charting Immunological Maps of Populations Across Complex disease and lifetime Trajectories

Descripción del proyecto

Descifrar el coste celular de la longevidad

La gente vive más años, pero la esperanza de vida sin enfermedades crónicas no ha aumentado al mismo ritmo. El envejecimiento se define por una lenta acumulación de enfermedades crónicas. En este declive es fundamental el sistema inmunitario, que registra los efectos acumulativos de la genética, el estilo de vida y los factores de estrés ambiental. Sin embargo, nuestra capacidad para leerlo sigue siendo limitada. El equipo del proyecto IMPACT, financiado por el CEI, pretende traducir estas complejas señales celulares en una herramienta de predicción para la salud pública. En concreto, utiliza tecnologías unicelulares para observar los estados y comportamientos específicos de las células individuales a lo largo de la vida adulta. Se trata de empezar a considerar el sistema inmunitario como un paisaje dinámico que envejece.

Objetivo

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.