This section contains all public deliverables produced by the project.
D9.1: Project ontology and terminology, including data mapper and RDF graph builder
It documents the design and development of the first version of the Brainteaser Ontology (BO) focused, in particular, on retrospective data for Amyotrophic Lateral Sclerosis (ALS) and Multiple Sclerosis (MS).
The BO is innovative since it relies on very few seed concepts – Patient, Clinical Trial, Disease, Event – which allow us to jointly model ALS and MS and to grasp the time dimension entailed by the progression of such diseases.
D10.1: DC&SE Strategy and Plan
It provides an in dept overview of the Dissemination, Communication and Stakeholder Engagement actions that BRAINTEASER will implement in its work packages. The document outlines plans, objectives, methods and tools to be implemented and a practical guideline to ensure a smooth interaction between the project’s dissemination team
and the rest of partners.
The plan must be seen as a living document and, as such, will be revised twice during the lifetime of the project to align the DC&SE strategy with BRAINTEASER results and achievements.
D10.4: Visual identity, website and communication package
The project’s initial communication package, consisting of the project branding and graphic identity, website and social media channels, flyer and poster, banners and visuals is here presented. Work documents templates made available to consortium partners to assure a homogeneous approach in the preparation of presentations and text documents are, also, here included.
D10.5: DC&SE Report
The present report aims to track progress made with dissemination, communications and stakeholders’ engagement (DC&SE) actions during the first year of the project. It documents actions recommended and/or guided by the first release of the project’s DC&SE Strategy and Plan. All the activities undertaken in this context are here addressed as well as challenges, risks, means of mitigation, and lessons learned from such actions.
This section contains papers, and any other published materials describing our outcomes as they are produced by the project.
Artificial intelligence and statistical methods for stratification and prediction of progression in amyotrophic lateral sclerosis: A systematic review
This systematic review aims at identifying areas of agreement and unanswered questions regarding two notable applications of AI in ALS, namely the automatic, data-driven stratification of patients according to their phenotype, and the prediction of ALS progression. Differently from previous works, this review is focused on the methodological landscape of AI in ALS.
Authors: Erica Tavazzi, Enrico Longato, Martina Vettoretti, Helena Aidos, Isotta Trescato, Chiara Roversi, Andreia S. Martins, Eduardo N. Castanho, Ruben Branco, Diogo F. Soares, Alessandro Guazzo, Giovanni Birolo, Daniele Pala, Pietro Bosoni, Adriano Chiò, Umberto Manera, Mamede de Carvalho, Bruno Miranda, Marta Gromicho, Inês Alves, Riccardo Bellazzi, Arianna Dagliati, Piero Fariselli, Sara C. Madeira, Barbara Di Camillo
iDPP@CLEF 2023: The Intelligent Disease Progression Prediction Challenge
Amyotrophic Lateral Sclerosis (ALS) and Multiple Sclerosis (MS) are chronic diseases characterized by progressive or alternate impairment of neurological functions (motor, sensory, visual, cognitive). The goal of iDPP@CLEF Open Evaluation Challenge is to design and develop an evaluation infrastructure for AI algorithms able to: better describe disease mechanisms; stratify patients according to their phenotype assessed all over the disease evolution; predict disease progression in a probabilistic, time dependent fashion. iDPP@CLEF will continue in CLEF 2023, focusing on the prediction of MS progression and exploring whether pollution and environmental data can improve the prediction of ALS progression.
Authors: Helena Aidos, Roberto Bergamaschi, Paola Cavalla, Adriano Chiò, Arianna Dagliati, Barbara Di Camillo, Mamede Alves de Carvalho, Nicola Ferro, Piero Fariselli, Jose Manuel García Dominguez, Sara C. Madeira & Eleonora Tavazzi
Delayed Diagnosis and Diagnostic Pathway of Amyotrophic Lateral Sclerosis Patients in Portugal: Where Can We Improve?
Amyotrophic lateral sclerosis (ALS) diagnosis still faces significant delays. Spinal onset, slower disease progression, cognitive symptoms at onset and lower income were independent factors associated with diagnosis delay. Late referral from non-neurologists to a neurologist is a potentially modifiable factor that could contribute to increased time to diagnosis.
The document analyses the diagnostic pathway and investigates different factors associated with diagnostic delay in ALS.
Authors: Catarina Falcão de Campos, Marta Gromicho, Hilmi Uysal, Julian Grosskreutz, Magdalena Kuzma-Kozakiewicz, Miguel Oliveira Santos, Susana Pinto, Susanne Petri, Michael Swash, Mamede de Carvalho
Mild Dysphagia Does Not Influence Survival in Ventilated Amyotrophic Lateral Sclerosis Patients.
It is unknown if mild dysphagia affects survival of patients with amyotrophic lateral sclerosis (ALS) on continuous non-invasive ventilation (NIV). We often must discuss the pros and cons of gastrostomy in patients with NIV, but there is a lack of information on the issue. We, therefore, studied dysphagia as a survival predictor factor in patients with ALS already adapted to continuous NIV, using our collected data.
Our findings are relevant for decision-making processes concerning gastrostomy in this particular population.
Authors: Miguel Oliveira Santos, Marta Gromicho, Susana Pinto, Michael Swash, Mamede de Carvalho.
Learning Prognostic Models Using a Mixture of Biclustering and Triclustering: Predicting The Need for Non-invasive Ventilation in Amyotrophic Lateral Sclerosis
This paper aims to promote state-of-the-art characteristics in methods related to prognostic predictions and the need for non-invasive ventilation in patients with amyotrophic lateral sclerosis (ALS). It does this by learning from interpretable disease progression patterns. Findings are applicable to other ALS endpoints and diseases.
Authors: Diogo F. Soares, Rui Henriques, Marta Gromicho, Mamede de Carvalho, Sara C.Madeira
Respiratory Onset in Amyotrophic Lateral Sclerosis: Clinical Features and Spreading Pattern
The paper characterises the respiratory onset phenotype in the targeted population, describes functional impairment and respiratory tests, investigates time to non-invasive ventilation (NIV) and survival, and details the spreading pattern. In particular, the paper considers how variability might influence survival.
Authors: Susana Pinto, Marta Gromicho, Miguel Oliveira Santos1, Michael Swash, Mamede de Carvalho
Thyroid Dysfunction in Portuguese Amyotrophic Lateral Sclerosis Patients
In current literature, there is no suspicion of the role that autoimmunity may play in the pathogenesis of amyotrophic lateral sclerosis (ALS). This is due to the fact that there are other recognised genetic, epigenetic, and environmental factors. This paper aims to investigate the prevalence of thyroid disease in patients with ALS and review publications related to the topic.
Authors: Cláudia Santos Silva, Marta Gromicho, Miguel Oliveira Santos, Susana Pinto, Michael Swash, Mamede de Carvalho.
Motor Neuron Disease in Three Asymptomatic pVal50Met TTR Gene Carriers
An association could be present between transthyretin (TTR) gene mutations and motor neuron disease. These mutations impair the physiologic properties of this protein, especially its protective role in motoneuron survival. The paper describes three unrelated patients with sporadic motor neuron disease (MND) and hereditary amyloid transthyretin (ATTRv) amyloidosis who were asymptomatic carriers of the pVal50Met mutation of the TTR gene. We analysed imaging, cerebrospinal fluid and nerve conduction and small fiber tests.
Authors: Cláudia Santos Silva, Miguel Oliveira Santos, Marta Gromicho, Ana Pronto-Laborinho, Isabel Conceição & Mamede de Carvalho.
Baseline Machine Learning Approaches To Predict Amyotrophic Lateral Sclerosis Disease Progression
During the CLEF Challenge 2022, two dataset versions of patients with amyotrophic lateral sclerosis (ALS) were used: naseline values (first visit at the clinical centre) and information collected at 6-month follow-up. The study aimed to benchmark survival methods and build a baseline comparable against other models. From a clinical viewpoint, the objective was to predict time to event (for selected events of interest in ALS: (i) the need for non-invasive ventilation, (ii) the need for percutaneous endoscopic gastrostomy, (iii) death) and predict the risk (in time) of each event in each patient.
Authors: Trescato I., Guazzo A., Longato E., Hazizaj E., Roversi C., Tavazzi E., Vettoretti M., Di Camillo B.