WashU weekly Neuroscience publications | Office of Neuroscience Research

"Differential neural dynamics underling pragmatic and semantic affordance processing in macaque ventral premotor cortex" (2019) Scientific Reports

Differential neural dynamics underling pragmatic and semantic affordance processing in macaque ventral premotor cortex
(2019) Scientific Reports, 9 (1), art. no. 11700, .

Maranesi, M.^a , Bruni, S.^a ^b , Livi, A.^a ^c , Donnarumma, F.^d , Pezzulo, G.^d , Bonini, L.^a

^a Department of Medicine and Surgery, University of Parma, via Volturno 39, Parma, 43125, Italy
^b Center for Neural Science, New York University, New York, NY, United States
^c Department of Neuroscience, Washington University, St. Louis, MO, United States
^d Institute of Cognitive Sciences and Technologies, National Research Council, via S. Martino della Battaglia 44, Rome, 00185, Italy

Abstract
Premotor neurons play a fundamental role in transforming physical properties of observed objects, such as size and shape, into motor plans for grasping them, hence contributing to “pragmatic” affordance processing. Premotor neurons can also contribute to “semantic” affordance processing, as they can discharge differently even to pragmatically identical objects depending on their behavioural relevance for the observer (i.e. edible or inedible objects). Here, we compared the response of monkey ventral premotor area F5 neurons tested during pragmatic (PT) or semantic (ST) visuomotor tasks. Object presentation responses in ST showed shorter latency and lower object selectivity than in PT. Furthermore, we found a difference between a transient representation of semantic affordances and a sustained representation of pragmatic affordances at both the single neuron and population level. Indeed, responses in ST returned to baseline within 0.5 s whereas in PT they showed the typical sustained visual-to-motor activity during Go trials. In contrast, during No-go trials, the time course of pragmatic and semantic information processing was similar. These findings suggest that premotor cortex generates different dynamics depending on pragmatic and semantic information provided by the context in which the to-be-grasped object is presented. © 2019, The Author(s).

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

"Non-coding variability at the APOE locus contributes to the Alzheimer’s risk" (2019) Nature Communications

Non-coding variability at the APOE locus contributes to the Alzheimer’s risk
(2019) Nature Communications, 10 (1), art. no. 3310, .

Zhou, X.^a , Chen, Y.^a ^b ^c , Mok, K.Y.^a ^d , Kwok, T.C.Y.^e , Mok, V.C.T.^f , Guo, Q.^g , Ip, F.C.^a ^b , Chen, Y.^a ^b ^c , Mullapudi, N.^a , Weiner, M.W.^l , Aisen, P.^m , Petersen, R.ⁿ , Jack, C.R.ⁿ , Jagust, W.^o , Trojanowski, J.Q.^p , Toga, A.W.^q , Beckett, L.^r , Green, R.C.^s , Saykin, A.J.^t , Morris, J.^u , Shaw, L.M.^p , Khachaturian, Z.^r ^v , Sorensen, G.^w , Kuller, L.^x , Raichle, M.^u , Paul, S.^y , Davies, P.^z , Fillit, H.^aa , Hefti, F.^ab , Holtzman, D.^u , Mesulam, M.M.^ac , Potter, W.^ad , Snyder, P.^ae , Schwartz, A.^af , Montine, T.^ag , Thomas, R.G.^ag , Donohue, M.^ag , Walter, S.^ag , Gessert, D.^ag , Sather, T.^ag , Jiminez, G.^ag , Harvey, D.^r , Bernstein, M.ⁿ , Thompson, P.^ah , Schuff, N.^l ^r , Borowski, B.ⁿ , Gunter, J.ⁿ , Senjem, M.ⁿ , Vemuri, P.ⁿ , Jones, D.ⁿ , Kantarci, K.ⁿ , Ward, C.ⁿ , Koeppe, R.A.^ai , Foster, N.^aj , Reiman, E.M.^ak , Chen, K.^ak , Mathis, C.^aa , Landau, S.^o , Cairns, N.J.^u , Householder, E.^u , Taylor-Reinwald, L.^u , Lee, V.^p , Korecka, M.^p , Figurski, M.^p , Crawford, K.^q , Neu, S.^q , Foroud, T.M.^t , Potkin, S.G.^al , Shen, L.^t , Faber, K.^t , Kim, S.^t , Nho, K.^t , Thal, L.^m , Buckholtz, N.^am , Albert, M.^an , Frank, R.^ao , Hsiao, J.^am , Kaye, J.^ap , Quinn, J.^ap , Lind, B.^ap , Carter, R.^ap , Dolen, S.^ap , Schneider, L.S.^q , Pawluczyk, S.^q , Beccera, M.^q , Teodoro, L.^q , Spann, B.M.^q , Brewer, J.^m , Vanderswag, H.^m , Fleisher, A.^m ^ak , Heidebrink, J.L.^ai , Lord, J.L.^ai , Mason, S.S.ⁿ , Albers, C.S.ⁿ , Knopman, D.ⁿ , Johnson, K.ⁿ , Doody, R.S.^aq , Villanueva-Meyer, J.^aq , Chowdhury, M.^aq , Rountree, S.^aq , Dang, M.^aq , Stern, Y.^aq , Honig, L.S.^aq , Bell, K.L.^aq , Ances, B.^u , Carroll, M.^u , Leon, S.^u , Mintun, M.A.^u , Schneider, S.^u , Oliver, A.^u , Marson, D.^ar , Griffith, R.^ar , Clark, D.^ar , Geldmacher, D.^ar , Brockington, J.^ar , Roberson, E.^ar , Grossman, H.^as , Mitsis, E.^as , de Toledo-Morrell, L.^at , Shah, R.C.^at , Duara, R.^au , Varon, D.^au , Greig, M.T.^au , Roberts, P.^au , Onyike, C.^an , D’Agostino, D.^an , Kielb, S.^an , Galvin, J.E.^av , Cerbone, B.^av , Michel, C.A.^av , Rusinek, H.^av , de Leon, M.J.^av , Glodzik, L.^av , De Santi, S.^av , Doraiswamy, P.M.^aw , Petrella, J.R.^aw , Wong, T.Z.^aw , Arnold, S.E.^p , Karlawish, J.H.^p , Wolk, D.^p , Smith, C.D.^ax , Jicha, G.^ax , Hardy, P.^ax , Sinha, P.^ax , Oates, E.^ax , Conrad, G.^ax , Lopez, O.L.^x , Oakley, M.A.^x , Simpson, D.M.^an , Porsteinsson, A.P.^ay , Goldstein, B.S.^az , Martin, K.^az , Makino, K.M.^az , Ismail, M.S.^az , Brand, C.^az , Mulnard, R.A.^al , Thai, G.^al , McAdams-Ortiz, C.^al , Womack, K.^az , Mathews, D.^az , Quiceno, M.^az , Diaz-Arrastia, R.^az , King, R.^az , Weiner, M.^az , Martin-Cook, K.^az , DeVous, M.^az , Levey, A.I.^ba , Lah, J.J.^ba , Cellar, J.S.^ba , Burns, J.M.^bb , Anderson, H.S.^bb , Swerdlow, R.H.^bb , Apostolova, L.^ah , Tingus, K.^ah , Woo, E.^ah , Silverman, D.H.S.^ah , Lu, P.H.^ah , Bartzokis, G.^ah , Graff-Radford, N.R.^bc , Parfitt, F.^bc , Kendall, T.^bc , Johnson, H.^bc , Farlow, M.R.^t , Hake, A.M.^t , Matthews, B.R.^t , Herring, S.^t , Hunt, C.^t , van Dyck, C.H.^bd , Carson, R.E.^bd , MacAvoy, M.G.^bd , Chertkow, H.^be , Bergman, H.^be , Hosein, C.^be , Hsiung, G.-Y.R.^bf , Feldman, H.^bf , Mudge, B.^bf , Assaly, M.^bf , Bernick, C.^bg , Munic, D.^bg , Kertesz, A.^bh , Rogers, J.^bh , Trost, D.^bh , Kerwin, D.^ac , Lipowski, K.^ac , Wu, C.-K.^ac , Johnson, N.^ac , Sadowsky, C.^bi , Martinez, W.^bi , Villena, T.^bi , Turner, R.S.^bj , Johnson, K.^bj , Reynolds, B.^bj , Sperling, R.A.^s , Johnson, K.A.^s , Marshall, G.^s , Frey, M.^s , Lane, B.^s , Rosen, A.^s , Tinklenberg, J.^s , Sabbagh, M.N.^bk , Belden, C.M.^bk , Jacobson, S.A.^bk , Sirrel, S.A.^bk , Kowall, N.^bk , Killiany, R.^bl , Budson, A.E.^bl , Norbash, A.^bl , Johnson, P.L.^bl , Allard, J.^bm , Lerner, A.^bn , Ogrocki, P.^bn , Hudson, L.^bn , Fletcher, E.^r , Carmichael, O.^r , Olichney, J.^r , DeCarli, C.^r , Kittur, S.^bo , Borrie, M.^bp , Lee, T.-Y.^bp , Bartha, R.^bp , Johnson, S.^bq , Asthana, S.^bq , Carlsson, C.M.^bq , Preda, A.^ah , Nguyen, D.^ah , Tariot, P.^aj , Reeder, S.^aj , Bates, V.^br , Capote, H.^br , Rainka, M.^br , Scharre, D.W.^bs , Kataki, M.^bs , Adeli, A.^bs , Zimmerman, E.A.^bt , Celmins, D.^bt , Brown, A.D.^bt , Pearlson, G.D.^bu , Blank, K.^bu , Anderson, K.^bu , Santulli, R.B.^bv , Kitzmiller, T.J.^bv , Schwartz, E.S.^bv , Sink, K.M.^bw , Williamson, J.D.^bw , Garg, P.^bw , Watkins, F.^bw , Ott, B.R.^bx , Querfurth, H.^bx , Tremont, G.^bx , Salloway, S.^by , Malloy, P.^by , Correia, S.^by , Rosen, H.J.^l , Miller, B.L.^l , Mintzer, J.^bz , Spicer, K.^bz , Bachman, D.^bz , Pasternak, S.^bh , Rachinsky, I.^bh , Drost, D.^bh , Pomara, N.^ca , Hernando, R.^ca , Sarrael, A.^ca , Schultz, S.K.^cb , Boles Ponto, L.L.^cb , Shim, H.^cb , Smith, K.E.^cb , Relkin, N.^y , Chaing, G.^y , Raudin, L.^v ^y , Smith, A.^cc , Fargher, K.^cc , Raj, B.A.^cc , Neylan, T.^l , Grafman, J.^ac , Davis, M.^m , Morrison, R.^m , Hayes, J.^l , Finley, S.^l , Friedl, K.^cd , Fleischman, D.^at , Arfanakis, K.^at , James, O.^aw , Massoglia, D.^bz , Fruehling, J.J.^bq , Harding, S.^bq , Peskind, E.R.^ag , Petrie, E.C.^bs , Li, G.^bs , Yesavage, J.A.^ce , Taylor, J.L.^ce , Furst, A.J.^ce , Giusti-Rodríguez, P.^h , Sullivan, P.F.^h ⁱ ^j , Hardy, J.^d , Fu, A.K.Y.^a ^b , Li, Y.^h ^k , Ip, N.Y.^a ^b , Alzheimer’s Disease Neuroimaging Initiative^h

^a Division of Life Science, State Key Laboratory of Molecular Neuroscience and Molecular Neuroscience Center, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong
^b Guangdong Provincial Key Laboratory of Brain Science, Disease and Drug Development, HKUST Shenzhen Research Institute, Shenzhen, Guangdong 518057, China
^c The Brain Cognition and Brain Disease Institute, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen-Hong Kong Institute of Brain Science-Shenzhen Fundamental Research Institutions, Shenzhen, Guangdong 518055, China
^d Department of Molecular Neuroscience, University College London Institute of Neurology, London, WC1N 3BG, United Kingdom
^e Therese Pei Fong Chow Research Centre for Prevention of Dementia, Division of Geriatrics, Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Shatin, Hong Kong
^f Gerald Choa Neuroscience Centre, Lui Che Woo Institute of Innovative Medicine, Therese Pei Fong Chow Research Centre for Prevention of Dementia, Division of Neurology, Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Shatin, Hong Kong
^g Department of Neurology, Huashan Hospital, Fudan University, Shanghai, 200040, China
^h Department of Genetics, University of North Carolina, Chapel Hill, NC 27599, United States
ⁱ Department of Medical Epidemiology and Biostatistics, Karolinska Institute, Stockholm, SE-171-77, Sweden
^j Department of Psychiatry, University of North Carolina, Chapel Hill, NC 27599, United States
^k Department of Biostatistics and Department of Computer Science, University of North Carolina, Chapel Hill, NC 27599, United States
^l UC San Francisco, San Francisco, CA 94143, United States
^m UC San Diego, San Diego, CA 92093, United States
ⁿ Mayo Clinic, Rochester, NY 14603, United States
^o UC Berkeley, Berkeley, CA 94720, United States
^p UPenn, Philadelphia, PA 9104, United States
^q USC, Los Angeles, CA 90089, United States
^r UC Davis, Davis, CA 95616, United States
^s Brigham and Women’s Hospital/Harvard Medical School, Boston, MA 02115, United States
^t Indiana University, Bloomington, IN 47405, United States
^u Washington University in St Louis, St Louis, MI 63130, United States
^v Prevent Alzheimer’s Disease 2020, Rockville, MD 20850, United States
^w Siemens, Munich, 80333, Germany
^x University of Pittsburgh, Pittsburgh, PA 15260, United States
^y Weill Cornell Medical College, Cornell University, New York City, NY 10065, United States
^z Albert Einstein College of Medicine of Yeshiva University, Bronx, NY 10461, United States
^aa AD Drug Discovery Foundation, New York City, NY 10019, United States
^ab Acumen Pharmaceuticals, Livermore, CA 94551, United States
^ac Northwestern University, Evanston and Chicago, Evanston, IL 60208, United States
^ad National Institute of Mental Health, Rockville, MD 20852, United States
^ae Brown University, Providence, RI 02912, United States
^af Eli Lilly, Indianapolis, IN 46225, United States
^ag University of Washington, Seattle, WA 98195, United States
^ah UCLA, Los Angeles, CA 90095, United States
^ai University of Michigan, Ann Arbor, MI 48109, United States
^aj University of Utah, Salt Lake City, UT 84112, United States
^ak Banner Alzheimer’s Institute, Phoenix, AZ 85006, United States
^al UC Irvine, Irvine, CA 92697, United States
^am National Institute on Aging, Bethesda, MD 20892, United States
^an Johns Hopkins University, Baltimore, MD 21218, United States
^ao Richard Frank Consulting, Washington, 20001, United States
^ap Oregon Health and Science University, Portland, OR 97239, United States
^aq Baylor College of Medicine, Houston, TX 77030, United States
^ar University of Alabama, Birmingham, AL 35233, United States
^as Mount Sinai School of Medicine, New York City, NY 10029, United States
^at Rush University Medical Center, Chicago, IL 60612, United States
^au Wien Center, Miami, FL 33140, United States
^av New York University, New York City, NY 10003, United States
^aw Duke University Medical Center, Durham, NC 27710, United States
^ax University of Kentucky, Lexington, KY 0506, United States
^ay University of Rochester Medical Center, Rochester, NY 14642, United States
^az University of Texas Southwestern Medical School, Dallas, TX 75390, United States
^ba Emory University, Atlanta, GA 30322, United States
^bb Medical Center, University of Kansas, Kansas City, KS 66103, United States
^bc Mayo Clinic, Jacksonville, FL 32224, United States
^bd Yale University School of Medicine, New Haven, CT 06510, United States
^be McGill University/Montreal-Jewish General Hospital, Montreal, QC H3T 1E2, Canada
^bf University of British Columbia Clinic for AD and Related Disorders, Vancouver, BC V6T 1Z3, Canada
^bg Cleveland Clinic Lou Ruvo Center for Brain Health, Las Vegas, NV 89106, United States
^bh St Joseph’s Health Care, London, ON N6A 4V2, Canada
^bi Premiere Research Institute, Palm Beach Neurology, Miami, FL 33407, United States
^bj Georgetown University Medical Center, Washington, DC 20007, United States
^bk Banner Sun Health Research Institute, Sun City, AZ 85351, United States
^bl Boston University, Boston, MA 02215, United States
^bm Howard University, Washington, DC 20059, United States
^bn Case Western Reserve University, Cleveland, OH 20002, United States
^bo Neurological Care of CNY, Liverpool, NY 13088, United States
^bp Parkwood Hospital, London, ON N6C 0A7, Canada
^bq University of Wisconsin, Madison, WI 53706, United States
^br Dent Neurologic Institute, Amherst, NY 14226, United States
^bs Ohio State University, Columbus, OH 43210, United States
^bt Albany Medical College, Albany, NY 12208, United States
^bu Olin Neuropsychiatry Research Center, Hartford Hospital, Hartford, CT 06114, United States
^bv Dartmouth-Hitchcock Medical Center, Lebanon, NH 03766, United States
^bw Wake Forest University Health Sciences, Winston-Salem, NC 27157, United States
^bx Rhode Island Hospital, Providence, RI 02903, United States
^by Butler Hospital, Providence, RI 02906, United States
^bz Medical University South Carolina, Charleston, SC 29425, United States
^ca Nathan Kline Institute, Orangeburg, NY 10962, United States
^cb University of Iowa College of Medicine, Iowa City, IA 52242, United States
^cc USF Health Byrd Alzheimer’s Institute, University of South Florida, Tampa, FL 33613, United States
^cd Department of Defense, Arlington, VA 22350, United States
^ce Stanford University, Stanford, CA 94305, United States

Abstract
Alzheimer’s disease (AD) is a leading cause of mortality in the elderly. While the coding change of APOE-ε4 is a key risk factor for late-onset AD and has been believed to be the only risk factor in the APOE locus, it does not fully explain the risk effect conferred by the locus. Here, we report the identification of AD causal variants in PVRL2 and APOC1 regions in proximity to APOE and define common risk haplotypes independent of APOE-ε4 coding change. These risk haplotypes are associated with changes of AD-related endophenotypes including cognitive performance, and altered expression of APOE and its nearby genes in the human brain and blood. High-throughput genome-wide chromosome conformation capture analysis further supports the roles of these risk haplotypes in modulating chromatin states and gene expression in the brain. Our findings provide compelling evidence for additional risk factors in the APOE locus that contribute to AD pathogenesis. © 2019, The Author(s).

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

"Reward motivation and neurostimulation interact to improve working memory performance in healthy older adults: A simultaneous tDCS-fNIRS study" (2019) NeuroImage

Reward motivation and neurostimulation interact to improve working memory performance in healthy older adults: A simultaneous tDCS-fNIRS study
(2019) NeuroImage, 202, art. no. 116062, .

Di Rosa, E.^a ^b , Brigadoi, S.^c ^d , Cutini, S.^c ^e , Tarantino, V.^a ^f , Dell’Acqua, R.^c ^e , Mapelli, D.^g , Braver, T.S.^b , Vallesi, A.^a ^h

^a Department of Neuroscience & Padova Neuroscience Center, University of Padova, Padova, Italy
^b Department of Psychological & Brain Sciences, Washington University in St. Louis, St. Louis, United States
^c Department of Developmental Psychology, University of Padova, Padova, Italy
^d Department of Information Engineering, University of Padova, Padova, Italy
^e Padova Neuroscience Center, University of Padova, Padova, Italy
^f Department of Psychology, Educational Science and Human Movement, University of Palermo, Palermo, Italy
^g Department of General Psychology, University of Padova, Padova, Italy
^h Brain Imaging and Neural Dynamics Research Group, IRCCS San Camillo Hospital, Venice, Italy

Abstract
Several studies have evaluated the effect of anodal transcranial direct current stimulation (tDCS) over the prefrontal cortex (PFC) for the enhancement of working memory (WM) performance in healthy older adults. However, the mixed results obtained so far suggest the need for concurrent brain imaging, in order to more directly examine tDCS effects. The present study adopted a continuous multimodal approach utilizing functional near-infrared spectroscopy (fNIRS) to examine the interactive effects of tDCS combined with manipulations of reward motivation. Twenty-one older adults (mean age = 69.7 years; SD = 5.05) performed an experimental visuo-spatial WM task before, during and after the delivery of 1.5 mA anodal tDCS/sham over the left prefrontal cortex (PFC). During stimulation, participants received performance-contingent reward for every fast and correct response during the WM task. In both sessions, hemodynamic activity of the bilateral frontal, motor and parietal areas was recorded across the entire duration of the WM task. Cognitive functions and reward sensitivity were also assessed with standard measures. Results demonstrated a significant impact of tDCS on both WM performance and hemodynamic activity. Specifically, faster responses in the WM task were observed both during and after anodal tDCS, while no differences were found under sham control conditions. However, these effects emerged only when taking into account individual visuo-spatial WM capacity. Additionally, during and after the anodal tDCS, increased hemodynamic activity relative to sham was observed in the bilateral PFC, while no effects of tDCS were detected in the motor and parietal areas. These results provide the first evidence of tDCS-dependent functional changes in PFC activity in healthy older adults during the execution of a WM task. Moreover, they highlight the utility of combining reward motivation with prefrontal anodal tDCS, as a potential strategy to improve WM efficiency in low performing healthy older adults. © 2019 Elsevier Inc.

Author Keywords
Cognitive aging; fNIRS; Prefrontal cortex; tDCS; Working memory

Document Type: Article
Publication Stage: Final
Source: Scopus

"Development of a brief clinician-reported outcome measure of multiple sclerosis signs and symptoms: The Clinician Rating of Multiple Sclerosis (CRoMS)" (2019) Multiple Sclerosis and Related Disorders

Development of a brief clinician-reported outcome measure of multiple sclerosis signs and symptoms: The Clinician Rating of Multiple Sclerosis (CRoMS)
(2019) Multiple Sclerosis and Related Disorders, 35, pp. 253-261.

Matza, L.S.^a , Stewart, K.D.^a , Phillips, G.^b , Delio, P.^c , Naismith, R.T.^d

^a Patient-centered Research, Evidera, Bethesda, MD, United States
^b Formerly with Value Based Medicine, Biogen, Cambridge, MA, United States
^c Neurology Associates of Santa Barbara, Santa Barbara, CA, United States
^d Washington University, St. Louis, MO, United States

Abstract
Objective: No available assessment tool offers a brief and psychometrically sound way for clinicians to quantify assessment of MS in a typical office visit. The objective of this study was to develop a brief clinician-reported outcome measure of MS signs and symptoms to standardize and quantify assessments that occur during a typical neurology office visit. Methods: A questionnaire, called the Clinician Rating of Multiple Sclerosis (CRoMS), was developed in the following steps: literature review; concept elicitation interviews (to generate questionnaire themes and content) with patients with MS (n = 14); concept elicitation interviews with neurologists (n = 9); online qualitative survey with neurologists in the US, UK, Germany, and Sweden (n = 72); online survey with neurologists to evaluate the first draft of the clinician-reported outcome measure (ClinRO) (n = 26); an in-person meeting with neurologists to discuss and revise the draft ClinRO (n = 9); and interviews with neurologists and MS nurses to further refine and finalize the ClinRO (n = 16). Results: Across all steps of this research, several signs and symptoms consistently emerged as important for assessment in a typical office visit: walking, balance, upper limb function, coordination, weakness, fatigue, pain, sensory symptoms, bladder function, visual function, cognition, spasticity, spasms, and mood. The importance of these signs and symptoms was supported by neurologists during the online surveys and the in-person meeting. Neurologists were generally able to complete the draft ClinRO measure without difficulty, although minor revisions were suggested to refine the ClinRO for future use. Conclusion: The CRoMS may be a useful tool for efficiently assessing the severity of MS symptoms. This brief clinician-reported measure could help standardize and quantify assessments in clinical studies and clinical settings. © 2019

Author Keywords
Clinician-reported outcome measure; ClinRO; Concept elicitation; MS; Multiple sclerosis

Document Type: Article
Publication Stage: Final
Source: Scopus

"Sensitivity of Mammalian Cone Photoreceptors to Infrared Light" (2019) Neuroscience

Sensitivity of Mammalian Cone Photoreceptors to Infrared Light
(2019) Neuroscience, 416, pp. 100-108.

Vinberg, F.^a , Palczewska, G.^b , Zhang, J.^c , Komar, K.^d ^e , Wojtkowski, M.^e ^f , Kefalov, V.J.^g , Palczewski, K.^c

^a John A. Moran Eye Center, University of Utah, 65 Mario Capecchi Drive, Salt Lake City, UT 84132, United States
^b Polgenix, Inc., Department of Medical Devices, 5171 California Ave., Suite 150, Irvine, CA 92617, United States
^c Gavin Herbert Eye Institute, Department of Ophthalmology, University of California, Irvine, CA 92697, United States
^d Institute of Physics, Faculty of Physics, Astronomy and Informatics, Nicolaus Copernicus University in Torun, Grudziadzka 5, Torun, 87-100, Poland
^e Baltic Institute of Technology, Al. Zwyciestwa 96/98, Gdynia, 81-451, Poland
^f Department of Physical Chemistry of Biological Systems, Institute of Physical Chemistry, Polish Academy of Sciences, Kasprzaka Str. 44/52, Warsaw, 01-224, Poland
^g Department of Ophthalmology and Visual Sciences, Washington University School of Medicine, 660 S. Euclid Avenue, Saint Louis, MO 63110, United States

Abstract
Two-photon vision arises from the perception of pulsed infrared (IR) laser light as color corresponding to approximately half of the laser wavelength. The physical process responsible for two-photon vision in rods has been delineated and verified experimentally only recently. Here, we sought to determine whether IR light can also be perceived by mammalian cone photoreceptors via a similar activation mechanism. To investigate selectively mammalian cone signaling in mice, we used animals with disabled rod signal transduction. We found that, contrary to the expected progressive sensitivity decrease based on the one-photon cone visual pigment spectral template, the sensitivity of mouse cone photoreceptors decreases only up to 800 nm and then increases at 900 nm and 1000 nm. Similarly, in experiments with the parafoveal region of macaque retinas, we found that the spectral sensitivity of primate cones diverged above the predicted one-photon spectral sensitivity template beyond 800 nm. In both cases, efficient detection of IR light was dependent on minimizing the dispersion of the ultrashort light pulses, indicating a non-linear two-photon activation process. Together, our studies demonstrate that mammalian cones can be activated by near IR light by a nonlinear two-photon excitation. Our results pave the way for the creation of a two-photon IR-based ophthalmoscope for the simultaneous imaging and functional testing of human retinas as a novel tool for the diagnosis and treatment of a wide range of visual disorders. © 2019 IBRO

Author Keywords
cone visual pigment; infrared vision; phototransduction; transretinal electrophysiology; two-photon absorption

Document Type: Article
Publication Stage: Final
Source: Scopus

"Lifestyle Risk Behaviors among Stroke Survivors with and Without Diabetes" (2019) American Journal of Physical Medicine and Rehabilitation

Lifestyle Risk Behaviors among Stroke Survivors with and Without Diabetes
(2019) American Journal of Physical Medicine and Rehabilitation, 98 (9), pp. 794-799.

Bailey, R.R., Phad, A., McGrath, R., Ford, A.L., Tabak, R., Haire-Joshu, D.

Brown School, Washington University, St. Louis, MI, United States

Abstract
History of stroke and diabetes increases risk for cardiometabolic disease, which can be mitigated through lifestyle management. To evaluate lifestyle risk behaviors among stroke survivors, we compared the prevalence of three lifestyle risk behaviors – physical inactivity, consuming one or less fruit and one or less vegetable daily, and overweight/obesity – between stroke survivors with and without diabetes. Design Data 2013 and 2015 Behavioral Risk Factor Surveillance System were examined. Weighted and age-adjusted prevalence estimates as well as crude and adjusted odds ratios (adjusted for sociodemographic characteristics) were calculated to compare lifestyle risk behaviors between US stroke survivors with and without diabetes. Results Prevalence and adjusted odds ratios for lifestyle risk behaviors were higher in respondents with diabetes compared with those without diabetes for consuming one or less fruit and one or less vegetable daily (58.8% vs. 53.7%, adjusted odds ratio = 1.14), physical inactivity (65.7% vs. 54.6%, adjusted odds ratio = 1.41), and overweight/obesity (87.2% vs. 63.1%, adjusted odds ratio = 2.42). Conclusions Prevalence of select lifestyle risk behaviors exceeds 50% in adults with stroke but is higher in adults with diabetes compared with adults without diabetes. Effective interventions, community programs, and healthcare policy are needed to promote lifestyle management in adults with stroke, particularly among those with diabetes. © 2019 Wolters Kluwer Health, Inc. All rights reserved.

Author Keywords
Diabetes Mellitus; Health; Health Risk Behavior; Stroke

Document Type: Article
Publication Stage: Final
Source: Scopus

"Steady-State Activation and Modulation of the Concatemeric α1β2γ2L GABAA Receptor" (2019) Molecular Pharmacology

Steady-State Activation and Modulation of the Concatemeric α1β2γ2L GABAA Receptor
(2019) Molecular Pharmacology, 96 (3), pp. 320-329.

Germann, A.L., Pierce, S.R., Burbridge, A.B., Steinbach, J.H., Akk, G.

Department of Anesthesiology (A.L.G., S.R.P., A.B.B., G.A.) and the Taylor Family Institute for Innovative Psychiatric Research (J.H.S., Washington University School of Medicine, St. Louis, MO, United States

Abstract
The two-state coagonist model has been successfully used to analyze and predict peak current responses of the γ-aminobutyric acid type A (GABAA) receptor. The goal of the present study was to provide a model-based description of GABAA receptor activity under steady-state conditions after desensitization has occurred. We describe the derivation and properties of the cyclic three-state resting-active-desensitized (RAD) model. The relationship of the model to receptor behavior was tested using concatemeric α1β2γ2 GABAA receptors expressed in Xenopus oocytes. The receptors were activated by the orthosteric agonists GABA or β-alanine, the allosteric agonist propofol, or combinations of GABA, propofol, pentobarbital, and the steroid allopregnanolone, and the observed steady-state responses were compared with those predicted by the model. A modified RAD model was employed to analyze and describe the actions on steady-state current of the inhibitory steroid pregnenolone sulfate. The findings indicate that the steady-state activity in the presence of multiple active agents that interact with distinct binding sites follows standard energetic additivity. The derived equations enable prediction of peak and steady-state activity in the presence of orthosteric and allosteric agonists, and the inhibitory steroid pregnenolone sulfate. SIGNIFICANCE STATEMENT: The study describes derivation and properties of a three-state resting-active-desensitized model. The model and associated equations can be used to analyze and predict peak and steady-state activity in the presence of one or more active agents. Copyright © 2019 by The American Society for Pharmacology and Experimental Therapeutics.

Document Type: Article
Publication Stage: Final
Source: Scopus

"Nerve transfers to restore upper limb function in tetraplegia" (2019) The Lancet

Nerve transfers to restore upper limb function in tetraplegia
(2019) The Lancet, 394 (10198), pp. 543-544.

Hill, E.J.R.^a , Fox, I.K.^a ^b

^a Division of Plastic and Reconstructive Surgery, Washington University, St Louis, MO 63110, United States
^b Plastic and Reconstructive Surgery Core, VA St Louis Health Care System, St Louis, MO, United States

Document Type: Note
Publication Stage: Final
Source: Scopus

"A single-nuclei RNA sequencing study of Mendelian and sporadic AD in the human brain" (2019) Alzheimer's Research and Therapy

A single-nuclei RNA sequencing study of Mendelian and sporadic AD in the human brain
(2019) Alzheimer’s Research and Therapy, 11 (1), art. no. 71, .

Del-Aguila, J.L.^a ^b ^d , Li, Z.^a ^b ^d , Dube, U.^a ^b ^d , Mihindukulasuriya, K.A.^a ^d , Budde, J.P.^a ^b ^d , Fernandez, M.V.^a ^b ^d , Ibanez, L.^a ^b ^d , Bradley, J.^a ^b ^d , Wang, F.^a ^b ^d , Bergmann, K.^a ^b , Davenport, R.^a ^b , Morris, J.C.^b ^c ^e , Holtzman, D.M.^b ^c ^e , Perrin, R.J.^b ^c ^f , Benitez, B.A.^a ^d , Dougherty, J.^g , Cruchaga, C.^a ^b ^c ^d ^g , Harari, O.^a ^b ^c ^d ^g

^a Department of Psychiatry, Washington University School of Medicine, Campus Box 8134, BJC Institute of Health, Office: 9607, 425 S. Euclid Ave, St. Louis, MO 63110, United States
^b Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, MO, United States
^c Knight Alzheimer’s Disease Research Center, Washington University School of Medicine, St. Louis, MO, United States
^d NeuroGenomics and Informatics, Department of Psychiatry, Washington University, St. Louis, MO, United States
^e Department of Neurology, Washington University School of Medicine, St. Louis, MO, United States
^f Department of Pathology and Immunology, Washington University School of Medicine, St. Louis, MO, United States
^g Department of Genetics, Washington University School of Medicine, St. Louis, MO, United States

Abstract
Background: Alzheimer’s disease (AD) is the most common form of dementia. This neurodegenerative disorder is associated with neuronal death and gliosis heavily impacting the cerebral cortex. AD has a substantial but heterogeneous genetic component, presenting both Mendelian and complex genetic architectures. Using bulk RNA-seq from the parietal lobes and deconvolution methods, we previously reported that brains exhibiting different AD genetic architecture exhibit different cellular proportions. Here, we sought to directly investigate AD brain changes in cell proportion and gene expression using single-cell resolution. Methods: We generated unsorted single-nuclei RNA sequencing data from brain tissue. We leveraged the tissue donated from a carrier of a Mendelian genetic mutation, PSEN1 p.A79V, and two family members who suffer from sporadic AD, but do not carry any autosomal mutations. We evaluated alternative alignment approaches to maximize the titer of reads, genes, and cells with high quality. In addition, we employed distinct clustering strategies to determine the best approach to identify cell clusters that reveal neuronal and glial cell types and avoid artifacts such as sample and batch effects. We propose an approach to cluster cells that reduces biases and enable further analyses. Results: We identified distinct types of neurons, both excitatory and inhibitory, and glial cells, including astrocytes, oligodendrocytes, and microglia, among others. In particular, we identified a reduced proportion of excitatory neurons in the Mendelian mutation carrier, but a similar distribution of inhibitory neurons. Furthermore, we investigated whether single-nuclei RNA-seq from the human brains recapitulate the expression profile of disease-associated microglia (DAM) discovered in mouse models. We also determined that when analyzing human single-nuclei data, it is critical to control for biases introduced by donor-specific expression profiles. Conclusion: We propose a collection of best practices to generate a highly detailed molecular cell atlas of highly informative frozen tissue stored in brain banks. Importantly, we have developed a new web application to make this unique single-nuclei molecular atlas publicly available. © 2019 The Author(s).

Author Keywords
Alzheimer’s disease; PSEN1; Single-nuclei RNA-seq; Web-based brain molecular atlas

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

"Secreted frizzled-related protein 1 frazzles the brain in Alzheimer's disease" (2019) Science Translational Medicine

Secreted frizzled-related protein 1 frazzles the brain in Alzheimer’s disease
(2019) Science Translational Medicine, 11 (504), art. no. eaay7697, .

Gallardo, G.

Department of Neurology, Washington University, School of Medicine, St. Louis, MO 63110, United States

Abstract
Inhibition of ADAM10 α-secretase activity in neurons by secreted frizzled-related protein 1 may contribute to Alzheimer’s disease progression. © 2019, American Association for the Advancement of Science.

Document Type: Review
Publication Stage: Final
Source: Scopus

"Impact of beef and beef product intake on cognition in children and young adults: A systematic review" (2019) Nutrients

Impact of beef and beef product intake on cognition in children and young adults: A systematic review
(2019) Nutrients, 11 (8), art. no. 1797, .

An, R.^a ^b , Nickols-Richardson, S.M.^c , Khan, N.^b , Liu, J.^d , Liu, R.^d , Clarke, C.^b

^a Brown School, Washington University, St. Louis, MO 63130, United States
^b Department of Kinesiology and Community Health, University of Illinois, Champaign, IL 61820, United States
^c Department of Food Science and Human Nutrition, Division of Nutritional Sciences, University of Illinois Extension, University of Illinois, Champaign, IL 61801, United States
^d Department of Physical Education, Tsinghua University, Beijing, 100084, China

Abstract
(1) Background: Undernutrition and micronutrient deficiency have been consistently linked to cognitive impairment among children and young adults. As a primary source of dietary animal protein, beef consumption holds the potential to improve diet quality and positively influence cognitive function. This study systematically reviewed evidence linking beef intake to cognition among children and young adults. (2) Methods: A literature search was conducted in seven electronic bibliographic databases for studies assessing the impact of beef consumption on cognition. (3) Results: We identified eight studies reporting results from five unique interventions. Two interventions were conducted in Kenya, two in the U.S. and one in four countries including Guatemala, Pakistan, Democratic Republic of the Congo and Zambia. Only one intervention employed a non-feeding control arm and found beef consumption to improve cognitive abilities compared to the control. However, the other interventions comparing beef consumption to other food types found no consistent result. (4) Conclusions: Evidence pertaining to the impact of beef consumption on cognition remains limited due to the small and heterogeneous set of studies. Future research should adopt a population representative sample and longer follow-up period, employ a non-feeding control arm and comprehensively measure nutrient intakes among study participants. © 2019 by the authors. Licensee MDPI, Basel, Switzerland.

Author Keywords
Beef; Child; Cognition; Review; Young adult

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

"Movement Disorders in Children" (2019) CONTINUUM Lifelong Learning in Neurology

Movement Disorders in Children
(2019) CONTINUUM Lifelong Learning in Neurology, 25 (4), pp. 1099-1120.

Pearson, T.S., Pons, R.

Department of Neurology, Washington University, School of Medicine, 660 S Euclid Ave, St. Louis, MO 63110, United States

Abstract
PURPOSE OF REVIEW This article provides an overview of the clinical features and disorders associated with movement disorders in childhood. This article discusses movement disorder phenomena and their clinical presentation in infants and children and presents a diagnostic approach to suspected genetic disorders with a focus on treatable conditions. RECENT FINDINGS Technologic advances in molecular genetic testing over the past decade continue to lead to the discovery of new diseases. This article discusses the clinical presentation and early experience with treatment for several recently described genetic forms of infantile-onset and childhood-onset dystonia and chorea. SUMMARY The clinical spectrum of pediatric movement disorders is broad and heterogeneous, ranging from acute or transient self-limited conditions to conditions that cause profound lifelong motor disability. Most movement disorders in childhood are chronic, and the large number of rare, genetic conditions associated with pediatric movement disorders can pose a significant diagnostic challenge. Recognition of distinctive diagnostic clues in the history and examination can facilitate the diagnosis of potentially treatable disorders. © Lippincott Williams & Wilkins.

Document Type: Review
Publication Stage: Final
Source: Scopus

"MRI Signal Intensity and Parkinsonism in Manganese-Exposed Workers" (2019) Journal of Occupational and Environmental Medicine

MRI Signal Intensity and Parkinsonism in Manganese-Exposed Workers
(2019) Journal of Occupational and Environmental Medicine, 61 (8), pp. 641-645.

Criswell, S.R.^a , Nielsen, S.S.^a , Warden, M.N.^a , Flores, H.P.^a , Lenox-Krug, J.^a , Racette, S.^a ^f , Sheppard, L.^b ^c , Checkoway, H.^d ^e , Racette, B.A.^a

^a Department of Neurology, Washington University, School of Medicine, St. Louis, United States
^b Department of Environmental and Occupational Health Sciences, University of Washington, School of Public Health, Seattle, WA, United States
^c Department of Biostatistics, University of Washington, School of Public Health, Seattle, WI, United States
^d Department of Family Medicine and Public Health, UC San Diego School of Medicine, San Diego, CA, United States
^e Department of Neurosciences, UC San Diego School of Medicine, San Diego, CA, United States
^f School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Parktown, South Africa

Abstract
T1-weighted brain magnetic resonance imaging (MRI) of the basal ganglia provides a noninvasive measure of manganese (Mn) exposure, and may also represent a biomarker for clinical neurotoxicity.Methods:We acquired T1-weighted MRI scans in 27 Mn-exposed welders, 12 other Mn-exposed workers, and 29 nonexposed participants. T1-weighted intensity indices were calculated for four basal ganglia regions. Cumulative Mn exposure was estimated from work history data. Participants were examined using the Unified Parkinson’s Disease Rating Scale motor subsection 3 (UPDRS3).Results:We observed a positive dose-response association between cumulative Mn exposure and the pallidal index (PI) (β=2.33; 95% confidence interval [CI], 0.93 to 3.74). There was a positive relationship between the PI and UPDRS3 (β=0.15; 95% CI, 0.03 to 0.27).Conclusion:The T1-weighted pallidal signal is associated with occupational Mn exposure and severity of parkinsonism. © 2019 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of the American College of Occupational and Environmental Medicine.

Author Keywords
MRI; parkinsonism; welding

Document Type: Article
Publication Stage: Final
Source: Scopus

"The State of Resting State Networks" (2019) Topics in Magnetic Resonance Imaging

The State of Resting State Networks
(2019) Topics in Magnetic Resonance Imaging, 28 (4), pp. 189-196.

Seitzman, B.A.^a , Snyder, A.Z.^b , Leuthardt, E.C.^c ^d , Shimony, J.S.^b

^a Department of Neurology, Washington University School of Medicine, St. Louis, MO, United States
^b Mallinckrodt Institute of Radiology, Campus Box 8131, 510 S. Kingshighway Blvd., St. Louis, MO 63110, United States
^c Department of Neurosurgery, Washington University School of Medicine, St. Louis, MO, United States
^d Department of Biomedical Engineering, Washington University School of Medicine, St. Louis, MO, United States

Abstract
Functional MRI (fMRI) is currently used for pre-surgical planning, but is often limited to information on the motor and language systems. Resting state fMRI can provide more information on multiple other networks to the neurosurgeon and neuroradiologist; however, currently, these networks are not well known among clinicians. The purpose of this manuscript is to provide an introduction to these networks for the clinician and to discuss how they could be used in the future for precise and individualized surgical planning. We provide a short introduction to resting state fMRI and discuss multiple currently accepted resting state networks with a review of the literature. We review the characteristics and function of multiple somatosensory, association, and other networks. We discuss the concept of critical nodes in the brain and how the neurosurgeon can use this information to individually customize patient care. Although further research is necessary, future application of pre-surgical planning will require consideration of networks other than just motor and language in order to minimize post-surgical morbidity and customize patient care. © 2019 Wolters Kluwer Health, Inc. All rights reserved.

Author Keywords
functional MRI (fMRI); resting state fMRI; resting state networks

Document Type: Review
Publication Stage: Final
Source: Scopus

"Pilot study of a new road test to assess cognitive fitness to drive" (2019) Transportation Research Part F: Traffic Psychology and Behaviour

Pilot study of a new road test to assess cognitive fitness to drive
(2019) Transportation Research Part F: Traffic Psychology and Behaviour, 65, pp. 258-267.

Vanlaar, W.G.M.^a , Mainegra Hing, M.^a , Meister, S.^a , Charles, J.-M.^a , Ireland, L.^a , Mayhew, D.^a , Carr, D.^b , Barco, P.^b , Robertson, R.D.^a

^a Traffic Injury Research Foundation, Canada
^b Washington University School of Medicine, United States

Abstract
The Traffic Injury Research Foundation (TIRF) developed and evaluated a new road test, called the Enhanced Road Test (ERT), to assess a driver’s cognitive fitness to drive for the Ministry of Transportation in Ontario, Canada (MTO). The ERT was designed to flag individuals for potential cognitive impairment, but was not meant to indicate, or assess the level of impairment. Practical feasibility for implementation of the ERT was determined in a pilot study as well as its ability to differentiate drivers with and without cognitive impairment. The research design included both process and outcome evaluation components. The qualitative process evaluation was conducted using surveys administered to participant drivers (N = 70) and feedback obtained from driver examiners involved in the pilot (N = 3). The quantitative outcome evaluation used an experimental design to administer the ERT to a sample of drivers with (N = 42), and without (N = 28), mild cognitive impairment. Regression analysis was conducted and scoring functions of the ERT were compared through a Receiver Operating Characteristic (ROC) curve analysis. Survey results revealed that drivers did not raise specific concerns about the ERT and that examiners believed more training on driving behaviours associated with cognitive impairment and some scoresheet formatting changes would be beneficial. ROC Area Under the Curve (AUC) results revealed that some components of the ERT were better at identifying individuals whose driving skills declined. These components are the adjust-control, route finding and divided attention tasks. Two final scoring schemes for the ERT are proposed as well as several recommendations for its possible implementation. © 2019 Elsevier Ltd

Author Keywords
Area Under the Curve (AUC); Cognitive impairment; Fitness to drive, road test; Receiver Operating Characteristic (ROC)

Document Type: Article
Publication Stage: Final
Source: Scopus

"Measurement of unnecessary psychiatric readmissions: a scoping review protocol" (2019) BMJ Open

Measurement of unnecessary psychiatric readmissions: a scoping review protocol
(2019) BMJ Open, 9 (7), p. e030696.

Kim, B.^a ^b , Weatherly, C.^c , Wolk, C.B.^d , Proctor, E.K.^c

^a HSR&D Center for Healthcare Organization and Implementation Research, VA Boston Healthcare System, Boston, MA, United States
^b Department of Psychiatry, Harvard Medical School, Boston, MA, United States
^c George Warren Brown School of Social Work, Washington University, Saint Louis, MO, United States
^d Center for Mental Health, Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States

Abstract
INTRODUCTION: Care transition for patients being discharged from inpatient mental healthcare to outpatient settings is a growing focus for healthcare delivery systems. Many studies of this inpatient to outpatient transition use the rate of postdischarge readmissions as a patient-level outcome measure to assess the quality of transition. However, it is unclear how studies define the measure, and whether there is a shared understanding by the field regarding which definition is appropriate for which circumstances. This scoping review thus aims to examine how published studies have approached measuring unnecessary psychiatric readmissions. METHODS AND ANALYSIS: The scoping review will be structured according to Levac et al’s enhancement to Arksey and O’Malley’s framework for conducting scoping reviews. The protocol is registered through the Open Science Framework (https://osf.io/5nxuc/). We will search literature databases for studies that (1) are about care transition processes associated with unnecessary psychiatric readmissions and (2) specify use of at least one readmission time interval (ie, time period since previous discharge from inpatient care, within which a hospitalisation can be considered a readmission). Screening and review of articles will be carried out by two reviewers, first independently then involving a third reviewer as needed for consensus. We will assess review findings through both tabular and thematic analyses, noting prevalent trends in study characteristics and emergent themes across our reviewed studies. ETHICS AND DISSEMINATION: This work comes at a time of heightened interest by many mental healthcare systems in high-quality practices that structure their care processes towards effective inpatient to outpatient transitions. Findings will support the systems’ careful examination of alternative potential transitional interventions, helping to ensure that their often limited quality enhancement resources are put to optimal use. We will focus on disseminating our findings to the healthcare community through strong communication infrastructures and connections with health system stakeholders that our multidisciplinary study consultants will foster throughout this study. © Author(s) (or their employer(s)) 2019. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.

Author Keywords
administrative data; care transition; hospital readmission; mental health; patient discharge

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

"TRESK K+ Channel Activity Regulates Trigeminal Nociception and Headache" (2019) eNeuro

TRESK K+ Channel Activity Regulates Trigeminal Nociception and Headache
(2019) eNeuro, 6 (4), .

Guo, Z.^a ^b , Qiu, C.-S.^a ^b , Jiang, X.^a ^b , Zhang, J.^a ^b , Li, F.^b ^c , Liu, Q.^b ^c , Dhaka, A.^d , Cao, Y.-Q.^a ^b

^a Washington University Pain Center, Washington University School of Medicine, St. Louis, MO 63110, United States
^b Department of Anesthesiology, Washington University School of Medicine, St. Louis, MO 63110, United States
^c Center for the Study of Itch, Washington University School of Medicine, St. Louis, MO 63110, United States
^d Department of Biological Structure, Neurobiology and Behavior Graduate Program, University of Washington, Seattle, WA 98195, United States

Abstract
Although TWIK-related spinal cord K+ (TRESK) channel is expressed in all primary afferent neurons in trigeminal ganglia (TG) and dorsal root ganglia (DRG), whether TRESK activity regulates trigeminal pain processing is still not established. Dominant-negative TRESK mutations are associated with migraine but not with other types of pain in humans, suggesting that genetic TRESK dysfunction preferentially affects the generation of trigeminal pain, especially headache. Using TRESK global knock-out mice as a model system, we found that loss of TRESK in all TG neurons selectively increased the intrinsic excitability of small-diameter nociceptors, especially those that do not bind to isolectin B4 (IB4-). Similarly, loss of TRESK resulted in hyper-excitation of the small IB4- dural afferent neurons but not those that bind to IB4 (IB4+). Compared with wild-type littermates, both male and female TRESK knock-out mice exhibited more robust trigeminal nociceptive behaviors, including headache-related behaviors, whereas their body and visceral pain responses were normal. Interestingly, neither the total persistent outward current nor the intrinsic excitability was altered in adult TRESK knock-out DRG neurons, which may explain why genetic TRESK dysfunction is not associated with body and/or visceral pain in humans. We reveal for the first time that, among all primary afferent neurons, TG nociceptors are the most vulnerable to the genetic loss of TRESK. Our findings indicate that endogenous TRESK activity regulates trigeminal nociception, likely through controlling the intrinsic excitability of TG nociceptors. Importantly, we provide evidence that genetic loss of TRESK significantly increases the likelihood of developing headache. Copyright © 2019 Guo et al.

Author Keywords
headache; intrinsic excitability; primary afferent neuron; TRESK; trigeminal ganglion; trigeminal pain

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

"Down syndrome mouse models have an abnormal enteric nervous system" (2019) JCI Insight

Down syndrome mouse models have an abnormal enteric nervous system
(2019) JCI Insight, 4 (11), art. no. :e124510, .

Schill, E.M.^a ^b , Wright, C.M.^b , Jamil, A.^b , LaCombe, J.M.^c , Roper, R.J.^c , Heuckeroth, R.O.^b ^d

^a Department of Pediatrics, Washington University School of Medicine, St. Louis, MO, United States
^b Department of Pediatrics, Children’s Hospital of Philadelphia Research Institute, Perelman School of Medicine, University of Pennsylvania, Abramson Research Center, Philadelphia, PA, United States
^c Department of Biology, Indiana University–Purdue University Indianapolis, Indianapolis, IN, United States
^d Children’s Hospital of Philadelphia Research Institute, Perelman School of Medicine, University of Pennsylvania, Abramson Research Center, Suite 1116I, 3615 Civic Center Boulevard, Philadelphia, PA 19104-4318, United States

Abstract
Children with trisomy 21 (Down syndrome [DS]) have a 130-fold increased incidence of Hirschsprung disease (HSCR), a developmental defect in which the enteric nervous system (ENS) is missing from the distal bowel (i.e., distal bowel is aganglionic). Treatment for HSCR is surgical resection of aganglionic bowel, but many children have bowel problems after surgery. Postsurgical problems, such as enterocolitis and soiling, are especially common in children with DS. To determine how trisomy 21 affects ENS development, we evaluated the ENS in 2 DS mouse models, Ts65Dn and Tc1. These mice are trisomic for many chromosome 21 homologous genes, including Dscam and Dyrk1a, which are hypothesized to contribute to HSCR risk. Ts65Dn and Tc1 mice have normal ENS precursor migration at E12.5 and almost normal myenteric plexus structure as adults. However, Ts65Dn and Tc1 mice have markedly reduced submucosal plexus neuron density throughout the bowel. Surprisingly, the submucosal neuron defect in Ts65Dn mice is not due to excess Dscam or Dyrk1a, since normalizing copy number for these genes does not rescue the defect. These findings suggest the possibility that the high frequency of bowel problems in children with DS and HSCR may occur because of additional unrecognized problems with ENS structure. Copyright: © 2019, American Society for Clinical Investigation.

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

"Author Correction: Genetic meta-analysis of diagnosed Alzheimer’s disease identifies new risk loci and implicates Aβ, tau, immunity and lipid processing (Nature Genetics, (2019), 51, 3, (414-430), 10.1038/s41588-019-0358-2)" (2019) Nature Genetics

Author Correction: Genetic meta-analysis of diagnosed Alzheimer’s disease identifies new risk loci and implicates Aβ, tau, immunity and lipid processing (Nature Genetics, (2019), 51, 3, (414-430), 10.1038/s41588-019-0358-2)
(2019) Nature Genetics, .

Kunkle, B.W.^a , Grenier-Boley, B.^b ^c ^d , Sims, R.^e ^f , Bis, J.C.^g , Damotte, V.^b ^c ^d , Naj, A.C.^h , Boland, A.ⁱ , Vronskaya, M.^e , van der Lee, S.J.^j , Amlie-Wolf, A.^k , Bellenguez, C.^b ^c ^d , Frizatti, A.^e , Chouraki, V.^b ^c ^d ^l ^m , Martin, E.R.^a , Sleegers, K.ⁿ ^o , Badarinarayan, N.^e , Jakobsdottir, J.^p , Hamilton-Nelson, K.L.^a , Moreno-Grau, S.^q ^r , Olaso, R.ⁱ , Raybould, R.^e ^f , Chen, Y.^s , Kuzma, A.B.^k , Hiltunen, M.^t ^u , Morgan, T.^e , Ahmad, S.^j , Vardarajan, B.N.^v ^w ^x , Epelbaum, J.^y , Hoffmann, P.^z ^aa ^ab , Boada, M.^q ^r , Beecham, G.W.^a , Garnier, J.-G.ⁱ , Harold, D.^ac , Fitzpatrick, A.L.^ad ^ae , Valladares, O.^k , Moutet, M.-L.ⁱ , Gerrish, A.^af , Smith, A.V.^ag ^ah , Qu, L.^k , Bacq, D.ⁱ , Denning, N.^e ^f , Jian, X.^ai , Zhao, Y.^k , Del Zompo, M.^aj , Fox, N.C.^af ^ak , Choi, S.-H.^q , Mateo, I.^al , Hughes, J.T.^am , Adams, H.H.^j , Malamon, J.^k , Sanchez-Garcia, F.^an , Patel, Y.^am , Brody, J.A.^g , Dombroski, B.A.^k , Naranjo, M.C.D.^an , Daniilidou, M.^ao , Eiriksdottir, G.^p , Mukherjee, S.^ap , Wallon, D.^aq , Uphill, J.^ar , Aspelund, T.^p ^as , Cantwell, L.B.^k , Garzia, F.ⁱ , Galimberti, D.^at ^au , Hofer, E.^av ^aw , Butkiewicz, M.^ax , Fin, B.ⁱ , Scarpini, E.^at ^au , Sarnowski, C.^s , Bush, W.S.^ax , Meslage, S.ⁱ , Kornhuber, J.^ay , White, C.C.^az , Song, Y.^ax , Barber, R.C.^ba , Engelborghs, S.^bb ^bc , Sordon, S.^bd , Voijnovic, D.^j , Adams, P.M.^be , Vandenberghe, R.^bf , Mayhaus, M.^bd , Cupples, L.A.^l ^s , Albert, M.S.^bg , De Deyn, P.P.^bb ^bc , Gu, W.^bd , Himali, J.J.^l ^m ^s , Beekly, D.^bh , Squassina, A.^aj , Hartmann, A.M.^bi , Orellana, A.^q , Blacker, D.^bj ^bk , Rodriguez-Rodriguez, E.^al , Lovestone, S.^bl , Garcia, M.E.^bm , Doody, R.S.^bn , Munoz-Fernadez, C.^an , Sussams, R.^bo , Lin, H.^bp , Fairchild, T.J.^bq , Benito, Y.A.^an , Holmes, C.^bo , Karamujić-Čomić, H.^j , Frosch, M.P.^br , Thonberg, H.^bs ^bt , Maier, W.^bu ^bv , Roshchupkin, G.^j , Ghetti, B.^bw , Giedraitis, V.^bx , Kawalia, A.^by , Li, S.^s , Huebinger, R.M.^bz , Kilander, L.^bx , Moebus, S.^ca , Hernández, I.^q ^r , Kamboh, M.I.^cb ^cc ^cd , Brundin, R.M.^bx , Turton, J.^ce , Yang, Q.^s , Katz, M.J.^cf , Concari, L.^cg ^ch , Lord, J.^ce , Beiser, A.S.^l ^m ^s , Keene, C.D.^ci , Helisalmi, S.^t ^u , Kloszewska, I.^cj , Kukull, W.A.^ae , Koivisto, A.M.^t ^u , Lynch, A.^ck ^cl , Tarraga, L.^q ^r , Larson, E.B.^cm , Haapasalo, A.^cn , Lawlor, B.^ck ^cl , Mosley, T.H.^co , Lipton, R.B.^cf , Solfrizzi, V.^cp , Gill, M.^ck ^cl , Longstreth, W.T., Jr^ae ^cq , Montine, T.J.^ci , Frisardi, V.^cr , Diez-Fairen, M.^cs ^ct , Rivadeneira, F.^j ^cu ^cv , Petersen, R.C.^cw , Deramecourt, V.^cx , Alvarez, I.^cs ^ct , Salani, F.^cy , Ciaramella, A.^cy , Boerwinkle, E.^cz ^da , Reiman, E.M.^db ^dc ^dd ^de , Fievet, N.^b ^c ^d , Rotter, J.I.^df , Reisch, J.S.^dg , Hanon, O.^dh , Cupidi, C.^di , Uitterlinden, A.G.A.^j ^cu ^cv , Royall, D.R.^dj , Dufouil, C.^dk ^dl , Maletta, R.G.^di , de Rojas, I.^q ^r , Sano, M.^dm , Brice, A.^dn ^do , Cecchetti, R.^dp , George-Hyslop, P.S.^dq ^dr , Ritchie, K.^ds ^dt ^du , Tsolaki, M.^ao , Tsuang, D.W.^dv ^dw , Dubois, B.^dx ^dy ^dz ^ea , Craig, D.^eb , Wu, C.-K.^ec , Soininen, H.^t ^u , Avramidou, D.^ao , Albin, R.L.^ed ^ee ^ef , Fratiglioni, L.^eg , Germanou, A.^ao , Apostolova, L.G.^eh ^ei ^ej ^ek , Keller, L.^eg , Koutroumani, M.^ao , Arnold, S.E.^el , Panza, F.^cr , Gkatzima, O.^ao , Asthana, S.^em ^en ^eo , Hannequin, D.^am , Whitehead, P.^a , Atwood, C.S.^ei ^ej ^ek , Caffarra, P.^cd ^ce , Hampel, H.^ep ^eq ^er ^es , Quintela, I.^et , Carracedo, Á.^et , Lannfelt, L.^bx , Rubinsztein, D.C.^dq ^eu , Barnes, L.L.^ev ^ew ^ex , Pasquier, F.^cx , Frölich, L.^ey , Barral, S.^v ^w ^x , McGuinness, B.^eb , Beach, T.G.^ez , Johnston, J.A.^eb , Becker, J.T.^cb ^fa ^fb , Passmore, P.^eb , Bigio, E.H.^fc ^fd , Schott, J.M.^af , Bird, T.D.^cq ^dv , Warren, J.D.^af , Boeve, B.F.^cw , Lupton, M.K.^am ^fe , Bowen, J.D.^ff , Proitsi, P.^am , Boxer, A.^fg , Powell, J.F.^am , Burke, J.R.^fh , Kauwe, J.S.K.^fi , Burns, J.M.^fj , Mancuso, M.^fk , Buxbaum, J.D.^dm ^fl ^fm , Bonuccelli, U.^fk , Cairns, N.J.^fn , McQuillin, A.^fo , Cao, C.^fp , Livingston, G.^fo , Carlson, C.S.^en ^eo , Bass, N.J.^fo , Carlsson, C.M.^fq , Hardy, J.^fr , Carney, R.M.^fs , Bras, J.^ak ^ft , Carrasquillo, M.M.^fu , Guerreiro, R.^ak ^ft , Allen, M.^fu , Chui, H.C.^fv , Fisher, E.^ft , Masullo, C.^fw , Crocco, E.A.^fx , DeCarli, C.^fy , Bisceglio, G.^fu , Dick, M.^fz , Ma, L.^fu , Duara, R.^ga , Graff-Radford, N.R.^fu , Evans, D.A.^gb , Hodges, A.^gc , Faber, K.M.^eh , Scherer, M.^gd , Fallon, K.B.^ge , Riemenschneider, M.^bd , Fardo, D.W.^gf , Heun, R.^bv , Farlow, M.R.^ej , Kölsch, H.^bv , Ferris, S.^gg , Leber, M.^gh , Foroud, T.M.^eh , Heuser, I.^gi , Galasko, D.R.^gj , Giegling, I.^bi , Gearing, M.^gk ^gl , Hüll, M.^gm , Geschwind, D.H.^gn , Gilbert, J.R.^a , Morris, J.^go ^gp , Green, R.C.^gq , Mayo, K.^go ^gr ^gs , Growdon, J.H.^gt , Feulner, T.^bd , Hamilton, R.L.^gu , Harrell, L.E.^gv , Drichel, D.^gw , Honig, L.S.^v , Cushion, T.D.^e ^f , Huentelman, M.J.^db , Hollingworth, P.^e , Hulette, C.M.^gx , Hyman, B.T.^gt , Marshall, R.^e , Jarvik, G.P.^gy ^gz , Meggy, A.^e , Abner, E.^ha , Menzies, G.E.^e ^f , Jin, L.-W.^hb , Leonenko, G.^e , Real, L.M.^hb , Jun, G.R.^hc , Baldwin, C.T.^hc , Grozeva, D.^e , Karydas, A.^ff , Russo, G.^hd , Kaye, J.A.^he ^hf , Kim, R.^hg , Jessen, F.^bu ^bv ^gh , Kowall, N.W.^m ^hh , Vellas, B.^hi , Kramer, J.H.^hj , Vardy, E.^hk , LaFerla, F.M.^hl , Jöckel, K.-H.^ca , Lah, J.J.^hm , Dichgans, M.^hn ^ho , Leverenz, J.B.^hp , Mann, D.^hq , Levey, A.I.^hm , Pickering-Brown, S.^hq , Lieberman, A.P.^hr , Klopp, N.^hs , Lunetta, K.L.^s , Wichmann, H.-E.^ht ^hu ^hv , Lyketsos, C.G.^hw , Morgan, K.^hx , Marson, D.C.^gv , Brown, K.^ce , Martiniuk, F.^hy , Medway, C.^ce , Mash, D.C.^hz , Nöthen, M.M.^z ^aa , Masliah, E.^gj ^ia , Hooper, N.M.^hq , McCormick, W.C.^ap , Daniele, A.^ib , McCurry, S.M.^ic , Bayer, A.^id , McDavid, A.N.^fp , Gallacher, J.^bl , McKee, A.C.^m ^hh , van den Bussche, H.^gd , Mesulam, M.^fd ^ie , Brayne, C.^if , Miller, B.L.^ig , Riedel-Heller, S.^ih , Miller, C.A.ⁱⁱ , Miller, J.W.^ij , Al-Chalabi, A.^ik , Morris, J.C.^fn ^gr , Shaw, C.E.^ik ^il , Myers, A.J.^fx , Wiltfang, J.^im ⁱⁿ ^io , O’Bryant, S.^ba , Olichney, J.M.^fy , Alvarez, V.^ip , Parisi, J.E.^iq , Singleton, A.B.^ir , Paulson, H.L.^ed ^ef , Collinge, J.^ar , Perry, W.R.^a , Mead, S.^ar , Peskind, E.^dw , Cribbs, D.H.^is , Rossor, M.^af , Pierce, A.^is , Ryan, N.S.^ar , Poon, W.W.^fz , Nacmias, B.^it ^iu , Potter, H.^iv , Sorbi, S.^it ^iw , Quinn, J.F.^gd ^ge , Sacchinelli, E.^cy , Raj, A.^fp , Spalletta, G.^ix ^iy , Raskind, M.^dw , Caltagirone, C.^ix , Bossù, P.^cy , Orfei, M.D.^ix , Reisberg, B.^gg ^iz , Clarke, R.^ja , Reitz, C.^v ^w ^jb , Smith, A.D.^jc , Ringman, J.M.^jd , Warden, D.^jc , Roberson, E.D.^gv , Wilcock, G.^jc , Rogaeva, E.^dr , Bruni, A.C.^di , Rosen, H.J.^fg , Gallo, M.^di , Rosenberg, R.N.^je , Ben-Shlomo, Y.^jf , Sager, M.A.^en , Mecocci, P.^dp , Saykin, A.J.^eh ^ej , Pastor, P.^cs ^ct , Cuccaro, M.L.^a , Vance, J.M.^a , Schneider, J.A.^ev ^ex ^jg , Schneider, L.S.^fv ^jh , Slifer, S.^a , Seeley, W.W.^fg , Smith, A.G.^fp , Sonnen, J.A.^ci , Spina, S.^bw , Stern, R.A.^m , Swerdlow, R.H.^fj , Tang, M.^k , Tanzi, R.E.^gt , Trojanowski, J.Q.^ji , Troncoso, J.C.^jj , Van Deerlin, V.M.^ji , Van Eldik, L.J.^jk , Vinters, H.V.^jl ^jm , Vonsattel, J.P.^jn , Weintraub, S.^fd ^jo , Welsh-Bohmer, K.A.^fh ^jp , Wilhelmsen, K.C.^jq , Williamson, J.^v , Wingo, T.S.^hm ^jr , Woltjer, R.L.^js , Wright, C.B.^jt , Yu, C.-E.^ap , Yu, L.^ev ^ex , Saba, Y.^ju , Pilotto, A.^jv ^jw , Bullido, M.J.^r ^jx ^jy , Peters, O.^gi ^jz , Crane, P.K.^ap , Bennett, D.^ev ^ex , Bosco, P.^ka , Coto, E.^ip , Boccardi, V.^dp , De Jager, P.L.^kb , Lleo, A.^r ^kc , Warner, N.^kd , Lopez, O.L.^cb ^cd ^fa , Ingelsson, M.^bx , Deloukas, P.^ke , Cruchaga, C.^go ^gp , Graff, C.^bs ^bt , Gwilliam, R.^ke , Fornage, M.^ai , Goate, A.M.^fl ^kf , Sanchez-Juan, P.^al , Kehoe, P.G.^kg , Amin, N.^j , Ertekin-Taner, N.^fu ^kh , Berr, C.^ds ^dt , Debette, S.^dn ^do , Love, S.^kg , Launer, L.J.^bm , Younkin, S.G.^fu ^kh , Dartigues, J.-F.^ki , Corcoran, C.^kj , Ikram, M.A.^j ^kk ^kl , Dickson, D.W.^fu , Nicolas, G.^aq , Campion, D.^aq ^km , Tschanz, J.A.^kj , Schmidt, H.^ju ^kn , Hakonarson, H.^ko ^kp , Clarimon, J.^r ^kc , Munger, R.^kj , Schmidt, R.^av , Farrer, L.A.^m ^s ^hc ^kq ^kr , Van Broeckhoven, C.ⁿ ^o , O’Donovan, M.C.^e , DeStefano, A.L.^m ^s , Jones, L.^e ^f , Haines, J.L.^ax , Deleuze, J.-F.ⁱ , Owen, M.J.^e , Gudnason, V.^p ^ah , Mayeux, R.^v ^w ^x , Escott-Price, V.^e ^f , Psaty, B.M.^g ^ae ^ks ^kt , Ramirez, A.^by ^gh , Wang, L.-S.^k , Ruiz, A.^q ^r , van Duijn, C.M.^j , Holmans, P.A.^e , Seshadri, S.^l ^m ^ku , Williams, J.^e ^f , Amouyel, P.^b ^c ^d ^kv , Schellenberg, G.D.^k , Lambert, J.-C.^b ^c ^d , Pericak-Vance, M.A.^a , Alzheimer Disease Genetics Consortium (ADGC)^kw , The European Alzheimer’s Disease Initiative (EADI)^kw , Cohorts for Heart and Aging Research in Genomic Epidemiology Consortium (CHARGE)^kx , Genetic and Environmental Risk in AD/Defining Genetic, Polygenic and Environmental Risk for Alzheimer’s Disease Consortium (GERAD/PERADES)^kx

^a John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL, United States
^b Inserm, U1167, RID-AGE-Risk Factors and Molecular Determinants of Aging-Related Diseases, Lille, France
^c Institut Pasteur de Lille, Lille, France
^d Univ. Lille, U1167-Excellence Laboratory LabEx DISTALZ, Lille, France
^e Division of Psychological Medicine and Clinical Neurosciences, MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, Cardiff, United Kingdom
^f UK Dementia Research Institute at Cardiff, Cardiff University, Cardiff, United Kingdom
^g Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, United States
^h Department of Biostatistics and Epidemiology/Center for Clinical Epidemiology and Biostatistics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, United States
ⁱ Centre National de Recherche en Génomique Humaine, Institut de Biologie François Jacob, CEA, Université Paris-Saclay, and LabEx GENMED, Evry, France
^j Department of Epidemiology, Erasmus Medical Center, Rotterdam, Netherlands
^k Penn Neurodegeneration Genomics Center, Department of Pathology and Laboratory Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, United States
^l Framingham Heart Study, Framingham, MA, United States
^m Department of Neurology, Boston University School of Medicine, Boston, MA, United States
ⁿ Neurodegenerative Brain Diseases Group, Center for Molecular Neurology, VIB, Antwerp, Belgium
^o Laboratory for Neurogenetics, Institute Born-Bunge, University of Antwerp, Antwerp, Belgium
^p Icelandic Heart Association, Kopavogur, Iceland
^q Research Center and Memory Clinic of Fundació ACE, Institut Català de Neurociències Aplicades-Universitat Internacional de Catalunya, Barcelona, Spain
^r Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas, Instituto de Salud Carlos III, Madrid, Spain
^s Department of Biostatistics, Boston University School of Public Health, Boston, MA, United States
^t Institute of Biomedicine, University of Eastern Finland, Kuopio, Finland
^u Department of Neurology, Kuopio University Hospital, Kuopio, Finland
^v Taub Institute on Alzheimer’s Disease and the Aging Brain, Department of Neurology, Columbia University, New York, NY, United States
^w Gertrude H. Sergievsky Center, Columbia University, New York, NY, United States
^x Department of Neurology, Columbia University, New York, NY, United States
^y UMR 894, Center for Psychiatry and Neuroscience, Inserm, Université Paris Descartes, Paris, France
^z Institute of Human Genetics, University of Bonn, Bonn, Germany
^aa Department of Genomics, Life & Brain Center, University of Bonn, Bonn, Germany
^ab Division of Medical Genetics, University Hospital and Department of Biomedicine, University of Basel, Basel, Switzerland
^ac School of Biotechnology, Dublin City University, Dublin, Ireland
^ad Department of Family Medicine, University of Washington, Seattle, WA, United States
^ae Department of Epidemiology, University of Washington, Seattle, WA, United States
^af Dementia Research Centre, Department of Neurodegenerative Disease, UCL Institute of Neurology, London, United Kingdom
^ag Department of Biostatistics, University of Michigan, Ann Arbor, MI, United States
^ah Faculty of Medicine, University of Iceland, Reykjavik, Iceland
^ai Brown Foundation Institute of Molecular Medicine, University of Texas Health Sciences Center at Houston, Houston, TX, United States
^aj Section of Neuroscience and Clinical Pharmacology, Department of Biomedical Sciences, University of Cagliari, Cagliari, Italy
^ak UK Dementia Research Institute at UCL, Department of Neurodegenerative Disease, UCL Institute of Neurology, London, United Kingdom
^al Neurology Service and CIBERNED, ‘Marqués de Valdecilla’ University Hospital (University of Cantabria and IDIVAL), Santander, Spain
^am Department of Basic and Clinical Neuroscience, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, United Kingdom
^an Department of Immunology, Hospital Universitario Doctor Negrín, Las Palmas de Gran Canaria, Spain
^ao Department of Neurology, Medical School, Aristotle University of Thessaloniki, Thessaloniki, Greece
^ap Department of Medicine, University of Washington, Seattle, WA, United States
^aq Normandie University, UNIROUEN, Inserm U1245, and Rouen University Hospital, Department of Neurology, Department of Genetics and CNR-MAJ, Normandy Center for Genomic and Personalized Medicine, Rouen, France
^ar Department of Neurodegenerative Disease, MRC Prion Unit at UCL, Institute of Prion Diseases, London, United Kingdom
^as Centre for Public Health, University of Iceland, Reykjavik, Iceland
^at Fondazione IRCCS Ca’ Granda, Ospedale Maggiore Policlinico, Neurodegenerative Diseases Unit, Milan, Italy
^au University of Milan, Centro Dino Ferrari, Milan, Italy
^av Clinical Division of Neurogeriatrics, Department of Neurology, Medical University Graz, Graz, Austria
^aw Institute for Medical Informatics, Statistics and Documentation, Medical University of Graz, Graz, Austria
^ax Institute for Computational Biology, Department of Population & Quantitative Health Sciences, Case Western Reserve University, Cleveland, OH, United States
^ay Department of Psychiatry and Psychotherapy, University of Erlangen-Nuremberg, Erlangen, Germany
^az Program in Medical and Population Genetics, Broad Institute, Cambridge, MA, United States
^ba Department of Pharmacology and Neuroscience, University of North Texas Health Science Center, Fort Worth, TX, United States
^bb Laboratory for Neurochemistry and Behavior, Institute Born-Bunge, University of Antwerp, Antwerp, Belgium
^bc Department of Neurology and Memory Clinic, Hospital Network Antwerp, Antwerp, Belgium
^bd Department of Psychiatry and Psychotherapy, University Hospital, Saarland, Germany
^be Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX, United States
^bf Laboratory for Cognitive Neurology, Department of Neurology, University Hospital and University of Leuven, Leuven, Belgium
^bg Department of Neurology, Johns Hopkins University, Baltimore, MD, United States
^bh National Alzheimer’s Coordinating Center, University of Washington, Seattle, WA, United States
^bi Department of Psychiatry, Martin Luther University Halle-Wittenberg, Halle, Germany
^bj Department of Epidemiology, Harvard T.H. Chan School of Public Health, Harvard University, Boston, MA, United States
^bk Department of Psychiatry, Massachusetts General Hospital/Harvard Medical School, Boston, MA, United States
^bl Department of Psychiatry, University of Oxford, Oxford, United Kingdom
^bm Laboratory of Epidemiology and Population Sciences, National Institute on Aging, Bethesda, MD, United States
^bn Alzheimer’s Disease and Memory Disorders Center, Baylor College of Medicine, Houston, TX, United States
^bo Division of Clinical Neurosciences, School of Medicine, University of Southampton, Southampton, United Kingdom
^bp Section of Computational Biomedicine, Department of Medicine, Boston University School of Medicine, Boston, MA, United States
^bq Office of Strategy and Measurement, University of North Texas Health Science Center, Fort Worth, TX, United States
^br C.S. Kubik Laboratory for Neuropathology, Massachusetts General Hospital, Charlestown, MA, United States
^bs Theme Aging, Unit for Hereditary Dementias, Karolinska University Hospital-Solna, Stockholm, Sweden
^bt Karolinska Institutet, Department of Neurobiology, Care Sciences and Society, Alzheimer Research Center, Division of Neurogeriatrics, Solna, Sweden
^bu German Center for Neurodegenerative Diseases, Bonn, Germany
^bv Department of Psychiatry and Psychotherapy, University of Bonn, Bonn, Germany
^bw Department of Pathology and Laboratory Medicine, Indiana University, Indianapolis, IN, United States
^bx Department of Public Health and Caring Sciences/Geriatrics, Uppsala University, Uppsala, Sweden
^by Department for Neurodegenerative Diseases and Geriatric Psychiatry, University Hospital Bonn, Bonn, Germany
^bz Department of Surgery, University of Texas Southwestern Medical Center, Dallas, TX, United States
^ca Institute for Medical Informatics, Biometry and Epidemiology, University Hospital of Essen, University Duisburg-Essen, Essen, Germany
^cb Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, United States
^cc Department of Human Genetics, University of Pittsburgh, Pittsburgh, PA, United States
^cd Alzheimer’s Disease Research Center, University of Pittsburgh, Pittsburgh, PA, United States
^ce Institute of Genetics, Queen’s Medical Centre, University of Nottingham, Nottingham, United Kingdom
^cf Department of Neurology, Albert Einstein College of Medicine, Bronx, NY, United States
^cg Section of Neuroscience, DIMEC-University of Parma, Parma, Italy
^ch FERB-Alzheimer Center, Gazzaniga (Bergamo), Italy
^ci Department of Pathology, University of Washington, Seattle, WA, United States
^cj Elderly and Psychiatric Disorders Department, Medical University of Lodz, Lodz, Poland
^ck Mercer’s Institute for Research on Aging, St. James’s Hospital and Trinity College, Dublin, Ireland
^cl St. James’s Hospital and Trinity College, Dublin, Ireland
^cm Kaiser Permanente Washington Health Research Institute, Seattle, WA, United States
^cn A.I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Kuopio, Finland
^co Departments of Medicine, Geriatrics, Gerontology and Neurology, University of Mississippi Medical Center, Jackson, MS, United States
^cp Interdisciplinary Department of Medicine, Geriatric Medicine and Memory Unity, University of Bari, Bari, Italy
^cq Department of Neurology, University of Washington, Seattle, WA, United States
^cr Department of Geriatrics, Center for Aging Brain, University of Bari, Bari, Italy
^cs Fundació per la Recerca Biomèdica i Social Mútua Terrassa, Terrassa, Barcelona, Spain
^ct Memory Disorders Unit, Department of Neurology, Hospital Universitari Mutua de Terrassa, Terrassa, Barcelona, Spain
^cu Department of Internal Medicine, Erasmus University Medical Center, Rotterdamt, Netherlands
^cv Netherlands Consortium on Health Aging and National Genomics Initiative, Leiden, Netherlands
^cw Department of Neurology, Mayo Clinic, Rochester, MN, United States
^cx CHU Lille, Memory Center of Lille (Centre Mémoire de Ressources et de Recherche), Lille, France
^cy Department of Clinical and Behavioral Neurology, Experimental Neuropsychobiology Laboratory, IRCCS Santa Lucia Foundation, Rome, Italy
^cz School of Public Health, Human Genetics Center, University of Texas Health Science Center at Houston, Houston, TX, United States
^da Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, United States
^db Neurogenomics Division, Translational Genomics Research Institute, Phoenix, AZ, United States
^dc Arizona Alzheimer’s Consortium, Phoenix, AZ, United States
^dd Banner Alzheimer’s Institute, Phoenix, AZ, United States
^de Department of Psychiatry, University of Arizona, Phoenix, AZ, United States
^df Institute for Translational Genomics and Population Sciences, Departments of Pediatrics and Medicine, Los Angeles BioMedical Research Institute at Harbor-UCLA Medical Center, Torrance, CA, United States
^dg Department of Clinical Sciences, University of Texas Southwestern Medical Center, Dallas, TX, United States
^dh University Paris Descartes, EA 4468, AP-HP, Geriatrics Department, Hôpital Broca, Paris, France
^di Regional Neurogenetic Centre (CRN), ASP Catanzaro, Lamezia Terme, Italy
^dj Departments of Psychiatry, Medicine, Family & Community Medicine, South Texas Veterans Health Administration Geriatric Research Education & Clinical Center (GRECC), UT Health Science Center at San Antonio, San Antonio, TX, United States
^dk University of Bordeaux, Inserm 1219, Bordeaux, France
^dl Department of Neurology, Bordeaux University Hospital / CHU de Bordeaux, Bordeaux, France
^dm Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, United States
^dn Inserm U1127, CNRS UMR 7225, Sorbonne Universités, UPMC Université Paris 06, UMRS 1127, Institut du Cerveau et de la Moelle Épinière, Paris, France
^do AP-HP, Department of Genetics, Pitié-Salpêtrière Hospital, Paris, France
^dp Section of Gerontology and Geriatrics, Department of Medicine, University of Perugia, Perugia, Italy
^dq Cambridge Institute for Medical Research, University of Cambridge, Cambridge, United Kingdom
^dr Tanz Centre for Research in Neurodegenerative Disease, University of Toronto, Toronto, ON, Canada
^ds Inserm U1061 Neuropsychiatry, La Colombière Hospital, Montpellier, France
^dt Montpellier University, Montpellier, France
^du Department of Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom
^dv VA Puget Sound Health Care System/>GRECC, Seattle, WA, United States
^dw Department of Psychiatry and Behavioral Sciences, University of Washington School of Medicine, Seattle, WA, United States
^dx Institut de la Mémoire et de la Maladie d’Alzheimer and Institut du Cerveau et de la Moelle Épinière, Département de Neurologie, Hôpital de la Pitié-Salpêtrière, Paris, France
^dy Institut des Neurosciences Translationnelles de Paris, Institut du Cerveau et de la Moelle Épinière, Paris, France
^dz Inserm, CNRS, UMR-S975, Institut du Cerveau et de la Moelle Epinière, Paris, France
^ea Sorbonne Universités, Université Pierre et Marie Curie, Hôpital de la Pitié-Salpêtrière, AP-HP, Paris, France
^eb Ageing Group, Centre for Public Health, School of Medicine, Dentistry and Biomedical Sciences, Queen’s University Belfast, Belfast, United Kingdom
^ec Departments of Neurology, Pharmacology & Neuroscience, Texas Tech University Health Science Center, Lubbock, TX, United States
^ed Department of Neurology, University of Michigan, Ann Arbor, MI, United States
^ee Geriatric Research, Education and Clinical Center (GRECC), VA Ann Arbor Healthcare System (VAAAHS), Ann Arbor, MI, United States
^ef Michigan Alzheimer Disease Center, Ann Arbor, MI, United States
^eg Aging Research Center, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet and Stockholm University, Stockholm, Sweden
^eh Indiana Alzheimer’s Disease Center, Indiana University School of Medicine, Indianapolis, IN, United States
^ei Department of Medical and Molecular Genetics, Indiana University, Indianapolis, IN, United States
^ej Department of Neurology, Indiana University, Indianapolis, IN, United States
^ek Department of Radiology and Imaging Sciences, Indiana University, Indianapolis, IN, United States
^el Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, United States
^em Geriatric Research, Education and Clinical Center (GRECC), University of Wisconsin, Madison, WI, United States
^en Department of Medicine, University of Wisconsin, Madison, WI, United States
^eo Wisconsin Alzheimer’s Disease Research Center, Madison, WI, United States
^ep AXA Research Fund & Sorbonne University Chair, Paris, France
^eq Sorbonne University, GRC n° 21, Alzheimer Precision Medicine (APM), AP-HP, Pitié-Salpêtrière Hospital, Paris, France
^er Brain & Spine Institute, Inserm U 1127, CNRS UMR 7225, Paris, France
^es Institute of Memory and Alzheimer’s Disease, Department of Neurology, Pitié-Salpêtrière Hospital, AP-HP, Paris, France
^et Grupo de Medicina Xenomica, Universidade de Santiago de Compostela, Centro Nacional de Genotipado, Centro de Investigación Biomédica en Red de Enfermedades Raras, Santiago de Compostela, Spain
^eu UK Dementia Research Institute, University of Cambridge, Cambridge, United Kingdom
^ev Department of Neurological Sciences, Rush University Medical Center, Chicago, IL, United States
^ew Department of Behavioral Sciences, Rush University Medical Center, Chicago, IL, United States
^ex Rush Alzheimer’s Disease Center, Rush University Medical Center, Chicago, IL, United States
^ey Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Heidelberg, Germany
^ez Civin Laboratory for Neuropathology, Banner Sun Health Research Institute, Phoenix, AZ, United States
^fa Department of Neurology, University of Pittsburgh, Pittsburgh, PA, United States
^fb Department of Psychology, University of Pittsburgh School of Medicine, Pittsburgh, PA, United States
^fc Department of Pathology, Northwestern University Feinberg School of Medicine, Chicago, IL, United States
^fd Mesulam Center for Cognitive Neurology and Alzheimer’s Disease, Northwestern University Feinberg School of Medicine, Chicago, IL, United States
^fe Genetic Epidemiology, QIMR Berghofer Medical Research Institute, Herston, QLD, Australia
^ff Swedish Medical Center, Seattle, WA, United States
^fg Department of Neurology, University of California, San Francisco, San Francisco, CA, United States
^fh Department of Neurology, Duke University, Durham, NC, United States
^fi Departments of Biology, Brigham Young University, Provo, UT, United States
^fj University of Kansas Alzheimer’s Disease Center, University of Kansas Medical Center, Kansas City, KS, United States
^fk Department of Experimental and Clinical Medicine, Neurological Institute, University of Pisa, Pisa, Italy
^fl Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, United States
^fm Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, United States
^fn Department of Pathology and Immunology, Washington University, St. Louis, MO, United States
^fo Division of Psychiatry, University College London, London, United Kingdom
^fp USF Health Byrd Alzheimer’s Institute, University of South Florida, Tampa, FL, United States
^fq Fred Hutchinson Cancer Research Center, Seattle, WA, United States
^fr Department of Molecular Neuroscience, UCL, Institute of Neurology, London, United Kingdom
^fs Mental Health & Behavioral Science Service, Bruce W. Carter VA Medical Center, Miami, FL, United States
^ft Department of Neurodegenerative Disease, UCL Institute of Neurology, London, United Kingdom
^fu Department of Neuroscience, Mayo Clinic, Jacksonville, FL, United States
^fv Department of Neurology, University of Southern California, Los Angeles, CA, United States
^fw Department of Neurology, Catholic University of Rome, Rome, Italy
^fx Department of Psychiatry and Behavioral Sciences, Miller School of Medicine, University of Miami, Miami, FL, United States
^fy Department of Neurology, University of California, Davis, Sacramento, CA, United States
^fz Institute for Memory Impairments and Neurological Disorders, University of California, Irvine, Irvine, CA, United States
^ga Wien Center for Alzheimer’s Disease and Memory Disorders, Mount Sinai Medical Center, Miami Beach, FL, United States
^gb Rush Institute for Healthy Aging, Department of Internal Medicine, Rush University Medical Center, Chicago, IL, United States
^gc Department of Old Age Psychiatry, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, United Kingdom
^gd Department of Primary Medical Care, University Medical Centre Hamburg-Eppendorf, Hamburg, Germany
^ge Department of Pathology, University of Alabama at Birmingham, Birmingham, AL, United States
^gf Sanders-Brown Center on Aging, Department of Biostatistics, University of Kentucky, Lexington, KY, United States
^gg Department of Psychiatry, New York University, New York, NY, United States
^gh Department of Psychiatry and Psychotherapy, University of Cologne, Cologne, Germany
^gi Department of Psychiatry and Psychotherapy, Charité University Medicine, Berlin, Germany
^gj Department of Neurosciences, University of California, San Diego, La Jolla, CA, United States
^gk Department of Pathology and Laboratory Medicine, Emory University, Atlanta, GA, United States
^gl Emory Alzheimer’s Disease Center, Emory University, Atlanta, GA, United States
^gm Department of Psychiatry, University of Freiburg, Freiburg, Germany
^gn Neurogenetics Program, University of California, Los Angeles, Los Angeles, CA, United States
^go Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, United States
^gp Hope Center Program on Protein Aggregation and Neurodegeneration, Washington University School of Medicine, St. Louis, MO, United States
^gq Division of Genetics, Department of Medicine and Partners Center for Personalized Genetic Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, United States
^gr Department of Neurology, Washington University, St. Louis, MO, United States
^gs Department of Genetics, Washington University, St. Louis, MO, United States
^gt Department of Neurology, Massachusetts General Hospital/Harvard Medical School, Boston, MA, United States
^gu Department of Pathology (Neuropathology), University of Pittsburgh, Pittsburgh, PA, United States
^gv Department of Neurology, University of Alabama at Birmingham, Birmingham, AL, United States
^gw Cologne Center for Genomics, University of Cologne, Cologne, Germany
^gx Department of Pathology, Duke University, Durham, NC, United States
^gy Department of Genome Sciences, University of Washington, Seattle, WA, United States
^gz Department of Medicine (Medical Genetics), University of Washington, Seattle, WA, United States
^ha Sanders-Brown Center on Aging, College of Public Health, Department of Epidemiology, University of Kentucky, Lexington, KY, United States
^hb Unidad Clínica de Enfermedades Infecciosas y Microbiología, Hospital Universitario de Valme, Sevilla, Spain
^hc Department of Medicine (Biomedical Genetics), Boston University School of Medicine, Boston, MA, United States
^hd Functional Genomics Center Zurich, ETH/University of Zurich, Zurich, Switzerland
^he Department of Neurology, Oregon Health &Science University, Portland, OR, United States
^hf Department of Neurology, Portland Veterans Affairs Medical Center, Portland, OR, United States
^hg Department of Pathology and Laboratory Medicine, University of California, Irvine, Irvine, CA, United States
^hh Department of Pathology, Boston University School of Medicine, Boston University, Boston, MA, United States
^hi Inserm U558, University of Toulouse, Toulouse, France
^hj Department of Neuropsychology, University of California San Francisco, San Francisco, CA, United States
^hk Institute for Ageing and Health, Newcastle University, Newcastle upon Tyne, United Kingdom
^hl Department of Neurobiology and Behavior, University of California, Irvine, Irvine, CA, United States
^hm Department of Neurology, Emory University, Atlanta, GA, United States
^hn Institute for Stroke and Dementia Research, Klinikum der Universität München, Munich, Germany
^ho German Center for Neurodegenerative Diseases, Munich, Germany
^hp Cleveland Clinic Lou Ruvo Center for Brain Health, Cleveland Clinic, Cleveland, OH, United States
^hq Division of Neuroscience and Experimental Psychology, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Science Centre, Manchester, United Kingdom
^hr Department of Pathology, University of Michigan, Ann Arbor, MI, United States
^hs Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Munich, Germany
^ht Helmholtz Center Munich, Institute of Epidemiology, Neuherberg, Munich, Germany
^hu Ludwig-Maximilians University Chair of Epidemiology, Munich, Germany
^hv Joint Biobank Munich and KORA Biobank, Baltimore, MD, United States
^hw Department of Psychiatry, Johns Hopkins University, Baltimore, MD, United States
^hx Human Genetics, Schools of Life Sciences and Medicine, University of Nottingham, Nottingham, United Kingdom
^hy Department of Medicine-Pulmonary, New York University, New York, NY, United States
^hz Department of Neurology, University of Miami, Miami, FL, United States
^ia Department of Pathology, University of California, San Diego, La Jolla, CA, United States
^ib Institute of Neurology, Catholic University of Sacred Hearth, Rome, Italy
^ic School of Nursing Northwest Research Group on Aging, University of Washington, Seattle, WA, United States
^id Institute of Primary Care and Public Health, Cardiff University, University Hospital of Wales, Cardiff, United Kingdom
^ie Department of Neurology, Northwestern University Feinberg School of Medicine, Chicago, IL, United States
^if Cambridge Institute of Public Health, University of Cambridge School of Clinical Medicine, Cambridge, United Kingdom
^ig Weill Institute for Neurosciences, Memory and Aging Center, University of California, San Francisco, San Francisco, CA, United States
^ih Institute of Social Medicine, Occupational Health and Public Health, University of Leipzig, Leipzig, Germany
ⁱⁱ Department of Pathology, University of Southern California, Los Angeles, CA, United States
^ij Department of Pathology and Laboratory Medicine, University of California, Davis, Sacramento, CA, United States
^ik Institute of Psychiatry, Psychology and Neuroscienceó, King’s College London, London, United Kingdom
^il UK Dementia Research Institute, King’s College London, London, United Kingdom
^im Department of Psychiatry and Psychotherapy, University Medical Center Goettingen, Goettingen, Germany
ⁱⁿ German Center for Neurodegenerative Diseases, Goettingen, Germany
^io IBiMED, Medical Sciences Department, University of Aveiro, Aveiro, Portugal
^ip Molecular Genetics Laboratory-Hospital, University of Central Asturias, Oviedo, Spain
^iq Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, United States
^ir Molecular Genetics Section, Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, United States
^is Department of Neurology, University of California, Irvine, Irvine, CA, United States
^it Department of Neuroscience, Psychology, Drug Research and Child Health, University of Florence, Florence, Italy
^iu Centro di Ricerca, Trasferimento e Alta Formazione DENOTHE, University of Florence, Florence, Italy
^iv Department of Neurology, University of Colorado School of Medicine, Aurora, CO, United States
^iw IRCCS Fondazione Don Carlo Gnocchi, Florence, Italy
^ix Laboratory of Neuropsychiatry, IRCCS Santa Lucia Foundation, Rome, Italy
^iy Division of Neuropsychiatry, Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, TX, United States
^iz Alzheimer’s Disease Center, New York University, New York, NY, United States
^ja Oxford Healthy Aging Project, Clinical Trial Service Unit, University of Oxford, Oxford, United Kingdom
^jb Department of Epidemiology, Columbia University, New York, NY, United States
^jc Oxford Project to Investigate Memory and Ageing, University of Oxford, Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, Oxford, United Kingdom
^jd Department of Neurology, Keck School of Medicine at the University of Southern California, Los Angeles, Los Angeles, CA, United States
^je Department of Neurology, University of Texas Southwestern Medical Center, Dallas, TX, United States
^jf Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
^jg Department of Pathology (Neuropathology), Rush University Medical Center, Chicago, IL, United States
^jh Department of Psychiatry, University of Southern California, Los Angeles, CA, United States
^ji Department of Pathology and Laboratory Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, United States
^jj Department of Pathology, Johns Hopkins University, Baltimore, MD, United States
^jk Sanders-Brown Center on Aging, Department of Neuroscience, University of Kentucky, Lexington, KY, United States
^jl Department of Neurology, University of California, Los Angeles, Los Angeles, CA, United States
^jm Department of Pathology and Laboratory Medicine, University of California, Los Angeles, Los Angeles, CA, United States
^jn Taub Institute on Alzheimer’s Disease and the Aging Brain, Department of Pathology, Columbia University, New York, NY, United States
^jo Department of Psychiatry and Behavioral Sciences, Northwestern University Feinberg School of Medicine, Chicago, IL, United States
^jp Department of Psychiatry and Behavioral Sciences, Duke University, Durham, NC, United States
^jq Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
^jr Department of Human Genetics, Emory University, Atlanta, GA, United States
^js Department of Pathology, Oregon Health & Science University, Portland, OR, United States
^jt National Institute of Neurological Disorders and Stroke, Bethesda, MD, United States
^ju Gottfried Schatz Research Center for Cell Signaling, Metabolism and Aging, Division of Molecular Biology and Biochemistry, Medical University Graz, Graz, Austria
^jv Gerontology and Geriatrics Research Laboratory, IRCCS Casa Sollievo della Sofferenza, San Giovanni Rotondo, Italy
^jw Department Geriatric Care, Orthogeriatrics and Rehabilitation, Galliera Hospital, Genova, Italy
^jx IdiPAZ, Instituto de Investigación Sanitaria la Paz, Madrid, Spain
^jy Centro de Biologia Molecular Severo Ochoa (CSIC-UAM), Madrid, Spain
^jz German Center for Neurodegenerative Diseases, Berlin, Germany
^ka Instituto di Ricovero e Cura a Carattere Scientifico, Associazione Oasi Maria Santissima Srl, Troina, Italy
^kb Center for Translational and Computational Neuroimmunology, Department of Neurology, Columbia University Medical Center, New York, NY, United States
^kc Memory Unit, Neurology Department and Sant Pau Biomedical Research Institute, Hospital de la Santa Creu i Sant Pau, Autonomous University Barcelona, Barcelona, Spain
^kd Somerset Partnership NHS Trust, Somerset, United Kingdom
^ke The Wellcome Trust Sanger Institute, Hinxton, Cambridge, United Kingdom
^kf Ronald M. Loeb Center for Alzheimer’s Disease, Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, United States
^kg University of Bristol Medical School, Learning & Research level 2, Southmead Hospital, Bristol, United Kingdom
^kh Department of Neurology, Mayo Clinic, Jacksonville, FL, United States
^ki Memory Research and Resources Center, CMRR de Bordeaux, Bordeaux, France
^kj Utah State University, Logan, UT, United States
^kk Department of Neurology, Erasmus MC University Medical Center, Rotterdam, Netherlands
^kl Departments of Radiology, Erasmus MC University Medical Center, Rotterdam, Netherlands
^km Department of Research Rouvray Psychiatric Hospital, Sotteville-lès-Rouen, France
^kn Department of Neurology, Medical University Graz, Graz, Austria
^ko Center for Applied Genomics, Children’s Hospital of Philadelphia, The Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
^kp Division of Human Genetics, Department of Pediatrics, The Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
^kq Department of Ophthalmology, Boston University School of Medicine, Boston University, Boston, MA, United States
^kr Department of Epidemiology, Boston University School of Public Health, Boston, MA, United States
^ks Department of Health Services, University of Washington, Seattle, WA, United States
^kt Kaiser Permanente, Washington Health Research Institute, Seattle, WA, United States
^ku Glenn Biggs Institute for Alzheimer’s and Neurodegenerative Diseases, San Antonio, TX, United States
^kv Centre Hospitalier Universitaire de Lille, Lille, France

Abstract
An amendment to this paper has been published and can be accessed via a link at the top of the paper. © 2019, The Author(s), under exclusive licence to Springer Nature America, Inc.

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

"Commentary on Hamilton et al. (2019): Why aren't cannabis use rates declining among US adolescents?"(2019) Addiction

Commentary on Hamilton et al. (2019): Why aren’t cannabis use rates declining among US adolescents?
(2019) Addiction, .

Grucza, R.A., Borodovsky, J.T.

Department of Psychiatry, Washington University School of Medicine, St Louis, MO, United States

Author Keywords
Cannabis; cohort; epidemiology; mutivariate; period; trends

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

"A Trial of Sertraline or Cognitive Behavior Therapy for Depression in Epilepsy" (2019) Annals of Neurology

A Trial of Sertraline or Cognitive Behavior Therapy for Depression in Epilepsy
(2019) Annals of Neurology, .

Gilliam, F.G.^a ^b , Black, K.J.^c , Carter, J.^c , Freedland, K.E.^c , Sheline, Y.I.^d , Tsai, W.-Y.^e , Lustman, P.J.^c ^f

^a Department of Neuroscience, University of Kentucky, Lexington, KY, United States
^b Epilepsy Research Center, University of Kentucky, Lexington, KY, United States
^c Department of Psychiatry, Washington University, St Louis, MO, United States
^d Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, United States
^e Department of Biostatistics, Columbia University, New York, NY, United States
^f Veterans Affairs St Louis Health Center, St Louis, MO, United States

Abstract
Objective: Limited evidence is available to guide treatment of depression for persons with epilepsy. We evaluated the comparative effectiveness of sertraline and cognitive behavior therapy (CBT) for depression, quality of life, seizures, and adverse treatment effects. Methods: We randomly assigned 140 adult outpatients with epilepsy and current major depressive disorder to sertraline or weekly CBT for 16 weeks. The primary outcome was remission from depression based on the Mini International Neuropsychiatric Interview (MINI). Secondary outcomes included the Quality of Life in Epilepsy Inventory-89 (QOLIE-89) seizure rates, the Adverse Events Profile (AEP), the Beck Depression Inventory, and MINI Suicide Risk Module. Results: In the intention-to-treat analysis, 38 (52.8%; 95% confidence interval [CI] = ±12) of the 72 subjects assigned to sertraline and 41 (60.3%; 95% CI = ±11.6) of the 68 subjects in the CBT group achieved remission; the lower bound of efficacy for both groups was greater than our historical placebo control group upper bound of 33.7%. Difference in time to remission between groups was 2.8 days (95% CI = ±0.43; p = 0.79). The percent improvement of mean QOLIE-89 scores was significant for both the CBT (25.7%; p < 0.001) and sertraline (28.3%; p < 0.001) groups. The difference in occurrence of generalized tonic–clonic seizures between groups was 0.3% (95% CI = ±8.6; p = 0.95). Suicide risk at final assessment was associated with persistent depression (p < 0.0001) but not seizures or sertraline. Interpretation: Depression remitted in just over one-half of subjects following sertraline or CBT. Despite the complex psychosocial disability associated with epilepsy, improving depression benefits quality of life. Serotonin reuptake inhibition does not appear to increase seizures or suicidality in persons with epilepsy. ANN NEUROL 2019. © 2019 American Neurological Association

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

"Peripheral Neuropathy as a Component of Skeletal Disease in Diabetes" (2019) Current Osteoporosis Reports

Peripheral Neuropathy as a Component of Skeletal Disease in Diabetes
(2019) Current Osteoporosis Reports, .

Beeve, A.T.^a ^b , Brazill, J.M.^a , Scheller, E.L.^a ^b ^c

^a Department of Medicine, Division of Bone and Mineral Diseases, Washington University, 660 South Euclid Avenue, Saint Louis, MO 63110, United States
^b Department of Biomedical Engineering, Washington University, 6201 Forsyth Blvd, Saint Louis, MO 63105, United States
^c Department of Cell Biology and Physiology, Washington University, 660 South Euclid Avenue, Saint Louis, MO 63110, United States

Abstract
Purpose of Review: The goal of this review is to explore clinical associations between peripheral neuropathy and diabetic bone disease and to discuss how nerve dysfunction may contribute to dysregulation of bone metabolism, reduced bone quality, and fracture risk. Recent Findings: Diabetic neuropathy can decrease peripheral sensation (sensory neuropathy), impair motor coordination (motor neuropathy), and increase postural hypotension (autonomic neuropathy). Together, this can impair overall balance and increase the risk for falls and fractures. In addition, the peripheral nervous system has the potential to regulate bone metabolism directly through the action of local neurotransmitters on bone cells and indirectly through neuroregulation of the skeletal vascular supply. Summary: This review critically evaluates existing evidence for diabetic peripheral neuropathy as a risk factor or direct actor on bone disease. In addition, we address therapeutic and experimental considerations to guide patient care and future research evaluating the emerging relationship between diabetic neuropathy and bone health. © 2019, The Author(s).

Author Keywords
Diabetes; Fracture; Marrow adiposity; Marrow fat; Metabolic bone disease; Microvascular disease; Neuropathy

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

"Photoreceptors in a mouse model of Leigh syndrome are capable of normal light-evoked signaling" (2019) Journal of Biological Chemistry

Photoreceptors in a mouse model of Leigh syndrome are capable of normal light-evoked signaling
(2019) Journal of Biological Chemistry, 294 (33), pp. 12432-12443.

Gospe, S.M., III^a ^d , Travis, A.M.^b , Kolesnikov, A.V.^c , Klingeborn, M.^a , Wang, L.^a , Kefalov, V.J.^c , Arshavsky, V.Y.^a ^b

^a Department of Ophthalmology, Duke University, Durham, NC 27710, United States
^b Departments of Pharmacology and Cancer Biology, Duke University, Durham, NC 27710, United States
^c Department of Ophthalmology and Visual Sciences, Washington University School of Medicine, Saint Louis, MO 63110, United States
^d Dept. of Ophthalmology and Visual Sciences, University of Michigan, Ann Arbor, MI 48105, United States

Abstract
Mitochondrial dysfunction is an important cause of heritable vision loss. Mutations affecting mitochondrial bioenergetics May lead to isolated vision loss or life-threatening systemic disease, depending on a mutation’s severity. Primary optic nerve atrophy resulting from death of retinal ganglion cells is the most prominent ocular manifestation of mitochondrial disease. However, dysfunction of other retinal cell types has also been described, sometimes leading to a loss of photoreceptors and retinal pigment epithelium that manifests clinically as pigmentary retinopathy. A popular mouse model of mitochondrial disease that lacks NADH:ubiquinone oxidoreductase subunit S4 (NDUFS4), a subunit of mitochondrial complex I, phenocopies many traits of the human disease Leigh syndrome, including the development of optic atrophy. It has also been reported that ndufs4/mice display diminished light responses at the level of photoreceptors or bipolar cells. By conducting electroretinography (ERG) recordings in live ndufs4/mice, we now demonstrate that this defect occurs at the level of retinal photoreceptors. We found that this deficit does not arise from retinal developmental anomalies, photoreceptor degeneration, or impaired regeneration of visual pigment. Strikingly, the impairment of ndufs4/photoreceptor function was not observed in ex vivo ERG recordings from isolated retinas, indicating that photoreceptors with complex I deficiency are intrinsically capable of normal signaling. The difference in electrophysiological phenotypes in vivo and ex vivo suggests that the energy deprivation associated with severe mitochondrial impairment in the outer retina renders ndufs4/photoreceptors unable to maintain the homeostatic conditions required to operate at their normal capacity. © 2019 Gospe et al.

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

"Transdiagnostic Multimodal Neuroimaging in Psychosis: Structural, Resting-State, and Task Magnetic Resonance Imaging Correlates of Cognitive Control" (2019) Biological Psychiatry: Cognitive Neuroscience and Neuroimaging

Transdiagnostic Multimodal Neuroimaging in Psychosis: Structural, Resting-State, and Task Magnetic Resonance Imaging Correlates of Cognitive Control
(2019) Biological Psychiatry: Cognitive Neuroscience and Neuroimaging, .

Lerman-Sinkoff, D.B.^a ^b , Kandala, S.^c , Calhoun, V.D.^f ^g , Barch, D.M.^c ^d ^e , Mamah, D.T.^c

^a Department of Biomedical Engineering, Washington University in St. Louis, St. Louis, MO, United States
^b Medical Scientist Training Program, Washington University in St. Louis, St. Louis, MO, United States
^c Department of Psychiatry, Washington University in St. Louis, St. Louis, MO, United States
^d Department of Psychological and Brain Science, Washington University in St. Louis, St. Louis, MO, United States
^e Department of Radiology, Washington University in St. Louis, St. Louis, MO, United States
^f Medical Image Analysis Lab, The Mind Research Network, University of New Mexico, Albuquerque, New Mexico, Mexico
^g Department of Electrical and Computer Engineering, University of New Mexico, Albuquerque, New Mexico, Mexico

Abstract
Background: Disorders with psychotic features, including schizophrenia and some bipolar disorders, are associated with impairments in regulation of goal-directed behavior, termed cognitive control. Cognitive control–related neural alterations have been studied in psychosis. However, studies are typically unimodal, and relationships across modalities of brain function and structure remain unclear. Thus, we performed transdiagnostic multimodal analyses to examine cognitive control–related neural variation in psychosis. Methods: Structural, resting, and working memory task imaging for 31 control participants, 27 participants with bipolar disorder, and 23 participants with schizophrenia were collected and processed identically to the Human Connectome Project, enabling identification of relationships with prior multimodal work. Two cognitive control–related independent components (ICs) derived from the Human Connectome Project using multiset canonical correlation analysis with joint IC analysis were used to predict performance in psychosis. De novo multiset canonical correlation analysis with joint IC analysis was performed, and the results were correlated with cognitive control. Results: A priori working memory and cortical thickness maps significantly predicted cognitive control in psychosis. De novo multiset canonical correlation analysis with joint IC analysis identified an IC correlated with cognitive control that also discriminated groups. Structural contributions included insular and cingulate regions; task contributions included precentral, posterior parietal, cingulate, and visual regions; and resting-state contributions highlighted canonical network organization. Follow-up analyses suggested that correlations with cognitive control were primarily influenced by participants with schizophrenia. Conclusions: A priori and de novo imaging replicably identified a set of interrelated patterns across modalities and the healthy-to-psychosis spectrum, suggesting robustness of these features. Relationships between imaging and cognitive control performance suggest that shared symptomatology may be key to identifying transdiagnostic relationships in psychosis. © 2019 Society of Biological Psychiatry

Author Keywords
Bipolar disorder; Cognitive control; mCCA+jICA; Multimodal fusion; Schizophrenia; Transdiagnostic psychosis

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

"Nerves in Bone: Evolving Concepts in Pain and Anabolism" (2019) Journal of Bone and Mineral Research

Nerves in Bone: Evolving Concepts in Pain and Anabolism
(2019) Journal of Bone and Mineral Research, 34 (8), pp. 1393-1406. Cited 1 time.

Brazill, J.M.^a , Beeve, A.T.^a ^b , Craft, C.S.^a ^c , Ivanusic, J.J.^d , Scheller, E.L.^a ^c

^a Department of Internal Medicine, Division of Bone and Mineral Diseases, Washington University, St. Louis, MO, United States
^b Department of Biomedical Engineering, Washington University, St. Louis, MO, United States
^c Department of Cell Biology and Physiology, Washington University, St. Louis, MO, United States
^d Department of Anatomy and Neuroscience, University of Melbourne, Melbourne, VIC, Australia

Abstract
The innervation of bone has been described for centuries, and our understanding of its function has rapidly evolved over the past several decades to encompass roles of subtype-specific neurons in skeletal homeostasis. Current research has been largely focused on the distribution and function of specific neuronal populations within bone, as well as their cellular and molecular relationships with target cells in the bone microenvironment. This review provides a historical perspective of the field of skeletal neurobiology that highlights the diverse yet interconnected nature of nerves and skeletal health, particularly in the context of bone anabolism and pain. We explore what is known regarding the neuronal subtypes found in the skeleton, their distribution within bone compartments, and their central projection pathways. This neuroskeletal map then serves as a foundation for a comprehensive discussion of the neural control of skeletal development, homeostasis, repair, and bone pain. Active synthesis of this research recently led to the first biotherapeutic success story in the field. Specifically, the ongoing clinical trials of anti-nerve growth factor therapeutics have been optimized to titrated doses that effectively alleviate pain while maintaining bone and joint health. Continued collaborations between neuroscientists and bone biologists are needed to build on this progress, leading to a more complete understanding of neural regulation of the skeleton and development of novel therapeutics. © 2019 The Authors. Journal of Bone and Mineral Research published by Wiley Periodicals, Inc. © 2019 The Authors. Journal of Bone and Mineral Research published by Wiley Periodicals, Inc.

Author Keywords
ANALYSIS/QUANTITATION OF BONE, OTHER; BONE-BRAIN-NERVOUS SYSTEM INTERACTIONS; SYSTEMS BIOLOGY – BONE INTERACTORS, OTHER; THERAPEUTICS; THERAPEUTICS, ANABOLICS

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

"Automatic detection of eating disorder-related social media posts that could benefit from a mental health intervention" (2019) International Journal of Eating Disorders

Automatic detection of eating disorder-related social media posts that could benefit from a mental health intervention
(2019) International Journal of Eating Disorders, .

Yan, H.^a , Fitzsimmons-Craft, E.E.^b , Goodman, M.^b , Krauss, M.^b , Das, S.^a , Cavazos-Rehg, P.^b

^a Department of Computer Science and Engineering, Washington University in St. Louis, St. Louis, MO, United States
^b Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, United States

Abstract
Objective: Online forums allow people to semi-anonymously discuss their struggles, often leading to greater honesty. This characteristic makes forums valuable for identifying users in need of immediate help from mental health professionals. Because it would be impractical to manually review every post on a forum to identify users in need of urgent help, there may be value to developing algorithms for automatically detecting posts reflecting a heightened risk of imminent plans to engage in disordered behaviors. Method: Five natural language processing techniques (tools to perform computational text analysis) were used on a data set of 4,812 posts obtained from six eating disorder-related subreddits. Two licensed clinical psychologists labeled 53 of these posts, deciding whether or not the content of the post indicated that its author needed immediate professional help. The remaining 4,759 posts were unlabeled. Results: Each of the five techniques ranked the 50 posts most likely to be intervention-worthy (the “top-50”). The two most accurate detection techniques had an error rate of 4% for their respective top-50. Discussion: This article demonstrates the feasibility of automatically detecting—with only a few dozen labeled examples—the posts of individuals in need of immediate mental health support for an eating disorder. © 2019 Wiley Periodicals, Inc.

Author Keywords
eating disorders; machine learning; mass screening; natural language processing; social media

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

"Socially oriented thinking and the biological stress response: Thinking of friends and family predicts trajectories of salivary cortisol decline" (2019) Psychophysiology

Socially oriented thinking and the biological stress response: Thinking of friends and family predicts trajectories of salivary cortisol decline
(2019) Psychophysiology, art. no. e13461, .

Vine, V.^a , Hilt, L.M.^b , Marroquín, B.^c , Gilbert, K.E.^d

^a Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA, United States
^b Department of Psychology, Lawrence University, Appleton, WI, United States
^c Department of Psychology, Loyola Marymount University, Los Angeles, CA, United States
^d Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, United States

Abstract
The cortisol stress response has been related to perceived social support, but previous studies rely on self-reported social support variables. The cortisol recovery phase in particular has been theorized to serve a social coping function, but individual differences in recovery slope have not yet been examined in relation to social coping-relevant indices. This study addressed these gaps by examining the relationship of cortisol trajectories after a socioevaluative task to individual differences in covertly assessed cognitions related to close social relationships. We examined trajectories of cortisol change related to socially oriented thinking, the semi-implicit activation of cognitive representations of friends or family. Young adults (N = 64) gave salivary cortisol samples before and for 45 min after a speech task. Participants’ thoughts were sampled repeatedly; the frequency of words related to friends or family was assessed to index socially oriented thinking. A free curve slope intercept latent growth curve model showed excellent fit with the cortisol data. Socially oriented thinking was unrelated to overall magnitude of cortisol response to the task (latent intercept) but predicted the latent cortisol trajectory, independently of cortisol intercept and baseline cortisol levels. Socially oriented thinkers showed more gradual cortisol declines, whereas nonsocially oriented thinkers showed a steeper downslope driven primarily by cortisol changes 45 min after the task. Individual differences in socially oriented thinking may manifest in different rates of biological changes following a performance task. © 2019 Society for Psychophysiological Research

Author Keywords
cortisol; cortisol recovery; free curve slope intercept; social support; socially oriented thinking

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

"Amyloid imaging of dutch-type hereditary cerebral amyloid angiopathy carriers" (2019) Annals of Neurology

Amyloid imaging of dutch-type hereditary cerebral amyloid angiopathy carriers
(2019) Annals of Neurology, .

Schultz, A.P.^a , Kloet, R.W.^b , Sohrabi, H.R.^c ^d , van der Weerd, L.^b , van Rooden, S.^b , Wermer, M.J.H.^b , Moursel, L.G.^b , Yaqub, M.^e , van Berckel, B.N.M.^e , Chatterjee, P.^d , Gardener, S.L.^c , Taddei, K.^c , Fagan, A.M.^f , Benzinger, T.L.^f , Morris, J.C.^f , Sperling, R.^a , Johnson, K.^a , Bateman, R.J.^f , Gurol, M.E.^a , van Buchem, M.A.^b , Martins, R.^c ^d , Chhatwal, J.P.^a , Greenberg, S.M.^a , Dominantly Inherited Alzheimer Network^g

^a Departments of Neurology and Radiology, Massachusetts General Hospital, Boston, MA, United States
^b Departments of Neurology and Radiology, Leiden University Medical Center, Leiden, Netherlands
^c School of Medical and Health Sciences, Edith Cowan University, Joondalup, WA, Australia
^d Department of Biomedical Sciences, Macquarie University, North Ryde, NSW, Australia
^e Department of Radiology and Nuclear Medicine and Department of Neurology (Alzheimer’s Center), VU University Medical Center, Amsterdam, Netherlands
^f Departments of Neurology and Radiology, Washington University School of Medicine, St Louis, MO, United States

Abstract
Objective: To determine whether amyloid imaging with the positron emission tomography (PET) agent Pittsburgh compound B (PiB) can detect vascular β-amyloid (Aβ) in the essentially pure form of cerebral amyloid angiopathy associated with the Dutch-type hereditary cerebral amyloid angiopathy (D-CAA) mutation. Methods: PiB retention in a cortical composite of frontal, lateral, and retrosplenial regions (FLR) was measured by PiB-PET in 19 D-CAA mutation carriers (M+; 13 without neurologic symptoms, 6 with prior lobar intracerebral hemorrhage) and 17 mutation noncarriers (M−). Progression of PiB retention was analyzed in a subset of 18 serially imaged individuals (10 asymptomatic M+, 8 M−). We also analyzed associations between PiB retention and cerebrospinal fluid (CSF) Aβ concentrations in 17 M+ and 11 M− participants who underwent lumbar puncture and compared the findings to PiB-PET and CSF Aβ in 37 autosomal dominant Alzheimer disease (ADAD) mutation carriers. Results: D-CAA M+ showed greater age-dependent FLR PiB retention (p < 0.001) than M−, and serially imaged asymptomatic M+ demonstrated greater longitudinal increases (p = 0.004). Among M+, greater FLR PiB retention associated with reduced CSF concentrations of Aβ40 (r = −0.55, p = 0.021) but not Aβ42 (r = 0.01, p = 0.991). Despite comparably low CSF Aβ40 and Aβ42, PiB retention was substantially less in D-CAA than ADAD (p < 0.001). Interpretation: Increased PiB retention in D-CAA and correlation with reduced CSF Aβ40 suggest this compound labels vascular amyloid, although to a lesser degree than amyloid deposits in ADAD. Progression in PiB signal over time suggests amyloid PET as a potential biomarker in trials of candidate agents for this untreatable cause of hemorrhagic stroke. ANN NEUROL 2019. © 2019 American Neurological Association

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

"An endogenous peptide marker differentiates SOD1 stability and facilitates pharmacodynamic monitoring in SOD1 amyotrophic lateral sclerosis" (2019) JCI Insight

An endogenous peptide marker differentiates SOD1 stability and facilitates pharmacodynamic monitoring in SOD1 amyotrophic lateral sclerosis
(2019) JCI Insight, 4 (10), art. no. e122768, . Cited 1 time.

Gertsman, I.^a ^b , Wuu, J.^c , McAlonis-Downes, M.^d , Ghassemian, M.^e , Ling, K.^f , Rigo, F.^f , Bennett, F.^f , Benatar, M.^c , Miller, T.M.^g , Da Cruz, S.^d

^a Biochemical Genetics and Metabolomics Laboratory, Department of Pediatrics, UCSD, 7917 Ostrow St., San Diego, CA 92111, United States
^b Clarus Analytical, LLC, San Diego, CA, United States
^c Department of Neurology, University of Miami, Miami, FL, United States
^d Ludwig Institute for Cancer Research, Department of Chemistry and Biochemistry, UCSD, San Diego, CA, United States
^e Biomolecular/Proteomics Mass Spectrometry Facility, Department of Chemistry and Biochemistry, UCSD, San Diego, CA, United States
^f Ionis Pharmaceuticals, Carlsbad, CA, United States
^g Department of Neurology, Washington University in St. Louis, St. Louis, MO, United States

Abstract
The discovery of novel biomarkers has emerged as a critical need for therapeutic development in amyotrophic lateral sclerosis (ALS). For some subsets of ALS, such as the genetic superoxide dismutase 1 (SOD1) form, exciting new treatment strategies, such as antisense oligonucleotide- mediated (ASO-mediated) SOD1 silencing, are being tested in clinical trials, so the identification of pharmacodynamic biomarkers for therapeutic monitoring is essential. We identify increased levels of a 7-amino acid endogenous peptide of SOD1 in cerebrospinal fluid (CSF) of human SOD1 mutation carriers but not in other neurological cases or nondiseased controls. Levels of peptide elevation vary based on the specific SOD1 mutation (ranging from 1.1-fold greater than control in D90A to nearly 30-fold greater in V148G) and correlate with previously published measurements of SOD1 stability. Using a mass spectrometry-based method (liquid chromatography-mass spectrometry), we quantified peptides in both extracellular samples (CSF) and intracellular samples (spinal cord from rat) to demonstrate that the peptide distinguishes mutation-specific differences in intracellular SOD1 degradation. Furthermore, 80% and 63% reductions of the peptide were measured in SOD1G93A and SOD1H46R rat CSF samples, respectively, following treatment with ASO, with an improved correlation to mRNA levels in spinal cords compared with the ELISA measuring intact SOD1 protein. These data demonstrate the potential of this peptide as a pharmacodynamic biomarker. © 2019 American Society for Clinical Investigation.

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

"Intraspecific Energetic Trade-Offs and Costs of Encephalization Vary from Interspecific Relationships in Three Species of Mormyrid Electric Fishes" (2019) Brain, Behavior and Evolution

Intraspecific Energetic Trade-Offs and Costs of Encephalization Vary from Interspecific Relationships in Three Species of Mormyrid Electric Fishes
(2019) Brain, Behavior and Evolution, .

Sukhum, K.V., Freiler, M.K., Carlson, B.A.

Department of Biology, Washington University, Campus Box 1137, 1 Brookings Drive, St. Louis, MO 63130-4899, United States

Abstract
The evolution of increased encephalization comes with an energetic cost. Across species, this cost may be paid for by an increase in metabolic rate or by energetic trade-offs between the brain and other energy-expensive tissues. However, it remains unclear whether these solutions to deal with the energetic requirements of an enlarged brain are related to direct physiological constraints or other evolved co-adaptations. We studied the highly encephalized mormyrid fishes, which have extensive species diversity in relative brain size. We previously found a correlation between resting metabolic rate and relative brain size across species; however, it is unknown how this interspecific relationship evolved. To address this issue, we measured intraspecific variation in relative brain size, the sizes of other organs, metabolic rate, and hypoxia tolerance to determine if intraspecific relationships between brain size and organismal energetics are similar to interspecific relationships. We found that 3 species of mormyrids with varying degrees of encephalization had no intraspecific relationships between relative brain size and relative metabolic rate or relative sizes of other organs, and only 1 species had a relationship between relative brain size and hypoxia tolerance. These species-specific differences suggest that the interspecific relationship between metabolic rate and relative brain size is not the result of direct physiological constraints or strong stabilizing selection, but is instead due to other species level co-adaptations. We conclude that variation within species must be considered when determining the energetic costs and trade-offs underlying the evolution of extreme encephalization. © 2019 S. Karger AG, Basel. Copyright: All rights reserved.

Author Keywords
Brainevolution; Electric fish; Hypoxia; Intraspecific variation; Resting metabolic rate; Species level adaptations

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

"Multi-loop model of Alzheimer disease: An integrated perspective on the Wnt/GSK3β, α-synuclein, and type 3 diabetes hypotheses" (2019) Frontiers in Aging Neuroscience

Multi-loop model of Alzheimer disease: An integrated perspective on the Wnt/GSK3β, α-synuclein, and type 3 diabetes hypotheses
(2019) Frontiers in Aging Neuroscience, 10 (JUL), art. no. 184, .

Norwitz, N.G.^a , Mota, A.S.^a , Norwitz, S.G.^b , Clarke, K.^a

^a Department of Physiology, Anatomy and Genetics, University of Oxford, Oxford, United Kingdom
^b Department of Neuroscience, Washington University in St. Louis, St. Louis, MO, United States

Abstract
As the prevalence of Alzheimer disease (AD) continues to rise unabated, new models have been put forth to improve our understanding of this devastating condition. Although individual models may have their merits, integrated models may prove more valuable. Indeed, the reliable failures of monotherapies for AD, and the ensuing surrender of major drug companies, suggests that an integrated perspective may be necessary if we are to invent multifaceted treatments that could ultimately prove more successful. In this review article, we discuss the Wnt/Glycogen Synthase Kinase 3β (GSK3β), α-synuclein, and type 3 diabetes hypotheses of AD, and their deep interconnection, in order to foster the integrative thinking that may be required to reach a solution for the coming neurological epidemic. Copyright © 2019 Norwitz, Mota, Norwitz and Clarke. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

Author Keywords
Alzheimer disease; Aβ; GSK3β; Parkinson’s disease; Tau; Type 3 diabetes; Wnt-signaling; α-synuclein

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

"Preregistration Is Hard, And Worthwhile" (2019) Trends in Cognitive Sciences

Preregistration Is Hard, And Worthwhile
(2019) Trends in Cognitive Sciences, .

Nosek, B.A.^a , Beck, E.D.^b , Campbell, L.^c , Flake, J.K.^d , Hardwicke, T.E.^e , Mellor, D.T.^a , van ’t Veer, A.E.^f , Vazire, S.^g

^a Center for Open Science, University of Virginia, Charlottesville, VA, United States
^b Washington University in St. Louis, St. Louis, MO, United States
^c University of Western Ontario, London, Ontario, Canada
^d McGill University, Montreal, Quebec, Canada
^e Meta-Research Innovation Center Berlin (METRIC-B), QUEST Center for Transforming Biomedical Research, Berlin Institute of Health, Charité – Universitätsmedizin Berlin, Berlin, Germany
^f Methodology and Statistics unit, Institute of Psychology, Leiden University, Leiden, Netherlands
^g University of California, Davis, CA, United States

Abstract
Preregistration clarifies the distinction between planned and unplanned research by reducing unnoticed flexibility. This improves credibility of findings and calibration of uncertainty. However, making decisions before conducting analyses requires practice. During report writing, respecting both what was planned and what actually happened requires good judgment and humility in making claims. © 2019 Elsevier Ltd

Author Keywords
confirmatory research; exploratory research; preregistration; reproducibility; transparency

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

"Influence of senior housing types on cognitive decline and nursing home admission among lower-income older adults" (2019) Aging and Mental Health

Influence of senior housing types on cognitive decline and nursing home admission among lower-income older adults
(2019) Aging and Mental Health, .

Park, S.^a , Kim, B.^b , Kwon, E.^c , Kown, G.^a

^a George Warren Brown School of Social Work, Washington University in Saint Louis, Saint Louis, MO, United States
^b College of Health and Human Services, University of New Hampshire, Durham, NH, United States
^c Department of Social Work, St. Cloud State University, St. Cloud, MN, United States

Abstract
Objectives: Focusing on unique ageing populations in subsidized senior housing for lower-income older adults, this study contributes to literature on housing and aging; provides initial understanding of existing housing types; and explores the extent to which living in different housing types may influence changes in cognitive function and likelihood of nursing home admission. Method: Data came from seven waves (2002–2014) of the Health and Retirement Study. A latent-class clustering approach was used to identify senior-housing types among lower-income older people; Results: We identified four discernible housing types among lower-income older adults: (1) High physical & Low service, (2) Low physical & Low service, (3) High physical & High service, and (4) Medium physical & High service. Individuals in Medium physical & High service and High physical & Low service types were likely to have higher cognitive-function levels at baseline (B = 0.58, p <.001; 0.58, p <.001) and slower rates of decline over time (B = 0.42, p <.001; B = 0.32, p <.01). Older adults in High physical & High service are significantly less likely to be admitted to a nursing home (OR = 0.55, p <.00). Conclusion: The mismatch between health needs and lack of service and support suggests that current residents in each housing type relocate, based on knowledge of subsidized housing or availability. Future studies should examine possible mismatches between health needs and housing environment. © 2019, © 2019 Informa UK Limited, trading as Taylor & Francis Group.

Author Keywords
cognitive decline; lower-income older people; nursing home admission; Support levels in senior housing

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

"Current Landscape of Treatments for Wolfram Syndrome" (2019) Trends in Pharmacological Sciences

Current Landscape of Treatments for Wolfram Syndrome
(2019) Trends in Pharmacological Sciences, .

Abreu, D.^a ^b , Urano, F.^a ^c

^a Department of Medicine, Division of Endocrinology, Metabolism, and Lipid Research, Washington University School of Medicine, St. Louis, MO 63110, United States
^b Medical Scientist Training Program, Washington University School of Medicine, St. Louis, MO 63110, United States
^c Department of Pathology and Immunology, Washington University School of Medicine, St. Louis, MO 63110, United States

Abstract
Wolfram syndrome is a rare genetic spectrum disorder characterized by insulin-dependent diabetes mellitus, optic nerve atrophy, and progressive neurodegeneration, and ranges from mild to severe clinical symptoms. There is currently no treatment to delay, halt, or reverse the progression of Wolfram syndrome, raising the urgency for innovative therapeutics for this disease. Here, we summarize our vision for developing novel treatment strategies and achieving a cure for Wolfram-syndrome-spectrum disorder. © 2019 The Author(s)

Author Keywords
endoplasmic reticulum; gene therapy; regenerative therapy; WFS1; Wolfram syndrome

Document Type: Short Survey
Publication Stage: Article in Press
Source: Scopus
Access Type: Open Access

"Local-Global Parcellation of the Human Cerebral Cortex from Intrinsic Functional Connectivity MRI" (2018) Cerebral Cortex (New York, N.Y. : 1991)

Local-Global Parcellation of the Human Cerebral Cortex from Intrinsic Functional Connectivity MRI
(2018) Cerebral Cortex (New York, N.Y. : 1991), 28 (9), pp. 3095-3114. Cited 9 times.

Schaefer, A.^a , Kong, R.^a , Gordon, E.M.^b , Laumann, T.O.^c , Zuo, X.-N.^d ^e , Holmes, A.J.^f , Eickhoff, S.B.^g ^h , Yeo, B.T.T.^a ⁱ ^j

^a Department of Electrical and Computer Engineering, ASTAR-NUS Clinical Imaging Research Centre, Singapore Institute for Neurotechnology and Memory Networks Program, National University of Singapore, Singapore
^b VISN 17 Center of Excellence for Research on Returning War Veterans, Waco, TX, United States
^c Department of Neurology, Washington University in St. Louis, St. Louis, MO, United States
^d CAS Key Laboratory of Behavioral Sciences, Institute of Psychology, Beijing, China
^e University of Chinese Academy of Sciences, Beijing, China
^f Yale University, New HavenCT, United States
^g Institute for Systems Neuroscience, Medical Faculty, Heinrich-Heine University Düsseldorf, Düsseldorf, Germany
^h Institute of Neuroscience and Medicine, Brain and Behaviour (INM-7), Research Center Jülich, Jülich, Germany
ⁱ Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, United States
^j Centre for Cognitive Neuroscience, Duke-NUS Medical School, Singapore

Abstract
A central goal in systems neuroscience is the parcellation of the cerebral cortex into discrete neurobiological “atoms”. Resting-state functional magnetic resonance imaging (rs-fMRI) offers the possibility of in vivo human cortical parcellation. Almost all previous parcellations relied on 1 of 2 approaches. The local gradient approach detects abrupt transitions in functional connectivity patterns. These transitions potentially reflect cortical areal boundaries defined by histology or visuotopic fMRI. By contrast, the global similarity approach clusters similar functional connectivity patterns regardless of spatial proximity, resulting in parcels with homogeneous (similar) rs-fMRI signals. Here, we propose a gradient-weighted Markov Random Field (gwMRF) model integrating local gradient and global similarity approaches. Using task-fMRI and rs-fMRI across diverse acquisition protocols, we found gwMRF parcellations to be more homogeneous than 4 previously published parcellations. Furthermore, gwMRF parcellations agreed with the boundaries of certain cortical areas defined using histology and visuotopic fMRI. Some parcels captured subareal (somatotopic and visuotopic) features that likely reflect distinct computational units within known cortical areas. These results suggest that gwMRF parcellations reveal neurobiologically meaningful features of brain organization and are potentially useful for future applications requiring dimensionality reduction of voxel-wise fMRI data. Multiresolution parcellations generated from 1489 participants are publicly available (https://github.com/ThomasYeoLab/CBIG/tree/master/stable_projects/brain_parcellation/Schaefer2018_LocalGlobal).

Document Type: Article
Publication Stage: Final
Source: Scopus

"Frontiers in Opioid Pharmacology" (2018) Anesthesiology

Frontiers in Opioid Pharmacology
(2018) Anesthesiology, 128 (5), pp. 865-866.

Rathmell, J.P., Kharasch, E.D.

From the Department of Anesthesiology, Perioperative and Pain Medicine, Brigham and Women’s Health Care, Harvard Medical School, Boston, Massachusetts (J.P.R.); the Department of Anesthesiology and the Department of Biochemistry and Molecular Biophysics, Washington University in St. Louis, St. Louis, Missouri (E.D.K.), and the Center for Clinical Pharmacology, St. Louis College of Pharmacy and Washington University in St. Louis, St. Louis, Missouri (E.D.K.)

Document Type: Editorial
Publication Stage: Final
Source: Scopus