DNA methylation analysis identifies key transcription factors involved in mesenchymal stem cell osteogenic differentiation.

BACKGROUND: Knowledge about regulating transcription factors (TFs) for osteoblastogenesis from mesenchymal stem cells (MSCs) is limited. Therefore, we investigated the relationship between genomic regions subject to DNA-methylation changes during osteoblastogenesis and the TFs known to directly interact with these regulatory regions. RESULTS: The genome-wide DNA-methylation signature of MSCs differentiated to osteoblasts and adipocytes was determined using the Illumina HumanMethylation450 BeadChip array. During adipogenesis no CpGs passed our test for significant methylation changes. Oppositely, during osteoblastogenesis we identified 2462 differently significantly methylated CpGs (adj. p < 0.05). These resided outside of CpGs islands and were significantly enriched in enhancer regions. We confirmed the correlation between DNA-methylation and gene expression. Accordingly, we developed a bioinformatic tool to analyse differentially methylated regions and the TFs interacting with them. By overlaying our osteoblastogenesis differentially methylated regions with ENCODE TF ChIP-seq data we obtained a set of candidate TFs associated to DNA-methylation changes. Among them, ZEB1 TF was highly related with DNA-methylation. Using RNA interference, we confirmed that ZEB1, and ZEB2, played a key role in adipogenesis and osteoblastogenesis processes. For clinical relevance, ZEB1 mRNA expression in human bone samples was evaluated. This expression positively correlated with weight, body mass index, and PPARγ expression. CONCLUSIONS: In this work we describe an osteoblastogenesis-associated DNA-methylation profile and, using these data, validate a novel computational tool to identify key TFs associated to age-related disease processes. By means of this tool we identified and confirmed ZEB TFs as mediators involved in the MSCs differentiation to osteoblasts and adipocytes, and obesity-related bone adiposity.

DNA methylation analysis identifies key transcription factors involved in mesenchymal stem cell osteogenic differentiation

BACKGROUND: Knowledge about regulating transcription factors (TFs) for osteoblastogenesis from mesenchymal stem cells (MSCs) is limited. Therefore, we investigated the relationship between genomic regions subject to DNA-methylation changes during osteoblastogenesis and the TFs known to directly interact with these regulatory regions. RESULTS: The genome-wide DNA-methylation signature of MSCs differentiated to osteoblasts and adipocytes was determined using the Illumina HumanMethylation450 BeadChip array. During adipogenesis no CpGs passed our test for significant methylation changes. Oppositely, during osteoblastogenesis we identified 2462 differently significantly methylated CpGs (adj. p < 0.05). These resided outside of CpGs islands and were significantly enriched in enhancer regions. We confirmed the correlation between DNA-methylation and gene expression. Accordingly, we developed a bioinformatic tool to analyse differentially methylated regions and the TFs interacting with them. By overlaying our osteoblastogenesis differentially methylated regions with ENCODE TF ChIP-seq data we obtained a set of candidate TFs associated to DNA-methylation changes. Among them, ZEB1 TF was highly related with DNA-methylation. Using RNA interference, we confirmed that ZEB1, and ZEB2, played a key role in adipogenesis and osteoblastogenesis processes. For clinical relevance, ZEB1 mRNA expression in human bone samples was evaluated. This expression positively correlated with weight, body mass index, and PPARγ expression. CONCLUSIONS: In this work we describe an osteoblastogenesis-associated DNA-methylation profile and, using these data, validate a novel computational tool to identify key TFs associated to age-related disease processes. By means of this tool we identified and confirmed ZEB TFs as mediators involved in the MSCs differentiation to osteoblasts and adipocytes, and obesity-related bone adiposity.

SBML Level 3: an extensible format for the exchange and reuse of biological models.

Systems biology has experienced dramatic growth in the number, size, and complexity of computational models. To reproduce simulation results and reuse models, researchers must exchange unambiguous model descriptions. We review the latest edition of the Systems Biology Markup Language (SBML), a format designed for this purpose. A community of modelers and software authors developed SBML Level 3 over the past decade. Its modular form consists of a core suited to representing reaction-based models and packages that extend the core with features suited to other model types including constraint-based models, reaction-diffusion models, logical network models, and rule-based models. The format leverages two decades of SBML and a rich software ecosystem that transformed how systems biologists build and interact with models. More recently, the rise of multiscale models of whole cells and organs, and new data sources such as single-cell measurements and live imaging, has precipitated new ways of integrating data with models. We provide our perspectives on the challenges presented by these developments and how SBML Level 3 provides the foundation needed to support this evolution.

Histone ChIP-Seq identifies differential enhancer usage during chondrogenesis as critical for defining cell-type specificity.

Epigenetic mechanisms are known to regulate gene expression during chondrogenesis. In this study, we have characterized the epigenome during the in vitro differentiation of human mesenchymal stem cells (hMSCs) into chondrocytes. Chromatin immunoprecipitation followed by next-generation sequencing (ChIP-seq) was used to assess a range of N-terminal posttranscriptional modifications (marks) to histone H3 lysines (H3K4me3, H3K4me1, H3K27ac, H3K27me3, and H3K36me3) in both hMSCs and differentiated chondrocytes. Chromatin states were characterized using histone ChIP-seq and cis-regulatory elements were identified in chondrocytes. Chondrocyte enhancers were associated with chondrogenesis-related gene ontology (GO) terms. In silico analysis and integration of DNA methylation data with chondrogenesis chromatin states revealed that enhancers marked by histone marks H3K4me1 and H3K27ac were de-methylated during in vitro chondrogenesis. Similarity analysis between hMSC and chondrocyte chromatin states defined in this study with epigenomes of cell-types defined by the Roadmap Epigenomics project revealed that enhancers are more distinct between cell-types compared to other chromatin states. Motif analysis revealed that the transcription factor SOX9 is enriched in chondrocyte enhancers. Luciferase reporter assays confirmed that chondrocyte enhancers characterized in this study exhibited enhancer activity which may be modulated by DNA methylation and SOX9 overexpression. Altogether, these integrated data illustrate the cross-talk between different epigenetic mechanisms during chondrocyte differentiation.

Length-independent telomere damage drives post-mitotic cardiomyocyte senescence.

Ageing is the biggest risk factor for cardiovascular disease. Cellular senescence, a process driven in part by telomere shortening, has been implicated in age-related tissue dysfunction. Here, we address the question of how senescence is induced in rarely dividing/post-mitotic cardiomyocytes and investigate whether clearance of senescent cells attenuates age-related cardiac dysfunction. During ageing, human and murine cardiomyocytes acquire a senescent-like phenotype characterised by persistent DNA damage at telomere regions that can be driven by mitochondrial dysfunction and crucially can occur independently of cell division and telomere length. Length-independent telomere damage in cardiomyocytes activates the classical senescence-inducing pathways, p21CIP and p16INK4a, and results in a non-canonical senescence-associated secretory phenotype, which is pro-fibrotic and pro-hypertrophic. Pharmacological or genetic clearance of senescent cells in mice alleviates detrimental features of cardiac ageing, including myocardial hypertrophy and fibrosis. Our data describe a mechanism by which senescence can occur and contribute to age-related myocardial dysfunction and in the wider setting to ageing in post-mitotic tissues.

Systems biology reveals how altered TGFß signalling with age reduces protection against pro-inflammatory stimuli.

Osteoarthritis (OA) is a degenerative condition caused by dysregulation of multiple molecular signalling pathways. Such dysregulation results in damage to cartilage, a smooth and protective tissue that enables low friction articulation of synovial joints. Matrix metalloproteinases (MMPs), especially MMP-13, are key enzymes in the cleavage of type II collagen which is a vital component for cartilage integrity. Transforming growth factor beta (TGFß) can protect against pro-inflammatory cytokine-mediated MMP expression. With age there is a change in the ratio of two TGFß type I receptors (Alk1/Alk5), a shift that results in TGFß losing its protective role in cartilage homeostasis. Instead, TGFß promotes cartilage degradation which correlates with the spontaneous development of OA in murine models. However, the mechanism by which TGFß protects against pro-inflammatory responses and how this changes with age has not been extensively studied. As TGFß signalling is complex, we used systems biology to combine experimental and computational outputs to examine how the system changes with age. Experiments showed that the repressive effect of TGFß on chondrocytes treated with a pro-inflammatory stimulus required Alk5. Computational modelling revealed two independent mechanisms were needed to explain the crosstalk between TGFß and pro-inflammatory signalling pathways. A novel meta-analysis of microarray data from OA patient tissue was used to create a Cytoscape network representative of human OA and revealed the importance of inflammation. Combining the modelled genes with the microarray network provided a global overview into the crosstalk between the different signalling pathways involved in OA development. Our results provide further insights into the mechanisms that cause TGFß signalling to change from a protective to a detrimental pathway in cartilage with ageing. Moreover, such a systems biology approach may enable restoration of the protective role of TGFß as a potential therapy to prevent age-related loss of cartilage and the development of OA.

Modelling the role of redox-related mechanisms in musculoskeletal ageing.

The decline in the musculoskeletal system with age is driven at the cellular level by random molecular damage. Cells possess mechanisms to repair or remove damage and many of the pathways involved in this response are regulated by redox signals. However, with ageing there is an increase in oxidative stress which can lead to chronic inflammation and disruption of redox signalling pathways. The complexity of the processes involved has led to the use of computational modelling to help increase our understanding of the system, test hypotheses and make testable predictions. This paper will give a brief background of the biological systems that have been modelled, an introduction to computational modelling, a review of models that involve redox-related mechanisms that are applicable to musculoskeletal ageing, and finally a discussion of the future potential for modelling in this field.

PyCoTools: a Python toolbox for COPASI.

Motivation: COPASI is an open source software package for constructing, simulating and analyzing dynamic models of biochemical networks. COPASI is primarily intended to be used with a graphical user interface but often it is desirable to be able to access COPASI features programmatically, with a high level interface. Results: PyCoTools is a Python package aimed at providing a high level interface to COPASI tasks with an emphasis on model calibration. PyCoTools enables the construction of COPASI models and the execution of a subset of COPASI tasks including time courses, parameter scans and parameter estimations. Additional 'composite' tasks which use COPASI tasks as building blocks are available for increasing parameter estimation throughput, performing identifiability analysis and performing model selection. PyCoTools supports exploratory data analysis on parameter estimation data to assist with troubleshooting model calibrations. We demonstrate PyCoTools by posing a model selection problem designed to show case PyCoTools within a realistic scenario. The aim of the model selection problem is to test the feasibility of three alternative hypotheses in explaining experimental data derived from neonatal dermal fibroblasts in response to TGF-ß over time. PyCoTools is used to critically analyze the parameter estimations and propose strategies for model improvement. Availability and implementation: PyCoTools can be downloaded from the Python Package Index (PyPI) using the command 'pip install pycotools' or directly from GitHub (https://github.com/CiaranWelsh/pycotools). Documentation at http://pycotools.readthedocs.io. Supplementary information: Supplementary data are available at Bioinformatics online.

'Molecular habituation' as a potential mechanism of gradual homeostatic loss with age.

The ability of reactive oxygen species (ROS) to cause molecular damage has meant that chronic oxidative stress has been mostly studied from the point of view of being a source of toxicity to the cell. However, the known duality of ROS molecules as both damaging agents and cellular redox signals implies another perspective in the study of sustained oxidative stress. This is a perspective of studying oxidative stress as a constitutive signal within the cell. In this work, we adopt a theoretical perspective as an exploratory and explanatory approach to examine how chronic oxidative stress can interfere with signal processing by redox signalling pathways in the cell. We report that constitutive signals can give rise to a 'molecular habituation' effect that can prime for a gradual loss of biological function. This is because a constitutive signal in the environment has the potential to reduce the responsiveness of a signalling pathway through the prolonged activation of negative regulators. Additionally, we demonstrate how this phenomenon is likely to occur in different signalling pathways exposed to persistent signals and furthermore at different levels of biological organisation.

Cross platform analysis of transcriptomic data identifies ageing has distinct and opposite effects on tendon in males and females.

The development of tendinopathy is influenced by a variety of factors including age, gender, sex hormones and diabetes status. Cross platform comparative analysis of transcriptomic data elucidated the connections between these entities in the context of ageing. Tissue-engineered tendons differentiated from bone marrow derived mesenchymal stem cells from young (20-24 years) and old (54-70 years) donors were assayed using ribonucleic acid sequencing (RNA-seq). Extension of the experiment to microarray and RNA-seq data from tendon identified gender specific gene expression changes highlighting disparity with existing literature and published pathways. Separation of RNA-seq data by sex revealed underlying negative binomial distributions which increased statistical power. Sex specific de novo transcriptome assemblies generated fewer larger transcripts that contained miRNAs, lincRNAs and snoRNAs. The results identify that in old males decreased expression of CRABP2 leads to cell proliferation, whereas in old females it leads to cellular senescence. In conjunction with existing literature the results explain gender disparity in the development and types of degenerative diseases as well as highlighting a wide range of considerations for the analysis of transcriptomic data. Wider implications are that degenerative diseases may need to be treated differently in males and females because alternative mechanisms may be involved.

Computer simulation models as a tool to investigate the role of microRNAs in osteoarthritis.

The aim of this study was to show how computational models can be used to increase our understanding of the role of microRNAs in osteoarthritis (OA) using miR-140 as an example. Bioinformatics analysis and experimental results from the literature were used to create and calibrate models of gene regulatory networks in OA involving miR-140 along with key regulators such as NF-κB, SMAD3, and RUNX2. The individual models were created with the modelling standard, Systems Biology Markup Language, and integrated to examine the overall effect of miR-140 on cartilage homeostasis. Down-regulation of miR-140 may have either detrimental or protective effects for cartilage, indicating that the role of miR-140 is complex. Studies of individual networks in isolation may therefore lead to different conclusions. This indicated the need to combine the five chosen individual networks involving miR-140 into an integrated model. This model suggests that the overall effect of miR-140 is to change the response to an IL-1 stimulus from a prolonged increase in matrix degrading enzymes to a pulse-like response so that cartilage degradation is temporary. Our current model can easily be modified and extended as more experimental data become available about the role of miR-140 in OA. In addition, networks of other microRNAs that are important in OA could be incorporated. A fully integrated model could not only aid our understanding of the mechanisms of microRNAs in ageing cartilage but could also provide a useful tool to investigate the effect of potential interventions to prevent cartilage loss.

Using computer simulation models to investigate the most promising microRNAs to improve muscle regeneration during ageing.

MicroRNAs (miRNAs) regulate gene expression through interactions with target sites within mRNAs, leading to enhanced degradation of the mRNA or inhibition of translation. Skeletal muscle expresses many different miRNAs with important roles in adulthood myogenesis (regeneration) and myofibre hypertrophy and atrophy, processes associated with muscle ageing. However, the large number of miRNAs and their targets mean that a complex network of pathways exists, making it difficult to predict the effect of selected miRNAs on age-related muscle wasting. Computational modelling has the potential to aid this process as it is possible to combine models of individual miRNA:target interactions to form an integrated network. As yet, no models of these interactions in muscle exist. We created the first model of miRNA:target interactions in myogenesis based on experimental evidence of individual miRNAs which were next validated and used to make testable predictions. Our model confirms that miRNAs regulate key interactions during myogenesis and can act by promoting the switch between quiescent/proliferating/differentiating myoblasts and by maintaining the differentiation process. We propose that a threshold level of miR-1 acts in the initial switch to differentiation, with miR-181 keeping the switch on and miR-378 maintaining the differentiation and miR-143 inhibiting myogenesis.

Systems approaches in osteoarthritis: Identifying routes to novel diagnostic and therapeutic strategies.

Systems orientated research offers the possibility of identifying novel therapeutic targets and relevant diagnostic markers for complex diseases such as osteoarthritis. This review demonstrates that the osteoarthritis research community has been slow to incorporate systems orientated approaches into research studies, although a number of key studies reveal novel insights into the regulatory mechanisms that contribute both to joint tissue homeostasis and its dysfunction. The review introduces both top-down and bottom-up approaches employed in the study of osteoarthritis. A holistic and multiscale approach, where clinical measurements may predict dysregulation and progression of joint degeneration, should be a key objective in future research. The review concludes with suggestions for further research and emerging trends not least of which is the coupled development of diagnostic tests and therapeutics as part of a concerted effort by the osteoarthritis research community to meet clinical needs. © 2017 The Authors. Journal of Orthopaedic Research Published by Wiley Periodicals, Inc. on behalf of Orthopaedic Research Society. J Orthop Res 35:1573-1588, 2017.

Modelling the molecular mechanisms of aging.

The aging process is driven at the cellular level by random molecular damage that slowly accumulates with age. Although cells possess mechanisms to repair or remove damage, they are not 100% efficient and their efficiency declines with age. There are many molecular mechanisms involved and exogenous factors such as stress also contribute to the aging process. The complexity of the aging process has stimulated the use of computational modelling in order to increase our understanding of the system, test hypotheses and make testable predictions. As many different mechanisms are involved, a wide range of models have been developed. This paper gives an overview of the types of models that have been developed, the range of tools used, modelling standards and discusses many specific examples of models that have been grouped according to the main mechanisms that they address. We conclude by discussing the opportunities and challenges for future modelling in this field.

A proteomic analysis of chondrogenic, osteogenic and tenogenic constructs from ageing mesenchymal stem cells.

BACKGROUND: Mesenchymal stem cells (MSCs) have prospective applications in regenerative medicine and tissue engineering but to what extent phenotype and differentiation capacity alter with ageing is uncertain. Consequently, any loss in functionality with age would have profound consequences for the maintenance of tissue viability and the quality of tissues. Proteomics enables the set of proteins responsible for a particular cell phenotype to be identified, as well as enabling insights into mechanisms responsible for age-related alterations in musculoskeletal tissues. Few proteomic studies have been undertaken regarding age-related effects on tissue engineered into cartilage and bone, and none for tendon. This study provides a proteome inventory for chondrogenic, osteogenic and tenogenic constructs synthesised from human MSCs, and elucidates proteomic alterations as a consequence of donor age. METHODS: Human bone-marrow derived MSCs from young (n = 4, 21.8 years ± 2.4SD) and old (n = 4, 65.5 years ± 8.3SD) donors were used to make chondrogenic, osteogenic and tenogenic tissue-engineered constructs. We utilised an analytical method relying on extracted peptide intensities as a label-free approach for peptide quantitation by liquid chromatography-mass spectrometry. Results were validated using western blotting. RESULTS: We identified proteins that were differentially expressed with ageing; 128 proteins in chondrogenic constructs, 207 in tenogenic constructs and four in osteogenic constructs. Differentially regulated proteins were subjected to bioinformatic analysis to ascertain their molecular functions and the signalling pathways. For all construct types, age-affected proteins were involved in altered cell survival and death, and antioxidant and cytoskeletal changes. Energy and protein metabolism were the principle pathways affected in tenogenic constructs, whereas lipid metabolism was strongly affected in chondrogenic constructs and mitochondrial dysfunction in osteogenic constructs. CONCLUSIONS: Our results imply that further work on MSC-based therapeutics for the older population needs to focus on oxidative stress protection. The differentially regulated proteome characterised by this study can potentially guide translational research specifically aimed at effective clinical interventions.

Decoding the Regulatory Landscape of Ageing in Musculoskeletal Engineered Tissues Using Genome-Wide DNA Methylation and RNASeq.

Mesenchymal stem cells (MSC) are capable of multipotent differentiation into connective tissues and as such are an attractive source for autologous cell-based regenerative medicine and tissue engineering. Epigenetic mechanisms, like DNA methylation, contribute to the changes in gene expression in ageing. However there was a lack of sufficient knowledge of the role that differential methylation plays during chondrogenic, osteogenic and tenogenic differentiation from ageing MSCs. This study undertook genome level determination of the effects of DNA methylation on expression in engineered tissues from chronologically aged MSCs. We compiled unique DNA methylation signatures from chondrogenic, osteogenic, and tenogenic engineered tissues derived from young; n = 4 (21.8 years ± 2.4 SD) and old; n = 4 (65.5 years±8.3SD) human MSCs donors using the Illumina HumanMethylation 450 Beadchip arrays and compared these to gene expression by RNA sequencing. Unique and common signatures of global DNA methylation were identified. There were 201, 67 and 32 chondrogenic, osteogenic and tenogenic age-related DE protein-coding genes respectively. Findings inferred the nature of the transcript networks was predominantly for 'cell death and survival', 'cell morphology', and 'cell growth and proliferation'. Further studies are required to validate if this gene expression effect translates to cell events. Alternative splicing (AS) was dysregulated in ageing with 119, 21 and 9 differential splicing events identified in chondrogenic, osteogenic and tenogenic respectively, and enrichment in genes associated principally with metabolic processes. Gene ontology analysis of differentially methylated loci indicated age-related enrichment for all engineered tissue types in 'skeletal system morphogenesis', 'regulation of cell proliferation' and 'regulation of transcription' suggesting that dynamic epigenetic modifications may occur in genes associated with shared and distinct pathways dependent upon engineered tissue type. An altered phenotype in engineered tissues was observed with ageing at numerous levels. These changes represent novel insights into the ageing process, with implications for stem cell therapies in older patients. In addition we have identified a number of tissue-dependant pathways, which warrant further studies.

Simulated Interventions to Ameliorate Age-Related Bone Loss Indicate the Importance of Timing.

Bone remodeling is the continuous process of bone resorption by osteoclasts and bone formation by osteoblasts, in order to maintain homeostasis. The activity of osteoclasts and osteoblasts is regulated by a network of signaling pathways, including Wnt, parathyroid hormone (PTH), RANK ligand/osteoprotegrin, and TGF-ß, in response to stimuli, such as mechanical loading. During aging there is a gradual loss of bone mass due to dysregulation of signaling pathways. This may be due to a decline in physical activity with age and/or changes in hormones and other signaling molecules. In particular, hormones, such as PTH, have a circadian rhythm, which may be disrupted in aging. Due to the complexity of the molecular and cellular networks involved in bone remodeling, several mathematical models have been proposed to aid understanding of the processes involved. However, to date, there are no models, which explicitly consider the effects of mechanical loading, the circadian rhythm of PTH, and the dynamics of signaling molecules on bone remodeling. Therefore, we have constructed a network model of the system using a modular approach, which will allow further modifications as required in future research. The model was used to simulate the effects of mechanical loading and also the effects of different interventions, such as continuous or intermittent administration of PTH. Our model predicts that the absence of regular mechanical loading and/or an impaired PTH circadian rhythm leads to a gradual decrease in bone mass over time, which can be restored by simulated interventions and that the effectiveness of some interventions may depend on their timing.

Oxidative changes and signalling pathways are pivotal in initiating age-related changes in articular cartilage.

OBJECTIVE: To use a computational approach to investigate the cellular and extracellular matrix changes that occur with age in the knee joints of mice. METHODS: Knee joints from an inbred C57/BL1/6 (ICRFa) mouse colony were harvested at 3-30 months of age. Sections were stained with H&E, Safranin-O, Picro-sirius red and antibodies to matrix metalloproteinase-13 (MMP-13), nitrotyrosine, LC-3B, Bcl-2, and cleaved type II collagen used for immunohistochemistry. Based on this and other data from the literature, a computer simulation model was built using the Systems Biology Markup Language using an iterative approach of data analysis and modelling. Individual parameters were subsequently altered to assess their effect on the model. RESULTS: A progressive loss of cartilage matrix occurred with age. Nitrotyrosine, MMP-13 and activin receptor-like kinase-1 (ALK1) staining in cartilage increased with age with a concomitant decrease in LC-3B and Bcl-2. Stochastic simulations from the computational model showed a good agreement with these data, once transforming growth factor-ß signalling via ALK1/ALK5 receptors was included. Oxidative stress and the interleukin 1 pathway were identified as key factors in driving the cartilage breakdown associated with ageing. CONCLUSIONS: A progressive loss of cartilage matrix and cellularity occurs with age. This is accompanied with increased levels of oxidative stress, apoptosis and MMP-13 and a decrease in chondrocyte autophagy. These changes explain the marked predisposition of joints to develop osteoarthritis with age. Computational modelling provides useful insights into the underlying mechanisms involved in age-related changes in musculoskeletal tissues.

Investigating interventions in Alzheimer's disease with computer simulation models.

Progress in the development of therapeutic interventions to treat or slow the progression of Alzheimer's disease has been hampered by lack of efficacy and unforeseen side effects in human clinical trials. This setback highlights the need for new approaches for pre-clinical testing of possible interventions. Systems modelling is becoming increasingly recognised as a valuable tool for investigating molecular and cellular mechanisms involved in ageing and age-related diseases. However, there is still a lack of awareness of modelling approaches in many areas of biomedical research. We previously developed a stochastic computer model to examine some of the key pathways involved in the aggregation of amyloid-beta (Aß) and the micro-tubular binding protein tau. Here we show how we extended this model to include the main processes involved in passive and active immunisation against Aß and then demonstrate the effects of this intervention on soluble Aß, plaques, phosphorylated tau and tangles. The model predicts that immunisation leads to clearance of plaques but only results in small reductions in levels of soluble Aß, phosphorylated tau and tangles. The behaviour of this model is supported by neuropathological observations in Alzheimer patients immunised against Aß. Since, soluble Aß, phosphorylated tau and tangles more closely correlate with cognitive decline than plaques, our model suggests that immunotherapy against Aß may not be effective unless it is performed very early in the disease process or combined with other therapies.