611 research outputs found

    A neuroimaging investigation of bipolar disorder and the neurocognitive effects of 5-HT7 antagonists

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    Bipolar disorder is a psychiatric disorder characterised by pathological mood states, but there is growing recognition of the role of cognitive impairment and dysfunction of emotional processes, which has a profound impact on quality of life. Many people with bipolar disorders exhibit brain volume impairment associated with cognitive dysfunction and an increased risk of dementia. In this thesis, I conducted a systematic review to understand the relationships between mood disorders and the 5-HT7 receptor. The 5-HT7 receptor is related to depression and anxiety, but the relationship between 5-HT7 and mania remains unclear; in addition, sleep and memory were also related to the 5-HT7 receptor. Followed by these findings, in the next two chapters, I examined the effects of 5-HT7 antagonists, using JNJ-18038683, on emotional and cognitive functioning, as well as their neural substrates. I then reported on neuroimaging investigations examining the effects of 5-HT7 antagonists on emotional processing and cognitive function in healthy volunteers to gain insight into their potential mode of action and utility for bipolar disorder. In fMRI analyses, the drug acted on 5-HT7 receptors potentially improving cognitive performance by modulating the function of the Cognitive Control Network in healthy controls. In the above-mentioned chapters, I gained a better understanding of the 5-HT7 antagonist, JNJ-18038683, and the putative promising effects for pharmacological treatments. However, the approach taken has some limitations, including a small sample size, potential participant bias, and a lack of systematic control of medication dose and duration of administration. In addition, in Chapter 5, I explored the brain basis of bipolar disorder and its links to cognitive and emotional dysfunction using a new ‘brain age’ approach. Individuals with bipolar disorder were found to have increased brain age compared to healthy controls. I hope that these findings can be applied to pharmacological treatment for individuals with bipolar disorder, ultimately allowing patients to benefit from the drug in the future

    Cardiovascular health, orthostatic hypotension, and cognitive aging

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    Cardiovascular health (CVH) plays an important role in dementia development. Ideal CVH, defined by Life’s Simple 7 (LS7), has been associated with a lower risk of dementia in older adults. Orthostatic hypotension (OH) may be a novel cardiovascular risk factor that can affect dementia development. In this thesis, population-based cohort studies were conducted to investigate the role of LS7-defined CVH and OH in cognitive aging in people aged ≥60 years using data from the Swedish National Study on Aging and Care in Kungsholmen (SNAC-K). Study I investigated LS7-defined CVH in relation to transitions between normal cognition, cognitive impairment, no dementia (CIND), and dementia. The study found that people with better CVH had a lower hazard of transitioning directly from normal cognition to CIND (HR = 0.76, 95% CI = 0.61-0.95) and dementia (HR = 0.42, 95% CI = 0.21-0.82) in people aged <78 years. In addition, people aged <78 years with better CVH had two to three more years of life living with normal cognition. However, CVH, defined by LS7, was not related to transitions between cognitive states in people aged ≥78 years. Study II evaluated the associations between OH and dementia. Of the 2532 people who were initially free of dementia, 615 (24.3%) people had OH. People with OH had higher hazards of developing dementia (HR = 1.40, 95% CI = 1.10–1.76) and Alzheimer’s disease (HR = 1.39, 95% CI = 1.04–1.86). In addition, OH was related to a higher hazard of progression from CIND to dementia in people with CIND (HR = 1.54, 95% CI = 1.05–2.25) but not with incident CIND in those without CIND and dementia (HR = 1.15, 95% CI = 0.94–1.40). Study III investigated the impact of OH on the development of CVDs and dementia in people initially free of CVDs as well as the impact of OH on dementia development in people with CVDs. The study found that in people who were initially free of CVDs, individuals who had OH at baseline had a higher hazard of developing CVDs (HR = 1.33, 95% CI = 1.12-1.59) but not dementia (HR = 1.22, 95% CI = 0.83-1.81) compared to those without OH. Among those with CVDs, persons with OH also had a higher hazard of dementia (HR = 1.54, 95% CI = 1.06-2.23) compared to those without OH. Study IV assessed the associations of OH, in the presence or absence of frailty, with dementia and mortality. This study found that individuals who had OH at baseline had a higher hazard of dementia in the presence (HR = 2.73, 95% CI = 1.82-4.10) and absence (HR = 2.28, 95% CI = 1.47-3.54) of frailty than robust persons without OH. However, OH was only associated with a higher hazard of death without dementia when accompanied by frailty (HR = 1.56, 95% CI = 1.25-1.96). Conclusions. Maintaining ideal CVH may protect against cognitive dysfunction and reduce years of life with cognitive dysfunction in younger old age. OH may be a potential modifiable risk factor for dementia, and the intermediate development of CVDs may help explain the association between OH and dementia

    Cerebrovascular dysfunction in cerebral small vessel disease

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    INTRODUCTION: Cerebral small vessel disease (SVD) is the cause of a quarter of all ischaemic strokes and is postulated to have a role in up to half of all dementias. SVD pathophysiology remains unclear but cerebrovascular dysfunction may be important. If confirmed many licensed medications have mechanisms of action targeting vascular function, potentially enabling new treatments via drug repurposing. Knowledge is limited however, as most studies assessing cerebrovascular dysfunction are small, single centre, single imaging modality studies due to the complexities in measuring cerebrovascular dysfunctions in humans. This thesis describes the development and application of imaging techniques measuring several cerebrovascular dysfunctions to investigate SVD pathophysiology and trial medications that may improve small blood vessel function in SVD. METHODS: Participants with minor ischaemic strokes were recruited to a series of studies utilising advanced MRI techniques to measure cerebrovascular dysfunction. Specifically MRI scans measured the ability of different tissues in the brain to change blood flow in response to breathing carbon dioxide (cerebrovascular reactivity; CVR) and the flow and pulsatility through the cerebral arteries, venous sinuses and CSF spaces. A single centre observational study optimised and established feasibility of the techniques and tested associations of cerebrovascular dysfunctions with clinical and imaging phenotypes. Then a randomised pilot clinical trial tested two medications’ (cilostazol and isosorbide mononitrate) ability to improve CVR and pulsatility over a period of eight weeks. The techniques were then expanded to include imaging of blood brain barrier permeability and utilised in multi-centre studies investigating cerebrovascular dysfunction in both sporadic and monogenetic SVDs. RESULTS: Imaging protocols were feasible, consistently being completed with usable data in over 85% of participants. After correcting for the effects of age, sex and systolic blood pressure, lower CVR was associated with higher white matter hyperintensity volume, Fazekas score and perivascular space counts. Lower CVR was associated with higher pulsatility of blood flow in the superior sagittal sinus and lower CSF flow stroke volume at the foramen magnum. Cilostazol and isosorbide mononitrate increased CVR in white matter. The CVR, intra-cranial flow and pulsatility techniques, alongside blood brain barrier permeability and microstructural integrity imaging were successfully employed in a multi-centre observational study. A clinical trial assessing the effects of drugs targeting blood pressure variability is nearing completion. DISCUSSION: Cerebrovascular dysfunction in SVD has been confirmed and may play a more direct role in disease pathogenesis than previously established risk factors. Advanced imaging measures assessing cerebrovascular dysfunction are feasible in multi-centre studies and trials. Identifying drugs that improve cerebrovascular dysfunction using these techniques may be useful in selecting candidates for definitive clinical trials which require large sample sizes and long follow up periods to show improvement against outcomes of stroke and dementia incidence and cognitive function

    Investigating small extracellular vesicle miRNA as biomarkers for Alzheimer’s disease

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    Alzheimer’s disease (AD) is the leading cause of dementia, a syndrome impacting over 900,000 people in the UK alone. There are currently no disease modifying treatments for AD, which is largely attributable to the heterogenous basis of the disease which is known to have multiple genetic and environmental contributors. Early identification of the pathogenic drivers of disease could help with both the diagnosis of specific dementia subtypes and the development of more targeted, personalised, therapeutic interventions.Extracellular vesicles (EVs) can cross the blood-brain-barrier and have been shown to carry AD associated cargoes, including amyloid-β and tau. EV miRNA presents a promising avenue for biomarkers for AD. Within this project, EVs were isolated from fibroblasts, hydrogen peroxide treated SH-SY5Y cells and human brain tissue, by sequential centrifugation and separation by size exclusion chromatography. Isolated EVs were characterised using western blotting, fluorescence nanoparticle tracking analysis, and transmission electron microscopy. MiRNA analysis was performed using qPCR and small RNA sequencing.Isolated EVs displayed size ranges in line with small EVs (< 150 nm) and expressed EV associated proteins, including tetraspanins CD9, CD63 and CD81, while not expressing cellular associated markers. Small RNA sequencing identified a panel of upregulated (miR-203a, miR-141, miR-361, miR-30a, and miR-125b-1) and downregulated (miR-582 and miR-1248) miRNAs in brain derived EVs (BDEVs) in AD. In fibroblast derived EVs, miR-146, miR-92a and miR-134 were upregulated in both qPCR and RNA sequencing, while miR-134 was downregulated in SH-SY5Y EVs. When stratified for females, miR-27a and miR-668 displayed increased dysregulation in BDEVs in AD. miR-185, miR-132 and miR-660 showed converse patterns of dysregulation in AD, between fibroblast derived and brain derived EVs. In both, fibroblast derived and brain derived EVs, miR-660 was inversely dysregulated in AD between males and females.Combined we highlight a panel of EV miRNAs that show promise as biomarkers for AD that express centrally and peripherally, that can support early intervention of disease.Key words: Alzheimer’s disease, extracellular vesicles, miRNA, fibroblast, brain tissue, SH-SY5Y, biomarker

    An overview of data integration in neuroscience with focus on Alzheimer's Disease

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    : This work represents the first attempt to provide an overview of how to face data integration as the result of a dialogue between neuroscientists and computer scientists. Indeed, data integration is fundamental for studying complex multifactorial diseases, such as the neurodegenerative diseases. This work aims at warning the readers of common pitfalls and critical issues in both medical and data science fields. In this context, we define a road map for data scientists when they first approach the issue of data integration in the biomedical domain, highlighting the challenges that inevitably emerge when dealing with heterogeneous, large-scale and noisy data and proposing possible solutions. Here, we discuss data collection and statistical analysis usually seen as parallel and independent processes, as cross-disciplinary activities. Finally, we provide an exemplary application of data integration to address Alzheimer's Disease (AD), which is the most common multifactorial form of dementia worldwide. We critically discuss the largest and most widely used datasets in AD, and demonstrate how the emergence of machine learning and deep learning methods has had a significant impact on disease's knowledge particularly in the perspective of an early AD diagnosis

    Artificial intelligence for dementia genetics and omics

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    Genetics and omics studies of Alzheimer's disease and other dementia subtypes enhance our understanding of underlying mechanisms and pathways that can be targeted. We identified key remaining challenges: First, can we enhance genetic studies to address missing heritability? Can we identify reproducible omics signatures that differentiate between dementia subtypes? Can high‐dimensional omics data identify improved biomarkers? How can genetics inform our understanding of causal status of dementia risk factors? And which biological processes are altered by dementia‐related genetic variation? Artificial intelligence (AI) and machine learning approaches give us powerful new tools in helping us to tackle these challenges, and we review possible solutions and examples of best practice. However, their limitations also need to be considered, as well as the need for coordinated multidisciplinary research and diverse deeply phenotyped cohorts. Ultimately AI approaches improve our ability to interrogate genetics and omics data for precision dementia medicine. Highlights: We have identified five key challenges in dementia genetics and omics studies. AI can enable detection of undiscovered patterns in dementia genetics and omics data. Enhanced and more diverse genetics and omics datasets are still needed. Multidisciplinary collaborative efforts using AI can boost dementia research

    Disease progression and genetic risk factors in the primary tauopathies

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    The primary tauopathies are a group of progressive neurodegenerative diseases within the frontotemporal lobar degeneration spectrum (FTLD) characterised by the accumulation of misfolded, hyperphosphorylated microtubule-associated tau protein (MAPT) within neurons and glial cells. They can be classified according to the underlying ratio of three-repeat (3R) to four-repeat (4R) tau and include Pick’s disease (PiD), which is the only 3R tauopathy, and the 4R tauopathies the most common of which are progressive supranuclear palsy (PSP) and corticobasal degeneration (CBD). There are no disease modifying therapies currently available, with research complicated by the wide variability in clinical presentations for each underlying pathology, with presentations often overlapping, as well as the frequent occurrence of atypical presentations that may mimic other non-FTLD pathologies. Although progress has been made in understanding the genetic contribution to disease risk in the more common 4R tauopathies (PSP and CBD), very little is known about the genetics of the 3R tauopathy PiD. There are two broad aims to this thesis; firstly, to use data-driven generative models of disease progression to try and more accurately stage and subtype patients presenting with PSP and corticobasal syndrome (CBS, the most common presentation of CBD), and secondly to identify genetic drivers of disease risk and progression in PiD. Given the rarity of these disorders, as part of this PhD I had to assemble two large cohorts through international collaboration, the 4R tau imaging cohort and the Pick’s disease International Consortium (PIC), to build large enough sample sizes to enable the required analyses. In Chapter 3 I use a probabilistic event-based modelling (EBM) approach applied to structural MRI data to determine the sequence of brain atrophy changes in clinically diagnosed PSP - Richardson syndrome (PSP-RS). The sequence of atrophy predicted by the model broadly mirrors the sequential spread of tau pathology in PSP post-mortem staging studies, and has potential utility to stratify PSP patients on entry into clinical trials based on disease stage, as well as track disease progression. To better characterise the spatiotemporal heterogeneity of the 4R tauopathies, I go on to use Subtype and Stage Inference (SuStaIn), an unsupervised machine algorithm, to identify population subgroups with distinct patterns of atrophy in PSP (Chapter 4) and CBS (Chapter 5). The SuStaIn model provides data-driven evidence for the existence of two spatiotemporal subtypes of atrophy in clinically diagnosed PSP, giving insights into the relationship between pathology and clinical syndrome. In CBS I identify two distinct imaging subtypes that are differentially associated with underlying pathology, and potentially a third subtype that if confirmed in a larger dataset may allow the differentiation of CBD from both PSP and AD pathology using a baseline MRI scan. In Chapter 6 I investigate the association between the MAPT H1/H2 haplotype and PiD, showing for the first time that the H2 haplotype, known to be strongly protective against developing PSP or CBD, is associated with an increased risk of PiD. This is an important finding and has implications for the future development of MAPT isoform-specific therapeutic strategies for the primary tauopathies. In Chapter 7 I perform the first genome wide association study (GWAS) in PiD, identifying five genomic loci that are nominally associated with risk of disease. The top two loci implicate perturbed GABAergic signalling (KCTD8) and dysregulation of the ubiquitin proteosome system (TRIM22) in the pathogenesis of PiD. In the final chapter (Chapter 8) I investigate the genetic determinants of survival in PiD, by carrying out a Cox proportional hazards genome wide survival study (GWSS). I identify a genome-wide significant association with survival on chromosome 3, within the NLGN1 gene. which encodes a synaptic scaffolding protein located at the neuronal pre-synaptic membrane. Loss of synaptic integrity with resulting dysregulation of synaptic transmission leading to increased pathological tau accumulation is a plausible mechanism though which NLGN1 dysfunction could impact on survival in PiD
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