Work Packages

Executive summary #

Project rationale and overall objectives of the project

Today, diseases are still defined largely based on the presentation of signs and symptoms, yet while two patients may share the same diagnosis, the underlying causes of their symptoms may be very different. Naturally, this means that a treatment that works in one patient may prove ineffective in another. There is now broad acceptance that a new approach to disease classification is needed; built not on symptomatology but derived from the inherent pathogenic mechanisms of the disease.

AETIONOMY will pave the way towards a new approach to the classification of neurodegenerative diseases focussing on Alzheimer's and Parkinson's diseases, deriving as a result the prototype of a new mechanism-based taxonomy. This will increase the probability of successfully discovering and developing new therapies for neurodegeneration, and thereby increasing patients' chances of receiving treatments that are effective.


Overall deliverables of the project 

The AETIONOMY team, through its 5 work packages, is tackling the problem of how to obtain, dynamically organise, structure, integrate and interpret the range of different types of data (ranging from molecular data, to information on symptoms) currently available in the community. We plan to bring new structure to the classification of disease by dissecting the underlying mechanistic/molecular causes of disease, and by bringing clinical evidence to support these mechanistic drivers.

Achieving this is far beyond the scope of any single company or university; the key to AETIONOMY success will be the broad nature of the project consortium, which brings together 18 partners made up of pharmaceutical companies, universities, and patient groups, and has expertise in neurodegenerative diseases, molecular biology, clinical research, research ethics, data modelling and simulation, data standards, and patient engagement in research. In addition, collaborations with EPAD (European Prevention of Alzheimer's Dementia), ADNI (Alzheimer´s Disease Neuroimaging Initiative), and MJJF (Michael J Fox Foundation for Parkinson´s Disease) have been established to increase available data for validation of our candidate mechanisms. And awareness of the approaches will be brought to other related initiatives like GAP (the Global Alzheimer Platform), C-PATH, UK-DP, HBP, TVB, ADAPTED and PHAGO.

AETIONOMY's innovative approach will deliver data, tools and postulated mechanistic hypotheses structured in a way to enable the biomedical community and regulators to direct the development, approval and use of new diagnostic tests and treatments for Alzheimer's and Parkinson's diseases.

 

After 5 years of work, AETIONOMY will generate the following key deliverables:

1)    A publicly accessible knowledge base with inventories of mechanistic hypotheses that form the basis for the prototypic mechanism-based taxonomies for AD and PD. This knowledge base, which combines curated clinical and relevant OMICS-data, disease models for AD and PD and dedicated curation, and analysis and visualisation services.

2)    An initial validation of the prototypic, mechanism-based taxonomies and the demonstration that the mechanism-based taxonomy can be used for patient subgroup identification and target/biomarker identification.

3)    The mechanism based taxonomy exposed to the academic and biomedical communities (including regulatory authorities) to influence future development of regulatory requirements, the future research landscape, to educate and enable patient organisations and the European citizens funding the project and the political and administrative bodies involved.

 

Strategic implications

AETIONOMY has achieved most of its objectives so far; in particular, a comprehensive selection of candidate mechanisms (the “inventory” of candidate mechanisms in NeuroMMSigDB) has been generated and all relevant data and all relevant knowledge has been curated and re-annotated. A clear strategic focus for the remaining 12 months of the funded period of the project is essential to achieve the key objective of AETIONOMY, namely, to come up with a prototype mechanism-based taxonomy for Alzheimer´s Disease and Parkinson´s Disease and its partial validation in a clinical study.

AETIONOMY will therefore focus on three different key activities:

1)    In-silico validation of the candidate mechanisms in NeuroMMSigDB, with a special focus on the seven shortlisted candidate mechanisms. Demonstrating the potential of these candidate mechanisms to identify strata of patients in patient-level data is a pre-requisite for the generation of the mechanism-based taxonomy of neurodegenerative diseases.

2)    Wet lab validation of the seven shortlisted candidate mechanisms based on biomarkers representing these mechanisms. A particular challenge here is the link between the readouts in the shortlisted candidate mechanisms and readouts (variables) in patient-level data

3)    Implementation of a prototype of the Virtual Dementia Cohort (VDC). The concept of the VDC has raised a lot of discussion in the scientific community, reaching far out beyond the core community of neurodegenerative disease research. AETIONOMY will focus resources and effort on the goal of having a first demonstrable implementation of the VDC published at the end of the funded period of the project.

Adapting to the changing circumstances of the project the coordinators have issued the following statement to ensure coordination across workstreams is emphasised.

“The project office (PO) appreciates the effort to generate the agreed (& mechanism-related) biomarker data from the clinical cohorts (either partner biomaterial banks or the prospective AETIONOMY PD cohort) and looks forward to obtaining the majority of those data by the end of April 2018.The necessity of imposing this deadline is driven by our overarching goal (namely the identification of patient-subgroups that are characterized by identifiable pathophysiology mechanisms), as it is WP3 who will be tasked with the wider integration of polyomic data there is a need to gain access early enough to facilitate the data pre-processing and data analysis tasks (including mechanism-association of patterns found) before our ultimate deadline.

WP3 remains committed to establishing the relationship between our internally derived (WP5) biomarker measurements and those external clinical / biomarker data sets (i.e. ADNI, EMIF-1000, AddNeuroMed, AIBL for AD; PPMI, MAP2PD – as an aside each of these named datasets should be considered as data only, as none of the studies are likely to provide sufficient samples to be integrated into our biomarker workflows).

The PO asks WP5 partners to redouble efforts to provide a "data generation plan", which consists of the complete picture of resource planning (incl. timelines) for the generation of their respective centres’ biomarker data, and the logistics of any sample transfers. This is important both for the planning for subsequent data transfer activities but is also critical for us to get the financial status of the project in line and ensure that budget is appropriately distributed. This description should make explicit whether any further characterization of biomarkers is planned in patient samples outside of the AETIONOMY cohort.

In parallel WP3 is likewise challenged to update the various analyses plans so that the requisite effort can be likewise costed, and naturally the flow of data around the consortium and into the central AKB needs to be managed by UL and Fraunhofer and therefore WP2 needs to appreciate the effort required.

Please note that both, the "data generation plan" and the "data analysis plan" will become part of the DoW in its final version for the last months of AETIONOMY.”

The consequence of this statement will be captured in greater detail in upcoming DoW amendments, but the emphasis here is to ensure accountability and ownership of practical elements of the overall delivery are properly assigned and that there is an element of structure to the planning of the final months of the project.

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Work Package 1

All management activities, all legal and organisational aspects of the project and all communications are being dealt with in WP1. This is the WP led by the EFPIA coordinating partner, UCB. The Associate Project Coordinator on the academic side is partner Fraunhofer; both partners have implemented a project management office that jointly takes care of the day-to-day management issues. Both partners have identified project managers that have been working on the project to date.

Summary of progress versus plan since last period
  • Management and coordination of the project including monitoring of progress and communications to IMI
  • Supervision of budgets / efforts; reassignments accordingly to needs Organizing the SC meetings
  • Improved internal communication by cross WP workshops and generation of monthly bulletins
  • Amendment including updates on workplan, milestones and deliverables, departure of two partners UCL & NeuroRad, incorporation of new recruitment centres in France, change in Coordinator and several budget reassignments
  • Extension of the ESAB
  • Involvement with PRECISESADS in the joint workshops
  • Organization of the General Assembly in collaboration with EFPIA partner Novartis
  • New layout for our AETIONOMY web presence and regular updates
  • Presentations of the project and first results at different events (see section 3.2)

Significant achievements since last report
  • Delivery of the 3rd Annual Report to IMI
  • Monitoring of project progress according to the DoW for all WPs
  • Budget reassignments and change in Coordinator
  • Incorporation of 3 new recruitment centres in France
  • Extension of the ESAB with new members
  • Organizing the GA in collaboration with EFPIA partner Novartis and convening the ESAB
  • Improved internal communication by cross WP workshops and generation of monthly bulletins
  • Participation in two Joint Ethical workshops with PRECISESADS

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Work Package 2

Work Package 2 deals with all data and knowledge management activities; WP2 is therefore the place where the AETIONOMY knowledge base is being designed, implemented and productively operated. WP2 is led by academic partner University of Luxembourg; the WP is co-led by EFPIA partner Boehringer Ingelheim (BI). As part of the contribution of BI to WP2, a postdoc position working at the interface between WP2 and WP3 will be sponsored at partner Fraunhofer. In addition, as part of the contribution of partner UCB to WP2, data curators are financed at partner Fraunhofer (students supervised by scientists).

Summary of progress versus plan since last period
  • Produced new mapping files for the newly provided datasets;
  • Consolidated the examination of provided datasets with users for inconsistences;
  • Released the literature mining pipelines for the update of the database resources;
  • Released the user documentation for the querying interface;
  • Released the user documentation for pipelines;
  • Provided the description of longitudinised, knowledge-based disease models;
  • Provided a report describing the complete inventory of trajectories and distributions plus a database with all trajectory and distribution information made available to public;
  • Realised and provided a report about the 1st Virtual Dementia Cohort modeling and implementation workshops;
  • Realised and provided a report about the 2nd Virtual Dementia Cohort modeling and implementation workshops;
  • Generation of an ADNI merge file incl. all disease specific features;
  • Exchange and alignment to 84 brain regions;
  • Processing structural and functional connectvities for virtualized ADNI patients, which is the basis for the 3D simulation of the brain;
  • Generation of first virtual ADNI patients with full imaging;
  • Generation of an ADNI Bayesian network model;
  • Mapping of ADNI Bayesian networks to the BEL disease models;
  • Generation of virtual patients based on the Bayesian modelling approach.
  • The BEL compoilation, analysis and visualization system PyBEL was enhanced. It provides a proposed language extensions (BEL Version 2.0), which is important for the BEL-coded disease models for AD and PD.

Significant achievements since last report
  • New mapping files for the newly provided datasets;
  • Users survey for provided datasets;
  • Literature mining pipelines available;
  • User documentation for the querying interface;
  • User documentation for pipelines;
  • Longitudinised, knowledge-based disease models;
  • Inventory of trajectories available to public;
  • 1st and 2nd Virtual Dementia Cohort modeling and implementation;
  • Realisation of 1st and 2nd Virtual Dementia Cohort workshops;
  • First virtual patient generations based on processed AD imaging data and the AD Bayesian network.
  • Mapping of ADNI Bayesian networks to the BEL disease models;

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Work Package 3

WP3 is the work package where all taxonomy construction, knowledge modelling, data- and graph- mining and hypotheses generation will take place. WP3 will also assist in the analysis of clinical data generated in the course of WP5 (clinical study). EFPIA partner UCB will be significantly involved in this work package providing informatics, omics and statistical support and this package will be led by SARD. As part of the contribution of partner BI to WP3, a postdoc position working on disease modeling will be sponsored at partner Fraunhofer.

Summary of progress versus plan since last period
  • Leadership changed from UCL to Fraunhofer - as a result of the General Assembly in Paris in Dec 2016 and took effect on 1st January 2017- to prepare the validation of candidate mechanisms.
  • WP3 has invested massively in various mining and modelling approaches. On the side of imaging readouts linked to genetic variations, partner EMC has provided initial statistical evidence for the association of individual SNPs with imaging readouts at Voxel basis.
  • The pathophysiology graph 'NeuroMMSig' is the inventory of candidate mechanisms in AETIONOMY; this inventory of candidate mechanisms comprises now 126 candidate mechanisms for AD and 76 candidate mechanisms for PD (also available in the AETIONOMY BSCW workspace in the folder 'Biomarker Lounge'); we are now able to perform systematic analyses of the "presence" or "absence" of mechanisms in data of cohort studies; it , is now accessible as a web service, which is integrated into the AETIONOMY Knowledge base; it was proven and approved by partner ICM, how NeuroMMSig-derived gene lists could be used for the identification of patient subgroups in PD.
  • A concept for the candidate mechanisms validation strategy was generated and approved; the workplan of the WP3 members is now aligned, which includes also the work of the new WP3 partner Pharmacoidea.
  • Main sources for the validations of candidate mechanisms and hypotheses were ADNI, PPMI, Swedish PD patient data (KI), AddNeuroMed data (EMIF catalogue). Additionally, we prepared validations against CRIS, EMIF-1000, Oxford PD cohort data, Tübingen, and Kings college data. The access of further data sets of the clinical partners will be proven. Agreements with C-PATH (USA) and Oxford NHS Trust Centre (GB) were made.
  • Submittted reports:
  • Deliverable D3.3.2 summarized the Webinar on the discoveries generated in AETIONOMY about disease mechanisms and provided knowledge-based and data-driven based hypothesis of disease mechanisms and initial patient stratification.
  • Two further Webinars were held explaining, how Bayesian Modelling of clinical Data (ADNI) can improve our understanding of features, mechanisms and stratification of patient subgroups, and in the second webinar first results for the ADNI cohort were presented. The 2 deliverables D3.3.3 and D3.3.4 describing both tutorials; it was demonstrated that a link is possible between literature based knowledge and data derived representations of patient-level data in Bayesian conditional dependency graphs. It is noteworthy to mention, that these Bayesian representations can be used for validation of patterns between independent cohorts and - moreover - for a virtual meta-cohort representing all major Alzheimer cohorts worldwide. In addition to the ADNI based Bayesian network, we are working on a PPMI based version too. Report D3.4.1 describe methodology and workflow involved in the development of a Brain Region Spatial Atlas management pipeline. It combines tractography data (e.g. MR DTI) with surface and volumetric data (MR structural brain scans).
  • Report D3.6 "Generation of specific Hypotheses about disease sub-groups" is mainly focussing on the NeuroMMSig approach to identify in-silico candidate mechanisms and their related patient subgroups. In this document disease knowledge assembly models were generated in order to capture the vast knowledge around AD and PD. The language used to build the underlying models is the open source version of the Biological Expression Language (BEL). BEL encodes knowledge-based (mostly literature-derived) "cause and effect" relationships into network models, which can be subjected to causal analysis using quantitative data such as gene expression.
  • Report D3.6.1 "Final pathophysiology graphs for AD and PD to be generated and any additional validation tests to be performed on the clinical samples identified via a webinar" described the final pathophysiology graphs for AD and PD and any additional validation tests to be performed on the clinical samples identified via a webinar. The models developed here not only represent a comprehensive view on the core established pathways involved in amyloid processing, but also cover a broad spectrum of events that lead to clinical readouts often seen in AD and PD patients, such as neuro-inflammatory cascades.
  • Report D3.7.2 is describing a pipeline that leverages complementary methodologies aimed at different data types and biological scales; this pipeline was discussed under 3 perspectives: the identification of clinical stratifiers, the conversion of the clinical signal into a hypothesized tissue-level pathophysiological mechanism, and the generation of multiscale cause-and-effect networks relevant for neurodegeneration.
  • An important deliverable is the report D3.8 "Data Analysis Work Plan for the WP5 Clinical Study"; it describes how to build a consistent and reusable OMICS feature extraction pipeline. To do this we looked into the different kind of data sets - Genomic, Epigenomic, and Protein expression - to be analyzed to support the WP5 clinical study and gave accordingly recommendations on methods and procedures. An important aspect is hereby patient stratification and the exploration of sub-groups within de-novo AD and PD patients based on existing ADNI and PPMI data (mainly based on genomic data).
  • To prepare the validation of the in-silico candidate mechanisms (NeuroMMSig) a webinar was hold on 18th December 2017 reported in document D3.9.1.2 "Review the pathophysiology graphs and potential hypotheses to be tested - Implementation of algorithms for mapping and stratification in NeuroMMSig-Server incl. Final pathophysiology graphs for AD and PD". Slides, report and a web recorded tutorial are uploaded to the AETIONOMY BSCW workspace.
  • Partner Pharmacoidea generated the 2 reports D3.9.2.1 and D3.9.2.2 on syndecan dependent assays and the identification of new syndecan-ligands and surrogate markers. These research is tareting heparan sulfate proteoglycans as key players behind spreading-associated processes in neurodegeneration. In the second report the identification of new syndecan-ligands and surrogate markers that link syndecan-mediated uptake and signaling mechanisms to clinical variables are described. The aim is to uncover the fundamental mechanisms underlying the cellular processes governing neurodegenration, including the cellular spreading of pathological misfolded proteins in AD and PD.
  • Partner EMC performed (after analysing extensive SNP-associations, VBM analysis, and Gene Expression experiments on the Rotterdam Scan Study; 4500 healthy subjects) new genotype-phenotype associations (HASE regression analyses developed at EMC) on 1175 subjects (338 Controls, 632 MCI, 205 AD) from the ADNI1 and ADNI_GO/2 database. In that cohort, 314134 genetic variants that passed quality control are available. For phenotyping the latest version of FreeSurfer (FS_6.0.0) was used to compute quantitative imaging biomarkers. Special in FS_6.0.0 is that the brain tissue segmentation results in volume measures of 12 subparts of the left and right hippocampus (an extremely relevant brain structure in the Alzheimer field) and 5 subparts of the brain stem (until now especially relevant for Parkinsons Disease).
  • Additionally, partners Fraunhofer and UCB Pharma generated longitudinal progression models for AD and PD. Longitudinal aspects were also the focus of a first modeling workshop between scientists of AETIONOMY, EPAD, and ROADMAP in Edinburgh. In "Contributions to the design of Clinical Study", we are currently focussing on the longitudinal modelling of disease progression based on ADNI and PPMI data. A first analysis of ADNI data showed substantial differences between the "reference biomarker trajectory model" published by Clifford Jack in 2010 (and its updated version in 2013) and ADNI data projected into the same, comparable metrics system. The work presented here is an example for the fruitful crosstalk between AETIONOMY and EPAD; the "Study viewer" developed for EPAD contains now both reconstructed Clifford Jack models and the ADNI biomarker trajectories extracted from ADNI data.
    For details please visit: http://epad.scai.fraunhofer.de/app/alzheimer-model.


Significant achievements since last report
  • Various mining and modelling approaches.
  • Initial statistical evidence for the association of individual SNPs with imaging readouts at Voxel basis.
  • Pathophysiology graph 'NeuroMMSig' comprises 126 candidate mechanisms for AD and 76 candidate mechanisms for PD
  • Concept for the candidate mechanisms validation strategy generated and approved;
  • Main sources for the validations of candidate mechanisms and hypotheses were ADNI, PPMI, PD patient data from partner KI, AddNeuroMed data (EMIF catalogue). Additionally, we prepared validations against CRIS, EMIF-1000, Oxford PD cohort data, Tuebingen, and Kings college data. Agreements with C-PATH (USA) and Oxford NHS Trust Center (GB) were made.
  • 3 Webinars were hold explaining, how Bayesian Modelling of clinical Data (ADNI) can improve our understanding of features, mechanisms and stratification of patient subgroups (reported in deliverables D3.3.2, D3.3.3, and D3.3.4).
  • A first modeling workshop on longitudinal aspects were hold between scientists of AETIONOMY, EPAD, and ROADMAP in Edinburgh.
  • Brain Region Spatial Atlas management pipeline is available, which combines tractography data (e.g. MR DTI) with surface and volumetric data (MR structural brain scans).
  • In-silico candidate mechanisms and their related patient subgroups are described (NeuroMMSig, reports D3.6 and D3.6.1). This includes final pathophysiology graphs for AD and PD.
  • A pipeline for the identification of clinical stratifiers, the conversion of the clinical signal into a hypothsized tissue-level pathophysiological mechanism, and the generation of multiscale cause-and-effect networks relevant for neurodegeneration.
  • Longitudinal modelling of disease progression based on ADNI and PPMI data (the "study viewer" http://epad.scai.fraunhofer.de/app/alzheimer-model ).
  • A Data Analysis Work Plan for the WP5 Clinical Study" describes how to build a consistent and reusable OMICS feature extraction pipeline incl. patient stratification and the exploration of sub-groups within de-novo AD and PD patients based on existing ADNI and PPMI data (mainly based on genomic data).
  • Available webinar reported in document D3.9.1.2 "Review the pathophysiology graphs and potential hypotheses to be tested - Implementation of algorithms for mapping and stratification in NeuroMMSig-Server incl. Final pathophysiology graphs for AD and PD". Slides, report and a webrecorded tutorial are uploaded to the AETIONOMY BSCW workspace.
  • New syndecan-ligands and surrogate markers identified (D3.9.2.1 and D3.9.2.2). in Ad and PD.
  • New genotype-phenotype associations (HASE regression analyses developed at EMC) on 1175 subjects (338 Controls, 632 MCI, 205 AD) from the ADNI1 and ADNI_GO/2 database.

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Work Package 4

WP4 contains all activities in the ethical and legal context. Two academic partners (LUH & Alzheimer Europe) and the coordinating EFPIA partner UCB will be involved in this WP; a Legal Ethics Advisory Board (LEAB) will be implemented and coordinated by this WP. In addition to the two academic partners LUH and AE, we are currently incorporating an additional patient representation organisation: the European Brain Council.

(See http://www.europeanbraincouncil.org/)

Summary of progress versus plan since last period
  • Ongoing communication and discussion with external legal and ethics advisory board (LEAB): fourth meeting held in M48 and reported in D4.2.4 (M48).
  • Ongoing cooperation with sister projects and harmonisation of approaches: follow-up joint ethics meeting of AETIONOMY-PRECISESADS projects held in M40 and reported in D4.3.2 (M41).
  • Ongoing scholarly collaboration: with WP4 co-leader AE on patient stratification in non-curable diseases; and with WP2 on ethics of research using artificially generated patient cohorts - joint dissemination articles in progress.

Updating project's initial data protection framework to take account of impending EU legislative change (replacement of Directive 95/46/EC by Regulation (EU) 2016/679 - 'GDPR') presented in D4.5 (M48).

Significant achievements since last report
  • Data Protection Framework for Project set up; establishes closed research community ('network of trust') in which securely de-identified data may be shared safely and lawfully between AETIONOMY partners: further agreements prepared for new partners; analysis of impact of new legislative landscape (EU Regulation 2016/679 applicable from 25 May 2018) and preparation of revised DP framework to ensure compliance, including drafting of new Data Protection Supplemental Agreement for partners to sign.
  • Ongoing discussions with EFPIA partners, and monitoring progress of agreement for these to transfer clinical data to SAS MSE after EFPIA audit of UL tranSMART led by BI; plan for EFPIA data (except Novartis) to be included in tranSMART, and liaising between EFPIA parties and UL on supplementary data-sharing agreement between them.
  • Discussions and advice to partners and PO on terms on which AETIONOMY may access data/samples from third party providers (UKT and KCL); legal and ethical analysis of issues arising from use of virtual dementia cohorts in patient stratification studies.

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Work Package 5

In WP5, the clinical studies for the validation of the mechanism-based taxonomy are organised. This WP also deals with two scenarios relevant for the SME partners in AETIONOMY: in WP5.4, partner Pharmacoidea will make use of the insights gained into disease mechanisms to identify possible targets for preventive or interventional therapy; in WP5.5 partner Neurorad will test to what extent a routine diagnostic imaging lab can utilize imaging-based indices for patient subgroup identification by means of image analysis. WP5 will be led by partner ICM, and Novartis will be the EFPIA partner lead in this work package. As part of the contribution of partner BI to WP5, a postdoc position working on cohorts will be sponsored at partner Fraunhofer.

There will also be an External Scientific Advisory Board (ESAB) that will receive annual reports from the General Assembly. The ESAB will be the consortium body through which external experts will give their advice and feedback on the main arising issues of the AETIONOMY project and the project’s overall strategy and progress.

The main goals of the ESAB will be:

  • Providing requirements and feedback to the project’s objectives and progress.
  • Monitoring the main milestones of the project, updating its feedback, and providing the necessary inputs for guiding the project’s research and activities towards the achievement of the project’s main objectives.
  • Providing a final feedback on results evaluation and expectations for future evolution.
Summary of progress versus plan since last period
  • Confirmation of the principal biomarkers to analyse from the patients' samples
  • End of recruitment in AETIONOMY Clinical Study. Recruitment objectives of PD group were achieved, notably thanks to the additional French centres opened in 2017. Recruitment goals for AD group are being reached through the offering of partners' additional cohorts.
  • 12 New articles based on research funded by AETIONOMY have been published or are currently (see section 3.2):
  • Pharmacoidea (PHI) explored heparan sulfate proteoglycans (HSPGs) dependent cellular processes underlying neurodegeneration. During the course of AETIONOMY, Tamas Letoha and his colleagues in PHI took on the task to uncover the fundamental mechanisms underlying the cellular processes governing neurodegeneration, including, but not limited to the cellular spreading of pathological misfolded proteins in AD and PD. Letoha et al. pursued these objectives with established cellular platforms overexpressing distinct isoforms of syndecans (SDCs), a heparan sulfate proteoglycan (HSPG) family. As postmortem human AD brains show increased expression of SDC3 and SDC4, two isoforms of the SDC family, SDCs are attracting increased interest in neurodegeneration research. Considering the growing evidence of SDC involvement in the cellular attachment and internalization of pathological protein aggregates, we carried out extensive studies to explore the role and contribution of SDCs to α-synuclein (a-SYN) and tau uptake, utilizing SDC-specific cellular assays. Data obtained from these experiments presents the major role of SDCs in the cellular attachment and translocation of a-SYN and tau, emphasizing the importance of SDCs in key events of cellular pathophysiology underlying neurodegeneration.

Significant achievements since last report
  • AETIONOMY prospective study finished recruiting
  • 420 subjects were successfully recruited, giving available clinical data and samples to analyse chosen biomarkers.
  • New partners' publications in 2017 (check our publication page).