Minimal clinically important differences of spatiotemporal gait variables in Parkinson disease
(2024) Gait and Posture, 108, pp. 257-263.
Baudendistel, S.T.a , Haussler, A.M.a , Rawson, K.S.a b , Earhart, G.M.a b c
a Program in Physical Therapy, Washington University School of Medicine in St. Louis, United States
b Department of Neurology, Washington University School of Medicine in St. Louis, United States
c Department of Neuroscience, Washington University School of Medicine in St. Louis, United States
Abstract
Background: Assessment of gait function in People with Parkinson Disease (PwPD) is an important tool for monitoring disease progression in PD. While comprehensive gait analysis has become increasingly popular, only one study, Hass et al. (2014), has established minimal clinically important differences (MCID) for one spatiotemporal variable (velocity) in PwPD. Research Question: What are the MCIDs for velocity and additional spatiotemporal variables, including mean, variability, and asymmetry of step length, time, and width? Methods: As part of a larger clinic-based initiative, 382 medicated, ambulatory PwPD walked on an instrumented walkway during routine clinical visits. Distribution and anchor-based methods (Unified Parkinson’s Disease Rating Scale-III, Modified Hoehn and Yahr, and the mobility subsection of the Parkinson Disease Questionnaire) were used to calculate MCIDs for variables of interest in a cross-sectional approach. Results: Distribution measures for all variables are presented. Of nine gait variables, four were significantly associated with every anchor and pooled to the following values: velocity (8.2 cm/s), step length mean (3.6 cm), step length variability (0.7%), and step time variability (0.67%). Significance: The finalized MCID for velocity (8.2 cm/s) was nearly half of the MCID of 15 cm/s reported by Hass et al., potentially due to differences in calculations. These results allow for evaluations of effectiveness of interventions by providing values that are specific to changes in gait for PwPD. Alterations of methodology including different versions of clinical or walking assessments, and/or different calculation and selection of gait variables necessitate careful reasoning when using presented MCIDs. © 2023 Elsevier B.V.
Author Keywords
Gait; MCID; Parkinson disease
Funding details
National Institutes of HealthNIH
Eunice Kennedy Shriver National Institute of Child Health and Human DevelopmentNICHDT32-HD007434
Document Type: Article
Publication Stage: Final
Source: Scopus
Comparative Outcomes of Mechanical Thrombectomy in Acute Ischemic Stroke Patients with ASPECTS 2-3 vs. 4-5
(2024) Journal of Stroke and Cerebrovascular Diseases, 33 (2), art. no. 107528, .
Orscelik, A.a , Matsukawa, H.a b , Elawady, S.S.a , Sowlat, M.M.a , Cunningham, C.a , Zandpazandi, S.a , Kasem, R.A.a , Maier, I.c , Jabbour, P.d , Kim, J.-T.e , Wolfe, S.Q.f , Rai, A.g , Starke, R.M.h , Psychogios, M.-N.i , Shaban, A.j , Goyal, N.k , Yoshimura, S.b , Cuellar, H.l , Howard, B.m , Alawieh, A.m , Romano, D.G.n , Tanweer, O.o , Mascitelli, J.p , Fragata, I.q , Polifka, A.r , Osbun, J.s , Crosa, R.t , Matouk, C.u , Park, M.S.v , Levitt, M.R.w , Brinjikji, W.x , Moss, M.y , Dumont, T.z , Williamson, R., Jr.aa , Navia, P.ab , Kan, P.ac , De Leacy, R.ad , Chowdhry, S.ae , Ezzeldin, M.af , Spiotta, A.M.a , Kasab, S.A.a , STAR Collaboratorsag
a Department of Neurosurgery, Division of Neuroendovascular Surgery, Medical University of South Carolina, Charleston, SC, United States
b Department of Neurosurgery, Hyogo College of Medicine, Hyogo, Nishinomiya, Japan
c Department of Neurology, University Medicine Goettingen, Goettingen, Germany
d Department of Neurosurgery, Thomas Jefferson University, Philadelphia, PA, United States
e Department of Neurology, Chonnam National University Hospital, Gwangju, South Korea
f Department of Neurosurgery, Wake Forest School of Medicine, Winston-Salem, NC, United States
g Department of Radiology, West Virginia University, Morgantown, WV, United States
h Department of Neurosurgery, University of Miami Miller School of Medicine, Miami, FL, United States
i Department of Neuroradiology, Clinic of Radiology and Nuclear Medicine, University of Basel, Basel, Switzerland
j Department of Neurology, University of Iowa, Iowa City, IA, United States
k Department of Neurosurgery, University of Tennessee Health Science Center/Semmes-Murphey Foundation, Memphis, TN, United States
l Department of Neurosurgery, Louisiana State University Health, Shreveport, LA, United States
m Department of Neurosurgery, Emory University School of Medicine, Atlanta, GA, United States
n Department of Neuroradiology, University Hospital San Giovanni di Dio e Ruggi d’Aragona, University of Salerno, Salerno, Italy
o Department of Neurosurgery, Baylor College of Medicine, Houston, TX, United States
p Department of Neurosurgery, University of Texas Health Science Center at San Antonio, San Antonio, TX, United States
q Department of Neuroradiology, Centro Hospitalar Universitario de Lisboa Central, Lisboa, Portugal
r Department of Neurosurgery, University of Florida, Gainesville, FL, United States
s Department of Neurological Surgery, Washington University in St. Louis, St., Louis, MO, United States
t Department of Neurosurgery, Endovascular Neurological Center, Medica Uruguaya, Montevideo, Uruguay
u Department of Neurosurgery, Yale School of Medicine, New Haven, CT, United States
v Department of Neurosurgery, University of Virginia, Charlottesville, VA, United States
w Department of Neurosurgery, University of Washington School of Medicine, Seattle, WA, United States
x Department of Radiology, Mayo Clinic, Rochester, MN, United States
y Department of Neuroradiology, Washington Regional Medical Center, Fayetteville, AZ, United States
z Department of Neurosurgery, University of Arizona, Tucson, AZ, United States
aa Department of Neurosurgery, Allegheny Health Network, Pittsburgh, PA, United States
ab Department of Neuroradiology, Hospital Universitario La Paz, Madrid, Spain
ac Department of Neurosurgery, University of Texas Medical Branch at Galveston, Galveston, TX, United States
ad Department of Neurosurgery, Icahn School of Medicine at Mount Sinai, New York, NY, United States
ae Department of Neurosurgery, NorthShore University Health System, Chicago, IL, United States
af Department of Clinical Sciences, University of Houston, HCA Houston Healthcare Kingwood, Houston, TX, United States
Abstract
Background: The influence of Alberta Stroke Program Early CT Score (ASPECTS) on outcomes following mechanical thrombectomy (MT) for acute ischemic stroke (AIS) patients with low ASPECTS remains unknown. In this study, we compared the outcomes of AIS patients treated with MT for large vessel occlusion (LVO) categorized by ASPECTS value. Methods: We conducted a retrospective analysis involving 305 patients with AIS caused by LVO, defined as the occlusion of the internal carotid artery and/or the M1 segments of the middle cerebral artery, stratified into two groups: ASPECTS 2-3 and 4-5. The primary outcome was favorable outcome defined as a 90-day modified Rankin Scale (mRS) score of 0-3. Secondary outcomes were 90-day mRS 0-2, 90-day mortality, any intracerebral hemorrhage (ICH), and symptomatic ICH (sICH). We performed multivariable logistic regression analysis to evaluate the impact of ASPECTS 2-3 vs. 4-5 on outcomes. Results: Fifty-nine patients (19.3%) had ASPECTS 2-3 and 246 (80.7%) had ASPECTS 4-5. Favorable outcomes showed no significant difference between the two groups (adjusted odds ratio [aOR]= 1.13, 95% confidence interval [CI]: 0.52-2.41, p=0.80). There were also no significant differences in 90-day mRS 0-2 (aOR= 1.65, 95% CI: 0.66-3.99, p=0.30), 90-day mortality (aOR= 1.14, 95% CI: 0.58-2.20, p=0.70), any ICH (aOR= 0.54, 95% CI: 0.28-1.00, p=0.06), and sICH (aOR= 0.70, 95% CI: 0.27-1.63, p = 0.40) between the groups. Conclusions: AIS patients with LVO undergoing MT with ASPECTS 2-3 had similar outcomes compared to ASPECTS 4-5. © 2023
Author Keywords
Acute ischemic stroke; ASPECTS; Large ischemic infarct; Large vessel occlusion; Mechanical thrombectomy
Document Type: Article
Publication Stage: Final
Source: Scopus
Newborn Brain Function and Early Emerging Callous-Unemotional Traits
(2024) JAMA Psychiatry, .
Brady, R.G.a b , Donohue, M.R.c , Waller, R.d , Latham, A.b , Ayala, M.c , Smyser, T.A.c , Warner, B.B.e , Barch, D.M.c f g , Luby, J.L.c e , Rogers, C.E.c e , Smyser, C.D.b e f
a Division of Biology and Biomedical Sciences, Washington University, School of Medicine, St Louis, MO, United States
b Department of Neurology, Washington University, School of Medicine, St Louis, MO, United States
c Department of Psychiatry, Washington University, School of Medicine, St Louis, MO, United States
d Department of Psychology, University of Pennsylvania, Philadelphia, United States
e Department of Pediatrics, Washington University, School of Medicine, St Louis, MO, United States
f Mallinckrot Institute of Radiology, Washington University, School of Medicine, St Louis, MO, United States
g Department of Psychological and Brain Sciences, Washington University in St Louis, St Louis, MO, United States
Abstract
Importance: Children with high callous-unemotional traits are more likely to develop severe and persistent conduct problems; however, the newborn neurobiology underlying early callous-unemotional traits remains unknown. Understanding the neural mechanisms that precede the development of callous-unemotional traits could help identify at-risk children and encourage development of novel treatments. Objective: To determine whether newborn brain function is associated with early-emerging empathy, prosociality, and callous-unemotional traits. Design, Setting, and Participants: In this prospective, longitudinal cohort study, pregnant women were recruited from obstetric clinics in St Louis, Missouri, from September 1, 2017, to February 28, 2020, with longitudinal data collected until March 20, 2023. Mothers were recruited during pregnancy. Newborns underwent brain magnetic resonance imaging shortly after birth. Mothers completed longitudinal follow-up when the children were aged 1, 2, and 3 years. Exposures: The sample was enriched for exposure to socioeconomic disadvantage. Main Outcome and Measure: Functional connectivity between hypothesized brain regions was assessed using newborn-specific networks and voxel-based connectivity analyses. Children’s callous-unemotional traits were measured using the Inventory of Callous-Unemotional Traits. Empathy and prosociality were assessed using the Infant and Toddler Socio-Emotional Assessment. Results: A total of 283 children (mean [SD] gestational age, 38 [2] weeks; 159 male [56.2%]; 2 Asian [0.7%], 171 Black [60%], 7 Hispanic or Latino [2.5%], 106 White [38%], 4 other racial or ethnic group [1.4%]) were included in the analysis. Stronger newborn functional connectivity between the cingulo-opercular network (CO) and medial prefrontal cortex (mPFC) was associated with higher callous-unemotional traits at age 3 years (β = 0.31; 95% CI, 0.17-0.41; P <.001). Results persisted when accounting for parental callous-unemotional traits and child externalizing symptoms. Stronger newborn CO-mPFC connectivity was also associated with lower empathy and lower prosociality at ages 1, 2, and 3 years using multilevel models (β = -0.12; 95% CI, -0.21 to -0.04; P =.004 and β = -0.20; 95% CI, -0.30 to -0.10; P <.001, respectively). Conclusions and Relevance: Newborn functional connectivity was associated with early-emerging empathy, prosociality, and callous-unemotional traits, even when accounting for parental callous-unemotional traits and child externalizing symptoms. Understanding the neurobiological underpinnings of empathy, prosociality, and callous-unemotional traits at the earliest developmental point may help early risk stratification and novel intervention development. © 2024 American Medical Association. All rights reserved.
Funding details
P50 HD103525
National Institutes of HealthNIH
National Institute of Mental HealthNIMH
National Institute on Drug AbuseNIDA
March of Dimes FoundationMDF
University of WashingtonUW
Intellectual and Developmental Disabilities Research CenterIDDRC
Children’s Discovery InstituteCDI
McDonnell Center for Systems Neuroscience
Document Type: Article
Publication Stage: Article in Press
Source: Scopus
Increasing Activity after Stroke: A Randomized Controlled Trial of High-Intensity Walking and Step Activity Intervention
(2024) Stroke, 55 (1), pp. 5-13.
Thompson, E.D.a , Pohlig, R.T.b , McCartney, K.M.a , Hornby, T.G.c , Kasner, S.E.d , Raser-Schramm, J.e , Miller, A.E.f , Henderson, C.E.c , Wright, H.a , Wright, T.a , Reisman, D.S.a
a Department of Physical Therapy, University of Delaware, Newark, United States
b Biostatistics Core, University of Delaware, Newark, United States
c Department of Physical Medicine and Rehabilitation, Indiana University, Indianapolis, United States
d Perelman School of Medicine, University of Pennsylvania, Philadelphia, United States
e Christiana Care Health System, Newark, DE, United States
f Program in Physical Therapy, Washington University School of Medicine, St. Louis, MO, United States
Abstract
BACKGROUND: Physical inactivity in people with chronic stroke profoundly affects daily function and increases recurrent stroke risk and mortality, making physical activity improvements an important target of intervention. We compared the effects of a high-intensity walking intervention (FAST), a step activity monitoring behavioral intervention (SAM), or a combined intervention (FAST+SAM) on physical activity (ie, steps/day). We hypothesized the combined intervention would yield the greatest increase in steps/day. METHODS: This assessor-blinded multisite randomized controlled trial was conducted at 4 university/hospital-based laboratories. Participants were 21 to 85 years old, walking without physical assistance following a single, unilateral noncerebellar stroke of ≥6 months duration, and randomly assigned to FAST, SAM, or FAST+SAM for 12 weeks (2-3 sessions/week). FAST training consisted of walking-related activities at 70% to 80% heart rate reserve, while SAM received daily feedback and goal setting of walking activity (steps/day). Assessors and study statistician were masked to group assignment. The a priori-determined primary outcome and end point was a comparison of the change in steps/day between the 3 intervention groups from pre- to post-intervention. Adverse events were tracked after randomization. All randomized participants were included in the intent-to-treat analysis. RESULTS: Participants were enrolled from July 18, 2016, to November 16, 2021. Of 2385 participants initially screened, 250 participants were randomized (mean [SE] age, 63 [0.80] years; 116 females/134 males), with 89 assigned to FAST, 81 to SAM, and 80 to FAST+SAM. Steps/day significantly increased in both the SAM (mean [SE], 1542 [267; 95% CI, 1014-2069] P<0.001) and FAST+SAM group (1307 [280; 95% CI, 752-1861] P<0.001) but not in the FAST group (406 [238; 95% CI, -63 to 876] P=0.09). There were no deaths or serious study-related adverse events. CONCLUSIONS: Only individuals with chronic stroke who completed a step activity monitoring behavioral intervention with skilled coaching and goal progression demonstrated improvements in physical activity (steps/day). REGISTRATION: URL: https://www.clinicaltrials.gov; Unique identifier: NCT02835313. © 2024 Lippincott Williams and Wilkins. All rights reserved.
Author Keywords
exercise; goals; heart rate; stroke; walking
Funding details
National Institutes of HealthNIHNIH-R01HD086362
Medtronic
Document Type: Article
Publication Stage: Final
Source: Scopus
Predicting cognitive decline: Which is more useful, baseline amyloid levels or longitudinal change?
(2024) NeuroImage: Clinical, 41, art. no. 103551, .
Chen, G.a b , McKay, N.S.a b , Gordon, B.A.a b c , Liu, J.d , Joseph-Mathurin, N.a b , Schindler, S.E.e , Hassenstab, J.e , Aschenbrenner, A.J.b e , Wang, Q.a b , Schultz, S.A.h , Su, Y.i , LaMontagne, P.J.a b , Keefe, S.J.a b , Massoumzadeh, P.a b , Cruchaga, C.f , Xiong, C.g , Morris, J.C.a b c , Benzinger, T.L.S.a b c
a Departments of Radiology, Washington University in St. Louis School of Medicine, St. Louis, MO, United States
b Knight Alzheimer’s Disease Research Center, Washington University in St. Louis School of Medicine, St. Louis, MO, United States
c Hope Center for Neurological Disorders, Washington University in St. Louis School of Medicine, St. Louis, MO, United States
d Department of Surgery, Washington University in St. Louis School of Medicine, St. Louis, MO, United States
e Department of Neurology, Washington University in St. Louis School of Medicine, St. Louis, MO, United States
f Department of Psychiatry, Washington University in St. Louis School of Medicine, St. Louis, MO, United States
g Divison of Biostatistics, Washington University in St. Louis School of Medicine, St. Louis, MO, United States
h Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States
i Banner Alzheimer’s Institute, Phoenix, AZ, United States
Abstract
The use of biomarkers for the early detection of Alzheimer’s disease (AD) is crucial for developing potential therapeutic treatments. Positron Emission Tomography (PET) is a well-established tool used to detect β-amyloid (Aβ) plaques in the brain. Previous studies have shown that cross-sectional biomarkers can predict cognitive decline (Schindler et al.,2021). However, it is still unclear whether longitudinal Aβ-PET may have additional value for predicting time to cognitive impairment in AD. The current study aims to evaluate the ability of baseline- versus longitudinal rate of change in-11C-Pittsburgh compound B (PiB) Aβ-PET to predict cognitive decline. A cohort of 153 participants who previously underwent PiB-PET scans and comprehensive clinical assessments were used in this study. Our analyses revealed that baseline Aβ is significantly associated with the rate of change in cognitive composite scores, with cognition declining more rapidly when baseline PiB Aβ levels were higher. In contrast, no signification association was identified between the rate of change in PiB-PET Aβ and cognitive decline. Additionally, the ability of the rate of change in the PiB-PET measures to predict cognitive decline was significantly influenced by APOE ε4 carrier status. These results suggest that a single PiB-PET scan is sufficient to predict cognitive decline and that longitudinal measures of Aβ accumulation do not improve the prediction of cognitive decline once someone is amyloid positive. © 2023 The Authors
Author Keywords
Alzheimer’s disease; Amyloid; Cognition; Longitudinal study; PET
Funding details
National Institutes of HealthNIHNCRR 1S10RR022984-01A1, P01AG003991, P01AG026276, P30NS09857781, P50AG00561, R01AG043434, R01EB009352, UL1TR000448, UL1TR002345
Document Type: Article
Publication Stage: Final
Source: Scopus
Pupillometry reveals differences in cognitive demands of listening to face mask-attenuated speech
(2023) Journal of the Acoustical Society of America, 154 (6), pp. 3973-3985.
Carraturo, S.a , McLaughlin, D.J.b , Peelle, J.E.c , Van Engen, K.J.a
a Department of Psychological & Brain Sciences, Washington University in St. Louis, Saint Louis, MO 63130, United States
b Basque Center on Cognition, Brain and Language, Basque Country, San Sebastian, 20009, Spain
c Department of Communication Sciences and Disorders, Northeastern University, Boston, MA 02115, United States
Abstract
Face masks offer essential protection but also interfere with speech communication. Here, audio-only sentences spoken through four types of masks were presented in noise to young adult listeners. Pupil dilation (an index of cognitive demand), intelligibility, and subjective effort and performance ratings were collected. Dilation increased in response to each mask relative to the no-mask condition and differed significantly where acoustic attenuation was most prominent. These results suggest that the acoustic impact of the mask drives not only the intelligibility of speech, but also the cognitive demands of listening. Subjective effort ratings reflected the same trends as the pupil data. © 2023 Acoustical Society of America.
Funding details
2022-2025
Eusko Jaurlaritza
Agencia Estatal de InvestigaciónAEICEX2020-001010-S
Document Type: Article
Publication Stage: Final
Source: Scopus
Describing providers’ perspectives on the needs and challenges of family caregivers of African American people living with dementia
(2023) Home Health Care Services Quarterly, .
Dimtsu Assfaw, A.a , Reinschmidt, K.M.b , Teasdale, T.A.b , Stephens, L.b c , Kleszynski, K.L.d , Dwyer, K.e
a Department of Neurology- Knight Alzheimer Disease Research Center, Washington University School of Medicine in St. Louis, St. Louis, United States
b Department of Health Promotion Sciences, University of Oklahoma Health Sciences Center- Hudson College of Public Health, Oklahoma, United States
c Department of Health Promotion Sciences, Oklahoma Shared Clinical and Translational Research Center, Oklahoma, United States
d Department of Health Promotion Sciences, University of Oklahoma Health Sciences Center, Oklahoma, United States
e Population Health and Health Systems Science, University of Oklahoma Health Sciences Center- Fran and Earl Ziegler College of Nursing, Oklahoma, United States
Abstract
The primary purpose of this study was to explore the needs and challenges of African American family caregivers of People living with dementia (PLWD) from the perspective of service providers including healthcare and social service providers. The study conducted three online semi-structured focus group interviews with service providers (n = 15). Data were analyzed using Braun & Clarke’s guide to thematic analysis approach. Five themes emerged from the analysis of the focus group data: (i) Inadequate information about resources; (ii) Dementia education; (iii) Burden of dementia on families; (iv) Limited financial support and funding; and (v) Suggestions for needed resources. Service providers expressed the lack of community-based dementia service and support programs in African American communities. Findings from the study indicated the need to provide culturally appropriate information on dementia caregiving. This study adds to the scope of knowledge by exploring the processes of seeking help and using services. © 2023 Taylor & Francis.
Author Keywords
African Americans; Dementia caregving; Dementia Service Providers; Family Caregivers; Focus Group
Document Type: Article
Publication Stage: Article in Press
Source: Scopus
Diffusion basis spectrum imaging detects subclinical traumatic optic neuropathy in a closed-head impact mouse model of traumatic brain injury
(2023) Frontiers in Neurology, 14, art. no. 1269817, .
Yang, H.-C.a f g , Lavadi, R.S.a , Sauerbeck, A.D.b c , Wallendorf, M.d , Kummer, T.T.b c e , Song, S.-K.a c , Lin, T.-H.a f g
a Department of Radiology, Washington University School of Medicine, St. Louis, MO, United States
b Department of Neurology, Washington University School of Medicine, St. Louis, MO, United States
c Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, MO, United States
d Department of Biostatistics, Washington University School of Medicine, St. Louis, MO, United States
e VA Medical Center, St. Louis, MO, United States
f Chemistry, Washington University in St. Louis, St. Louis, MO, United States
g Bioimaging, GSK, Collegeville, PA, United States
Abstract
Introduction: Traumatic optic neuropathy (TON) is the optic nerve injury secondary to brain trauma leading to visual impairment and vision loss. Current clinical visual function assessments often fail to detect TON due to slow disease progression and clinically silent lesions resulting in potentially delayed or missed treatment in patients with traumatic brain injury (TBI). Methods: Diffusion basis spectrum imaging (DBSI) is a novel imaging modality that can potentially fill this diagnostic gap. Twenty-two, 16-week-old, male mice were equally divided into a sham or TBI (induced by moderate Closed-Head Impact Model of Engineered Rotational Acceleration device) group. Briefly, mice were anesthetized with isoflurane (5% for 2.5 min followed by 2.5% maintenance during injury induction), had a helmet placed over the head, and were placed in a holder prior to a 2.1-joule impact. Serial visual acuity (VA) assessments, using the Virtual Optometry System, and DBSI scans were performed in both groups of mice. Immunohistochemistry (IHC) and histological analysis of optic nerves was also performed after in vivo MRI. Results: VA of the TBI mice showed unilateral or bilateral impairment. DBSI of the optic nerves exhibited bilateral involvement. IHC results of the optic nerves revealed axonal loss, myelin injury, axonal injury, and increased cellularity in the optic nerves of the TBI mice. Increased DBSI axon volume, decreased DBSI λ||, and elevated DBSI restricted fraction correlated with decreased SMI-312, decreased SMI-31, and increased DAPI density, respectively, suggesting that DBSI can detect coexisting pathologies in the optic nerves of TBI mice. Conclusion: DBSI provides an imaging modality capable of detecting subclinical changes of indirect TON in TBI mice. Copyright © 2023 Yang, Lavadi, Sauerbeck, Wallendorf, Kummer, Song and Lin.
Author Keywords
axonal loss; diffusion basis spectrum imaging; diffusion MRI; inflammation; modCHIMERA; traumatic brain injury; traumatic optic neuropathy
Funding details
National Institutes of HealthNIHR01-NS047592, R01-NS116091, R01-NS121612, U01-EY025500
U.S. Department of Veterans AffairsVA1I01BX005204-01
National Multiple Sclerosis SocietyNMSSRG 4549A4/1
Document Type: Article
Publication Stage: Final
Source: Scopus
Multi-ancestry genome-wide association meta-analysis of Parkinson’s disease
(2023) Nature Genetics, .
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a Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, United States
b Preventive Neurology Unit, Centre for Prevention Diagnosis and Detection, Wolfson Institute of Population Health, Queen Mary University of London, London, United Kingdom
c Data Tecnica International, Washington, DC, United States
d Center for Alzheimer’s and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, United States
e Neurogenetics Research Center, Instituto Nacional de Ciencias Neurológicas, Lima, Peru
f Institute for Genome Sciences, University of Maryland, Baltimore, MD, United States
g Lee Kong Chian School of Medicine, Nanyang Technological University Singapore, Singapore, Singapore
h Genome Institute of Singapore, Agency for Science, Technology and Research, A*STAR, Singapore, Singapore
i 23andMe, Inc., Sunnyvale, CA, United States
j Pharmaceutical Sciences and Pharmacogenomics, UCSF, San Francisco, CA, United States
k Department of Neurology and Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, United States
l Memory and Aging Center, UCSF, San Francisco, CA, United States
m Department of Clinical and Movement Neurosciences, UCL Queen Square Institute of Neurology, London, United Kingdom
n UCL Movement Disorders Centre, University College London, London, United Kingdom
o Department of Neurology, National Neuroscience Institute, Duke NUS Medical School, Singapore, Singapore
p Genomic Medicine, Lerner Research Institute, Cleveland Clinic Foundation, Cleveland, OH, United States
q Sanatorio de la Trinidad Mitre- INEBA, Buenos Aires, Argentina
r Hospital JM Ramos Mejia, Buenos Aires, Argentina
s Somnus Neurology Clinic, Yerevan, Armenia
t Neuroscience Research Australia, Sydney, NSW, Australia
u ANZAC Research Institute, Concord, NSW, Australia
v Garvan Institute of Medical Research and Concord Repatriation General Hospital, Darlinghurst, NSW, Australia
w Concord Hospital, Concord, NSW, Australia
x QIMR Berghofer Medical Research Institute, Herston, QLD, Australia
y Murdoch University, Perth, WA, Australia
z Medical University Vienna Austria, Vienna, Austria
aa Universidade Federal do Rio Grande do Sul / Hospital de Clínicas de Porto Alegre, Porto Alegre, Brazil
ab Federal University of Health Sciences of Porto Alegre, Porto Alegre, Brazil
ac Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
ad University of São Paulo, São Paulo, Brazil
ae Universidade Federal de Minas Gerais, Belo Horizonte, Brazil
af Montreal Neurological Institute, Montreal, Quebec, Canada
ag Institut universitaire de gériatrie de Montréal, Montreal, QC, Canada
ah McGill University, Montreal, Quebec, Canada
ai Universidad de Chile, Santiago, Chile
aj Fundación Diagnosis, Santiago, Chile
ak Faculty of Medicine Universidad de Chile, Santiago, Chile
al CETRAM, Santiago, Chile
am Central South University, Changsha, China
an West China Hospital Sichuan University, Chengdu, China
ao Xiangya Hospital, Changsha, China
ap Capital Medical University, Beijing, China
aq Zhejiang University, Hangzhou, China
ar Universidad Nacional de Colombia, Bogotá, Colombia
as Fundación Valle del Lili, Santiago De Cali, Colombia
at University of Antioquia, Medellin, Colombia
au University of Costa Rica, San Jose, Costa Rica
av The American University in Cairo, Cairo, Egypt
aw Beni-Suef University, Beni Suef, Egypt
ax Addis Ababa University, Addis Ababa, Ethiopia
ay Paris Brain Institute, Paris, France
az Sorbonne Université, Paris, France
ba University of Lübeck, Lübeck, Germany
bb Deutsches Zentrum für Neurodegenerative Erkrankungen, Göttingen, Germany
bc University Medical Center Göttingen, Göttingen, Germany
bd Department of Neurology, University Hospital, LMU Munich, Munich, Germany
be University Medical Center Schleswig-Holstein, Lübeck, Germany
bf University of Tubingen, Tübingen, Germany
bg University of Mainz, Mainz, Germany
bh The German Center for Neurodegenerative Diseases, Göttingen, Germany
bi University of Ghana Medical School, Accra, Ghana
bj University of Thessaly, Volos, Greece
bk Aristotle University of Thessaloniki, Thessaloniki, Greece
bl Ionian University, Corfu, Greece
bm Biomedical research Foundation of the Academy of Athens, Athens, Greece
bn Diagnostic and Therapeutic Centre HYGEIA Hospital, Marousi, Greece
bo Hospital San Felipe, Tegucigalpa, Honduras
bp Queen Elizabeth Hospital, Kowloon, Hong Kong
bq The Hong Kong University of Science and Technology, Kowloon, Hong Kong
br Aster Medcity, Kochi, India
bs Sree Chitra Tirunal Institute for Medical Sciences and Technology, Thiruvananthapuram, India
bt National Institute of Mental Health & Neurosciences, Bengaluru, India
bu Manipal Hospital, Delhi, India
bv All India Institute of Medical Sciences, Delhi, India
bw Nizam’s Institute of Medical Sciences, Hyderabad, India
bx Shahid Beheshti University of Medical Science, Tehran, Iran
by Magna Græcia University of Catanzaro, Catanzaro, Italy
bz University of Pavia, Pavia, Italy
ca University of Perugia, Perugia, Italy
cb University of Rome Tor Vergata, Rome, Italy
cc Juntendo University, Tokyo, Japan
cd Faculty of Medicine, Juntendo University, Tokyo, Japan
ce Jikei University School of Medicine, Tokyo, Japan
cf Institute of Neurology and Neurorehabilitation, Almaty, Kazakhstan
cg Kyrgyz State Medical Academy, Bishkek, Kyrgyzstan
ch University of Luxembourg, Luxembourg, Luxembourg
ci University of Malaya, Kuala Lumpur, Malaysia
cj Universiti Kebangsaan Malaysia, Selangor, Malaysia
ck UKM Medical Molecular Biology Institute, Kuala Lumpur, Malaysia
cl Universiti Kebangsaan Malaysia Medical Centre, Kuala Lumpur, Malaysia
cm International Islamic University, Kuala Lumpur, Malaysia
cn Tecnologico de Monterrey, Monterrey, Mexico
co Instituto Nacional de Neurologia y Neurocirugia, Mexico City, Mexico
cp Universidad Nacional Autónoma de México, Mexico City, Mexico
cq Mongolian National University of Medical Sciences, Ulaanbaatar, Mongolia
cr Tribhuvan University, Kirtipur, Nepal
cs University of Otago, Dunedin, New Zealand
ct University of Lagos, Lagos, Nigeria
cu College of Medicine of the University of Lagos, Lagos, Nigeria
cv Norwegian University of Science and Technology, Trondheim, Norway
cw Oslo University Hospital, Oslo, Norway
cx University of Science and Technology Bannu, Bannu, Pakistan
cy Universidad Cientifica del Sur, Lima, Peru
cz Metropolitan Medical Center, Manila, Philippines
da University of Puerto Rico, San Juan, Puerto Rico
db Research Center of Neurology, Moscow, Russian Federation
dc King Faisal Specialist Hospital and Research Center, Riyadh, Saudi Arabia
dd King Abdullah International Medical Research Center, Jeddah, Saudi Arabia
de University of KwaZulu-Natal, Durban, South Africa
df Stellenbosch University, Stellenbosch, South Africa
dg Seoul National University Hospital, Seoul, South Korea
dh Yongin Severance Hospital, Seoul, South Korea
di Hospital Universitario Burgos, Burgos, Spain
dj University Hospital Mutua Terrassa, Barcelona, Spain
dk Institut de Recerca Sant Joan de Deu, Barcelona, Spain
dl Research Institute Germans Trias i Pujol, Barcelona, Spain
dm Instituto de Biomedicina de Sevilla, Seville, Spain
dn University Hospital Germans Trias i Pujol, Barcelona, Spain
do Faculty of medicine university of Khartoum, Khartoum, Sudan
dp Lund University, Lund, Sweden
dq Inselspital Bern, University of Bern, Bern, Switzerland
dr University Hospital Bern, Bern, Switzerland
ds National Taiwan University Hospital, Taipei City, Taiwan
dt Chang Gung Memorial Hospital, Taoyuan City, Taiwan
du National Taiwan University, Taipei City, Taiwan
dv National Institute Mongi Ben Hamida of Neurology, Tunis, Tunisia
dw Mongi Ben Hmida National Institute of Neurology, Tunis, Tunisia
dx Koç University, Istanbul, Turkey
dy Şişli Etfal Training and Research Hospital, Istanbul, Turkey
dz University of Plymouth, Plymouth, United Kingdom
ea Parkinson’s UK, London, United Kingdom
eb University of Glasgow, Glasgow, United Kingdom
ec Cardiff University, Cardiff, United Kingdom
ed Royal Veterinary College University of London, London, United Kingdom
ee University of Bristol, Bristol, United Kingdom
ef Cure Parkinson’s, London, United Kingdom
eg University of Cincinnati, Cincinnati, OH, United States
eh The Michael J. Fox Foundation for Parkinson’s Research, New York, NY, United States
ei Augusta University / University of Georgia Medical Partnership, Augusta, GA, United States
ej Mid-Atlantic Permanente Medical Group, Bethesda, MD, United States
ek Washington University, St. Louis, MO, United States
el Indiana University, Bloomington, IN, United States
em Rush University, Chicago, IL, United States
en Kaiser Permanente, Oakland, CA, United States
eo Coalition for Aligning Science, Washington, WA, United States
ep Banner Sun Health Research Institute, Sun City, AZ, United States
eq Michigan State University, East Lansing, MI, United States
er Northwestern University, Evanston, IL, United States
es Baylor College of Medicine, Houston, TX, United States
et Texas Children’s Hospital, Houston, TX, United States
eu University of Miami Miller School of Medicine, Miami, FL, United States
ev Beth Israel Deaconess Medical Center, Boston, MA, United States
ew North Shore University Health System, Chicago, IL, United States
ex Institute for Neurodegenerative Disorders, New Haven, CT, United States
ey University of Pittsburgh, Pittsburgh, PA, United States
ez Washington University, Saint Louis, MO, United States
fa University of Alabama at Birmingham, Birmingham, AL, United States
fb University of Maryland, Baltimore, MD, United States
fc University of Michigan, Ann Arbor, MI, United States
fd Columbia University, New York, NY, United States
fe James J. Peters Veterans Affairs Medical Center, New York, NY, United States
ff Aligning Science Across Parkinson’s, Washington, WA, United States
fg University of Chicago, Chicago, IL, United States
fh Indiana University School of Medicine, Indianapolis, IN, United States
fi Hue University, Huế, Viet Nam
fj University of Zambia, Lusaka, Zambia
Abstract
Although over 90 independent risk variants have been identified for Parkinson’s disease using genome-wide association studies, most studies have been performed in just one population at a time. Here we performed a large-scale multi-ancestry meta-analysis of Parkinson’s disease with 49,049 cases, 18,785 proxy cases and 2,458,063 controls including individuals of European, East Asian, Latin American and African ancestry. In a meta-analysis, we identified 78 independent genome-wide significant loci, including 12 potentially novel loci (MTF2, PIK3CA, ADD1, SYBU, IRS2, USP8, PIGL, FASN, MYLK2, USP25, EP300 and PPP6R2) and fine-mapped 6 putative causal variants at 6 known PD loci. By combining our results with publicly available eQTL data, we identified 25 putative risk genes in these novel loci whose expression is associated with PD risk. This work lays the groundwork for future efforts aimed at identifying PD loci in non-European populations. © 2023, This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply.
Funding details
MOH-000207, MOH-000559
MOE-MOET32020-0004, MOE-T2EP30220-0005
National Institutes of HealthNIH
U.S. Department of Health and Human ServicesHHS
National Institute on AgingNIA
National Institute of Neurological Disorders and StrokeNINDSR01NS112499, ZIA AG000949, ZO1 AG000535
Michael J. Fox Foundation for Parkinson’s ResearchMJFF
American Parkinson Disease AssociationAPDA
Aligning Science Across Parkinson’sASAP
Document Type: Article
Publication Stage: Article in Press
Source: Scopus