144 results found
Cole JH, Caan MWA, Underwood J, et al., 2018, No evidence for accelerated ageing-related brain pathology in treated HIV: longitudinal neuroimaging results from the Comorbidity in Relation to AIDS (COBRA) project., Clin Infect Dis
Background: Despite successful antiretroviral therapy people living with HIV (PLWH) experience higher rates of age-related morbidity, including abnormal brain structure, brain function and cognitive impairment. This has raised concerns that PLWH may experience accelerated ageing-related brain pathology. Methods: We performed a multi-centre longitudinal study of 134 virologically-suppressed PLWH (median age = 56.0 years) and 79 demographically-similar HIV-negative controls (median age = 57.2 years). To measure cognitive performance and brain pathology, we conducted detailed neuropsychological assessments and multi-modality neuroimaging (T1-weighted, T2-weighted, diffusion-MRI, resting-state functional-MRI, spectroscopy, arterial spin labelling) at baseline and after two-year follow-up. Group differences in rates of change were assessed using linear mixed effects models. Results: 123 PLWH and 78 HIV-negative controls completed longitudinal assessments (median interval = 1.97 years). There were no differences between PLWH and HIV-negative controls in age, sex, years of education, smoking, alcohol use, recreational drug use, blood pressure, body-mass index or cholesterol levels. At baseline, PLWH had poorer global cognitive performance (P<0.01), lower grey matter volume (P=0.04), higher white matter hyperintensity load (P=0.02), abnormal white-matter microstructure (P<0.005) and greater 'brain-predicted age difference' (P=0.01). Longitudinally, there were no significant differences in rates of change in any neuroimaging measure between PLWH and HIV-negative controls (P>0.1). Cognitive performance was stable across the study period in both groups. Conclusions: Our finding indicate that when receiving successful treatment, middle-aged PLWH are not at increased risk of accelerated ageing-related brain changes or cognitive decline over two years, when compared to closely-matched HIV-negative controls.
Cole JH, Jolly A, de Simoni S, et al., 2018, Spatial patterns of progressive brain volume loss after moderate-severe traumatic brain injury, BRAIN, Vol: 141, Pages: 822-836, ISSN: 0006-8950
De Simoni S, Jenkins PO, Bourke NJ, et al., 2018, Altered caudate connectivity is associated with executive dysfunction after traumatic brain injury, BRAIN, Vol: 141, Pages: 148-164, ISSN: 0006-8950
Jenkins PO, De Simoni S, Bourke NJ, et al., 2018, Dopaminergic abnormalities following traumatic brain injury, BRAIN, Vol: 141, Pages: 797-810, ISSN: 0006-8950
Scott G, Zetterberg H, Jolly A, et al., 2018, Minocycline reduces chronic microglial activation after brain trauma but increases neurodegeneration, BRAIN, Vol: 141, Pages: 459-471, ISSN: 0006-8950
Underwood J, Cole JH, Leech R, et al., 2018, Multivariate pattern analysis of volumetric neuroimaging data and its relationship with cognitive function in treated HIV-disease., J Acquir Immune Defic Syndr
BACKGROUND: Accurate prediction of longitudinal changes in cognitive function would potentially allow targeted intervention in those at greatest risk of cognitive decline. We sought to build a multivariate model using volumetric neuroimaging data alone to accurately predict cognitive function. METHODS: Volumetric T1-weighted neuroimaging data from virally suppressed HIV-positive individuals from the CHARTER cohort (n=139) were segmented into grey and white matter and spatially normalised before were entering into machine learning models. Prediction of cognitive function at baseline and longitudinally was determined using leave-one-out cross validation. Additionally, a multivariate model of brain ageing was used to measure the deviation of apparent brain age from chronological age and assess its relationship with cognitive function. RESULTS: Cognitive impairment, defined using the global deficit score, was present in 37.4%. However, it was generally mild and occurred more commonly in those with confounding comorbidities (p<0.001). Although multivariate prediction of cognitive impairment as a dichotomous variable at baseline was poor (AUC 0.59), prediction of the global T-score was better than a comparable linear model (adjusted R=0.08, p<0.01 vs. adjusted R=0.01, p=0.14). Accurate prediction of longitudinal changes in cognitive function was not possible (p=0.82).Brain-predicted age exceeded chronological age by mean (95% confidence interval) 1.17 (-0.14-2.53) years, but was greatest in those with confounding comorbidities (5.87 [1.74-9.99] years) and prior AIDS (3.03 [0.00-6.06] years). CONCLUSION: Accurate prediction of cognitive impairment using multivariate models using only T1-weighted data was not achievable, which may reflect the small sample size, heterogeneity of the data or that impairment was usually mild.
van Zoest RA, Underwood J, De Francesco D, et al., 2018, Structural Brain Abnormalities in Successfully Treated HIV Infection: Associations With Disease and Cerebrospinal Fluid Biomarkers, JOURNAL OF INFECTIOUS DISEASES, Vol: 217, Pages: 69-81, ISSN: 0022-1899
Arshad Q, Roberts RE, Ahmad H, et al., 2017, Patients with chronic dizziness following traumatic head injury typically have multiple diagnoses involving combined peripheral and central vestibular dysfunction, CLINICAL NEUROLOGY AND NEUROSURGERY, Vol: 155, Pages: 17-19, ISSN: 0303-8467
Booiman T, Wit FW, Maurer I, et al., 2017, High Cellular Monocyte Activation in People Living With Human Immunodeficiency Virus on Combination Antiretroviral Therapy and Lifestyle-Matched Controls Is Associated With Greater Inflammation in Cerebrospinal Fluid, OPEN FORUM INFECTIOUS DISEASES, Vol: 4, ISSN: 2328-8957
Chhabra S, Underwood J, Cole JH, et al., 2017, Clinical research cerebral MRI findings in HIV positive subjects and appropriate controls, Publisher: WILEY, Pages: 10-10, ISSN: 1464-2662
Chiou SY, Hellyer PJ, Sharp DJ, et al., 2017, Relationships between the integrity and function of lumbar nerve roots as assessed by diffusion tensor imaging and neurophysiology, NEURORADIOLOGY, Vol: 59, Pages: 893-903, ISSN: 0028-3940
Age-associated disease and disability are placing a growing burden on society. However, ageing does not affect people uniformly. Hence, markers of the underlying biological ageing process are needed to help identify people at increased risk of age-associated physical and cognitive impairments and ultimately, death. Here, we present such a biomarker, 'brain-predicted age', derived using structural neuroimaging. Brain-predicted age was calculated using machine-learning analysis, trained on neuroimaging data from a large healthy reference sample (N=2001), then tested in the Lothian Birth Cohort 1936 (N=669), to determine relationships with age-associated functional measures and mortality. Having a brain-predicted age indicative of an older-appearing brain was associated with: weaker grip strength, poorer lung function, slower walking speed, lower fluid intelligence, higher allostatic load and increased mortality risk. Furthermore, while combining brain-predicted age with grey matter and cerebrospinal fluid volumes (themselves strong predictors) not did improve mortality risk prediction, the combination of brain-predicted age and DNA-methylation-predicted age did. This indicates that neuroimaging and epigenetics measures of ageing can provide complementary data regarding health outcomes. Our study introduces a clinically-relevant neuroimaging ageing biomarker and demonstrates that combining distinct measurements of biological ageing further helps to determine risk of age-related deterioration and death.Molecular Psychiatry advance online publication, 25 April 2017; doi:10.1038/mp.2017.62.
Cole JH, Underwood J, Caan MWA, et al., 2017, Increased brain-predicted aging in treated HIV disease, NEUROLOGY, Vol: 88, Pages: 1349-1357, ISSN: 0028-3878
Feeney C, Sharp DJ, Hellyer PJ, et al., 2017, Serum Insulin-like Growth Factor-I Levels are Associated with Improved White Matter Recovery after Traumatic Brain Injury, ANNALS OF NEUROLOGY, Vol: 82, Pages: 30-43, ISSN: 0364-5134
Ghajari M, Hellyer PJ, Sharp DJ, 2017, Computational modelling of traumatic brain injury predicts the location of chronic traumatic encephalopathy pathology, BRAIN, Vol: 140, Pages: 333-343, ISSN: 0006-8950
Goverdovsky V, von Rosenberg W, Nakamura T, et al., 2017, Hearables: Multimodal physiological in-ear sensing, SCIENTIFIC REPORTS, Vol: 7, ISSN: 2045-2322
Martin-Bastida A, Ward RJ, Newbould R, et al., 2017, Brain iron chelation by deferiprone in a phase 2 randomised double-blinded placebo controlled clinical trial in Parkinson's disease, SCIENTIFIC REPORTS, Vol: 7, ISSN: 2045-2322
Roberts RE, Ahmad H, Arshad Q, et al., 2017, Functional neuroimaging of visuo-vestibular interaction, BRAIN STRUCTURE & FUNCTION, Vol: 222, Pages: 2329-2343, ISSN: 1863-2653
Shamshiri EA, Tierney TM, Centeno M, et al., 2017, Interictal activity is an important contributor to abnormal intrinsic network connectivity in paediatric focal epilepsy, HUMAN BRAIN MAPPING, Vol: 38, Pages: 221-236, ISSN: 1065-9471
Sharp DJ, 2017, BRAIN IMAGING AFTER TBI, 30th Annual General Meeting of the British-Neuropsychiatry-Association (BNPA), Publisher: BMJ PUBLISHING GROUP, Pages: E10-E10, ISSN: 0022-3050
Su T, Mutsaerts HJMM, Caan MWA, et al., 2017, Cerebral blood flow and cognitive function in HI-infected men with sustained suppressed viremia on combination antiretroviral therapy, AIDS, Vol: 31, Pages: 847-856, ISSN: 0269-9370
Underwood J, Cole JH, Caan M, et al., 2017, Gray and White Matter Abnormalities in Treated Human Immunodeficiency Virus Disease and Their Relationship to Cognitive Function, CLINICAL INFECTIOUS DISEASES, Vol: 65, Pages: 422-432, ISSN: 1058-4838
Violante IR, Li LM, Carmichael DW, et al., 2017, Externally induced frontoparietal synchronization modulates network dynamics and enhances working memory performance., Elife, Vol: 6
Cognitive functions such as working memory (WM) are emergent properties of large-scale network interactions. Synchronisation of oscillatory activity might contribute to WM by enabling the coordination of long-range processes. However, causal evidence for the way oscillatory activity shapes network dynamics and behavior in humans is limited. Here we applied transcranial alternating current stimulation (tACS) to exogenously modulate oscillatory activity in a right frontoparietal network that supports WM. Externally induced synchronization improved performance when cognitive demands were high. Simultaneously collected fMRI data reveals tACS effects dependent on the relative phase of the stimulation and the internal cognitive processing state. Specifically, synchronous tACS during the verbal WM task increased parietal activity, which correlated with behavioral performance. Furthermore, functional connectivity results indicate that the relative phase of frontoparietal stimulation influences information flow within the WM network. Overall, our findings demonstrate a link between behavioral performance in a demanding WM task and large-scale brain synchronization.
Whittington A, Sharp DJ, Gunn RN, 2017, An automated algorithm to quantify brain amyloid load, 28th International Symposium on Cerebral Blood Flow, Metabolism and Function / 13th International Conference on Quantification of Brain Function with PET, Publisher: SAGE PUBLICATIONS INC, Pages: 80-80, ISSN: 0271-678X
Whittington A, Sharp DJ, Gunn RN, 2017, Spatiotemporal distribution of β-amyloid in Alzheimer's disease results from heterogeneous regional carrying capacities., J Nucl Med
β-amyloid (Aβ) accumulation in the brain is one of two pathological hallmarks of Alzheimer's Disease (AD) and its spatial distribution has been studied extensively ex vivo. We apply mathematical modelling to Aβ in vivo PET imaging data in order to investigate competing theories of Aβ spread in AD. Our results provide evidence that Aβ accumulation starts in all brain regions simultaneously and that its spatiotemporal distribution is a result of heterogeneous regional carrying capacities (regional maximum possible concentration of Aβ) for the aggregated protein rather than longer term spreading from seed regions.
Ahmad H, Arshad Q, Roberts R, et al., 2016, CHRONIC DIZZINESS POST TRAUMATIC BRAIN INJURY: A CROSS-SECTIONAL STUDY, Annual Meeting of the Association-of-British-Neurologists (ABN), Publisher: BMJ PUBLISHING GROUP, ISSN: 0022-3050
De Simoni S, Grover PJ, Jenkins PO, et al., 2016, Disconnection between the default mode network and medial temporal lobes in post-traumatic amnesia, BRAIN, Vol: 139, Pages: 3137-3150, ISSN: 0006-8950
De Simoni S, Kochaj R, Jenkins P, et al., 2016, Changes in cerebral blood flow and their relationship to cognition following traumatic brain injury, Publisher: TAYLOR & FRANCIS INC, Pages: 605-605, ISSN: 0269-9052
Dinov M, Lorenz R, Scott G, et al., 2016, Novel Modeling of Task vs. Rest Brain State Predictability Using a Dynamic Time Warping Spectrum: Comparisons and Contrasts with Other Standard Measures of Brain Dynamics, FRONTIERS IN COMPUTATIONAL NEUROSCIENCE, Vol: 10, ISSN: 1662-5188
Fagerholm ED, Scott G, Shew WL, et al., 2016, Cortical Entropy, Mutual Information and Scale-Free Dynamics in Waking Mice, CEREBRAL CORTEX, Vol: 26, Pages: 3945-3952, ISSN: 1047-3211
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