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Poos JM, Moore KM, Nicholas J, Russell LL, Peakman G, Convery RS, Jiskoot LC, van der Ende E, van den Berg E, Papma JM, Seelaar H, Pijnenburg YAL, Moreno F, Sanchez-Valle R, Borroni B, Laforce R, Masellis M, Tartaglia C, Graff C, Galimberti D, Rowe JB, Finger E, Synofzik M, Vandenberghe R, de Mendonça A, Tiraboschi P, Santana I, Ducharme S, Butler C, Gerhard A, Levin J, Danek A, Otto M, Le Ber I, Pasquier F, van Swieten JC, Rohrer JD. Cognitive composites for genetic frontotemporal dementia: GENFI-Cog. Alzheimers Res Ther 2022; 14:10. [PMID: 35045872 PMCID: PMC8772227 DOI: 10.1186/s13195-022-00958-0] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2021] [Accepted: 12/28/2021] [Indexed: 11/18/2022]
Abstract
Background Clinical endpoints for upcoming therapeutic trials in frontotemporal dementia (FTD) are increasingly urgent. Cognitive composite scores are often used as endpoints but are lacking in genetic FTD. We aimed to create cognitive composite scores for genetic frontotemporal dementia (FTD) as well as recommendations for recruitment and duration in clinical trial design. Methods A standardized neuropsychological test battery covering six cognitive domains was completed by 69 C9orf72, 41 GRN, and 28 MAPT mutation carriers with CDR® plus NACC-FTLD ≥ 0.5 and 275 controls. Logistic regression was used to identify the combination of tests that distinguished best between each mutation carrier group and controls. The composite scores were calculated from the weighted averages of test scores in the models based on the regression coefficients. Sample size estimates were calculated for individual cognitive tests and composites in a theoretical trial aimed at preventing progression from a prodromal stage (CDR® plus NACC-FTLD 0.5) to a fully symptomatic stage (CDR® plus NACC-FTLD ≥ 1). Time-to-event analysis was performed to determine how quickly mutation carriers progressed from CDR® plus NACC-FTLD = 0.5 to ≥ 1 (and therefore how long a trial would need to be). Results The results from the logistic regression analyses resulted in different composite scores for each mutation carrier group (i.e. C9orf72, GRN, and MAPT). The estimated sample size to detect a treatment effect was lower for composite scores than for most individual tests. A Kaplan-Meier curve showed that after 3 years, ~ 50% of individuals had converted from CDR® plus NACC-FTLD 0.5 to ≥ 1, which means that the estimated effect size needs to be halved in sample size calculations as only half of the mutation carriers would be expected to progress from CDR® plus NACC FTLD 0.5 to ≥ 1 without treatment over that time period. Discussion We created gene-specific cognitive composite scores for C9orf72, GRN, and MAPT mutation carriers, which resulted in substantially lower estimated sample sizes to detect a treatment effect than the individual cognitive tests. The GENFI-Cog composites have potential as cognitive endpoints for upcoming clinical trials. The results from this study provide recommendations for estimating sample size and trial duration. Supplementary Information The online version contains supplementary material available at 10.1186/s13195-022-00958-0.
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Affiliation(s)
- Jackie M Poos
- Department of Neurology, Erasmus MC University Medical Center, Rotterdam, The Netherlands.,Dementia Research Centre, Department of Neurodegenerative Disease, National Hospital for Neurology and Neurosurgery, UCL Institute of Neurology, 8-11 Queen Square, Box 16, London, WC1N 3BG, UK
| | - Katrina M Moore
- Dementia Research Centre, Department of Neurodegenerative Disease, National Hospital for Neurology and Neurosurgery, UCL Institute of Neurology, 8-11 Queen Square, Box 16, London, WC1N 3BG, UK
| | - Jennifer Nicholas
- Department of Medical Statistics, London School of Hygiene and Tropical Medicine, London, UK
| | - Lucy L Russell
- Dementia Research Centre, Department of Neurodegenerative Disease, National Hospital for Neurology and Neurosurgery, UCL Institute of Neurology, 8-11 Queen Square, Box 16, London, WC1N 3BG, UK
| | - Georgia Peakman
- Dementia Research Centre, Department of Neurodegenerative Disease, National Hospital for Neurology and Neurosurgery, UCL Institute of Neurology, 8-11 Queen Square, Box 16, London, WC1N 3BG, UK
| | - Rhian S Convery
- Dementia Research Centre, Department of Neurodegenerative Disease, National Hospital for Neurology and Neurosurgery, UCL Institute of Neurology, 8-11 Queen Square, Box 16, London, WC1N 3BG, UK
| | - Lize C Jiskoot
- Department of Neurology, Erasmus MC University Medical Center, Rotterdam, The Netherlands.,Dementia Research Centre, Department of Neurodegenerative Disease, National Hospital for Neurology and Neurosurgery, UCL Institute of Neurology, 8-11 Queen Square, Box 16, London, WC1N 3BG, UK
| | - Emma van der Ende
- Department of Neurology, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - Esther van den Berg
- Department of Neurology, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - Janne M Papma
- Department of Neurology, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - Harro Seelaar
- Department of Neurology, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - Yolande A L Pijnenburg
- Department of Neurology, Alzheimer Center, Amsterdam University Medical Center, Amsterdam Neuroscience, Amsterdam, The Netherlands
| | - Fermin Moreno
- Cognitive Disorders Unit, Department of Neurology, Donostia University Hospital, San Sebastian, Gipuzkoa, Spain
| | - Raquel Sanchez-Valle
- Alzheimer's disease and Other Cognitive Disorders Unit, Neurology Service, Hospital Clínic, Institut d'Investigacións Biomèdiques August Pi I Sunyer, University of Barcelona, Barcelona, Spain
| | - Barbara Borroni
- Centre for Neurodegenerative Disorders, Neurology Unit, Department of Clinical and Experimental Sciences, University of Brescia, Brescia, Italy
| | - Robert Laforce
- Clinique Interdisciplinaire de Mémoire, Département des Sciences Neurologiques, Université Laval, Québec, Canada
| | - Mario Masellis
- Sunnybrook Health Sciences Centre, Sunnybrook Research Institute, University of Toronto, Toronto, Canada
| | - Carmela Tartaglia
- Tanz Centre for Research in Neurodegenerative Diseases, University of Toronto, Toronto, Canada
| | - Caroline Graff
- Department of Geriatric Medicine, Karolinska University Hospital-Huddinge, Stockholm, Sweden
| | - Daniela Galimberti
- University of Milan, Centro Dino Ferrari, Milan, Italy.,Neurodegenerative Diseases Unit, Fondazione IRCCS Ca' Granda, Ospedale Policlinico, Milan, Italy
| | - James B Rowe
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
| | - Elizabeth Finger
- Department of Clinical Neurological Sciences, University of Western Ontario, London, Ontario, Canada
| | - Matthis Synofzik
- Department of Neurodegenerative Diseases, Hertie-Institute for Clinical Brain Research and Center of Neurology, University of Tübingen, Tübingen, Germany.,German Center for Neurodegenerative Diseases (DZNE), Tübingen, Germany
| | - Rik Vandenberghe
- Laboratory for Cognitive Neurology, Department of Neurosciences, KU Leuven, Leuven, Belgium
| | | | - Pietro Tiraboschi
- Fondazione Istituto di Ricovero e Cura a Carattere Scientifico Istituto Neurologica Carlo Besta, Milan, Italy
| | - Isabel Santana
- Faculty of Medicine, University of Coimbra, Coimbra, Portugal
| | - Simon Ducharme
- Department of Psychiatry, McGill University Health Centre, McGill University, Montreal, Québec, Canada
| | - Chris Butler
- Department of Clinical Neurology, University of Oxford, Oxford, UK
| | - Alexander Gerhard
- Faculty of Medical and Human Sciences, Institute of Brain, Behaviour and Mental Health, University of Manchester, Manchester, UK
| | - Johannes Levin
- Department of Neurology, Ludwig-Maximilians-University, Munich, Germany.,German Center for Neurodegenerative Diseases (DZNE), Munich, Germany.,Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
| | - Adrian Danek
- Department of Neurology, Ludwig-Maximilians-University, Munich, Germany
| | - Markus Otto
- Department of Neurology, University of Ulm, Ulm, Germany
| | - Isabel Le Ber
- Paris Brain Institute - Institut du Cerveau - ICM, Inserm U1127, CNRS UMR 7225, AP-HP - Hôpital Pitié-Salpêtrière, Sorbonne Université, Paris, France.,Centre de référence des démences rares ou précoces, IM2A, Département de Neurologie, AP-HP - Hôpital Pitié-Salpêtrière, Paris, France.,Département de Neurologie, AP-HP - Hôpital Pitié-Salpêtrière, Paris, France
| | - Florence Pasquier
- University of Lille, Lille, France.,Inserm 1172, Lille, France.,CHU, CNR-MAJ, Labex Distalz, LiCEND, Lille, France
| | - John C van Swieten
- Department of Neurology, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - Jonathan D Rohrer
- Dementia Research Centre, Department of Neurodegenerative Disease, National Hospital for Neurology and Neurosurgery, UCL Institute of Neurology, 8-11 Queen Square, Box 16, London, WC1N 3BG, UK.
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Müller HP, Huppertz HJ, Dreyhaupt J, Ludolph AC, Tabrizi SJ, Roos RAC, Durr A, Landwehrmeyer GB, Kassubek J. Combined cerebral atrophy score in Huntington's disease based on atlas-based MRI volumetry: Sample size calculations for clinical trials. Parkinsonism Relat Disord 2019; 63:179-184. [PMID: 30846243 DOI: 10.1016/j.parkreldis.2019.02.004] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/26/2018] [Revised: 12/18/2018] [Accepted: 02/03/2019] [Indexed: 12/19/2022]
Abstract
INTRODUCTION A volumetric MRI analysis of longitudinal regional cerebral atrophy in Huntington's disease (HD) was performed as a read-out of disease progression to calculate sample sizes for future clinical trials. METHODS This study was based on MRI data of 59 patients with HD and 40 controls recruited within the framework of the PADDINGTON study and investigated at baseline and follow-up after 6 and 15 months. Automatic atlas-based volumetry (ABV) of structural T1-weighted scans was used to calculate longitudinal volume changes of brain structures relevant in HD and to assess standardized effect sizes and sample sizes required for potential future studies. RESULTS Atrophy rates were largest in the caudate (-3.4%), putamen (-2.8%), nucleus accumbens (-1.6%), and the parietal lobes (-1.7%); the lateral ventricles showed an expansion by 6.0%. Corresponding effect sizes were -1.35 (caudate), -0.84 (putamen), -0.91 (nucleus accumbens), -1.05 (parietal lobe), and 0.92 (lateral ventricles) leading to N = 36 subjects per study group for detecting a 50% attenuation of atrophy for the best performing structure (caudate). A combined score of volume changes in non-overlapping compartments (striatum, parietal lobes, lateral ventricles) increased the effect size to -1.60 and substantially reduced the required sample sizes by 10 to N = 26 subjects per study group. This combined imaging score correlated significantly both with the CAP score and with the progression of the clinical phenotype. CONCLUSION We propose ABV of the striatum together with parietal lobe and lateral ventricle volumes as a combined imaging read-out for progression studies including clinical trials in HD.
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Affiliation(s)
| | | | - Jens Dreyhaupt
- Institute of Epidemiology and Medical Biometry, University of Ulm, Germany
| | | | - Sarah J Tabrizi
- Department of Neurodegenerative Disease, UCL Institute of Neurology, London, UK
| | - Raymund A C Roos
- Department of Neurology, Leiden University Medical Centre, Leiden, the Netherlands
| | - Alexandra Durr
- ICM - Institut du Cerveau et de la Moelle Epinière, INSERM U1127, CNRS UMR7225, Sorbonne Universités - UPMC Université Paris VI UMR_S1127 and APHP, Genetic Department, Pitié-Salpêtrière University Hospital, Paris, France
| | | | - Jan Kassubek
- Department of Neurology, University of Ulm, Germany
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Kloos AD, Kegelmeyer DA, Fritz NE, Daley AM, Young GS, Kostyk SK. Cognitive Dysfunction Contributes to Mobility Impairments in Huntington's Disease. J Huntingtons Dis 2018; 6:363-370. [PMID: 29254103 PMCID: PMC5757646 DOI: 10.3233/jhd-170279] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
Background: Huntington’s disease (HD) is a progressive neurodegenerative disorder that results in a gradual decline in mobility and balance. Increasing evidence has documented an important role of executive function in the safe ambulation of the elderly and people with a variety of neurological disorders. Little is known about the contribution of cognitive deficits to decline in mobility over time in HD. Objective: This study examined the relationships of mobility, motor and cognitive function measures at baseline, and of mobility and cognitive measures over four years. Methods: A retrospective chart review was performed on 70 patients with genetically confirmed HD (age 20–75 years old) across 121 HD clinic visits. Correlations between Unified Huntington’s Disease Rating Scale – Total Motor, Tinetti Mobility Test (TMT), and cognitive measures (Letter Verbal Fluency, Symbol Digit Modalities Test (SDMT), and Stroop Test) were analyzed. Longitudinal relationships between TMT and cognitive measures were examined using mixed effect regression models. Results: Gait and balance measures representing domains of mobility (TMT scores) were significantly correlated with each of the cognitive measures with the exception of the Verbal Fluency score. Mixed effects regression modeling showed that the Stroop Interference sub-test and SDMT were significant predictors (p-values <0.01) of TMT total scores. Conclusions: Impairments in executive function measures correlate highly with measures of gait, balance and mobility in individuals with HD. Interventions designed to improve mobility and decrease fall risk should also address issues of cognitive impairments with particular consideration given to interventions that may focus on motor-cognitive dual task training.
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Affiliation(s)
- Anne D Kloos
- Division of Physical Therapy, College of Medicine, The Ohio State University, Columbus, OH, USA
| | - Deb A Kegelmeyer
- Division of Physical Therapy, College of Medicine, The Ohio State University, Columbus, OH, USA
| | - Nora E Fritz
- Division of Physical Therapy, College of Medicine, The Ohio State University, Columbus, OH, USA.,Department of Neurology, Program in Physical Therapy, College of Pharmacy and Health Sciences, College of Medicine, Wayne State University, Detroit, MI, USA
| | - Allison M Daley
- Department of Neurology, College of Medicine, The Ohio State University, Columbus, OH, USA
| | - Gregory S Young
- Center for Biostatistics, The Ohio State University, Columbus, OH, USA
| | - Sandra K Kostyk
- Department of Neurology, College of Medicine, The Ohio State University, Columbus, OH, USA.,Department of Neuroscience, College of Medicine, The Ohio State University, Columbus, OH, USA
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Gregory S, Crawford H, Seunarine K, Leavitt B, Durr A, Roos RAC, Scahill RI, Tabrizi SJ, Rees G, Langbehn D, Orth M. Natural biological variation of white matter microstructure is accentuated in Huntington's disease. Hum Brain Mapp 2018; 39:3516-3527. [PMID: 29682858 PMCID: PMC6099203 DOI: 10.1002/hbm.24191] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2017] [Revised: 03/26/2018] [Accepted: 04/06/2018] [Indexed: 01/11/2023] Open
Abstract
Huntington's disease (HD) is a monogenic neurodegenerative disorder caused by a CAG‐repeat expansion in the Huntingtin gene. Presence of this expansion signifies certainty of disease onset, but only partly explains age at which onset occurs. Genome‐wide association studies have shown that naturally occurring genetic variability influences HD pathogenesis and disease onset. Investigating the influence of biological traits in the normal population, such as variability in white matter properties, on HD pathogenesis could provide a complementary approach to understanding disease modification. We have previously shown that while white matter diffusivity patterns in the left sensorimotor network were similar in controls and HD gene‐carriers, they were more extreme in the HD group. We hypothesized that the influence of natural variation in diffusivity on effects of HD pathogenesis on white matter is not limited to the sensorimotor network but extends to cognitive, limbic, and visual networks. Using tractography, we investigated 32 bilateral pathways within HD‐related networks, including motor, cognitive, and limbic, and examined diffusivity metrics using principal components analysis. We identified three independent patterns of diffusivity common to controls and HD gene‐carriers that predicted HD status. The first pattern involved almost all tracts, the second was limited to sensorimotor tracts, and the third encompassed cognitive network tracts. Each diffusivity pattern was associated with network specific performance. The consistency in diffusivity patterns across both groups coupled with their association with disease status and task performance indicates that naturally‐occurring patterns of diffusivity can become accentuated in the presence of the HD gene mutation to influence clinical brain function.
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Affiliation(s)
- Sarah Gregory
- Huntington's Disease Research Centre, UCL Institute of Neurology, London, United Kingdom
| | - Helen Crawford
- Huntington's Disease Research Centre, UCL Institute of Neurology, London, United Kingdom
| | - Kiran Seunarine
- Developmental Imaging and Biophysics Section, UCL Institute of Child Health, London, WC1N 1EH, United Kingdom
| | - Blair Leavitt
- Centre for Molecular Medicine and Therapeutics, Department of Medical Genetics, University of British Columbia, Vancouver, BC, V5Z 4H4, Canada
| | - Alexandra Durr
- APHP Department of Genetics, Groupe Hospitalier Pitié-Salpêtrière, and Institut du Cerveau et de la Moelle, INSERM U1127, CNRS UMR7225, Sorbonne Universités - UPMC Université Paris VI UMR_S1127, Paris, France
| | - Raymund A C Roos
- Department of Neurology, Leiden University Medical Centre, Leiden, 2300RC, The Netherlands
| | - Rachael I Scahill
- Huntington's Disease Research Centre, UCL Institute of Neurology, London, United Kingdom
| | - Sarah J Tabrizi
- Huntington's Disease Research Centre, UCL Institute of Neurology, London, United Kingdom
| | - Geraint Rees
- Wellcome Trust Centre for Neuroimaging, University College London, London, United Kingdom
| | - Douglas Langbehn
- Departments of Psychiatry and Biostatistics, University of Iowa, Iowa City, Iowa
| | - Michael Orth
- Department of Neurology, Ulm University Hospital, Ulm, Germany
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Höglinger GU, Schöpe J, Stamelou M, Kassubek J, Del Ser T, Boxer AL, Wagenpfeil S, Huppertz HJ. Longitudinal magnetic resonance imaging in progressive supranuclear palsy: A new combined score for clinical trials. Mov Disord 2017; 32:842-852. [PMID: 28436538 DOI: 10.1002/mds.26973] [Citation(s) in RCA: 45] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2016] [Revised: 02/16/2017] [Accepted: 02/19/2017] [Indexed: 12/30/2022] Open
Abstract
BACKGROUND Two recent, randomized, placebo-controlled phase II/III trials (clinicaltrials.gov: NCT01110720, NCT01049399) of davunetide and tideglusib in progressive supranuclear palsy (PSP) generated prospective, 1-year longitudinal datasets of high-resolution T1-weighted three-dimensional MRI. OBJECTIVE The objective of this study was to develop a quantitative MRI disease progression measurement for clinical trials. METHODS The authors performed a fully automated quantitative MRI analysis employing atlas-based volumetry and provide sample size calculations based on data collected in 99 PSP patients assigned to placebo in these trials. Based on individual volumes of 44 brain compartments and structures at baseline and 52 weeks of follow-up, means and standard deviations of annualized percentage volume changes were used to estimate standardized effect sizes and the required sample sizes per group for future 2-armed, placebo-controlled therapeutic trials. RESULTS The highest standardized effect sizes were found for midbrain, frontal lobes, and the third ventricle. Using the annualized percentage volume change of these structures to detect a 50% change in the 1-year progression (80% power, significance level 5%) required lower numbers of patients per group (third ventricle, n = 32; midbrain, n = 37; frontal lobe, n = 43) than the best clinical scale (PSP rating scale total score, n = 58). A combination of volume changes in these 3 structures reduced the number of required patients to only 20 and correlated best with the progression in the clinical scales. CONCLUSIONS We propose the 1-year change in the volumes of third ventricle, midbrain, and frontal lobe as combined imaging read-out for clinical trials in PSP that require the least number of patients for detecting efficacy to reduce brain atrophy. © 2017 International Parkinson and Movement Disorder Society.
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Affiliation(s)
- Günter U Höglinger
- Department of Neurology, Technische Universität München, Munich, Germany.,German Center for Neurodegenerative Diseases, Munich, Germany.,Department of Neurology, University Hospital Gießen and Marburg, Marburg, Germany
| | - Jakob Schöpe
- Institute for Medical Biometry, Epidemiology and Medical Informatics, Saarland University, Campus Homburg, Germany
| | - Maria Stamelou
- Department of Neurology, University Hospital Gießen and Marburg, Marburg, Germany.,Second Department of Neurology, Attikon University Hospital, University of Athens, Athens, Greece
| | - Jan Kassubek
- Department of Neurology, University of Ulm, Ulm, Germany
| | | | - Adam L Boxer
- Memory and Aging Center, Department of Neurology, University of California, San Francisco, California, USA
| | - Stefan Wagenpfeil
- Institute for Medical Biometry, Epidemiology and Medical Informatics, Saarland University, Campus Homburg, Germany
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Gorges M, Müller HP, Mayer IM, Grupe GS, Kammer T, Grön G, Kassubek J, Landwehrmeyer GB, Wolf RC, Orth M. Intact sensory-motor network structure and function in far from onset premanifest Huntington's disease. Sci Rep 2017; 7:43841. [PMID: 28266655 DOI: 10.1038/srep43841] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2016] [Accepted: 01/27/2017] [Indexed: 12/19/2022] Open
Abstract
Structural and functional changes attributable to the neurodegenerative process in Huntington's disease (HD) may be evident in HTT CAG repeat expansion carriers before the clinical manifestations of HD. It remains unclear, though, how far from motor onset a consistent signature of the neurodegenerative process in HD can be detected. Twelve far from onset preHD and 22 age-matched healthy control participants underwent volumetric structural magnetic resonance imaging (MRI), diffusion tensor imaging (DTI), and resting-state functional MRI (11 preHD, 22 controls) as well as electrophysiological measurements (12 preHD, 13 controls). There were no significant differences in white matter macro- and microstructure between far from onset preHD participants and controls. Functional connectivity in a basal ganglia-thalamic and motor networks, all measures of the motor efferent and sensory afferent pathways as well as sensory-motor integration were also similar in far from onset preHD and controls. With the methods used in far from onset preHD sensory-motor neural macro- or micro-structure and brain function were similar to healthy controls. This suggests that any observable structural and functional change in preHD nearer to onset, or in manifest HD, at least using comparable techniques such as in this study, most likely reflects an ongoing neurodegenerative process.
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7
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Strizich G, Kaplan RC, González HM, Daviglus ML, Giachello AL, Teng Y, Lipton RB, Grober E. Glycemic control, cognitive function, and family support among middle-aged and older Hispanics with diabetes: The Hispanic Community Health Study/Study of Latinos. Diabetes Res Clin Pract 2016; 117:64-73. [PMID: 27329024 PMCID: PMC4918095 DOI: 10.1016/j.diabres.2016.04.052] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/30/2015] [Revised: 04/02/2016] [Accepted: 04/30/2016] [Indexed: 12/20/2022]
Abstract
AIMS To examine among Hispanics in the U.S., a population with increased reliance on informal healthcare support structures, (1) the association between cognitive function and control of diabetes; and (2) whether this association is modified by family support. METHODS The Digit Symbol Substitution Test (DSST), word fluency, and learning and delayed recall components of the Spanish English Verbal Learning Test were administered to 1794 Hispanic adults aged 45-76years with diagnosed diabetes. An executive function index and global cognitive function index (GCFI) were derived. Uncontrolled diabetes (HbA1c⩾7% [53mmol/mol]) was compared across quartiles of cognitive function using multivariable logit models with interaction terms for cognitive function and family support. RESULTS After adjustment, lower DSST scores were associated with uncontrolled diabetes (P=0.03). Family support modified the relationship between other measures of cognition and diabetes control (Pinteraction: 0.002, 0.09). Among individuals with low family support, as cognitive function declined, the odds of uncontrolled diabetes increased (P-trend across quartiles of the GCFI, 0.015). Among those with low family support, persons in the lowest quartile of global cognitive function were more than twice as likely to have uncontrolled diabetes as those in the highest performing quartile (OR=2.31; 95% CI: 1.17, 4.55). There was no similar effect among those with high family support. CONCLUSIONS Family support may buffer the negative association between low cognitive functioning and diabetes control in US Hispanics/Latinos. Educational programs targeted at family members of middle-age and older persons with diabetes regardless of neurocognitive status may help improve population-level glycemic control.
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Affiliation(s)
- Garrett Strizich
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, 1300 Morris Park Ave., Bronx, NY 10461
| | - Robert C Kaplan
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, 1300 Morris Park Ave., Bronx, NY 10461
| | - Hector M González
- Department of Epidemiology and Biostatistics, Michigan State University, 909 Fee Road, East Lansing, MI 48824
| | - Martha L Daviglus
- Institute for Minority Health Research, University of Illinois at Chicago, 1819 W. Polk Street, Chicago, IL 60612
| | - Aida L Giachello
- Department of Preventive Medicine, Feinberg School of Medicine, Northwestern University, 680 N Lake Shore Drive, Suite 1400, Chicago, IL 60611
| | - Yanping Teng
- Collaborative Studies Coordinating Center, University of North Carolina, 137 East Franklin Street, Chapel Hill, NC 27514
| | - Richard B Lipton
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, 1300 Morris Park Ave., Bronx, NY 10461
- The Saul R. Korey Department of Neurology, Albert Einstein College of Medicine, 1410 Pelham Parkway South, Kennedy Center Room 316, Bronx, NY 10461
- Department of Psychiatry and Behavioral Sciences, Albert Einstein College of Medicine, 1300 Morris Park Ave., Bronx, NY 10461
| | - Ellen Grober
- The Saul R. Korey Department of Neurology, Albert Einstein College of Medicine, 1410 Pelham Parkway South, Kennedy Center Room 316, Bronx, NY 10461
- Corresponding author: Garrett Strizich, Albert Einstein College of Medicine, 1300 Morris Park Avenue, Suite 1306, Bronx, NY 10461. Tel: 406-249-6387, Fax: 718.430.3588,
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Müller HP, Gorges M, Grön G, Kassubek J, Landwehrmeyer GB, Süßmuth SD, Wolf RC, Orth M. Motor network structure and function are associated with motor performance in Huntington's disease. J Neurol 2016; 263:539-49. [PMID: 26762394 DOI: 10.1007/s00415-015-8014-y] [Citation(s) in RCA: 24] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2015] [Revised: 12/25/2015] [Accepted: 12/27/2015] [Indexed: 12/11/2022]
Abstract
In Huntington's disease, the relationship of brain structure, brain function and clinical measures remains incompletely understood. We asked how sensory-motor network brain structure and neural activity relate to each other and to motor performance. Thirty-four early stage HD and 32 age- and sex-matched healthy control participants underwent structural magnetic resonance imaging (MRI), diffusion tensor, and intrinsic functional connectivity MRI. Diffusivity patterns were assessed in the cortico-spinal tract and the thalamus-somatosensory cortex tract. For the motor network connectivity analyses the dominant M1 motor cortex region and for the basal ganglia-thalamic network the thalamus were used as seeds. Region to region structural and functional connectivity was examined between thalamus and somatosensory cortex. Fractional anisotropy (FA) was higher in HD than controls in the basal ganglia, and lower in the external and internal capsule, in the thalamus, and in subcortical white matter. Between-group axial and radial diffusivity differences were more prominent than differences in FA, and correlated with motor performance. Within the motor network, the insula was less connected in HD than in controls, with the degree of connection correlating with motor scores. The basal ganglia-thalamic network's connectivity differed in the insula and basal ganglia. Tract specific white matter diffusivity and functional connectivity were not correlated. In HD sensory-motor white matter organization and functional connectivity in a motor network were independently associated with motor performance. The lack of tract-specific association of structure and function suggests that functional adaptation to structural loss differs between participants.
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Affiliation(s)
- Hans-Peter Müller
- Department of Neurology, University of Ulm, Oberer Eselsberg 45/1, 89081, Ulm, Germany
| | - Martin Gorges
- Department of Neurology, University of Ulm, Oberer Eselsberg 45/1, 89081, Ulm, Germany
| | - Georg Grön
- Section Neuropsychology and Functional Imaging, Department of Psychiatry, University of Ulm, Ulm, Germany
| | - Jan Kassubek
- Department of Neurology, University of Ulm, Oberer Eselsberg 45/1, 89081, Ulm, Germany
| | | | - Sigurd D Süßmuth
- Department of Neurology, University of Ulm, Oberer Eselsberg 45/1, 89081, Ulm, Germany
| | - Robert Christian Wolf
- Department of Psychiatry, Psychotherapy and Psychosomatics, Saarland University, Homburg, Germany
| | - Michael Orth
- Department of Neurology, University of Ulm, Oberer Eselsberg 45/1, 89081, Ulm, Germany.
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