DNA copy number variation associated with anti-tumour necrosis factor drug response and paradoxical psoriasiform reactions in patients with moderate-to-severe psoriasis

Biological drugs targeting tumour necrosis factor are effective for psoriasis. However, 30–50% of patients do not respond to these drugs and may even develop paradoxical psoriasiform reactions. This study search-ed for DNA copy number variations that could predict anti-tumour necrotic factor drug response or the ap-pearance of anti-tumour necrotic factor induced pso-riasiform reactions. Peripheral blood samples were collected from 70 patients with anti-tumour necrotic factor drug-treated moderate-to-severe plaque pso-riasis. Samples were analysed with an Illumina 450K methylation microarray. Copy number variations were obtained from raw methylation data using conumee and Chip Analysis Methylation Pipeline (ChAMP) R packa-ges. One copy number variation was found, harbouring one gene (CPM) that was significantly associated with adalimumab response (Bonferroni-adjusted p-value < 0.05). Moreover, one copy number variation was identified harbouring 3 genes (ARNT2, LOC101929586 and MIR5572) related to the development of paradoxical psoriasiform reactions. In conclusion, this study has identified DNA copy number variations that could be good candidate markers to predict response to ada-limumab and the development of anti-tumour necrotic factor paradoxical psoriasiform reactions.This study was supported by Instituto de Salud Carlos III PI 13/01598 and the Ministry of Science and Innovation and the European Regional Development’s funds (FEDER). Conflicts of interest. FA-S has been a consultant or investigator in clinical trials sponsored by the following pharmaceutical companies: Abbott, Alter, Chemo, Farmalíder, Ferrer, GlaxoSmithKline, Gilead, Janssen-Cilag, Kern, Normon, Novartis, Servier, Teva, and Zambon. ED has potential conflicts of interest (advisory board member, consultant, grants, research support, participation in clinical trials, honoraria for speaking, and research support) with the following pharmaceutical companies: AbbVie (Abbott), Amgen, Janssen-Cilag, Leo Pharma, Novartis, Pfizer, MSD, Lilly and Celgene. ML-V has potential conflicts of interest as she has participated in clinical trials or as consultant with Abbvie (Abbott), Galderma, Janssen-Cilag, Leo Pharma, Pfizer, Novarties, Lilly, Almirall and Celgene. MCO-B has potential conflicts of interest (honoraria for speaking and research support) with Janssen-Cilag and Leo Pharma. The other authors have no other relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript apart from those disclosed. AS-T has served as a consultant and/or paid speaker for and/or participated in clinical trials sponsored by companies that manufacture drugs used for the treatment of psoriasis, including AbbVie, Celgene, Janssen-Cilag, LEO Pharma, Lilly, Novartis and Pfizer. RB-E has served as a consultant and/or paid speaker for and/or participated in clinical trials sponsored by companies that manufacture drugs used for the treatment of psoriasis, including AbbVie, Celgene, Janssen-Cilag, LEO Pharma, Lilly, Novartis and Pfizer

A New Hierarchy of Research Evidence for Tumor Pathology: A Delphi Study to Define Levels of Evidence in Tumor Pathology

The hierarchy of evidence is a fundamental concept in evidence-based medicine, but existing models can be challenging to apply in laboratory-based health care disciplines, such as pathology, where the types of evidence and contexts are significantly different from interventional medicine. This project aimed to define a comprehensive and complementary framework of new levels of evidence for evaluating research in tumor pathology-introducing a novel Hierarchy of Research Evidence for Tumor Pathology collaboratively designed by pathologists with help from epidemiologists, public health professionals, oncologists, and scientists, specifically tailored for use by pathologists-and to aid in the production of the World Health Organization Classification of Tumors (WCT) evidence gap maps. To achieve this, we adopted a modified Delphi approach, encompassing iterative online surveys, expert oversight, and external peer review, to establish the criteria for evidence in tumor pathology, determine the optimal structure for the new hierarchy, and ascertain the levels of confidence for each type of evidence. Over a span of 4 months and 3 survey rounds, we collected 1104 survey responses, culminating in a 3-day hybrid meeting in 2023, where a new hierarchy was unanimously agreed upon. The hierarchy is organized into 5 research theme groupings closely aligned with the subheadings of the WCT, and it consists of 5 levels of evidence-level P1 representing evidence types that merit the greatest level of confidence and level P5 reflecting the greatest risk of bias. For the first time, an international collaboration of pathology experts, supported by the International Agency for Research on Cancer, has successfully united to establish a standardized approach for evaluating evidence in tumor pathology. We intend to implement this novel Hierarchy of Research Evidence for Tumor Pathology to map the available evidence, thereby enriching and informing the WCT effectively.The overall project, International Agency for Research on Cancer, and beneficiaries (German Heart Centre Munich, Maria Sklodowska-Curie National Research Institute of Oncology, and Instituto de Salud Carlos III) are funded by the European Commission (HORIZON grant no. 101057127). R.C. and F.C. are funded by UK Research and Innovation. S.H. has received research funding or honoraria from Roche, BMS, Merck, Sysmex, Thermo, Volition, Trillium, Medica, and Instand and is a founder of SFZ BioCoDE and CEBIO. P.H.T. has received honoraria from AstraZeneca.S

Cómo poner puertas al campo : tres revisiones panorámicas sobre el uso de biomarcadores en prevención personalizada de enfermedades crónicas

Se incluye PDF de la presentación y vídeo del seminario.El seminario trata de dar respuesta a qué biomarcadores hay disponibles o en desarrollo para la prevención personalizada de enfermedades crónicas en la población general. Las revisiones realizadas resumen las principales características y conclusiones de la bibliografía sobre este tema. Abarca los tres principales grupos de enfermedades crónicas:11 tipos de cáncer, 9 enfermedades cardiovasculares y 7 enfermedades neurodegenerativas.N

Impact of Chronic Disease Self-Management Program on the Self-Perceived Health of People in Areas of Social Vulnerability in Asturias, Spain

The Chronic Disease Self-Management Program (CDSMP) focuses on a health promotion perspective with a salutogenic approach, reinforcing the pillars of self-efficacy. The aim of this study was to assess the impact of the CDSMP on Self-perceived Health (SPH) in disadvantaged areas of Asturias, España. The study included vulnerable adults with experience of chronic diseases for over six months, along with their caregivers. The intervention consisted of a six-session workshop led by two trained peers. SPH was evaluated by administering the initial item of the SF-12 questionnaire at both baseline and six months post-intervention. To evaluate the variable "Change in SPH" [improvement; remained well; worsening/no improvement (reference category)], global and disaggregated by sex multivariate multinomial logistic regression models were applied. There were 332 participants (mean = 60.5 years; 33.6% were at risk of social vulnerability; 66.8% had low incomes). Among the participants, 22.9% reported an improvement in their SPH, without statistically significant sex-based differences, while 38.9% remained in good health. The global model showed age was linked to decreased "improvement" probability (RRRa = 0.96), and the "remaining well" likelihood drops with social risk (RRRa = 0.42). In men, the probability of "remaining well" decreased by having secondary/higher education (RRRa = 0.25) and increased by cohabitation (RRRa = 5.11). Women at social risk were less likely to report "remaining well" (RRRa = 0.36). In conclusion, six months after the intervention, 22.9% of the participants had improved SPH. Age consistently decreased the improvement in the different models.This research was funded by European Union’s Health Programme (2014–2020) GA738127.N

How to stem the tide? Development of three scoping reviews in biomarkers and personalized prevention

XLI Reunión anual de la Sociedad Española de Epidemiología (SEE) y XVIII Congresso da Associação Portuguesa de Epidemiología (APE). Porto (Portugal), del 5 al 8 de septiembre de 2023.The “PeRsOnalized Prevention roadmap for the future HEalThcare” (PROPHET) project, seeks to assess the effectiveness, clinical utility and existing gaps in current personalized preventive approaches, and to develop a Strategy Research and Innovation Agenda (SRIA) for the European Union. The first draft of the SRIA concept paper needs to incorporate the state of the art of personalized prevention carried out through scoping reviews. Among them, our work aimed to answer whether there is any biomarker or combination of biomarkers that can help to better identify subgroups of individuals with different risks of developing a particular disease for primary or secondary prevention. These results were needed at early stage of the project; despite covering such a broad topic, it had to be carried out in record time (4 months) by a geographically dispersed team (Granada, Madrid, United Kingdom). Our challenge has been to maintain effective coordination and speed without losing scientific rigor. Between Feb-June 2023, our team conducted three independent scoping reviews (for cardiovascular diseases, neurodegenerative diseases and cancer, respectively) that involved quick and difficult decisions to narrow down the inclusion criteria, study populations, biomarkers included, and types of prevention. To maintain consistency, we created different glossaries and had multiple meetings and constant contact between team members. As a first step, we identified key terms on the topics of interest, helped by expert consultations, identification of significant publications and several specific tools (SR-Accelerator, etc.). A pilot study was conducted to refine the search matrix and to initiate coordination among reviewers. However, in order to shorten timeframes, we limited peer review to 10% of the records in all phases. The protocol, published in OSF, served as a guide for the report. All phases, when possible, overlapped to deliver the report on time. In addition, we made interactive evidence maps to show the results graphically, thanks to the creation of a script, using R and Python, to allow the input of the datasheet extraction file into the mapping application. Despite these challenges, we successfully met the project deadlines.Funding: HE No 10105772. UKRI No 10040946.N

Comparison of machine learning algorithms for clinical event prediction (risk of coronary heart disease)

The aim of this study is to compare the utility of several supervised machine learning (ML) algorithms for predicting clinical events in terms of their internal validity and accuracy. The results, which were obtained using two statistical software platforms, were also compared. The data used in this research come from the open database of the Framingham Heart Study, which originated in 1948 in Framingham, Massachusetts as a prospective study of risk factors for cardiovascular disease. Through data mining processes, three data models were elaborated and a comparative methodological study between the different ML algorithms – decision tree, random forest, support vector machines, neural networks, and logistic regression – was carried out. The global selection criterium for choosing the right set of hyperparameters and the type of data manipulation was the area under a curve (AUC). The software tools used to analyze the data were R-Studio® and RapidMiner®. The Framingham study open database contains 4240 observations. The algorithm that yielded the greatest AUC when analyzing the data in R-Studio was neural network applied to a model that excluded all observations in which there was at least one missing value (AUC = 0.71); when analyzing the data in RapidMiner and applying the same model, the best algorithm was support vector machines (AUC = 0.75). ML algorithms can reinforce the diagnostic and prognostic capacity of traditional regression techniques. Differences between the applicability of those algorithms and the results obtained with them were a function of the software platforms used in the data analysis.2019/UEM113.526 JCR (2019) Q2, 32/109 Computer Science, Interdisciplinary Applications, 7/27 Medical Informatics1.140 SJR (2019) Q1, 115/1377 Computer Science Applications, 10/141 Health InformaticsNo data IDR 2019UE

CNVs Associated with Different Clinical Phenotypes of Psoriasis and Anti-TNF-Induced Palmoplantar Pustulosis

Background: Psoriasis can present different phenotypes and could affect diverse body areas. In contrast to the high effectiveness of biological drugs in the treatment of trunk and extremities plaque psoriasis, in palmoplantar phenotypes and in plaque scalp psoriasis, these same drugs usually have reduced efficacy. Anti-TNF drugs could induce the appearance of palmoplantar pustulosis (PPP) in patients with other inflammatory diseases. The objective of this study is to identify if there are DNA Copy Number Variations (CNVs) associated with these different clinical phenotypes, which could justify the differences found in clinical practice. Moreover, we intend to elucidate if anti-TNF-induced PPP has a similar genetic background to idiopathic PPP. Methods: Skin samples were collected from 39 patients with different patterns of psoriasis and six patients with anti-TNF-induced PPP. The CNVs were obtained from methylation array data (Illumina Infinium Human Methylation) using the conumee R package. Results: No significant CNVs were found between the different phenotypes and the locations of psoriasis compared. Nevertheless, we found two significant bins harboring five different genes associated with anti-TNF-induced PPP in patients with a different background other than psoriasis. Conclusions: Our results may help to predict which patients could develop anti-TNF-induced PPP

Biomarkers for personalised prevention of chronic diseases: a common protocol for three rapid scoping reviews

Dataset disponible en: http://hdl.handle.net/20.500.12105/19630Introduction: Personalised prevention aims to delay or avoid disease occurrence, progression, and recurrence of disease through the adoption of targeted interventions that consider the individual biological, including genetic data, environmental and behavioural characteristics, as well as the socio-cultural context. This protocol summarises the main features of a rapid scoping review to show the research landscape on biomarkers or a combination of biomarkers that may help to better identify subgroups of individuals with different risks of developing specific diseases in which specific preventive strategies could have an impact on clinical outcomes. This review is part of the "Personalised Prevention Roadmap for the future HEalThcare" (PROPHET) project, which seeks to highlight the gaps in current personalised preventive approaches, in order to develop a Strategic Research and Innovation Agenda for the European Union. Objective: To systematically map and review the evidence of biomarkers that are available or under development in cancer, cardiovascular and neurodegenerative diseases that are or can be used for personalised prevention in the general population, in clinical or public health settings. Methods: Three rapid scoping reviews are being conducted in parallel (February-June 2023), based on a common framework with some adjustments to suit each specific condition (cancer, cardiovascular or neurodegenerative diseases). Medline and Embase will be searched to identify publications between 2020 and 2023. To shorten the time frames, 10% of the papers will undergo screening by two reviewers and only English-language papers will be considered. The following information will be extracted by two reviewers from all the publications selected for inclusion: source type, citation details, country, inclusion/exclusion criteria (population, concept, context, type of evidence source), study methods, and key findings relevant to the review question/s. The selection criteria and the extraction sheet will be pre-tested. Relevant biomarkers for risk prediction and stratification will be recorded. Results will be presented graphically using an evidence map. Inclusion criteria: Population: general adult populations or adults from specific pre-defined high-risk subgroups; concept: all studies focusing on molecular, cellular, physiological, or imaging biomarkers used for individualised primary or secondary prevention of the diseases of interest; context: clinical or public health settings. Systematic review registration: https://doi.org/10.17605/OSF.IO/7JRWD (OSF registration DOI).The PROPHET project has received funding from the European Union’s Horizon Europe research and innovation program under grant agreement no. 101057721. UK participation in Horizon Europe Project PROPHET is supported by UKRI grant number 10040946 (Foundation for Genomics & Population Health).S

Biomarkers for personalized prevention of chronic diseases

The “PeRsOnalized Prevention roadmap for the future HEalThcare” (PROPHET) project, funded by the European Union’s Horizon Europe research and innovation program and linked to ICPerMed, seeks to develop a Strategy Research and Innovation Agenda (SRIA) for the European Union. Find attached the protocol that corresponds to one of the first steps in the PROPHET, namely a review that aims to map the evidence and highlight the evidence gaps in research or use of biomarkers in personalized prevention in the general population, as well as their integration with digital technologies

Interactive Gap Maps on Available Biomarkers for Risk Prediction and Stratification in Cancer, Cardiovascular, and Neurodegenerative Diseases (PROPHET Project)

Web del proyecto: https://biodama.isciii.es/prophet/ | Material: “Biomarkers for personalized prevention of chronic diseases”: https://osf.io/wg62b/ - "Interactive Evidence Gap Maps": https://osf.io/48g5p/Artículo disponible en: http://hdl.handle.net/20.500.12105/19654[EN] The PROPHET project (“PeRsOnalized Prevention roadmap for the future HEalThcare”), funded by the European Union's Horizon Europe research and innovation program, aims to assess the effectiveness, clinical utility, key success factors, and gaps in personalised preventive approaches for healthcare settings. One of the main task focuses on biomarkers for personalised prevention in the general adult population and their integration with digital technologies. The objective of the task is to highlight gaps in biomarkers research for primary and secondary prevention for cancer, cardiovascular, and neurodegenerative diseases. Three rapid scoping reviews were conducted in parallel by three research teams, one for each group of diseases: cancer, cardiovascular and neurodegenerative diseases. The reviews used a common protocol and framework for searching, data extraction and the representation of results, with disease specific corresponding information and specifications. The following evidence and gap map is a product of these scoping reviews. [ES] El proyecto PROPHET (“PeRsOnalized Prevention roadmap for the future HEalThcare”), financiado por el programa de investigación e innovación Horizonte Europa de la Unión Europea, tiene como objetivo evaluar la eficacia, la utilidad clínica, los factores clave de éxito y las lagunas en los enfoques preventivos personalizados para entornos sanitarios. Una de las principales tareas se centra en los biomarcadores para la prevención personalizada en la población adulta general y su integración con las tecnologías digitales. El objetivo de la tarea es resaltar las lagunas en la investigación de biomarcadores para la prevención primaria y secundaria del cáncer, enfermedades cardiovasculares y neurodegenerativas. Tres equipos de investigación llevaron a cabo en paralelo tres revisiones rápidas de alcance, una para cada grupo de enfermedades: cáncer, enfermedades cardiovasculares y neurodegenerativas. Las revisiones utilizaron un protocolo y un marco común para la búsqueda, la extracción de datos y la representación de los resultados, con la información y especificaciones correspondientes específicas de la enfermedad. La siguiente evidencia y mapa de brechas es producto de estas revisiones de alcance.Co-funded by the European Union. UK participant in Horizon Europe Project PROPHET is supported by UKRI grant number 10040946 (Foundation for Genomics & Population Health)