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Salih A, Galazzo IB, Petersen SE, Lekadir K, Radeva P, Menegaz G, Altmann A. Telomere length is causally connected to brain MRI image derived phenotypes: A mendelian randomization study. PLoS One 2022; 17:e0277344. [PMID: 36399449 PMCID: PMC9674175 DOI: 10.1371/journal.pone.0277344] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2021] [Accepted: 10/25/2022] [Indexed: 11/19/2022] Open
Abstract
Recent evidence suggests that shorter telomere length (TL) is associated with neuro degenerative diseases and aging related outcomes. The causal association between TL and brain characteristics represented by image derived phenotypes (IDPs) from different magnetic resonance imaging (MRI) modalities remains unclear. Here, we use two-sample Mendelian randomization (MR) to systematically assess the causal relationships between TL and 3,935 brain IDPs. Overall, the MR results suggested that TL was causally associated with 193 IDPs with majority representing diffusion metrics in white matter tracts. 68 IDPs were negatively associated with TL indicating that longer TL causes decreasing in these IDPs, while the other 125 were associated positively (longer TL leads to increased IDPs measures). Among them, ten IDPs have been previously reported as informative biomarkers to estimate brain age. However, the effect direction between TL and IDPs did not reflect the observed direction between aging and IDPs: longer TL was associated with decreases in fractional anisotropy and increases in axial, radial and mean diffusivity. For instance, TL was positively associated with radial diffusivity in the left perihippocampal cingulum tract and with mean diffusivity in right perihippocampal cingulum tract. Our results revealed a causal role of TL on white matter integrity which makes it a valuable factor to be considered when brain age is estimated and investigated.
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Affiliation(s)
- Ahmed Salih
- Department of Computer Science, University of Verona, Verona, Italy
| | | | - Steffen E. Petersen
- William Harvey Research Institute, NIHR Barts Biomedical Research Centre, Queen Mary University of London, London, United Kingdom
- Barts Heart Centre, St Bartholomew’s Hospital, Barts Health NHS Trust, London, United Kingdom
| | - Karim Lekadir
- Dept. de Matemàtiques i Informàtica, University of Barcelona, Barcelona, Spain
| | - Petia Radeva
- Dept. de Matemàtiques i Informàtica, University of Barcelona, Barcelona, Spain
| | - Gloria Menegaz
- Department of Computer Science, University of Verona, Verona, Italy
| | - André Altmann
- Centre for Medical Image Computing (CMIC), Department of Medical Physics and Biomedical Engineering, University College London, London, United Kingdom
- * E-mail:
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Relating Response Inhibition, Brain Connectivity, and Freezing of Gait in People with Parkinson's Disease. J Int Neuropsychol Soc 2021; 27:733-743. [PMID: 33292899 PMCID: PMC8187475 DOI: 10.1017/s135561772000123x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
OBJECTIVE Freezing of gait (FoG) in Parkinson's disease (PD) has been associated with response inhibition. However, the relationship between response inhibition, neural dysfunction, and PD remains unclear. We assessed response inhibition and microstructural integrity of brain regions involved in response inhibition [right hemisphere inferior frontal cortex (IFC), bilateral pre-supplementary motor areas (preSMA), and subthalamic nuclei (STN)] in PD subjects with and without FoG and elderly controls. METHOD Twenty-one people with PD and FoG (PD-FoG), 18 without FoG (PD-noFoG), and 19 age-matched controls (HC) completed a Stop-Signal Task (SST) and MRI scan. Probabilistic fiber tractography assessed structural integrity (fractional anisotropy, FA) among IFC, preSMA, and STN regions. RESULTS Stop-signal performance did not differ between PD and HC, nor between PD-FoG and PD-noFoG. Differences in white matter integrity were observed across groups (.001 < p < .064), but were restricted to PD versus HC groups; no differences in FA were observed between PD-FoG and PD-noFoG (p > .096). Interestingly, worse FoG was associated with higher (better) mean FA in the r-preSMA, (β = .547, p = .015). Microstructural integrity of the r-IFC, r-preSMA, and r-STN tracts correlated with stop-signal performance in HC (p ≤ .019), but not people with PD. CONCLUSION These results do not support inefficient response inhibition in PD-FoG. Those with PD exhibited white matter loss in the response inhibition network, but this was not associated with FoG, nor with response inhibition deficits, suggesting FoG-specific neural changes may occur outside the response inhibition network. As shown previously, white matter loss was associated with response inhibition in elderly controls, suggesting PD may disturb this relationship.
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Brennan D, Wu T, Fan J. Morphometrical Brain Markers of Sex Difference. Cereb Cortex 2021; 31:3641-3649. [PMID: 33774662 DOI: 10.1093/cercor/bhab037] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2020] [Revised: 01/22/2021] [Accepted: 02/06/2021] [Indexed: 01/02/2023] Open
Abstract
Many major neuropsychiatric pathologies, some of which appear in adolescence, show differentiated prevalence, onset, and symptomatology across the biological sexes. Therefore, mapping differences in brain structure between males and females during this critical developmental period may provide information about the neural mechanisms underlying the dimorphism of these pathologies. Utilizing a large dataset collected through the Adolescent Brain Cognitive Development study, we investigated the differences of adolescent (9-10 years old) male and female brains (n = 8325) by using a linear Support-Vector Machine Classifier to predict sex based on morphometry and image intensity values of structural brain imaging data. The classifier correctly classified the sex of 86% individuals with the insula, the precentral and postcentral gyri, and the pericallosal sulcus as the most discernable features. These results demonstrate the existence of complex, yet robustly measurable morphometrical brain markers of sex difference.
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Affiliation(s)
- Daniel Brennan
- Department of Psychology, The Graduate Center, The City University of New York, New York, NY 10016, USA
| | - Tingting Wu
- Department of Psychology, Queens College, The City University of New York, Queens, NY 11367, USA
| | - Jin Fan
- Department of Psychology, Queens College, The City University of New York, Queens, NY 11367, USA
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Sheng L, Zhao P, Ma H, Radua J, Yi Z, Shi Y, Zhong J, Dai Z, Pan P. Cortical thickness in Parkinson's disease: a coordinate-based meta-analysis. Aging (Albany NY) 2021; 13:4007-4023. [PMID: 33461168 PMCID: PMC7906199 DOI: 10.18632/aging.202368] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2020] [Accepted: 11/30/2020] [Indexed: 12/24/2022]
Abstract
Parkinson's disease (PD) is a common age-related neurodegenerative disease that affects the structural architecture of the cerebral cortex. Cortical thickness (CTh) via surface-based morphometry (SBM) analysis is a popular measure to assess brain structural alterations in the gray matter in PD. However, the results of CTh analysis in PD lack consistency and have not been systematically reviewed. We conducted a comprehensive coordinate-based meta-analysis (CBMA) of 38 CTh studies (57 comparison datasets) in 1,843 patients with PD using the latest seed-based d mapping software. Compared with 1,172 healthy controls, no significantly consistent CTh alterations were found in patients with PD, suggesting CTh as an unreliable neuroimaging marker for PD. The lack of consistent CTh alterations in PD could be ascribed to the heterogeneity in clinical populations, variations in imaging methods, and underpowered small sample sizes. These results highlight the need to control for potential confounding factors to produce robust and reproducible CTh results in PD.
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Affiliation(s)
- LiQin Sheng
- Department of Neurology, Kunshan Hospital of Traditional Chinese Medicine, Kunshan, PR China
| | - PanWen Zhao
- Department of Central Laboratory, The Yancheng School of Clinical Medicine of Nanjing Medical University, Yancheng, PR China
| | - HaiRong Ma
- Department of Neurology, Kunshan Hospital of Traditional Chinese Medicine, Kunshan, PR China
| | - Joaquim Radua
- Imaging of Mood- and Anxiety-Related Disorders (IMARD) Group, Institut d’Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), CIBERSAM, Barcelona, Spain
- Early Psychosis: Interventions and Clinical-Detection (EPIC) Laboratory, Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK
- Centre for Psychiatric Research and Education, Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - ZhongQuan Yi
- Department of Central Laboratory, The Yancheng School of Clinical Medicine of Nanjing Medical University, Yancheng, PR China
| | - YuanYuan Shi
- Department of Central Laboratory, The Yancheng School of Clinical Medicine of Nanjing Medical University, Yancheng, PR China
| | - JianGuo Zhong
- Department of Neurology, The Yancheng School of Clinical Medicine of Nanjing Medical University, Yancheng, PR China
| | - ZhenYu Dai
- Department of Radiology, The Yancheng School of Clinical Medicine of Nanjing Medical University, Yancheng, PR China
| | - PingLei Pan
- Department of Neurology, The Yancheng School of Clinical Medicine of Nanjing Medical University, Yancheng, PR China
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5
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Backman JD, Li AH, Marcketta A, Sun D, Mbatchou J, Kessler MD, Benner C, Liu D, Locke AE, Balasubramanian S, Yadav A, Banerjee N, Gillies CE, Damask A, Liu S, Bai X, Hawes A, Maxwell E, Gurski L, Watanabe K, Kosmicki JA, Rajagopal V, Mighty J, Jones M, Mitnaul L, Stahl E, Coppola G, Jorgenson E, Habegger L, Salerno WJ, Shuldiner AR, Lotta LA, Overton JD, Cantor MN, Reid JG, Yancopoulos G, Kang HM, Marchini J, Baras A, Abecasis GR, Ferreira MAR. Exome sequencing and analysis of 454,787 UK Biobank participants. Nature 2021; 599:628-634. [PMID: 34662886 PMCID: PMC8596853 DOI: 10.1038/s41586-021-04103-z] [Citation(s) in RCA: 311] [Impact Index Per Article: 103.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2021] [Accepted: 10/06/2021] [Indexed: 12/19/2022]
Abstract
A major goal in human genetics is to use natural variation to understand the phenotypic consequences of altering each protein-coding gene in the genome. Here we used exome sequencing1 to explore protein-altering variants and their consequences in 454,787 participants in the UK Biobank study2. We identified 12 million coding variants, including around 1 million loss-of-function and around 1.8 million deleterious missense variants. When these were tested for association with 3,994 health-related traits, we found 564 genes with trait associations at P ≤ 2.18 × 10-11. Rare variant associations were enriched in loci from genome-wide association studies (GWAS), but most (91%) were independent of common variant signals. We discovered several risk-increasing associations with traits related to liver disease, eye disease and cancer, among others, as well as risk-lowering associations for hypertension (SLC9A3R2), diabetes (MAP3K15, FAM234A) and asthma (SLC27A3). Six genes were associated with brain imaging phenotypes, including two involved in neural development (GBE1, PLD1). Of the signals available and powered for replication in an independent cohort, 81% were confirmed; furthermore, association signals were generally consistent across individuals of European, Asian and African ancestry. We illustrate the ability of exome sequencing to identify gene-trait associations, elucidate gene function and pinpoint effector genes that underlie GWAS signals at scale.
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Affiliation(s)
- Joshua D. Backman
- grid.418961.30000 0004 0472 2713Regeneron Genetics Center, Tarrytown, NY USA
| | - Alexander H. Li
- grid.418961.30000 0004 0472 2713Regeneron Genetics Center, Tarrytown, NY USA
| | - Anthony Marcketta
- grid.418961.30000 0004 0472 2713Regeneron Genetics Center, Tarrytown, NY USA
| | - Dylan Sun
- grid.418961.30000 0004 0472 2713Regeneron Genetics Center, Tarrytown, NY USA
| | - Joelle Mbatchou
- grid.418961.30000 0004 0472 2713Regeneron Genetics Center, Tarrytown, NY USA
| | - Michael D. Kessler
- grid.418961.30000 0004 0472 2713Regeneron Genetics Center, Tarrytown, NY USA
| | - Christian Benner
- grid.418961.30000 0004 0472 2713Regeneron Genetics Center, Tarrytown, NY USA
| | - Daren Liu
- grid.418961.30000 0004 0472 2713Regeneron Genetics Center, Tarrytown, NY USA
| | - Adam E. Locke
- grid.418961.30000 0004 0472 2713Regeneron Genetics Center, Tarrytown, NY USA
| | | | - Ashish Yadav
- grid.418961.30000 0004 0472 2713Regeneron Genetics Center, Tarrytown, NY USA
| | - Nilanjana Banerjee
- grid.418961.30000 0004 0472 2713Regeneron Genetics Center, Tarrytown, NY USA
| | | | - Amy Damask
- grid.418961.30000 0004 0472 2713Regeneron Genetics Center, Tarrytown, NY USA
| | - Simon Liu
- grid.418961.30000 0004 0472 2713Regeneron Genetics Center, Tarrytown, NY USA
| | - Xiaodong Bai
- grid.418961.30000 0004 0472 2713Regeneron Genetics Center, Tarrytown, NY USA
| | - Alicia Hawes
- grid.418961.30000 0004 0472 2713Regeneron Genetics Center, Tarrytown, NY USA
| | - Evan Maxwell
- grid.418961.30000 0004 0472 2713Regeneron Genetics Center, Tarrytown, NY USA
| | - Lauren Gurski
- grid.418961.30000 0004 0472 2713Regeneron Genetics Center, Tarrytown, NY USA
| | - Kyoko Watanabe
- grid.418961.30000 0004 0472 2713Regeneron Genetics Center, Tarrytown, NY USA
| | - Jack A. Kosmicki
- grid.418961.30000 0004 0472 2713Regeneron Genetics Center, Tarrytown, NY USA
| | - Veera Rajagopal
- grid.418961.30000 0004 0472 2713Regeneron Genetics Center, Tarrytown, NY USA
| | - Jason Mighty
- grid.418961.30000 0004 0472 2713Regeneron Genetics Center, Tarrytown, NY USA
| | | | | | - Marcus Jones
- grid.418961.30000 0004 0472 2713Regeneron Genetics Center, Tarrytown, NY USA
| | - Lyndon Mitnaul
- grid.418961.30000 0004 0472 2713Regeneron Genetics Center, Tarrytown, NY USA
| | - Eli Stahl
- grid.418961.30000 0004 0472 2713Regeneron Genetics Center, Tarrytown, NY USA
| | - Giovanni Coppola
- grid.418961.30000 0004 0472 2713Regeneron Genetics Center, Tarrytown, NY USA
| | - Eric Jorgenson
- grid.418961.30000 0004 0472 2713Regeneron Genetics Center, Tarrytown, NY USA
| | - Lukas Habegger
- grid.418961.30000 0004 0472 2713Regeneron Genetics Center, Tarrytown, NY USA
| | - William J. Salerno
- grid.418961.30000 0004 0472 2713Regeneron Genetics Center, Tarrytown, NY USA
| | - Alan R. Shuldiner
- grid.418961.30000 0004 0472 2713Regeneron Genetics Center, Tarrytown, NY USA
| | - Luca A. Lotta
- grid.418961.30000 0004 0472 2713Regeneron Genetics Center, Tarrytown, NY USA
| | - John D. Overton
- grid.418961.30000 0004 0472 2713Regeneron Genetics Center, Tarrytown, NY USA
| | - Michael N. Cantor
- grid.418961.30000 0004 0472 2713Regeneron Genetics Center, Tarrytown, NY USA
| | - Jeffrey G. Reid
- grid.418961.30000 0004 0472 2713Regeneron Genetics Center, Tarrytown, NY USA
| | - George Yancopoulos
- grid.418961.30000 0004 0472 2713Regeneron Genetics Center, Tarrytown, NY USA
| | - Hyun M. Kang
- grid.418961.30000 0004 0472 2713Regeneron Genetics Center, Tarrytown, NY USA
| | - Jonathan Marchini
- grid.418961.30000 0004 0472 2713Regeneron Genetics Center, Tarrytown, NY USA
| | - Aris Baras
- grid.418961.30000 0004 0472 2713Regeneron Genetics Center, Tarrytown, NY USA
| | - Gonçalo R. Abecasis
- grid.418961.30000 0004 0472 2713Regeneron Genetics Center, Tarrytown, NY USA
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Schonhoff AM, Williams GP, Wallen ZD, Standaert DG, Harms AS. Innate and adaptive immune responses in Parkinson's disease. PROGRESS IN BRAIN RESEARCH 2019; 252:169-216. [PMID: 32247364 DOI: 10.1016/bs.pbr.2019.10.006] [Citation(s) in RCA: 62] [Impact Index Per Article: 12.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
Parkinson's disease (PD) has classically been defined as a movement disorder, in which motor symptoms are explained by the aggregation of alpha-synuclein (α-syn) and subsequent death of dopaminergic neurons of the substantia nigra pars compacta (SNpc). More recently, the multisystem effects of the disease have been investigated, with the immune system being implicated in a number of these processes in the brain, the blood, and the gut. In this review, we highlight the dysfunctional immune system found in both human PD and animal models of the disease, and discuss how genetic risk factors and risk modifiers are associated with pro-inflammatory immune responses. Finally, we emphasize evidence that the immune response drives the pathogenesis and progression of PD, and discuss key questions that remain to be investigated in order to identify immunomodulatory therapies in PD.
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Affiliation(s)
- Aubrey M Schonhoff
- Center for Neurodegeneration and Experimental Therapeutics, Department of Neurology, The University of Alabama at Birmingham, Birmingham, AL, United States
| | - Gregory P Williams
- Center for Neurodegeneration and Experimental Therapeutics, Department of Neurology, The University of Alabama at Birmingham, Birmingham, AL, United States
| | - Zachary D Wallen
- Center for Neurodegeneration and Experimental Therapeutics, Department of Neurology, The University of Alabama at Birmingham, Birmingham, AL, United States
| | - David G Standaert
- Center for Neurodegeneration and Experimental Therapeutics, Department of Neurology, The University of Alabama at Birmingham, Birmingham, AL, United States
| | - Ashley S Harms
- Center for Neurodegeneration and Experimental Therapeutics, Department of Neurology, The University of Alabama at Birmingham, Birmingham, AL, United States.
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