Content description of the project
Non Communicable Diseases (NCDs) are the leading cause of ill health worldwide and their burden is increasing due to ageing and changing demographic patterns in the population (fertility, life expectancy, mortality and causes of death). The NCD burden is particularly large in the WHO European Region, where NCDs cause 90% of deaths and 85% of years lived with disability is caused by four major NCDs: cardiovascular diseases, cancers, chronic respiratory disease and diabetes, that are all linked to other NCDs. A large proportion of NCDs that are avoidable, preventable and amenable to health care cause more than two thirds of NCD burden in the Region. Recently, the links between air pollution, other environmental factors, psychological, social and economic risks and NCDs have been increasingly recognized. A strengthened effort is necessary across multiple sectors with effective tools as the impact of NCDs goes well beyond ill health and poor well-being, as they also cause huge economic losses.
EU4Health programme 2021-2027 – a vision for a healthier European Union, was adopted as a contribution to the long-term health challenges by building stronger, more resilient health systems. The main aims were established as (i) health promotion and disease prevention, in particular cancer, next to (ii) reinforcing health data, digital tools and services, next to digital transformation of healthcare. In addition, Healthier together – EU non-communicable diseases initiative (NCD) was launched in December 2021 to support EU countries in identifying and implementing effective policies and actions to reduce the burden of major NCDs and improve citizens’ health and well-being in the 2022-2027 period (cardiovascular diseases, diabetes, chronic respiratory diseases, mental health and neurological disorders, cancer). Actions on cancer, which is also a major NCD, are covered in Europe’s Beating Cancer Plan. While addressing particular challenges of each disease group, the initiative as such promotes a holistic and coordinated approach to prevention, care, better knowledge, data, screening and early detection, diagnosis and treatment management.
Microbiomes with their metabolic activities contribute to hundreds of blood metabolites, 64% blood metabolites were significantly associated with either host genetics or the gut microbiome, with 69% of these associations driven solely by the microbiome, 15% driven solely by genetics and 16% under hybrid genome–microbiome control. In addition, more than 70% of metabolites present in human feces are of microbiome origin. Hence, microbiome derived metabolites constitute an important source and modifier of signaling, energetic and other molecules, driving, regulating and cross talking to human genome and epigenetics but also other microbiome constituents. Different metabolic groups of microorganisms are involved, depending on the time of development, body location, diet, and a number of other parameters. As a result of the 3.8 x 10e9 years of evolution of self replicating biochemical automates into currently existing complex microbiome systems nonlinear interactions resulted in novel traits to appear in these systems that were not possessed by any of the constituents before, giving rise to tremendous number of interacting biochemical pathways involved in production/degradation of natural chemical compounds, not traditionally observed, that were, are being and can be linked to the rise in NCDs. Science (microbial chemistry, biogeochemistry, ecological chemistry, systems medicine, computational biology and others) has provided ample evidence of existence of additional vast number of chemical compounds in this (bio)chemical space, reaching estimates of 60 x 10e6 natural metabolites being present in the human body alone. In addition to naturally occurring chemical space, humans have been inventing highly effective artificial ways to mass produce an ever increasing number of novel compounds in evolutionary speaking short time that are being released or deposited to the environment, inhaled, applied or ingested by humans and other living beings: pharmaceuticals (drugs), industrial chemicals, innovative polymers (plastics, bio(polymers)), food supplements, diets, sweeteners, amounting to exponential increase reaching tens of thousands of novel compounds being introduced per year with adverse effects on human health and reproduction.
Objectives of the proposed research:
In the present proposal entitled “Building Efficient NCDs Early Warning Tools (BE NEWT)” the following major decisive steps to NCDs control are going to be made, spanning multiple separate fields of science and research next to clinics to provide the following solutions:
Objective 1: Fully functional gut microbiome response chip - GMRC as novel tool to profile microbiome metabolic responses in real time in high-throughput manner will be developed as a multiplex tool from its existing TRL5 implementation to TRL8 or above (96 to 384 plex). The number of effective GMRC reporting mechanisms will be increased to 6 and used for monitoring the personalized fine-scale metabolic responses to various chemical challenges (e.g. micro and nano plastic, drugs, pharmaceuticals of choice, food additives, diets, fecal matter transplantation donor-acceptor characteristics, concentration gradients etc.). Most efficient operation, sample storage, reproduction protocols are going to be elucidated and distilled, the resulting data collected in machine readable format. For urine, swab and saliva samples additional optimized protocols will be established.
Objective 2: To establish chemical links between microbiome space in relation to paired urine metabolomes - for interrogation of chemical space of test gut samples and microbiome responses observed in GMRC (WP1), different chemometric analyses will be used: 1H-NMR, GC-MS, LC-MS-QTOF, GC-MS/MS, ATR-FTIR(solid/liquid), NIRS, MIRS, XRFS, metagenomics (WGS (taxonomy, diversity, functional gene, enzymatic reactions, metabolic pathways, predicted metabolites)). These will provide information layers for data driven, top down, high-throughput, chemometric, ML/AI applicable approach, capable of integrating over multiple data layers. Gut sample info will be linked to urine metabolomes and chemistry, due to its medical relevance and availability (hence feces-urine pairing; with additional extensions to serum and swab samples where ethically and clinically feasible) for the same subjects. Based on agglomerated data, statistical links between medically relevant groups will be established. In order to accomplish that, our existing parts of the computational infrastructure for data integration of both data streams (gut - urine) wil be further developed and synchronized. Bioinformatic tools will be produced as stable self sufficient Singularity containers ready for heavy duty HPC deployment. This will result in integration of workflows from various data streams and matrices, creation of Singularity containers, conversions of data formats, QC, data integration steps, into big data assembly, amenable for in-depth exploration. Non/parametric statistics and ML/AI will be prepared and made ready to train, test and validate classification models on real clinical data (WP3) as NCDs early warning tools for medicine.
Objective 3: Deployment of developed tools to clinical settings (pairing gut-urine samples) to build early NCD warning tools. Assembled collection of paired samples from NCDs relevant clinical environments, early timepoints, deployment of all developed analytical tools to real clinical samples (urine-gut; other pairs if possible) to generate relevant data matrices, analysis of generated data, model building, testing and validation. Generation of early warning computational tools based on real clinical data that take in as input GMRC data, microbiome metagenomic data, gut metabolomic and chemical data, paired urine characteristics or any combination of the available layers. Assessment of the analytical techniques, measured variables, to formulate a more limited set-up of most cost-effective measurements to support NCDs early warning and monitoring.
Objective 4: To prepare an ethical and legal framework for future biobanks containing large-scale data and human metadata in Slovenia within ELIXIR-SI. Governing protocols and materials will be finalized to secure the ethical permission to initiate and proceed with medical sampling beyond technology test samples, to establish effective data protection measures and procedures, define access rights to agglomerated data and define responsibilities of data scientists during and after project completion, define procedures for continuous data banks growth and extensions, compliant with medical ethics, GDPR, FAIR and EU next to national legislation, following best practices.
Objective 5: To integrate medical data with ELIXIR-SI infrastructure to generate infrastructure of tomorrow. Integration of the developed protocols, pipelines and databases produced in WP1, WP2, WP3 with structured, operational, accessible, secure empty databases at ELIXIR-SI in order (i) to be populated with real data from analyses of clinical samples; (ii) to provide expandable sets of NDCs oriented databases to serve the community and science of the future, (iii) to prepare the basal form of scientific/national infrastructure, resulting in datasets amenable for high throughput statistical interrogation and as building blocks for infrastructure of tomorrow as national NCD oriented screening databases and medical programs to be hosted permanently by ELIXIR-SI (GDPR, FAIR, Ethical Commission Permit, EU and national law compliant, anonymized, transformed, local), and made available to eligible researchers for further exploration under the ELIXIR-SI flagship (see the existing: SVIT, DORA, ZORA)
Objective 6: Project management, dissemination and exploitation.The objectives for the effective development of the project proposal include data sharing platform, mid-term and final report, project webpage, at least 12 peer-reviewed scientific publications and active popular science dissemination events to showcase the efforts invested in NCDs detection, control, but also to raise public awareness on the problem being addressed in this project proposal. There is an urgent need for the development of such a screening approach as an early warning tool to support digitalisation and innovation in the use of real world data to open new possibilities for NCDs control, in line with EU health programs and initiatives, next to enable systematic studies of drug/chemicals -microbiome interactions.
Work plan and implementation
Composition of the project team with links to SICRIS
prof. dr. Blaž Stes (National Institute of Chemistry), 19104 https://cris.cobiss.net/ecris/si/sl/researcher/11176
prof. Janez Plavec (National Institute of Chemistry), 10082 https://cris.cobiss.net/ecris/si/sl/researcher/6890
dr. Damjan Makuc (National Institute of Chemistry), 24975 https://cris.cobiss.net/ecris/si/sl/researcher/18322
prof. dr. Blaž Likozar (National Institute of Chemistry), 25446 https://cris.cobiss.net/ecris/si/sl/researcher/18823
dr. Miša Mojca Cajnko (National Institute of Chemistry), 37381 https://cris.cobiss.net/ecris/si/sl/researcher/43169
doc. dr. Uroš Novak (National Institute of Chemistry), 33161 https://cris.cobiss.net/ecris/si/sl/researcher/36026
Maša Ošlak (National Institute of Chemistry), 59473 https://cris.cobiss.net/ecris/si/sl/researcher/56787
prof. dr. Dušan Žigon (Institut Jožef Stefan), 03950 https://cris.cobiss.net/ecris/si/sl/researcher/4966
dr. Tina Kosjek (Institut Jožef Stefan), 27733 https://cris.cobiss.net/ecris/si/sl/researcher/20411
dr. Daša Perko (University Medical Centre Ljubljana), 35406 https://cris.cobiss.net/ecris/si/sl/researcher/40424
Domen Trampuž, 56616 https://cris.cobiss.net/ecris/si/sl/researcher/53549
Ula Arkar, 56193 https://cris.cobiss.net/ecris/si/sl/researcher/53051
Eva Vrščaj, 55105 https://cris.cobiss.net/ecris/si/sl/researcher/51787
prof. dr. Damjan Osredkar, 21413 https://cris.cobiss.net/ecris/si/sl/researcher/13336
prof. dr. Rok Gašperšič, 19210 https://cris.cobiss.net/ecris/si/sl/researcher/11276
prof dr. Eda Vrtačnik-Bokal, 12177 https://cris.cobiss.net/ecris/si/sl/researcher/13459
dr. Martin Štimpfel, 33917 https://cris.cobiss.net/ecris/si/sl/researcher/38335
Melita Bokalič, 55066 https://cris.cobiss.net/ecris/si/sl/researcher/51741
Jasna Oražem, 36604 https://cris.cobiss.net/ecris/si/sl/researcher/42015
Haris Munjaković, 56921 https://cris.cobiss.net/ecris/si/sl/researcher/53883
dr. Branimir Leskošek, 15355 https://cris.cobiss.net/ecris/si/sl/researcher/14847
dr. Polonca Ferk, 22621 https://cris.cobiss.net/ecris/si/sl/researcher/15645
