WashU weekly Neuroscience publications

Blood plasma phosphorylated-tau isoforms track CNS change in Alzheimer’s disease
(2020) The Journal of Experimental Medicine, 217 (11), .

Barthélemy, N.R.^a , Horie, K.^a , Sato, C.^a , Bateman, R.J.^a b c

^a Department of Neurology, Washington University School of Medicine, St. Louis, MO
^b Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, MO
^c Charles F. and Joanne Knight Alzheimer’s Disease Research Center, Washington University School of Medicine, St. Louis, MO

Abstract
Highly sensitive and specific plasma biomarkers for Alzheimer’s disease (AD) have the potential to improve diagnostic accuracy in the clinic and facilitate research studies including enrollment in prevention and treatment trials. We recently reported CSF tau hyperphosphorylation, especially on T217, is an accurate predictor of β-amyloidosis at asymptomatic and symptomatic stages. In the current study, we determine by mass spectrometry the potential utility of plasma p-tau isoforms to detect AD pathology and investigate CSF and plasma tau isoforms’ profile relationships. Plasma tau was truncated as previously described in CSF. CSF and plasma measures of p-tau-217 and p-tau-181 were correlated. No correlation was found between CSF and plasma on total-tau levels and pS202 measures. We found p-tau-217 and p-tau-181 were highly specific for amyloid plaque pathology in the discovery cohort (n = 36, AUROC = 0.99 and 0.98 respectively). In the validation cohort (n = 92), p-tau-217 measures were still specific to amyloid status (AUROC = 0.92), and p-tau-181 measures were less specific (AUROC = 0.75). © 2020 Barthelemy et al.

Document Type: Article
Publication Stage: Final
Source: Scopus
Access Type: Open Access

Plasticity and Spontaneous Activity Pulses in Disused Human Brain Circuits
(2020) Neuron, 107 (3), pp. 580-589.e6. Cited 1 time.

Newbold, D.J.^a , Laumann, T.O.^b , Hoyt, C.R.^c , Hampton, J.M.^b , Montez, D.F.^a b , Raut, R.V.^d , Ortega, M.^a , Mitra, A.^d e , Nielsen, A.N.^a f , Miller, D.B.^a , Adeyemo, B.^a , Nguyen, A.L.^a , Scheidter, K.M.^a , Tanenbaum, A.B.^a , Van, A.N.^a g , Marek, S.^a , Schlaggar, B.L.^a h i j , Carter, A.R.^a c , Greene, D.J.^b d , Gordon, E.M.^k l m , Raichle, M.E.^a d , Petersen, S.E.^{a d g n o} , Snyder, A.Z.^a d , Dosenbach, N.U.F.^{a c d g p}

^a Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, United States
^b Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, United States
^c Program in Occupational Therapy, Washington University School of Medicine, St. Louis, MO 63110, United States
^d Department of Radiology, Washington University School of Medicine, St. Louis, MO 63110, United States
^e Department of Psychiatry, Stanford University, Stanford, CA 94305, United States
^f Institute for Innovations in Developmental Sciences, Northwestern University, Chicago, IL 60611, United States
^g Department of Biomedical Engineering, Washington University in St. Louis, St. Louis, MO 63110, United States
^h Kennedy Krieger Institute, Baltimore, MD 21205, United States
ⁱ Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD 21287, United States
^j Department of Pediatrics, Johns Hopkins University School of Medicine, Baltimore, MD 21287, United States
^k VISN 17 Center of Excellence for Research on Returning War Veterans, Waco, TX 76711, United States
^l Center for Vital Longevity, School of Behavioral and Brain Sciences, University of Texas at Dallas, Dallas, TX 75080, United States
^m Department of Psychology and Neuroscience, Baylor University, Waco, TX 76706, United States
ⁿ Department of Neuroscience, Washington University School of Medicine, St. Louis, MO 63110, United States
^o Department of Psychological and Brain Sciences, Washington University in St. Louis, St. Louis, MO 63130, United States
^p Department of Pediatrics, Washington University School of Medicine, St. Louis, MO 63110, United States

Abstract
To induce brain plasticity in humans, we casted the dominant upper extremity for 2 weeks and tracked changes in functional connectivity using daily 30-min scans of resting-state functional MRI (rs-fMRI). Casting caused cortical and cerebellar regions controlling the disused extremity to functionally disconnect from the rest of the somatomotor system, while internal connectivity within the disused sub-circuit was maintained. Functional disconnection was evident within 48 h, progressed throughout the cast period, and reversed after cast removal. During the cast period, large, spontaneous pulses of activity propagated through the disused somatomotor sub-circuit. The adult brain seems to rely on regular use to maintain its functional architecture. Disuse-driven spontaneous activity pulses may help preserve functionally disconnected sub-circuits. © 2020 Elsevier Inc.

Newbold et al. induced human brain plasticity by casting the dominant arm for 2 weeks. Disused brain regions rapidly (<48 h) disconnected from the motor system and manifested large, spontaneous activity pulses. Maintaining the brain’s functional architecture may require regular use, and spontaneous activity pulses could serve as a substitute. © 2020 Elsevier Inc.

Author Keywords
ALFF;  amplitude of low-frequency fluctuations;  cerebellum;  disuse;  fMRI;  functional connectivity;  plasticity;  primary motor cortex;  resting state;  spontaneous activity;  supplementary motor area

Document Type: Article
Publication Stage: Final
Source: Scopus

Brain Reward System Dysfunction in Adolescence: Current, Cumulative, and Developmental Periods of Depression
(2020) The American Journal of Psychiatry, 177 (8), pp. 754-763.

Rappaport, B.I., Kandala, S., Luby, J.L., Barch, D.M.

Department of Psychological and Brain Sciences (Rappaport, Barch), Washington University in St. Louis, St. Louis, Mo.; and Department of Psychiatry (Kandala, Luby, Barch) and Department of Radiology (Barch), Washington University School of Medicine, St. Louis, Mo

Abstract
OBJECTIVE: Reward system dysfunction is a well-known correlate and predictor of depression in adults and adolescents, with depressed individuals showing blunted (hyporeactive) striatal response to monetary rewards. Furthermore, studies of remitted depression suggest network-wide hyporeactivity of striatal (caudate, putamen, nucleus accumbens) and cortical (insula, anterior cingulate cortex [ACC]) regions even in the absence of current symptoms. Thus, it remains unclear which patterns of hyporeactivity represent a trait-like indicator of depression and which represent a current depressed state. The authors examined the relationships between regions of a cortico-striatal circuit supporting reward processing and both current depression and cumulative depression history. METHODS: Using a functional MRI monetary reward task, the authors measured brain response to monetary gains and losses in a longitudinal sample of adolescents (N=131) who had been annually assessed for psychiatric symptoms since ages 3-5 years. RESULTS: Current depression severity was associated with hyporeactivity exclusively in the nucleus accumbens in response to the anticipation of a reward, while cumulative depression severity was associated with blunted response to anticipation across a cortico-striatal circuit (striatum, ACC, insula). Follow-up analyses investigating the effects of depression on reward processing at different developmental stages revealed a similar pattern: recent depression severity during adolescence was associated with more focal hyporeactivity in the nucleus accumbens, while depression severity during early childhood (i.e., preschool) was associated with more global hyporeactivity across the cortico-striatal circuit. CONCLUSIONS: The study findings indicate important distinctions between disruptions in reward system neural circuitry associated with a history of depression (particularly early-onset depression) and current depression. These results have implications for understanding the etiology and treatment of reward processing deficits in depression.

Author Keywords
Adolescents;  Childhood;  Depression;  Developmental Period;  Preschool;  Reward Anticipation

Document Type: Article
Publication Stage: Final
Source: Scopus

Understanding the Nature and Treatment of Psychopathology: Can the Data Guide the Way?
(2020) Biological Psychiatry: Cognitive Neuroscience and Neuroimaging, 5 (8), pp. 719-722.

Barch, D.M.

Departments of Psychological and Brain Sciences, Psychiatry, and Radiology, Washington University in St. Louis, St. Louis, MO, United States

Document Type: Note
Publication Stage: Final
Source: Scopus

Genome-Wide Association Study Meta-Analysis of Stroke in 22 000 Individuals of African Descent Identifies Novel Associations With Stroke
(2020) Stroke, 51 (8), pp. 2454-2463.

Keene, K.L.^a , Hyacinth, H.I.^b , Bis, J.C.^c , Kittner, S.J.^d , Mitchell, B.D.^d , Cheng, Y.-C.^d , Pare, G.^e , Chong, M.^e , O’Donnell, M.^f , Meschia, J.F.^g , Chen, W.-M.^h , Sale, M.M.^h , Rich, S.S.^h , Nalls, M.A.^i j , Zonderman, A.B.^k , Evans, M.K.^k , Wilson, J.G.^l , Correa, A.^l , Markus, H.S.^m , Traylor, M.ⁿ , Lewis, C.M.^o , Carty, C.L.^p , Reiner, A.^q , Haessler, J.^q , Langefeld, C.D.^r , Gottesman, R.^s , Mosley, T.H.^l , Woo, D.^t , Yaffe, K.^u , Liu, Y.^r , Longstreth, W.T.^c , Psaty, B.M.^v w , Kooperberg, C.^q , Lange, L.A.^x , Sacco, R.^y , Rundek, T.^y , Lee, J.-M.^z , Cruchaga, C.^z , Furie, K.L.^aa , Arnett, D.K.^ab , Benavente, O.R.^ac , Grewal, R.P.^ad , Peddareddygari, L.R.^ad , Dichgans, M.^ae af , Malik, R.^ae , Worrall, B.B.^ag , Fornage, M.^ah , COMPASS, SiGN, and METASTROKE Consortia^ai

^a Department of Biology; Brody School of Medicine Center for Health Disparities, East Carolina University, Greenville, NC (K.L.K.)
^b Aflac Cancer and Blood Disorder Center of Emory University and Children’s Healthcare of Atlanta University
^c University of Washington, Seattle, United States
^d Baltimore Veterans Administration Medical Center and University of Maryland School of Medicine, Baltimore, United States
^e McMaster University and Population Health Research Institute
^f National University of Ireland Galway
^g Mayo Clinic Florida
^h Center for Public Health Genomics, University of Virginia, M.M.S.
ⁱ Laboratory of Neurogenetics, National Institute on Aging, Bethesda, United States
^j Data Tecnica International, Glen Echo, United States
^k Laboratory of Epidemiology and Population Science, National Institute on Aging, Baltimore, United States
^l University of Mississippi Medical Center, A.C.
^m University of Cambridge, United Kingdom (H.S.M.), United Kingdom
ⁿ William Harvey Research Institute, Queen Mary University of London, United Kingdom (M.T.), Barts and The London School of Medicine and Dentistry
^o Social, Genetic and Developmental Psychiatry Centre, King’s College London, United Kingdom (C.M.L.)
^p Initiative for Research and Education to Advance Community Health, Washington State University
^q Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, United States
^r Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem
^s Johns Hopkins University School of Medicine, Baltimore, United States
^t Department of Neurology, University of Cincinnati
^u University of California, San Francisco (K.Y.)
^v Cardiovascular Health Research Unit, Departments of Medicine, Epidemiology and Health Services, University of Washington
^w Kaiser Permanente Washington Health Research Institute, Seattle, United States
^x University of Colorado Anschutz Medical Campus
^y University of Miami, Miller School of Medicine, FL (R.S.
^z Washington University School of Medicine, St. Louis, United States
^aa Brown University Warren Alpert Medical School, Providence, United States
^ab University of Kentucky, College of Public Health
^ac University of British Columbia, Vancouver, Canada
^ad Neuroscience Institute, Saint Francis Medical Center, Trenton, United States
^ae Institute for Stroke and Dementia Research (ISD), University Hospital, LMU Munich, Germany (M.D.
^af Munich Cluster for Systems Neurology (SyNergy), Germany (M.D.)
^ag Department of Neurology, University of Virginia
^ah Brown Foundation Institute of Molecular Medicine, University of Texas Health Science Center at Houston (M.F.)

Abstract
BACKGROUND AND PURPOSE: Stroke is a complex disease with multiple genetic and environmental risk factors. Blacks endure a nearly 2-fold greater risk of stroke and are 2× to 3× more likely to die from stroke than European Americans. METHODS: The COMPASS (Consortium of Minority Population Genome-Wide Association Studies of Stroke) has conducted a genome-wide association meta-analysis of stroke in >22 000 individuals of African ancestry (3734 cases, 18 317 controls) from 13 cohorts. RESULTS: In meta-analyses, we identified one single nucleotide polymorphism (rs55931441) near the HNF1A gene that reached genome-wide significance (P=4.62×10-8) and an additional 29 variants with suggestive evidence of association (P<1×10-6), representing 24 unique loci. For validation, a look-up analysis for a 100 kb region flanking the COMPASS single nucleotide polymorphism was performed in SiGN (Stroke Genetics Network) Europeans, SiGN Hispanics, and METASTROKE (Europeans). Using a stringent Bonferroni correction P value of 2.08×10-3 (0.05/24 unique loci), we were able to validate associations at the HNF1A locus in both SiGN (P=8.18×10-4) and METASTROKE (P=1.72×10-3) European populations. Overall, 16 of 24 loci showed evidence for validation across multiple populations. Previous studies have reported associations between variants in the HNF1A gene and lipids, C-reactive protein, and risk of coronary artery disease and stroke. Suggestive associations with variants in the SFXN4 and TMEM108 genes represent potential novel ischemic stroke loci. CONCLUSIONS: These findings represent the most thorough investigation of genetic determinants of stroke in individuals of African descent, to date.

Author Keywords
brain ischemia;  coronary artery disease;  genome-wide association study;  meta-analysis;  phenotype;  risk factors

Document Type: Article
Publication Stage: Final
Source: Scopus
Access Type: Open Access

Pandemic Guidance for Stroke Centers Aiding COVID-19 Treatment Teams
(2020) Stroke, 51 (8), pp. 2587-2592.

Wira, C.R.^a , Goyal, M.^b , Southerland, A.M.^c , Sheth, K.N.^d , McNair, N.D.^e , Khosravani, H.^f , Leonard, A.^g , Panagos, P.^h , AHA/ASA Stroke Council Science Subcommittees: Emergency Neurovascular Care (ENCC), Telestroke and the Neurovascular Intervention Committees; and on behalf of the Stroke Nursing Science Subcommittee of the AHA/ASA Cardiovascular and Stroke Nursing Councilⁱ

^a Yale Department of Emergency Medicine and Yale Stroke Program, CT (C.R.W.), New Haven, United States
^b Departments of Clinical Neurosciences and Diagnostic Imaging, University of Calgary
^c Departments of Neurology and Public Health Sciences, University of Virginia
^d Division of Neurocritical Care and Emergency Neurology, Yale School of Medicine & Yale New Haven Hospital, CT (K.N.S.), New Haven, United States
^e University of California
^f Neurology Quality and Innovation Laboratory (NQIL), Division of Neurology, Department of Medicine, Sunnybrook Health Sciences Centre, University of Toronto
^g American Heart Association, Dallas, United States
^h Division of Emergency Medicine, Washington University School of Medicine in St. Louis

Abstract
The coronavirus disease 2019 (COVID-19) pandemic has in some regions overwhelmed the capacity and staffing needs of healthcare systems, necessitating the provision of resources and staff from different disciplines to aid COVID treatment teams. Stroke centers have multidisciplinary clinical and procedural expertise to support COVID treatment teams. Staff safety and patient safety are essential, as are open lines of communication between stroke center leaders and hospital leadership in a pandemic where policies and procedures can change or evolve rapidly. Support needs to be allocated in a way that allows for the continued operation of a fully capable stroke center, with the ability to adjust if stroke center volume or staff attrition requires.

Author Keywords
coronavirus;  COVID-19;  hospital;  pandemic;  patients

Document Type: Article
Publication Stage: Final
Source: Scopus

Default-mode network streams for coupling to language and control systems
(2020) Proceedings of the National Academy of Sciences of the United States of America, 117 (29), pp. 17308-17319.

Gordon, E.M.^a b c , Laumann, T.O.^d , Marek, S.^e , Raut, R.V.^f , Gratton, C.^g , Newbold, D.J.^e , Greene, D.J.^d f , Coalson, R.S.^e f , Snyder, A.Z.^e f , Schlaggar, B.L.^h i j , Petersen, S.E.^e f k l , Dosenbach, N.U.F.^{e f m n o} , Nelson, S.M.^b c p q

^a Veterans Integrated Service Network 17 Center of Excellence for Research on Returning War Veterans, US Department of Veterans Affairs, Waco, TX 76711;
^b Center for Vital Longevity, School of Behavioral and Brain Sciences, University of Texas at Dallas, Dallas, United States
^c Department of Psychology and Neuroscience, Baylor University, Waco, United States
^d Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110
^e Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110
^f Department of Radiology, Washington University School of Medicine, St. Louis, MO 63110
^g Department of Psychology, Northwestern University, Evanston, IL 60208, United States
^h Kennedy Krieger Institute, Baltimore, MD 21205, United States
ⁱ Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD 21205, United States
^j Department of Pediatrics, Johns Hopkins University School of Medicine, Baltimore, MD 21205, United States
^k Department of Neuroscience, Washington University School of Medicine, St. Louis, MO 63110
^l Department of Psychological & Brain Sciences, Washington University School of Medicine, St. Louis, MO 63110
^m Department of Pediatrics, Washington University School of Medicine, St. Louis, MO 63110
ⁿ Department of Biomedical Engineering, Washington University School of Medicine, St. Louis, MO 63110
^o Program in Occupational Therapy, Washington University School of Medicine, St. Louis, MO 63110
^p Veterans Integrated Service Network 17 Center of Excellence for Research on Returning War Veterans, US Department of Veterans Affairs, Waco, United States
^q Department of Psychiatry and Behavioral Science, Texas A&M Health Science Center, Bryan, United States

Abstract
The human brain is organized into large-scale networks identifiable using resting-state functional connectivity (RSFC). These functional networks correspond with broad cognitive domains; for example, the Default-mode network (DMN) is engaged during internally oriented cognition. However, functional networks may contain hierarchical substructures corresponding with more specific cognitive functions. Here, we used individual-specific precision RSFC to test whether network substructures could be identified in 10 healthy human brains. Across all subjects and networks, individualized network subdivisions were more valid-more internally homogeneous and better matching spatial patterns of task activation-than canonical networks. These measures of validity were maximized at a hierarchical scale that contained ∼83 subnetworks across the brain. At this scale, nine DMN subnetworks exhibited topographical similarity across subjects, suggesting that this approach identifies homologous neurobiological circuits across individuals. Some DMN subnetworks matched known features of brain organization corresponding with cognitive functions. Other subnetworks represented separate streams by which DMN couples with other canonical large-scale networks, including language and control networks. Together, this work provides a detailed organizational framework for studying the DMN in individual humans.

Author Keywords
brain networks;  Default network;  fMRI;  functional connectivity;  individual variability

Document Type: Article
Publication Stage: Final
Source: Scopus

Translation information processing is regulated by protein kinase C-dependent mechanism in Purkinje cells in murine posterior vermis
(2020) Proceedings of the National Academy of Sciences of the United States of America, 117 (29), pp. 17348-17358.

Hernández, R.G.^a , De Zeeuw, C.I.^b , Zhang, R.^a , Yakusheva, T.A.^c , Blazquez, P.M.^d

^a Department of Otolaryngology, Washington University, St. Louis, MO 63110
^b Department of Neuroscience, Erasmus University Medical Center, DR Rotterdam, 3000, Netherlands
^c Department of Otolaryngology, Washington University, St. Louis, MO 63110; pablo@wustl.edu
^d Department of Otolaryngology, Washington University, St. Louis, MO 63110; yakushevat@wustl.edu pablo@wustl.edu

Abstract
The cerebellar posterior vermis generates an estimation of our motion (translation) and orientation (tilt) in space using cues originating from semicircular canals and otolith organs. Theoretical work has laid out the basic computations necessary for this signal transformation, but details on the cellular loci and mechanisms responsible are lacking. Using a multicomponent modeling approach, we show that canal and otolith information are spatially and temporally matched in mouse posterior vermis Purkinje cells and that Purkinje cell responses combine translation and tilt information. Purkinje cell-specific inhibition of protein kinase C decreased and phase-shifted the translation component of Purkinje cell responses, but did not affect the tilt component. Our findings suggest that translation and tilt signals reach Purkinje cells via separate information pathways and that protein kinase C-dependent mechanisms regulate translation information processing in cerebellar cortex output neurons.

Author Keywords
cerebellar plasticity;  posterior vermis;  Purkinje cell;  spatial navigation;  vestibular

Document Type: Article
Publication Stage: Final
Source: Scopus

Editorial: Decoding the Fetal Circadian System and Its Role in Adult Sickness and Health: Melatonin, a Dark History
(2020) Frontiers in Endocrinology, 11, art. no. 380, .

Torres-Farfan, C.^a b , Cipolla Neto, J.^c , Herzog, E.D.^d

^a Laboratory of Developmental Chronobiology, Faculty of Medicine, Universidad Austral de Chile, Valdivia, Chile
^b Centro Interdisciplinario de Estudios del Sistema Nervioso (CISNe), Faculty of Medicine, Universidad Austral de Chile, Valdivia, Chile
^c Department of Physiology and Biophysics, Institute of Biomedical Sciences, University of São Paulo, São Paulo, Brazil
^d Department of Biology, Washington University, St. Louis, MO, United States

Author Keywords
circadian rhythms;  DOHaD (developmental origins of health and disease);  epigenetic;  melatonin;  pregnancy

Document Type: Editorial
Publication Stage: Final
Source: Scopus
Access Type: Open Access

Lifetime patterns of comorbidity in eating disorders: An approach using sequence analysis
(2020) European Eating Disorders Review, .

Van Alsten, S.C., Duncan, A.E.

Brown School, Washington University in St. Louis, St. Louis, MO, United States

Abstract
Objective: Eating disorders (EDs) have high rates of psychiatric comorbidity. This study aimed to characterize longitudinal patterns of comorbidities in adults with EDs. Methods: Sequence analysis and hierarchical clustering were applied to ages of onset and recency for select eating, substance, mood, and anxiety disorders from the 479 participants in the Collaborative Psychiatric Epidemiology Surveys with lifetime DSM-IV bulimia nervosa, binge eating disorder, or anorexia nervosa. External validators were compared across clusters using chi-square tests. Results: Five clusters were identified among individuals with any lifetime ED based on longitudinal sequence of psychiatric disorder onset and remission, characterized as: (1) multi-comorbid with early onset of comorbid disorder (46%); (2) moderate preeminent anxiety with moderate comorbidity and low ED persistence (20%); (3) late ED onset with low comorbidity (15%); (4) early onset, persistent ED with low comorbidity (14%); and (5) chronic, early onset depression (5%). Clusters were well differentiated by significant differences in age, body mass index, race, and psychiatric indicators. Conclusions: This study demonstrates a new method to assess clustering of comorbidity among individuals with lifetime EDs. Having a psychiatric diagnosis prior to an ED was associated with greater psychopathology and illness duration. Information on timing of diagnoses may allow for more refined comorbidity classification. © 2020 John Wiley & Sons, Ltd and Eating Disorders Association

Author Keywords
cluster analysis;  comorbidity;  development;  eating disorder

Document Type: Article
Publication Stage: Article in Press
Source: Scopus

Long-Term Influence of Electrode Array Length on Speech Recognition in Cochlear Implant Users
(2020) Laryngoscope, .

Canfarotta, M.W.^a , Dillon, M.T.^a , Buchman, C.A.^b , Buss, E.^a , O’Connell, B.P.^a , Rooth, M.A.^a , King, E.R.^c , Pillsbury, H.C.^a , Adunka, O.F.^d , Brown, K.D.^a

^a Department of Otolaryngology–Head and Neck Surgery, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
^b Department of Otolaryngology–Head and Neck Surgery, Washington University School of Medicine, St. Louis, MO, United States
^c Department of Audiology, University of North Carolina Health Care, Chapel Hill, NC, United States
^d Department of Otolaryngology–Head and Neck Surgery, The Ohio State University, Columbus, OH, United States

Abstract
Objectives/Hypothesis: Results from a prospective trial demonstrated better speech recognition for cochlear implant (CI) recipients implanted with a long lateral wall electrode array compared to subjects with a short array after 1 year of listening experience. As short array recipients may require an extended adaptation period, this study investigated whether differences in speech recognition continued through 4 years of CI use. Study Design: Long-term follow-up of a prospective randomized trial. Methods: Subjects were randomized to receive a MED-EL medium (24 mm) or standard (31.5 mm) array. Linear mixed models compared speech recognition between cohorts with word recognition in quiet and sentence recognition in noise at 1, 3, 6, 12, 24, and 48 months postactivation. Postoperative imaging and electric frequency filters were reviewed to assess the influence of frequency-to-place mismatch and angular separation between neighboring contacts, a metric associated with peripheral spectral selectivity. Results: Long (31.5 mm) array recipients demonstrated superior speech recognition out to 4 years postactivation. There was a significant effect of angular separation between contacts, with more closely spaced contacts associated with poorer speech recognition. There was no significant effect of mismatch, yet this may have been obscured by changes in frequency filters over time. Conclusions: Conventional MED-EL CI recipients implanted with 31.5-mm arrays experience better speech recognition than 24-mm array recipients, initially and with long-term listening experience. The benefit conferred by longer arrays in the present cohort can be partially attributed to more widely spaced electrode contacts, presumably a result of reduced channel interaction. Level of Evidence: 2 Laryngoscope, 2020. © 2020 The American Laryngological, Rhinological and Otological Society, Inc.

Author Keywords
channel interaction;  Cochlear implant;  frequency-to-place mismatch;  insertion depth;  speech outcomes

Document Type: Article
Publication Stage: Article in Press
Source: Scopus

Genome-wide DNA methylation differences in nucleus accumbens of smokers vs. nonsmokers
(2020) Neuropsychopharmacology, .

Markunas, C.A.^a , Semick, S.A.^b , Quach, B.C.^a , Tao, R.^b , Deep-Soboslay, A.^b , Carnes, M.U.^a , Bierut, L.J.^c , Hyde, T.M.^b , Kleinman, J.E.^b , Johnson, E.O.^a d , Jaffe, A.E.^b , Hancock, D.B.^a

^a GenOmics, Bioinformatics, and Translational Research Center, Biostatistics and Epidemiology Division, RTI International, Research Triangle Park, NC, United States
^b Lieber Institute for Brain Development (LIBD), Baltimore, MD, United States
^c Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, United States
^d Fellow Program, RTI International, Research Triangle Park, NC, United States

Abstract
Numerous DNA methylation (DNAm) biomarkers of cigarette smoking have been identified in peripheral blood studies, but because of tissue specificity, blood-based studies may not detect brain-specific smoking-related DNAm differences that may provide greater insight as neurobiological indicators of smoking and its exposure effects. We report the first epigenome-wide association study (EWAS) of smoking in human postmortem brain, focusing on nucleus accumbens (NAc) as a key brain region in developing and reinforcing addiction. Illumina HumanMethylation EPIC array data from 221 decedents (120 European American [23% current smokers], 101 African American [26% current smokers]) were analyzed. DNAm by smoking (current vs. nonsmoking) was tested within each ancestry group using robust linear regression models adjusted for age, sex, cell-type proportion, DNAm-derived negative control principal components (PCs), and genotype-derived PCs. The resulting ancestry-specific results were combined via meta-analysis. We extended our NAc findings, using published smoking EWAS results in blood, to identify DNAm smoking effects that are unique (tissue-specific) vs. shared between tissues (tissue-shared). We identified seven CpGs (false discovery rate < 0.05), of which three CpGs are located near genes previously indicated with blood-based smoking DNAm biomarkers: ZIC1, ZCCHC24, and PRKDC. The other four CpGs are novel for smoking-related DNAm changes: ABLIM3, APCDD1L, MTMR6, and CTCF. None of the seven smoking-related CpGs in NAc are driven by genetic variants that share association signals with predisposing genetic risk variants for smoking, suggesting that the DNAm changes reflect consequences of smoking. Our results provide the first evidence for smoking-related DNAm changes in human NAc, highlighting CpGs that were undetected as peripheral biomarkers and may reflect brain-specific responses to smoking exposure. © 2020, The Author(s), under exclusive licence to American College of Neuropsychopharmacology.

Document Type: Article
Publication Stage: Article in Press
Source: Scopus

How Outcome Uncertainty Mediates Attention, Learning, and Decision-Making
(2020) Trends in Neurosciences, .

Monosov, I.E.^a b c

^a Department of Neuroscience and Neurosurgery, Washington University School of Medicine in St. LouisMO, United States
^b Department of Biomedical Engineering, Washington University School of Medicine in St. LouisMO, United States
^c Washington University Pain Center, Washington University School of Medicine in St. LouisMO, United States

Abstract
Animals and humans evolved sophisticated nervous systems that endowed them with the ability to form internal-models or beliefs and make predictions about the future to survive and flourish in a world in which future outcomes are often uncertain. Crucial to this capacity is the ability to adjust behavioral and learning policies in response to the level of uncertainty. Until recently, the neuronal mechanisms that could underlie such uncertainty-guided control have been largely unknown. In this review, I discuss newly discovered neuronal circuits in primates that represent uncertainty about future rewards and propose how they guide information-seeking, attention, decision-making, and learning to help us survive in an uncertain world. Lastly, I discuss the possible relevance of these findings to learning in artificial systems. © 2020 Elsevier Ltd

Author Keywords
artificial intelligence;  basal-forebrain;  basal-ganglia;  cingulate;  information-seeking

Document Type: Review
Publication Stage: Article in Press
Source: Scopus

Diabetic Retinopathy Screening with Automated Retinal Image Analysis in a Primary Care Setting Improves Adherence to Ophthalmic Care
(2020) Ophthalmology Retina, .

Liu, J.^a , Gibson, E.^a , Ramchal, S.^a , Shankar, V.^a , Piggott, K.^a , Sychev, Y.^a , Li, A.S.^b , Rao, P.K.^a , Margolis, T.P.^a , Fondahn, E.^c , Bhaskaranand, M.^d , Solanki, K.^d , Rajagopal, R.^a

^a Department of Ophthalmology and Visual Sciences, Washington University School of Medicine, St. Louis, MO, United States
^b Department of Ophthalmology and Visual Sciences, University of Maryland School of Medicine, Baltimore, MD, United States
^c Department of Medicine, Washington University School of Medicine, St. Louis, MO, United States
^d Eyenuk, Inc., Woodland Hills, CA, United States

Abstract
Purpose: Retinal screening examinations can prevent vision loss resulting from diabetes but are costly and highly underused. We hypothesized that artificial intelligence-assisted nonmydriatic point-of-care screening administered during primary care visits would increase the adherence to recommendations for follow-up eye care in patients with diabetes. Design: Prospective cohort study. Participants: Adults 18 years of age or older with a clinical diagnosis of diabetes being cared for in a metropolitan primary care practice for low-income patients. Methods: All participants underwent nonmydriatic fundus photography followed by automated retinal image analysis with human supervision. Patients with positive or inconclusive screening results were referred for comprehensive ophthalmic evaluation. Adherence to referral recommendations was recorded and compared with the historical adherence rate from the same clinic. Main Outcome Measure: Rate of adherence to eye screening recommendations. Results: By automated screening, 8.3% of the 180 study participants had referable diabetic eye disease, 13.3% had vision-threatening disease, and 29.4% showed inconclusive results. The remaining 48.9% showed negative screening results, confirmed by human overread, and were not referred for follow-up ophthalmic evaluation. Overall, the automated platform showed a sensitivity of 100% (confidence interval, 92.3%–100%) in detecting an abnormal screening results, whereas its specificity was 65.7% (confidence interval, 57.0%–73.7%). Among patients referred for follow-up ophthalmic evaluation, the adherence rate was 55.4% at 1 year compared with the historical adherence rate of 18.7% (P < 0.0001, Fisher exact test). Conclusions: Implementation of an automated diabetic retinopathy screening system in a primary care clinic serving a low-income metropolitan patient population improved adherence to follow-up eye care recommendations while reducing referrals for patients with low-risk features. © 2020 American Academy of Ophthalmology

Document Type: Conference Paper
Publication Stage: Article in Press
Source: Scopus

Quantitative Serial CT Imaging-Derived Features Improve Prediction of Malignant Cerebral Edema after Ischemic Stroke
(2020) Neurocritical Care, .

Foroushani, H.M.^a , Hamzehloo, A.^b , Kumar, A.^b , Chen, Y.^b , Heitsch, L.^c , Slowik, A.^d , Strbian, D.^e , Lee, J.-M.^b , Marcus, D.S.^f , Dhar, R.^b

^a Department of Electrical and Systems Engineering, Washington University in St. Louis, Saint Louis, United States
^b Department of Neurology, Washington University in St. Louis School of Medicine, 660 S Euclid Avenue, Campus Box 8111, Saint Louis, MO 63110, United States
^c Department of Emergency Medicine, Washington University School of Medicine, Washington, United States
^d Department of Neurology, Jagiellonian University Medical College, Kraków, Poland
^e Department of Neurology, Helsinki University Hospital, Helsinki, Finland
^f Department of Radiology, Washington University School of Medicine, Saint Louis, United States

Abstract
Introduction: Malignant cerebral edema develops in a small subset of patients with hemispheric strokes, precipitating deterioration and death if decompressive hemicraniectomy (DHC) is not performed in a timely manner. Predicting which stroke patients will develop malignant edema is imprecise based on clinical data alone. Head computed tomography (CT) imaging is often performed at baseline and 24-h. We determined the incremental value of incorporating imaging-derived features from serial CTs to enhance prediction of malignant edema. Methods: We identified hemispheric stroke patients at three sites with NIHSS ≥ 7 who had baseline as well as 24-h clinical and CT imaging data. We extracted quantitative imaging features from baseline and follow-up CTs, including CSF volume, intracranial reserve (CSF/cranial volume), as well as midline shift (MLS) and infarct-related hypodensity volume. Potentially lethal malignant edema was defined as requiring DHC or dying with MLS over 5-mm. We built machine-learning models using logistic regression first with baseline data and then adding 24-h data including reduction in CSF volume (ΔCSF). Model performance was evaluated with cross-validation using metrics of recall (sensitivity), precision (predictive value), as well as area under receiver-operating-characteristic and precision-recall curves (AUROC, AUPRC). Results: Twenty of 361 patients (6%) died or underwent DHC. Baseline clinical variables alone had recall of 60% with low precision (7%), AUROC 0.59, AUPRC 0.15. Adding baseline intracranial reserve improved recall to 80% and AUROC to 0.82 but precision remained only 16% (AUPRC 0.28). Incorporating ΔCSF improved AUPRC to 0.53 (AUROC 0.91) while all imaging features further improved prediction (recall 90%, precision 38%, AUROC 0.96, AUPRC 0.66). Conclusion: Incorporating quantitative CT-based imaging features from baseline and 24-h CT enhances identification of patients with malignant edema needing DHC. Further refinements and external validation of such imaging-based machine-learning models are required. © 2020, Springer Science+Business Media, LLC, part of Springer Nature and Neurocritical Care Society.

Author Keywords
Cerebral edema;  Imaging;  Prediction models;  Regression;  Stroke

Document Type: Article
Publication Stage: Article in Press
Source: Scopus