charting Immunological Maps of Populations Across Complex disease and lifetime Trajectories

Descrizione del progetto

Decifrare il costo cellulare della longevità

Le persone vivono più a lungo, ma l’aspettativa di salute (il periodo di vita libero da malattie croniche) non ha tenuto il passo. L’invecchiamento è definito da un lento accumulo di condizioni croniche. Al centro di questo declino c’è il sistema immunitario, che registra gli effetti cumulativi della genetica, dello stile di vita e dei fattori di stress ambientale. Tuttavia, la nostra capacità di leggerlo rimane limitata. Il progetto IMPACT, finanziato dal CER, intende tradurre questi complessi segnali cellulari in uno strumento predittivo per la salute pubblica. In particolare, utilizza tecnologie a cellula singola per osservare gli stati e i comportamenti specifici di singole cellule nel corso della vita adulta. Si tratta di un passaggio alla visione del sistema immunitario come un paesaggio dinamico e in via di invecchiamento.

Obiettivo

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.