Biology subjects

Lovestone, S.

Publications and source records attributed to Lovestone, S..

9 recordsLinked to original sources

bioRxiv2023

iPSC-Astrocyte morphology reflects patient clinical markers

Human iPSCs provide powerful cellular models of Alzheimers disease (AD) and offer many advantages over non-human models, including the potential to reflect variation in individual-specific pathophysiology and clinical symptoms Previous studies have demonstrated that iPSC-neurons from individuals with Alzheimers disease (AD) reflect clinical markers, including {beta}-amyloid (A{beta}) levels and synaptic vulnerability. However, despite neuronal loss being a key hallmark of AD pathology, many risk genes are predominantly expressed in glia, highlighting them as potential therapeutic targets. In this work iPSC-derived astrocytes were generated from a cohort of individuals with high versus low levels of the inflammatory marker YKL-40, in their cerebrospinal fluid (CSF). iPSC-derived astrocytes were treated with exogenous A{beta} oligomers and high content imaging demonstrated a correlation between astrocytes that underwent the greatest morphology change from patients with low levels of CSF-YKL-40 and more protective APOE genotypes. This finding was subsequently verified using similarity learning as an unbiased approach. This study shows that iPSC-derived astrocytes from AD patients reflect key aspects of the pathophysiological phenotype of those same patients, thereby offering a novel means of modelling AD, stratifying AD patients and conducting therapeutic screens. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=93 SRC="FIGDIR/small/548687v1_ufig1.gif" ALT="Figure 1"> View larger version (24K): org.highwire.dtl.DTLVardef@1df3486org.highwire.dtl.DTLVardef@f184d8org.highwire.dtl.DTLVardef@48a33dorg.highwire.dtl.DTLVardef@d53a90_HPS_FORMAT_FIGEXP M_FIG C_FIG

neuroscience↗

bioRxiv2021

Neurons derived from individual early Alzheimer's disease patients reflect clinical vulnerability

Establishing preclinical models of Alzheimers disease that predict clinical outcomes remains a critically important, yet to date not fully realised, goal. Models derived from human cells offer considerable advantages over non-human models, including the potential to reflect some of the inter-individual differences that are apparent in patients. Here we report an approach using induced pluripotent stem cell-derived cortical neurons from people with early symptomatic Alzheimers disease where we sought a match between individual disease characteristics in cells with analogous characteristics in the people from whom they were derived. We show that the response to amyloid-{beta} burden in life, as measured by cognitive decline and brain activity levels, varies between individuals and this vulnerability rating correlates with the individual cellular vulnerability to extrinsic amyloid-{beta} in vitro as measured by synapse loss and function. Our findings indicate that patient induced pluripotent stem cell-derived cortical neurons not only present key aspects of Alzheimers disease pathology, but also reflect key aspects of the clinical phenotypes of the same patients. Cellular models that reflect an individuals in-life clinical vulnerability thus represent a tractable method of Alzheimers disease modelling using clinical data in combination with cellular phenotypes.

neuroscience↗

bioRxiv2020

Behavioural and transcriptomic characterization of the comorbidity between Alzheimer s disease and Major Depression

Major Depression (MD) is the most prevalent psychiatric disease in the population and is considered a prodromal stage of the Alzheimers disease (AD). Despite both diseases having a robust genetic component, the common transcriptomic signature remains unknown. In this regard, we investigated the cognitive and emotional responses in 3- and 6-month-old in APP/PSEN1-Tg mutant mice, before {beta}-amyloid plaques were detected. Then, we studied the deregulation of genes and pathways in prefrontal cortex, striatum, hippocampus and amygdala, using transcriptomic and functional data analysis. The results demonstrated that depressive-like and anxiety-like behaviours, as well as memory impairments are already present at 3-month-old together with the deregulation of several genes and gene sets, including components of the circadian rhythms, electronic transport chain and neurotransmission. Finally, DisGeNET GSEA provides translational support for common depregulated gene sets related to MD and AD. Altogether, the results demonstrate that MD could be an early manifestation of AD.

neuroscience↗

bioRxiv2020

TMEM106B and CPOX are genetic determinants of cerebrospinal fluid Alzheimer's disease biomarker levels

BackgroundNeurofilament light (NF-L), chitinase-3-like protein 1 (YKL-40), and neurogranin (Ng) are utilized as biomarkers for Alzheimers disease (AD), to monitor axonal damage, astroglial activation, and synaptic degeneration, respectively. Here we performed genome-wide association study (GWAS) analyses using all three biomarkers as outcome. MethodsDNA and cerebrospinal fluid (CSF) samples originated from the European Medical Information Framework AD Multimodal Biomarker Discovery (EMIF-AD MBD) study. Overlapping genotype/phenotype data were available for n=671 (NF-L), 677 (YKL-40), and 672 (Ng) individuals. GWAS analyses applied linear regression models adjusting for relevant covariates. FindingsWe identify novel genome-wide significant associations with markers in TMEM106B and CSF levels of NF-L. Additional novel signals were observed with DNA variants in CPOX and CSF levels of YKL-40. Lastly, we confirmed previous work suggesting that YKL-40 levels are regulated by cis protein quantitative trait loci (pQTL) in CHI3L1. InterpretationOur study provides important new insights into the genetic architecture underlying inter-individual variation in all three tested AD-related CSF biomarkers. In particular, our data shed light on the sequence of events regarding the initiation and progression of neuropathological processes relevant in AD.

genomics↗

bioRxiv2019

Data Resource Profile:The Dementias Platform UK (DPUK) Data Portal

The Dementias Platform UK (DPUK) Data Portal is a data repository facilitating access to data for 3 370 929 individuals in 42 cohorts. The Data Portal is an end-to-end data management solution providing a secure, fully auditable, remote access environment for the analysis of cohort data. All projects utilising the data are by default collaborations with the cohort research teams generating the data. The Data Portal uses UK Secure eResearch Platform (UKSeRP) infrastructure to provide three core utilities: data discovery, access, and analysis. These are delivered using a 7 layered architecture comprising: data ingestion, data curation, platform interoperability, data discovery, access brokerage, data analysis and knowledge preservation. Automated, streamlined, and standardised procedures reduce the administrative burden for all stakeholders, particularly for requests involving multiple independent datasets, where a single request may be forwarded to multiple data controllers. Researchers are provided with their own secure lab using VMware which is accessed using two factor authentication. Over the last 2 years, 160 project proposals involving 579 individual cohort data access requests were received. These were received from 268 applicants spanning 72 institutions (56 academic, 13 commercial, 3 government) in 16 countries with 84 requests involving multiple cohorts. Project are varied including multi-modal, machine learning, and Mendelian randomisation analyses. Data access is usually free at point of use although a small number of cohorts require a data access fee.

neuroscience↗

bioRxiv2019

Tau pathology in early Alzheimer’s disease disrupts selective neurophysiological networks dynamics

The role of aggregation of misfolded Tau protein in the pathogenesis of Alzheimers disease is the subject of rapid biomarker development and new therapeutic strategies to slow or prevent dementia. We tested the hypothesis that Tau pathology is associated with functional organization of widespread neurophysiological networks. We used electro-magnetoencephalography (E/MEG) in combination with [18F]AV1451 PET scanning to quantify Tau-dependent network disruption. Using a graph theoretical approach to MEG connectivity, we quantified nodal measures of functional segregation, centrality and efficiency of information transfer. We correlated these metrics against the nodes uptake of [18F]AV1451. There were both regional- and frequency-specific effects of Tau levels on the efficiency of information transfer and network segregation in early AD. Tau correlated with temporal regional participation coefficient (in delta, theta, beta bands); and temporal lobar eigenvector centrality (in theta, alpha, beta bands), but greater eccentricity at higher frequencies (gamma). The results support the translational development of neurophysiological "signatures" as biomarkers of Alzheimers disease, with potential to facilitate experimental medicines studies.

neuroscience↗

bioRxiv2018

Headache and type 2 diabetes association: a US national ambulatory case-control study.

ObjectiveWe investigate the joint observation between type 2 diabetes and headache using a case-control study of a US ambulatory dataset.\n\nBackgroundRecent whole-population cohort studies propose that type 2 diabetes may have a protective effect against headache prevalence. With headaches ranked as a leading cause of disability, headache-associated comorbidities could help identify shared molecular mechanisms.\n\nMethodsWe performed a case-control study using the US National Ambulatory Medical Care Survey, 2009, on the joint observation between headache and specific comorbidities, namely type 2 diabetes, hypertension and anxiety, for all patients between 18 and 65 years of age. The odds ratio of having a headache and a comorbidity were calculated using conditional logistic regression, controlling for gender and age over a study population of 3,327,947 electronic health records in the absence of prescription medication data.\n\nResultsWe observed estimated odds ratio of 0.89 (95% CI: 0.83-0.95) of having a headache and a record of type 2 diabetes over the population, and 0.83 (95% CI: 2.02-2.57) and 0.89 (95% CI: 3.00-3.49) for male and female, respectively.\n\nConclusionsWe find that patients with type 2 diabetes are less likely to present a recorded headache indication. Patients with hypertension are almost twice as likely of having a headache indication and patients with an anxiety disorder are almost three times as likely. Given the possibility of confounding indications and prescribed medications, additional studies are recommended.

epidemiology↗

bioRxiv2017

Genetic and real-world clinical data, combined with empirical validation, nominate JAK-STAT signalling as a target for Alzheimer’s Disease therapeutic development

As Genome Wide Association Studies (GWAS) have grown in size, the number of genetic variants that have been nominated for an increasing number of diseases has correspondingly increased. Despite this increase in the number of associated SNPs per disease, their biological interpretation has in many cases remained elusive. To address this, we have combined GWAS results with an orthogonal source of evidence, namely real-world, routinely collected clinical data from more than 6 million patients in order to drive target nomination. First we show that when examined at a pathway level, analysis of all GWAS studies groups Alzheimers disease (AD) in a cluster with disorders of immunity and inflammation. Using clinical data we show that the degree of comorbidity of these diseases with AD correlates with the strength of their genetic association with molecular participants in the JAK-STAT pathway. Using four independent open-science datasets we then find evidence for altered regulation of JAK-STAT pathway genes in AD. Finally, we use both in vitro and in vivo rodent models to demonstrate that A{beta} induces gene expression of key drivers of this pathway, providing experimental evidence validating these data-driven observations. These results therefore nominate JAK-STAT anomalies as a prominent aetiopathological event in AD and hence potential target for therapeutic development, and moreover demonstrate a de-novo multi-modal approach to derive information from rapidly increasing genomic datasets.\n\nOne Sentence SummaryCombining evidence from genome wide association studies, real-world clinical and cohort molecular data together with experimental studies in rodent model systems nominates JAK-STAT signaling as an aetiopathological event in Alzheimers disease

bioinformatics↗

bioRxiv2017

Cellular phenotyping of hippocampal progenitors exposed to patient serum predicts conversion to Alzheimer’s Disease

The generation of new neurons persists into adulthood in the human hippocampus and can be modulated by the circulatory systemic environment. Hippocampal neurogenesis is important for learning and memory and is altered in Alzheimers Disease (AD). Evaluating the hippocampal neurogenic process during disease progression could therefore identify neurogenesis as an important target for AD prevention and intervention as well as a biomarker for early disease detection. In this study, we used a human hippocampal progenitor cell line to design an in vitro assay evaluating over time the neurogenic impact of the systemic milieu (i.e. serum) of individuals with mild cognitive impairment (MCI) as they either converted to AD or remained cognitively stable. Cells were exposed to serum collected over several years from the same patients. Cellular phenotyping and linear mixed effects models for repeated measures revealed that decreased proliferation, increased apoptotic hippocampal progenitor cell death and increased hippocampal neurogenesis characterized progression from MCI to AD. Using stepwise logistic regression and machine learning we show that these cellular readouts for the baseline serum sample and years of education of the patient are significant predictors of conversion from MCI to AD, already 3.5 years before AD clinical diagnosis. Finally, serum proteomic analyses indicated pathways linked to the cellular readouts distinguishing MCI to AD converters from non-converters. The proposed assay is thus not only promising for AD pre-clinical diagnosis, but it also provides a proxy into temporal changes of the hippocampal neurogenic process during disease progression.\n\nOne Sentence SummaryIn this study, we demonstrate for the first time that the systemic environment (i.e. blood serum) of mild cognitively impaired patients differentially alters human hippocampal progenitor cell fate to predict conversion to Alzheimers Disease up to 3.5 years before clinical diagnosis.

neuroscience↗