Background: Personalised medicine is a medical model that aims to provide tailor-made prevention and treatment strategies for defined groups of individuals. The concept brings new challenges to the translational step, both in clinical relevance and validity of models. We have developed a set of recommendations aimed at improving the robustness of preclinical methods in translational research for personalised medicine. Methods: These recommendations have been developed following four main steps: (1) a scoping review of the literature with a gap analysis, (2) working sessions with a wide range of experts in the field, (3) a consensus workshop, and (4) preparation of the final set of recommendations. Results: Despite the progress in developing innovative and complex preclinical model systems, to date there are fundamental deficits in translational methods that prevent the further development of personalised medicine. The literature review highlighted five main gaps, relating to the relevance of experimental models, quality assessment practices, reporting, regulation, and a gap between preclinical and clinical research. We identified five points of focus for the recommendations, based on the consensus reached during the consultation meetings: (1) clinically relevant translational research, (2) robust model development, (3) transparency and education, (4) revised regulation, and (5) interaction with clinical research and patient engagement. Here, we present a set of 15 recommendations aimed at improving the robustness of preclinical methods in translational research for personalised medicine. Conclusions: Appropriate preclinical models should be an integral contributor to interventional clinical trial success rates, and predictive translational models are a fundamental requirement to realise the dream of personalised medicine. The implementation of these guidelines is ambitious, and it is only through the active involvement of all relevant stakeholders in this field that we will be able to make an impact and effectuate a change which will facilitate improved translation of personalised medicine in the future.

Personalised medicine (PM) presents a great opportunity to improve the future of individualised healthcare. Recent advances in -omics technologies have led to unprecedented efforts characterising the biology and molecular mechanisms that underlie the development and progression of a wide array of complex human diseases, supporting further development of PM. This article reflects the outcome of the 2021 EATRIS-Plus Multi-omics Stakeholder Group workshop organised to 1) outline a global overview of common promises and challenges that key European stakeholders are facing in the field of multi-omics research, 2) assess the potential of new technologies, such as artificial intelligence (AI), and 3) establish an initial dialogue between key initiatives in this space. Our focus is on the alignment of agendas of European initiatives in multi-omics research and the centrality of patients in designing solutions that have the potential to advance PM in long-term healthcare strategies.

Background: Several studies performed in the last years on the brain, showed that beta2-microglobulin (β2m) and MHC can act independently of their canonical immune function to regulate normal brain development, synaptic plasticity and behaviour. Increased systemic levels of soluble β2m have been implicated in cognitive impairments like that associated with chronic haemodialysis, or aortic valve replacement. Increased soluble β2m has also been detected in the cerebral spinal fluid (CSF) of patients with HIV-associated dementia and Alzheimer’s disease (AD). Objective: To compare plasma β2m levels in healthy subjects and subjects with dementia or cognitive impairment. Methods: We measured the concentration of β2m in a cohort of 245 individuals and compared sex matched, cognitive healthy individuals. Results: We found higher levels of β2m in AD patients compared to non-AD MCI and healthy controls (2063 ng/mL ±852 versus 1613 ± 503 and 1832 ± 382 ng/mL, p< 0.001 and 0.05). Conclusions: Our data confirm that β2m could play a role in AD. However, a replication study in an independent cohort would be necessary to confirm our preliminary results.

Background: Postoperative atrial fibrillation (POAF) occurs in 30% to 50% of patients undergoing cardiac surgery and is associated with increased morbidity and mortality. Prospective identification of structural/molecular changes in atrial myocardium that correlate with myocardial injury and precede and predict risk of POAF may identify new molecular pathways and targets for prevention of this common morbid complication. Methods: Right atrial appendage samples were prospectively collected during cardiac surgery from 239 patients enrolled in the OPERA trial (Omega-3 Fatty Acids for Prevention of Post-Operative Atrial Fibrillation), fixed in 10% buffered formalin, and embedded in paraffin for histology. We assessed general tissue morphology, cardiomyocyte diameters, myocytolysis (perinuclear myofibril loss), accumulation of perinuclear glycogen, interstitial fibrosis, and myocardial gap junction distribution. We also assayed NT-proBNP (N-terminal pro-B-type natriuretic peptide), hs-cTnT, CRP (C-reactive protein), and circulating oxidative stress biomarkers (F2-isoprostanes, F3-isoprostanes, isofurans) in plasma collected before, during, and 48 hours after surgery. POAF was defined as occurrence of postcardiac surgery atrial fibrillation or flutter of at least 30 seconds duration confirmed by rhythm strip or 12-lead ECG. The follow-up period for all arrhythmias was from surgery until hospital discharge or postoperative day 10. Results: Thirty-five percent of patients experienced POAF. Compared with the non-POAF group, they were slightly older and more likely to have chronic obstructive pulmonary disease or heart failure. They also had a higher European System for Cardiac Operative Risk Evaluation and more often underwent valve surgery. No differences in left atrial size were observed between patients with POAF and patients without POAF. The extent of atrial interstitial fibrosis, cardiomyocyte myocytolysis, cardiomyocyte diameter, glycogen score or Cx43 distribution at the time of surgery was not significantly associated with incidence of POAF. None of these histopathologic abnormalities were correlated with levels of NT-proBNP, hs-cTnT, CRP, or oxidative stress biomarkers. Conclusions: In sinus rhythm patients undergoing cardiac surgery, histopathologic changes in the right atrial appendage do not predict POAF. They also do not correlate with biomarkers of cardiac function, inflammation, and oxidative stress. Graphic A graphic abstract is available for this article.

The introduction of personalized medicine, through the increasing multi-omics characterization of disease, brings new challenges to disease modeling. The scope of this review was a broad evaluation of the relevance, validity, and predictive value of the current preclinical methodologies applied in stratified medicine approaches. Two case models were chosen: oncology and brain disorders. We conducted a scoping review, following the Joanna Briggs Institute guidelines, and searched PubMed, EMBASE, and relevant databases for reports describing preclinical models applied in personalized medicine approaches. A total of 1292 and 1516 records were identified from the oncology and brain disorders search, respectively. Quantitative and qualitative synthesis was performed on a final total of 63 oncology and 94 brain disorder studies. The complexity of personalized approaches highlights the need for more sophisticated biological systems to assess the integrated mechanisms of response. Despite the progress in developing innovative and complex preclinical model systems, the currently available methods need to be further developed and validated before their potential in personalized medicine endeavors can be realized. More importantly, we identified underlying gaps in preclinical research relating to the relevance of experimental models, quality assessment practices, reporting, regulation, and a gap between preclinical and clinical research. To achieve a broad implementation of predictive translational models in personalized medicine, these fundamental deficits must be addressed.

Molecular characterization of a biological sample, e.g., with omics approaches, is fundamental for the development and implementation of personalized and precision medicine approaches. In this context, quality assessment is one of the most critical aspects. Accurate performance and interpretation of omics techniques is based on consensus, harmonization, and standardization of protocols, procedures, data analysis and reference values and materials. EATRIS, the European Infrastructure for Translational Medicine (www.EATRIS.eu), brings together resources and services to support researchers in developing their biomedical discoveries into novel translational tools and interventions for better health outcomes. Here we describe the efforts within the Horizon 2020 EATRIS-Plus project and activities of member facilities of EATRIS towards quality assessment of pre-clinical sample processing, clinical omics data generation, multi-omics data integration, and dissemination of the resources in a Multi-Omics Toolbox, which is the principal deliverable of the EATRIS-Plus project for the consolidation of EATRIS towards translational medicine.