3,689 research outputs found

    How real-world data can facilitate the development of precision medicine treatment in psychiatry

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    Precision medicine has the ambition to improve treatment response and clinical outcomes through patient stratification, and holds great potential in mental disorders. However, several important factors are needed to transform current practice into a ‚Äúprecision psychiatry‚ÄĚ framework. Most important are (1) the generation of accessible large real-world training and test data including genomic data integrated from multiple sources, (2) the development and validation of advanced analytical tools for stratification and prediction, and (3) the development of clinically useful management platforms for patient monitoring that can be integrated into healthcare systems in real-life settings. This narrative review summarizes strategies for obtaining the key elements ‚Äď well-powered samples from large biobanks, integrated with electronic health records and health registry data using novel artificial intelligence algorithms ‚Äď to predict outcomes in severe mental disorders and translate these models into clinical management and treatment approaches. Key elements are massive mental health data and novel artificial intelligence algorithms. For the clinical translation of these strategies, we discuss a precision medicine platform for improved management of mental disorders. We include use cases to illustrate how precision medicine interventions could be brought into psychiatry to improve the clinical outcomes of mental disorders

    Computational techniques to interpret the neural code underlying complex cognitive processes

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    Advances in large-scale neural recording technology have significantly improved the capacity to further elucidate the neural code underlying complex cognitive processes. This thesis aimed to investigate two research questions in rodent models. First, what is the role of the hippocampus in memory and specifically what is the underlying neural code that contributes to spatial memory and navigational decision-making. Second, how is social cognition represented in the medial prefrontal cortex at the level of individual neurons. To start, the thesis begins by investigating memory and social cognition in the context of healthy and diseased states that use non-invasive methods (i.e. fMRI and animal behavioural studies). The main body of the thesis then shifts to developing our fundamental understanding of the neural mechanisms underpinning these cognitive processes by applying computational techniques to ana lyse stable large-scale neural recordings. To achieve this, tailored calcium imaging and behaviour preprocessing computational pipelines were developed and optimised for use in social interaction and spatial navigation experimental analysis. In parallel, a review was conducted on methods for multivariate/neural population analysis. A comparison of multiple neural manifold learning (NML) algorithms identified that non linear algorithms such as UMAP are more adaptable across datasets of varying noise and behavioural complexity. Furthermore, the review visualises how NML can be applied to disease states in the brain and introduces the secondary analyses that can be used to enhance or characterise a neural manifold. Lastly, the preprocessing and analytical pipelines were combined to investigate the neural mechanisms in volved in social cognition and spatial memory. The social cognition study explored how neural firing in the medial Prefrontal cortex changed as a function of the social dominance paradigm, the "Tube Test". The univariate analysis identified an ensemble of behavioural-tuned neurons that fire preferentially during specific behaviours such as "pushing" or "retreating" for the animal’s own behaviour and/or the competitor’s behaviour. Furthermore, in dominant animals, the neural population exhibited greater average firing than that of subordinate animals. Next, to investigate spatial memory, a spatial recency task was used, where rats learnt to navigate towards one of three reward locations and then recall the rewarded location of the session. During the task, over 1000 neurons were recorded from the hippocampal CA1 region for five rats over multiple sessions. Multivariate analysis revealed that the sequence of neurons encoding an animal’s spatial position leading up to a rewarded location was also active in the decision period before the animal navigates to the rewarded location. The result posits that prospective replay of neural sequences in the hippocampal CA1 region could provide a mechanism by which decision-making is supported

    Burden of child mortality from malaria in high endemic areas: results from the CHAMPS Network using minimally invasive tissue sampling

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    Background Malaria is a leading cause of childhood mortality worldwide. However, accurate estimates of malaria prevalence and causality among patients who die at the country level are lacking due to the limited specificity of diagnostic tools used to attribute etiologies. Accurate estimates are crucial for prioritizing interventions and resources aimed at reducing malaria-related mortality. Methods Seven Child Health and Mortality Prevention Surveillance (CHAMPS) Network sites collected comprehensive data on stillbirths and children <5 years, using minimally invasive tissue sampling (MITS). A DeCoDe (Determination of Cause of Death) panel employed standardized protocols for assigning underlying, intermediate, and immediate causes of death, integrating sociodemographic, clinical, laboratory (including extensive microbiology, histopathology, and malaria testing), and verbal autopsy data. Analyses were conducted to ascertain the strength of evidence for cause of death (CoD), describe factors associated with malaria-related deaths, estimate malaria-specific mortality, and assess the proportion of preventable deaths. Findings Between December 3, 2016, and December 31, 2022, 2673 deaths underwent MITS and had a CoD attributed from four CHAMPS sites with at least 1 malaria-attributed death. No malaria-attributable deaths were documented among 891 stillbirths or 924 neonatal deaths, therefore this analysis concentrates on the remaining 858 deaths among children aged 1-59 months. Malaria was in the causal chain for 42.9% (126/294) of deaths from Sierra Leone, 31.4% (96/306) in Kenya, 18.2% (36/198) in Mozambique, 6.7% (4/60) in Mali, and 0.3% (1/292) in South Africa. Compared to non-malaria related deaths, malaria-related deaths skewed towards older infants and children (p<0.001), with 71.0% among ages 12-59 months. Malaria was the sole infecting pathogen in 184 (70.2%) of malaria-attributed deaths, whereas bacterial and viral co-infections were identified in the causal pathway in 24·0% and 12.2% of cases, respectively. Malnutrition was found at a similar level in the causal pathway of both malaria (26.7%) and non-malaria (30.7%, p=0.256) deaths. Less than two-thirds (164/262; 62.6%) of malaria deaths had received antimalarials prior to death. Nearly all (98·9%) malaria-related deaths were deemed preventable. Interpretation Malaria remains a significant cause of childhood mortality in the CHAMPS malaria-endemic sites. The high bacterial co-infection prevalence among malaria deaths underscores the potential benefits of antibiotics for severe malaria patients. Compared to non-malaria deaths, many of malaria-attributed deaths are preventable through accessible malaria control measures. Funding This work was supported by the Bill & Melinda Gates Foundation [OPP1126780]

    Penetrance and expressivity of mitochondrial variants in a large clinically unselected population

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    This is the final version. Available on open access from Oxford University Press via the DOI in this recordData availability: The data supporting the findings of this study are available within the article and its Supplementary Data files. Additional information for reproducing the results described in the article is available upon reasonable request and subject to a data use agreement. The UK Biobank dataset is available from https://biobank.ctsu.ox.ac.ukBACKGROUND: Whole genome sequencing (WGS) from large clinically unselected cohorts provides a unique opportunity to assess the penetrance and expressivity of rare and/or known pathogenic mitochondrial variants in population. METHOD: Using WGS from 179‚ÄČ862 clinically unselected individuals from the UK Biobank, we performed extensive single and rare variant aggregation association analyses of 15‚ÄČ881 mtDNA variants and 73 known pathogenic variants with 15 mitochondrial disease-relevant phenotypes. RESULTS: We identified 12 homoplasmic and one heteroplasmic variant (m.3243A>G) with genome-wide significant associations in our clinically unselected cohort. Heteroplasmic m.3243A>G (MAF‚ÄČ=‚ÄČ0.0002, a known pathogenic variant) was associated with diabetes, deafness and heart failure and 12 homoplasmic variants increased aspartate aminotransferase levels including three low-frequency variants (MAF ~0.002 and beta~0.3 SD). Most pathogenic mitochondrial disease variants (n‚ÄČ=‚ÄČ66/74) were rare in the population (G. Multi-system disease risk and penetrance of diabetes, deafness and heart failure greatly increased with m.3243A>G level ‚Č•‚ÄČ10%. The odds ratio of these traits increased from 5.61, 12.3 and 10.1 to 25.1, 55.0 and 39.5 respectively. Diabetes risk with m.3243A>G was further influenced by type 2 diabetes genetic risk. CONCLUSION: Our study of mitochondrial variation in a large-unselected population identified novel associations and demonstrated that pathogenic mitochondrial variants have lower penetrance in clinically unselected settings. m.3243A>G was an exception at higher heteroplasmy showing a significant impact on health making it a good candidate for incidental reporting.Diabetes UKMedical Research Council (MRC)Wellcome TrustNational Institute for Health and Care Research (NIHR

    Multidisciplinary perspectives on Artificial Intelligence and the law

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    This open access book presents an interdisciplinary, multi-authored, edited collection of chapters on Artificial Intelligence (‚ÄėAI‚Äô) and the Law. AI technology has come to play a central role in the modern data economy. Through a combination of increased computing power, the growing availability of data and the advancement of algorithms, AI has now become an umbrella term for some of the most transformational technological breakthroughs of this age. The importance of AI stems from both the opportunities that it offers and the challenges that it entails. While AI applications hold the promise of economic growth and efficiency gains, they also create significant risks and uncertainty. The potential and perils of AI have thus come to dominate modern discussions of technology and ethics ‚Äď and although AI was initially allowed to largely develop without guidelines or rules, few would deny that the law is set to play a fundamental role in shaping the future of AI. As the debate over AI is far from over, the need for rigorous analysis has never been greater. This book thus brings together contributors from different fields and backgrounds to explore how the law might provide answers to some of the most pressing questions raised by AI. An outcome of the Cat√≥lica Research Centre for the Future of Law and its interdisciplinary working group on Law and Artificial Intelligence, it includes contributions by leading scholars in the fields of technology, ethics and the law.info:eu-repo/semantics/publishedVersio

    Information about cancer on the internet : comparative analysis of the institutional website of AECC, GEPAC and FEFOC

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    La b√ļsqueda de informaci√≥n sobre salud en internet est√° asociada fundamentalmente al diagn√≥stico de una enfermedad del usuario o de un familiar y puede considerarse la primera fuente a la que acuden tras una consulta m√©dica (Mar√≠n-Torres et al., isanidad.com, 2015; 2012; III Bar√≥metro PIC, 2019; INE, 2019;). Las principales barreras para el acceso y uso de la eSalud (eHealth en su terminolog√≠a inglesa) tienen que ver con la legibilidad del contenido y con una pobre usabilidad de los sitios (Cline y Haynes, 2001; Kim y Xie, 2017). A esto se suma en el contexto actual el enorme volumen de datos disponible en la red que hace imprescindible desarrollar protocolos de an√°lisis que permitan a los usuarios identificar de un modo comprensible los sitios que ofrecen informaci√≥n de calidad tanto en sus contenidos como en su presentaci√≥n. Esta investigaci√≥n plantea un an√°lisis de las p√°ginas web corporativas de tres instituciones espa√Īolas de reconocido prestigio ‚ÄĒy naturaleza diversa‚ÄĒ en el √°mbito de la divulgaci√≥n y prevenci√≥n del c√°ncer: la Asociaci√≥n Espa√Īola Contra el C√°ncer, el Grupo Espa√Īol de Pacientes con C√°ncer y la Fundaci√≥n para la Educaci√≥n P√ļblica y la Formaci√≥n en C√°ncer; abordando tanto la usabilidad como el tipo de informaci√≥n ofrecida, con el objetivo de conocer el estado de la informaci√≥n en la red sobre el c√°ncer en Espa√Īa y de identificar buenas pr√°cticas en la comunicaci√≥n sobre la enfermedad.The search for health information on the Internet is fundamentally associated with the diagnosis of a disease of the user or a relative and it can be considered the first source to which they come after a medical consultation(Mar√≠n-Torres et al., isanidad.com, 2015; 2012; III Bar√≥metro PIC, 2019; INE, 2019;).The main barriers to the access and use of eHealth have to do with the readability of the content and with a poor usability of the sites (Cline and Haynes, 2001; Kim and Xie, 2017). Added to this, the enormous volume of data available on the network in the current context is what makes it essential to develop analysis protocols that allow users to identify in a comprehensible way the sites that offer quality information both in their content and in their presentation.This research proposes an analysis of the corporate sites of three Spanish institutions of recognized prestige -and diverse nature- in the field of cancer promotion and prevention: Asociaci√≥n Espa√Īola Contra el C√°ncer, Grupo Espa√Īol de Pacientes con C√°ncer and Fundaci√≥n para la Educaci√≥n P√ļblica y la Formaci√≥n en C√°ncer; addressing both the usability and the type of information offered, in order to know the status of online information on cancer in Spain and to identify good practices in comvbmunication about the disease

    Multi-trait analysis characterizes the genetics of thyroid function and identifies causal associations with clinical implications

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    To date only a fraction of the genetic footprint of thyroid function has been clarified. We report a genome-wide association study meta-analysis of thyroid function in up to 271,040 individuals of European ancestry, including reference range thyrotropin (TSH), free thyroxine (FT4), free and total triiodothyronine (T3), proxies for metabolism (T3/FT4 ratio) as well as dichotomized high and low TSH levels. We revealed 259 independent significant associations for TSH (61% novel), 85 for FT4 (67% novel), and 62 novel signals for the T3 related traits. The loci explained 14.1%, 6.0%, 9.5% and 1.1% of the total variation in TSH, FT4, total T3 and free T3 concentrations, respectively. Genetic correlations indicate that TSH associated loci reflect the thyroid function determined by free T3, whereas the FT4 associations represent the thyroid hormone metabolism. Polygenic risk score and Mendelian randomization analyses showed the effects of genetically determined variation in thyroid function on various clinical outcomes, including cardiovascular risk factors and diseases, autoimmune diseases, and cancer. In conclusion, our results improve the understanding of thyroid hormone physiology and highlight the pleiotropic effects of thyroid function on various diseases

    Weak-Instrument and Pleiotropy-Robust Methods for Mendelian randomisation, with Applications to Mental Health

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    This PhD dissertation focused on developing and applying new methods for Mendelian Randomisation (MR), a technique that uses genetic variants as instrumental variables in order to assess causal effects of exposures on health outcomes. The major focus of the applied research is psychiatric research and mental health, with a range of analyses that address the topic of causal risk factors for depression with the use of these genetics-informed methods. The first contribution of this dissertation is the development of new methods for pleiotropy-robust MR by leveraging sex specificity of phenotypes. These methods allow for more accurate and robust estimation of causal effects by cancelling out potential pleiotropic effects of genetic instruments. The second contribution is a new method for appraising high-dimensional correlated variables in multivariable MR. This method allows for the inclusion of multiple correlated variables as exposures in MR analyses, through a transformation to groups of exposures that have attractive statistical properties and biological meaning. Finally, the dissertation provides an applied analysis of how inflammation and BMI affect a range of depression phenotypes with cutting-edge methods. This analysis replicates previous results on the harmful effects of overweight on mood and challenges the independent effect of inflammation as proxied by CRP. The introduction of the dissertation is divided into two parts. The first part provides a walkthrough of the epidemiological concepts of bias, randomisation, and causal inference with observational data. The second part is a specific introduction to MR, including its underlying assumptions and limitations, as well as detailed discussion of developments that make it more robust. Overall, this dissertation contributes new methods and applied analyses to the field of MR, with potential implications for researchers and practitioners

    Tau pathology in Alzheimer's disease and other dementias : translational approach from in vitro autoradiography to in vivo PET imaging

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    Tauopathies, including Alzheimer's disease (AD), corticobasal degeneration (CBD), and progressive supranuclear palsy (PSP), are complex neurodegenerative disorders characterized by the pathological accumulation of tau proteins in the brain. These often overlapping disorders, with intricate pathologies and growing prevalence, lack definitive treatments, highlighting the necessity for advanced research. Positron emission tomography (PET) imaging aids in the diagnosis and monitoring of diseases, by providing in vivo insights into pathological features. This thesis focused on deciphering the binding properties and brain regional distribution of PET tracers for accurate disease differentiation. Spanning four studies, we aimed to bridge in vitro and in vivo PET data to investigate tau pathology and its association with dementia-related markers such as reactive astrogliosis, peripheral inflammation, and dopaminergic dysfunction. The 2nd generation tau PET tracers, 3H-MK6240 and 3H-PI2620, demonstrated high affinity and specificity in AD post-mortem brain tissues, especially in early-onset AD, compared to controls. 3H-PI2620, 3H-MK6240, and 3HRO948 displayed similar binding patterns in AD tissue, with multiple binding sites and equivalent high affinities (Papers I and II). 3H-PI2620 showed specificity in CBD and PSP tissues, in contrast to 3H-MK6240. However, differentiating CBD from PSP brains with 3H-PI2620 remained challenging in multiple brain regions, potentially due to complex tracer-target interactions (Papers II and III). Reactive astrogliosis PET tracers 3H-Deprenyl and 3H-BU99008 bound primarily to stable distinct high-affinity binding sites in AD, CBD and PSP, but also to transient binding sites, differing by brain region and condition. This pattern implied that these tracers may interact with similar or diverse subtypes or populations of astrocytes, expressing varying ratios of transient sites, which may vary depending on the brain location and the disease (Paper III). Using 3H-FEPE2I, we delineated a reduction in dopamine transporter (DAT) levels within the putamen across CBD, PSP and Parkinson's Disease (PD) brains. Concomitantly, elevated 3H-Raclopride binding reflected higher dopamine D2 receptor (D2R) levels in PSP and PD. Nonetheless, our observations underscored the heterogeneity inherent to these neurodegenerative pathologies, emphasizing the criticality of individual variability in neuropathological manifestations (Paper III). Lastly, we investigated late middle-aged cognitively unimpaired Hispanic individuals, in dichotomous groups of in vivo amyloid-ő≤ (Aő≤) PET (18F-Florbetaben) and plasma neurofilament light (NfL) biomarkers. Our findings suggest that elevated plasma inflammation and tau burden as measured by 18FMK6240, can be detected at early preclinical stages of AD, offering potential for early diagnosis (Paper IV). This thesis underscored the importance of PET imaging in advancing our understanding of tauopathies. The innovative use of multiple PET tracers provided crucial insights into their potential use in clinics to distinguish pathological features of AD, CBD and PSP. The findings emphasized the need for more studies applying a multifaceted approach to studying and managing these complex neurodegenerative disorders, combining advanced imaging techniques with a broad spectrum of biological markers
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