers for NPS and NPS-related clinical disease progression. METHODS:A panel of 190 plasma proteins was quantified using Luminex xMAP in the Alzheimer's Disease Neuroimaging Initiative cohort. NPS and cognitive performance were assessed at baseline and after 1 and 2 years. Logistic regression, receiver operating characteristic analysis and cross-validation were used to address the relations of interest. RESULTS:A total of 507 participants with mild cognitive impairment (n=396) or mild AD dementia (n=111) were considered. Selected plasma proteins improved the prediction of NPS (area under the curve (AUC) from 0.61 to 0.76, p<0.001) and future NPS (AUC from 0.63 to 0.80, p<0.001) when added to a reference model. Distinct protein panels were identified for single symptoms. Among the selected proteins, ANGT, CCL1 and IL3 were associated with NPS at all three time points while CCL1, serum glutamic oxaloacetic transaminase and complement factor H were also associated with cognitive decline. The associations were independent of the presence of cerebral AD pathology as assessed using cerebrospinal fluid biomarkers. CONCLUSIONS:Plasma proteins are associated with NPS and improve prediction of future NPS.

Alzheimer's disease (AD) is characterized by the deposition of full-length and truncated amyloid beta (Aβ) species within brain parenchyma and cerebral vessels. However, Aβ truncated species remain understudied. Here, we present a protocol for culture and characterization of a mouse monoclonal antibody targeting N-terminally truncated proteoforms starting at position 4. We describe a detailed procedure for hybridoma culture, antibody collection, and isolation via affinity chromatography. We then describe steps for target validation via dot blot, as well as potential applications. For complete details on the use and execution of this protocol, please refer to Cabrera et al. and Rostagno et al.¹

BACKGROUND AND OBJECTIVES/OBJECTIVE:Older chronological age is associated with decreased multiple sclerosis (MS) relapse rates and increased risk of progressive disease. Measurement of biological age may be more precise than birthdate in understanding these aging effects. In addition to normal aging, MS-related accelerated aging may contribute. Measurement of biological age in adults may be confounded by the effects of natural aging and age-related comorbidities. Examining age extremes can be informative, and demonstrating accelerated biological aging in children would support a hypothesis of MS driving premature aging. We sought to compare epigenetic age in participants with pediatric-onset MS (POMS) and age-similar controls. METHODS:We performed a multicenter case-control analysis of epigenetic age in a prospectively collected set of whole blood DNA samples and clinical data. Quantitative methylation scores were derived for approximately 850,000 cytosine-phosphate-guanine (CpG) sites. Epigenetic age was calculated based on 4 established epigenetic clock algorithms. Epigenetic age and age acceleration residual (AAR) were compared between participants with POMS and age-similar controls using multivariate regression analysis, adjusted for demographic variables. RESULTS:= 0.004). DISCUSSION/CONCLUSIONS:We observed greater point estimates of epigenetic age in participants with POMS compared with healthy controls in all epigenetic clocks tested. This difference was statistically significant for the Hannum and PhenoAge clocks after multivariable modeling. These results are consistent with those of studies in adult MS and suggest that accelerated aging may be present even in the youngest people living with MS.

SARS-CoV-2 infection has been associated with increased autoimmune disease risk. Past studies have not aligned regarding the most prevalent autoimmune diseases after infection, however. Furthermore, the relationship between infection severity and new autoimmune disease risk has not been well examined. We used RECOVER's electronic health record (EHR) networks, N3C, PCORnet, and PEDSnet, to estimate types and frequency of autoimmune diseases arising after SARS-CoV-2 infection and assessed how infection severity related to autoimmune disease risk. We identified patients of any age with SARS-CoV-2 infection between April 1, 2020 and April 1, 2021, and assigned them to a World Health Organization COVID-19 severity category for adults or the PEDSnet acute COVID-19 illness severity classification system for children (<age 21). We collected baseline covariates from the EHR in the year pre-index infection date and followed patients for 2 years for new autoimmune disease, defined as ≥ 2 new ICD-9, ICD-10, or SNOMED codes in the same concept set, starting >30 days after SARS-CoV-2 infection index date and occurring ≥1 day apart. We calculated overall and infection severity-stratified incidence ratesper 1000 person-years for all autoimmune diseases. With least severe COVID-19 severity as reference, survival analyses examined incident autoimmune disease risk. The most common new-onset autoimmune diseases in all networks were thyroid disease, psoriasis/psoriatic arthritis, and inflammatory bowel disease. Among adults, inflammatory arthritis was the most common, and Sjögren's disease also had high incidence. Incident type 1 diabetes and hematological autoimmune diseases were specifically found in children. Across networks, after adjustment, patients with highest COVID-19 severity had highest risk for new autoimmune disease vs. those with least severe disease (N3C: adjusted Hazard Ratio, (aHR) 1.47 (95%CI 1.33-1.66); PCORnet aHR 1.14 (95%CI 1.02-1.26); PEDSnet: aHR 3.14 (95%CI 2.42-4.07)]. Overall, severe acute COVID-19 was most strongly associated with autoimmune disease risk in three EHR networks.

Sentence production is the uniquely human ability to transform complex thoughts into strings of words. Despite the importance of this process, language production research has primarily focused on single words. It remains a largely untested assumption that the principles of word production generalize to more naturalistic utterances like sentences. Here, we investigate this using high-resolution neurosurgical recordings (ECoG) and an overt production experiment where ten patients produced six words in isolation (picture naming) and in sentences (scene description). We trained machine learning classifiers to identify the unique brain activity patterns for each word during picture naming, and used these patterns to decode which words patients were processing while they produced sentences. Our findings confirm that words share cortical representations across tasks, but reveal a division of labor within the language network. In sensorimotor cortex, words were consistently activated in the order in which they were said in the sentence. However, in prefrontal cortex, the order in which words were processed depended on the syntactic structure of the sentence. In non-canonical sentences (passives), we further observed a spatial code for syntactic roles, with subjects selectively encoded in inferior frontal gyrus (IFG) and objects selectively encoded in middle frontal gyrus (MFG). We suggest that these complex dynamics of prefrontal cortex may impose a subtle pressure on language evolution, potentially explaining why nearly all the world's languages position subjects before objects.