Suchergebnisse

As genome-wide association studies (GWAS) have grown in size, the number of genetic variants that have been associated per disease has correspondingly increased. Despite this increase in the number of single-nucleotide polymorphisms (SNPs) identified per disease, their biological interpretation has in many cases remained elusive. To address this, we have combined GWAS results with orthogonal sources of evidence, namely the current knowledge of molecular pathways; real-world clinical data from six million patients; RNA expression across tissues from Alzheimer's disease (AD) patients, and purpose-built rodent models for experimental validation. In more detail, first we show that when examined at a pathway level, analysis of all GWAS studies groups AD in a cluster with disorders of immunity and inflammation. Using clinical data, we show that the degree of comorbidity of these diseases with AD correlates with the strength of their genetic association with molecular participants in the Janus kinases/signal transducer and activator of transcription (JAK-STAT) pathway. Using four independent RNA expression datasets we then find evidence for the altered regulation of JAK-STAT pathway genes in AD. Finally, we use both in vitro and in vivo rodent models to demonstrate that Aβ induces gene expression of the key drivers of this pathway, providing experimental evidence to validate these data-driven observations. These results therefore nominate JAK-STAT anomalies as a prominent aetiopathological event in AD and hence a potential target for therapeutic development, and moreover demonstrate a de novo multi-modal approach to derive information from rapidly increasing genomic datasets. ; This work was supported by the Wellcome Trust [104025], the European Union's Horizon 2020 research and innovation programme 2014-2020 under Grant Agreement No 634143, the MRC Data Pathfinder award [MC_PC_17215], and the NIHR Oxford Health Biomedical Research Centre.

Most hospitals have already implemented information systems and Electronic Health Records (EHRs), but the reuse of such data for research is still infrequent. We present a pilot project on the exploitation of clinical information from a Spanish hospital database in the context of the European Medical Information Framework project (EMIF). Specific use cases such as patients with diabetes mellitus type 2, obesity and dementia were assessed, by exploiting EHR data integrated from several separated clinical databases. The possibility to analyse the features of specific groups of patients based on their diagnosis codes can provide new data about relationships between different conditions that can contribute for decision-making, healthcare and research. ; EMIF is a project funded by the Innovative Medicines Initiative (IMI), a public-private partnership between the European Union and the European Federation of Pharmaceutical Industries and Associations (EFPIA).

eTRANSAFE is a research project funded within the Innovative Medicines Initiative (IMI), which aims at developing integrated databases and computational tools (the eTRANSAFE ToxHub) that support the translational safety assessment of new drugs by using legacy data provided by the pharmaceutical companies that participate in the project. The project objectives include the development of databases containing preclinical and clinical data, computational systems for translational analysis including tools for data query, analysis and visualization, as well as computational models to explain and predict drug safety events. ; This research received funding from the Innovative Medicines Initiative 2 Joint Undertaking under grant agreements eTRANSAFE (777365). This Joint Undertaking receives support from the European Union's Horizon 2020 research and innovation programme and EFPIA companies in kind contribution.

Objective: The objective of the study is to compare body mass index (BMI), systolic/diastolic blood pressure (SBP/DBP) and serum total cholesterol levels between dementia cases and controls at multiple time intervals prior to dementia onset, and to test time interval as a modifying factor for these associations. Design: Case-control study. Setting: Six European electronic health records databases. Participants: 291 780 cases at the date of first-recorded dementia diagnosis, compared with 29 170 549 controls randomly selected from the same databases, age matched and sex matched at this index date. Exposure: The following measures were extracted whenever recorded within each dataset: BMI (kg/m2), SBP and DBP (mm Hg) and serum total cholesterol (mmol/L). Levels for each of these variables were defined within six 2-year time intervals over the 12 years prior to the index date. Main outcomes: Case-control differences in exposures of interest were modelled for each time period and adjusted for demographic and clinical factors (ischaemic/unspecified stroke, type 2 diabetes mellitus, acute myocardial infarction, hypertension diagnosis, antihypertensive medication, cholesterol-lowering medication). Coefficients and interactions with time period were meta-analysed across the six databases. Results: Mean BMI (coefficient -1.16 kg/m2; 95% CI -1.38 to 0.93) and SBP (-2.83 mm Hg; 95% CI -4.49 to -1.16) were lower in cases at diagnosis, and case-control differences were greater in more recent time periods, as indicated by significant case-x-time interaction and case-x-time-squared interaction terms. Time variations in coefficients for cholesterol levels were less consistent between databases and those for DBP were largely not significant. Conclusion: Routine clinical data show emerging divergence in levels of BMI and SBP prior to the diagnosis of dementia but less evidence for DBP or total cholesterol levels. These divergences should receive at least some consideration in routine dementia risk screening, although underlying mechanisms still require further investigation. ; The research leading to these results has received support from the Innovative Medicines Initiative (IMI) Joint Undertaking under EMIF grant agreement n° 115372, resources of which are composed of financial contribution from the European Union's Seventh Framework Programme (FP7/2007-2013) and EFPIA companies' in kind contribution. RS and GP are part-funded by the National Institute for Health Research (NIHR) Biomedical Research Centre and Dementia Biomedical Research Unit at South London and Maudsley NHS Foundation Trust and King's College London.

INTRODUCTION: The European Medical Information Framework consortium has assembled electronic health record (EHR) databases for dementia research. We calculated dementia prevalence and incidence in 25 million persons from 2004 to 2012. METHODS: Six EHR databases (three primary care and three secondary care) from five countries were interrogated. Dementia was ascertained by consensus harmonization of clinical/diagnostic codes. Annual period prevalences and incidences by age and gender were calculated and meta-analyzed. RESULTS: The six databases contained 138,625 dementia cases. Age-specific prevalences were around 30% of published estimates from community samples and incidences were around 50%. Pooled prevalences had increased from 2004 to 2012 in all age groups but pooled incidences only after age 75 years. Associations with age and gender were stable over time. DISCUSSION: The European Medical Information Framework initiative supports EHR data on unprecedented number of people with dementia. Age-specific prevalences and incidences mirror estimates from community samples in pattern at levels that are lower but increasing over time. ; The research leading to these results has received support from the Innovative Medicines Initiative Joint Undertaking under European Medical Informatics Framework (EMIF) grant agreement no. 115372, resources of which are composed of financial contribution from the European Union's Seventh Framework Programme (FP7/2007-2013) and European Federation of Pharmaceutical Industries and Associations (EFPIA) companies' in kind contribution. R.S. and G.P. are partly funded by the National Institute for Health Research (NIHR) Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King's College London.

Whether the increased risk for coronavirus disease 2019 (COVID-19) hospitalization and death observed in Down syndrome (DS) are disease specific or also occur in individuals with DS and non-COVID-19 pneumonias is unknown. This retrospective cohort study compared COVID-19 cases in persons with DS hospitalized in Spain reported to the Trisomy 21 Research Society COVID-19 survey (n = 86) with admissions for non-COVID-19 pneumonias from a retrospective clinical database of the Spanish Ministry of Health (n = 2832 patients). In-hospital mortality rates were significantly higher for COVID-19 patients (26.7% vs. 9.4%), especially among individuals over 40 and patients with obesity, dementia, and/or epilepsy. The mean length of stay of deceased patients with COVID-19 was significantly shorter than in those with non-COVID-19 pneumonias. The rate of admission to an ICU in patients with DS and COVID-19 (4.3%) was significantly lower than that reported for the general population with COVID-19. Our findings confirm that acute SARS-CoV-2 infection leads to higher mortality than non-COVID-19 pneumonias in individuals with DS, especially among adults over 40 and those with specific comorbidities. However, differences in access to respiratory support might also account for some of the heightened mortality of individuals with DS with COVID-19. ; The lab of M.D. is supported by the Departament d'Universitats, Recerca i Societat de la Informació de la Generalitat de Catalunya (Grups consolidats 2017 SGR 926, 2017 SGR 138). We also acknowledge the support of the Agencia Estatal de Investigación (PID2019-110755RB-I00/AEI/10.13039/501100011033), the European Union's Horizon 2020 research and innovation programme under grant agreement No 848077, Jerôme Lejeune Foundation (No 2002), NIH (Grant Number: 1R01EB 028159-01), Marató TV3 (#2016/20-30), JPND Heroes project. CRG acknowledges the support of the Spanish Ministry of Science and Innovation to the EMBL partnership, the Centro de Excelencia Severo Ochoa, and the CERCA Programme/Generalitat de Catalunya. The CIBER of Rare Diseases (CIBERER) and CIBER of Physiopathology of Obesity and Nutrition (CIBEROBN) are initiatives of the ISCIII. D.R.A. is partially supported by the Fondo de Investigaciones Sanitarias (FIS grant PI19/00634, European Fund for Regional Development—EFRD) and the Foundation Jérôme Lejeune (grant no. 1777-2018). The Research Programme on Biomedical Informatics (GRIB) is a member of the Spanish National Bioinformatics Institute (INB), funded by ISCIII and EDER (PT17/0009/0014). The DCEXS is a 'Unidad de Excelencia María de Maeztu', funded by the AEI (CEX2018-000782-M). The GRIB is also supported by the Agencia de Gestio d'Ajuts Universitaris i de Recerca (AGAUR), Generalitat de Catalunya (2017 SGR 00519). AH was supported by the HERCULES Center (NIEHS P30ES019776) and by the LuMind IDSC Foundation.