Main hypotheses: 1) Integration of multi-omics data from samples of progeroid mice obtained at two disease stages (early and intermediate, before severe disease signs develop) will identify robust biomarkers of HGPS stage/progression; 2) Biomarkers identified in progeroid mouse plasma and PBMCs might find clinical application upon validation in human samples.
WP1-6 will cover research tasks carried out in WT and HGPS mice at early and intermediate disease stage. Mice will be thoroughly phenotyped, and samples for omics studies will be collected (aorta—a major progerin target—and plasma and PBMCs—which have high translational value). Results from each omics approach will be analyzed to identify alterations that best correlate with disease stage. In WP7, computational and mathematical analysis and modeling will unveil complex interactions between phenotype and multi-omics data. This holistic approach will facilitate the identification of robust biomarkers of HGPS stage and progression. To expedite translation from basic to clinical research, candidate biomarkers identified in mice will be assessed in human plasma and PBMCs (WP8).
The participation of three PAOs in the project ensures clinical translation and dissemination of results to targeted HGPS audiences and lay public. In addition, ProgerOmics data management plan will ensure “FAIR” data collection and deposit in Open Access repositories after publication of results.
To achieve ProgerOmics goals, the proposal is structured in 10 work packages (WPs).
The ample experience of partners in all methods needed to carry out the proposed research ensures its feasibility.
HGPS is an ultra-rare disease (estimated prevalence 1 in18 million people); for this reason, HGPS mouse models are invaluable tools to advance in our understanding of the disease. To discover biomarkers of HGPS stage and progression, ProgerOmics will take advantage of the progeroid HGPS mouse model that was generated and thoroughly characterized by P1. P1 will collect plasma and PBMCs (samples with easy clinical translation for biomarker purposes), and aorta (a tissue severely damaged by progerin) from HGPS mice at early and intermediate HGPS stages and age-matched WT controls. Samples will be snap frozen and shipped to all ProgerOmics partners for their omics studies (WP3-WP6). P1 will also perform in vivo phenotyping of mice (WP1 and WP2) 1-2 weeks before euthanasia. Post-mortem studies will focus on immunohistopathological examination in aorta (WP1), major target of progerin, to generate clinical readouts of disease that can be associated with the results of radiomics (WP2), individual omics studies (WP3-WP6), and multi-omics integration (WP7).
To identify non-invasive multimodal imaging biomarkers associated with the presence of HGPS clinical signs and their progression in mice.
In vivo multimodal imaging data can be used alone or combined with non-imaging data such as omics data for supporting biomedical decisions. Imaging data mining (“radiomics”) may contribute to finding new biomarkers that permit monitoring of disease progression, which may lead to more precise risk stratification in patients and assessment of treatment efficacy.
To identify alterations in RNA expression (miRNA, LncRNA, cRNA & mRNA) associated with the presence of HGPS clinical signs and their progression in mice.
Little is known about the impact that ubiquitous progerin expression has on the expression of long and short RNAs species, and on their target genes in different tissues. A global picture of the transcriptomic landscape in HGPS plasma, PBMCs and aorta will be an invaluable tool for better understanding mechanisms underlying disease onset and progression and to identify clinically meaningful biomarkers of HGPS at the transcriptional level.
To identify by single-cell analysis epigenetic profiles associated with the presence of HGPS clinical signs and their progression in mice.
Transcriptome analysis at single cell resolution (single cell RNA-seq) has led to significant advances in our understanding of biology, elucidating cellular heterogeneity in complex systems and tissues, and enabling discovery of novel cell types, states, and biomarkers with clinical relevance. However, single cell RNA-seq does not directly capture information about the drivers of gene regulation.
This has left gaps in our understanding of how gene regulatory programs are established, and ultimately how cell types and states are specified. To bridge this gap, innovative multi-omics tools have emerged that simultaneously interrogate both gene expression and chromatin accessibility, enabling direct epigenetic and transcriptomic measurements at a single cell level.
To identify protein alterations associated with the presence of HGPS clinical signs and their progression in mice.
Global “discovery proteomics” (= classical proteomics) is a powerful tool to extract comprehensive information from plasma, cells, and tissues which can be used in an integrative approach for diagnosis, assessment of prognosis and therapeutic decision making in clinics. Several CVD entities (e.g. atherosclerosis, degenerative aortic stenosis, and acute coronary syndrome) have clearly benefited from global “discovery proteomics” studies in the clinical setting.
Here, we will use “discovery proteomics” to reveal HGPS proteomic profiles with potential clinical application. We will also analyze samples from WT and HGPS mice by “quantitative targeted proteomics”, which allows the highest sensitivity, specificity and accuracy among mass spectrometry (MS)-based proteomic methods and is commonly employed in clinical practice.
To identify metabolite perturbations associated with the presence of HGPS clinical signs and their progression in mice.
Metabolomics is a powerful tool for biomarkers discovery which has been scarcely used to study HGPS.
In this project we will perform untargeted metabolomics with sensitive mass spectrometry analysis after separation by liquid and gas mass chromatography (LC-MS and GC-MS, respectively) to identify alterations in small molecules associated with HGPS. We will also perform targeted metabolomics to quantify specific metabolites.
Use bioinformatics tools to integrate mouse phenotypic data (WP1-2) and omics data (WP3-6) to identify biomarkers of HGPS presence and progression with potential clinical value.
Previous omics-based HGPS studies have not led to the incorporation of disease-progression biomarkers into clinical practice, largely due to the multifaceted cellular and molecular basis of HGPS and its complex clinical phenotype, which requires a holistic strategy that has not been implemented to date. Omics-based HGPS studies have generally been limited by the use of a single omics strategy and the analysis of a single tissue/cell type without considering distinct disease stages. Here, we will overcome these limitations by integrating data from different omics in three different types of samples from HGPSrev mice at early and intermediate disease stages.
This approach will allow us to construct a refined list of biomarkers that robustly indicate HGPS presence and progression in mice, which will be used in WP8 for validation in human samples.
To validate the candidate mouse biomarkers identified in WP7 in human plasma and PBMCs from HGPS patients.
HGPS progression shows high inter-individual variability, with death occurring from 6 to 20 years (average lifespan: 14.5 years), but biomarkers to predict prognosis after diagnosis are lacking. This limits the capacity to implement early interventions to decelerate deterioration and prolong quality of life and survival of HGPS patients. Likewise, robust biomarkers are needed to score the therapeutic benefit of current and future treatments. The predictive biomarkers identified in HGPS mouse plasma and PBMCs using our proposed multi-omics and integrative strategy may help overcome these limitations. To ascertain their clinical value, we will perform pilot studies in human samples of HGPS patients and gender- and age-matched healthy controls.
HGPS is an ultra-rare disease, with only around 150 cases identified through genetic testing worldwide. Therefore, the collections of samples from properly-diagnosed HGPS patients are small in number and priceless. ProgerOmics will rationalize the use of HGPS patients´ samples by refining the list of candidate biomarkers to be tested through our holistic and integrative approach (WP2-WP7), which will be validated in WP8 by performing targeted analysis of the refined list using the most adequate methods. Our studies may lay the ground for improved monitoring of HGPS progression using circulating biomarkers, which will improve personalized medicine for patients.
To maximize the communication, dissemination, and exploitation of results generated in ProgerOmics.
Dissemination of results to the scientific community is essential to optimize the possibilities of transfer of the newly generated knowledge to the relevant stakeholders and interested groups, including basic and clinical HGPS researchers, HGPS patient organizations, pharmaceutical companies, biotechnology companies, lay public, health providers and authorities. This is critical to increase patient engagement and for improving healthcare access for rare-disease patients and increasing international policy cooperation. Early detection, correct protection and clear strategy on how to handle further inventions is critical to achieve maximal impact and translation of the results to the clinic.
To coordinate and manage ProgerOmics and prepare and submit reports.
