charting Immunological Maps of Populations Across Complex disease and lifetime Trajectories

Description du projet

Comprendre le coût cellulaire de la longévité

Les individus vivent plus longtemps, mais la durée de vie en bonne santé (la période de vie sans maladie chronique) n’a pas suivi le rythme. Le vieillissement se caractérise par une lente accumulation de maladies chroniques. Le système immunitaire, qui enregistre les effets cumulatifs de la génétique, du mode de vie et des facteurs de stress environnementaux, joue un rôle central dans ce déclin. Cependant, notre capacité à le lire reste limitée. Le projet IMPACT, financé par le CER, vise à traduire ces signaux cellulaires complexes en un outil prédictif pour la santé publique. Plus précisément, l’équipe utilise des technologies unicellulaires pour observer les états et les comportements spécifiques de cellules individuelles tout au long de la vie adulte. Il s’agit de considérer le système immunitaire comme un paysage dynamique et vieillissant.

Objectif

The extending human lifespan and its associated accumulation of morbidities due to chronic disorders calls for new models to accelerate the early detection, prognosis and treatment of chronic conditions. To date, anchoring detailed molecular knowledge of disease processes with diagnoses of chronic diseases from ‘real-world’ biomedical data remains an open challenge.The immune system plays a central role in human health and survival, while deterioration of immune function is implicated in the development of many devastating chronic conditions. While many aspects of immune functions have been studied in exquisite molecular detail, we still lack a comprehensive understanding of how lifestyle factors, environmental exposures and biology contribute to deterioration of immune functions during the human life-course, and consequently to risk of disease as individuals age. With this project we propose a new research paradigm to study chronic human diseases by combining the power of single-cell technologies with multimodal information of health states and genomics derived in large-scale population settings. In Objective 1, we will use state of the art statistical modelling on a world-unique dataset of 12M peripheral blood mononuclear cells (PBMCs) generated by my group. We will combine immunological states with data from health records to discover cell states associated with markers of normal ageing processes, diverse disease diagnoses and environmental exposures. In Objective 2, we will use multimodal profiling and ex vivo experiments to validate genes and networks associated with disease-relevant cell state variation. In Objective 3, we will apply this new knowledge to predict the long-term risk of disease in diverse population settings. Overall, this project promises to add a fundamental new perspective to our understanding of the dynamic changes of the immune system over the human adult lifecourse, and its interaction with health and disease states.