https://doi.org/10.1038/s41586-020-2715-9 Accelerated Article Preview LifeTime and improving European healthcareW through cell-based interceptive medicineE VI Received: 29 April 2020 Nikolaus Rajewsky, Geneviève Almouzni, Stanislaw A. Gorski, Stein Aerts, Ido Amit, Michela G. Bertero, Christoph Bock, Annelien L. Bredenoord, GiacomoE Cavalli, Accepted: 25 August 2020 Susanna Chiocca, Hans Clevers, Bart De Strooper, Angelika Eggert, Jan Ellenberg, Accelerated Article Preview Published Xosé M. Fernández, Marek Figlerowicz, Susan M. Gasser, NorbertR Hubner, Jørgen Kjems, online 7 September 2020 Jürgen A. Knoblich, Grietje Krabbe, Peter Lichter, Sten Linnarsson, Jean-Christophe Marine, John Marioni, Marc A. Marti-Renom, Mihai G. Netea, DörtheP Nickel, Marcelo Nollmann, Cite this article as: Rajewsky, N. et al. Halina R. Novak, Helen Parkinson, Stefano Piccolo, Inês Pinheiro, Ana Pombo, Christian Popp, LifeTime and improving European healthcare Wolf Reik, Sergio Roman-Roman, Philip Rosenstiel, Joachim L. Schultze, Oliver Stegle, through cell-based interceptive medicine. Amos Tanay, Giuseppe Testa, Dimitris Thanos, EFabian J. Theis, Maria-Elena Torres-Padilla, Nature https://doi.org/10.1038/s41586-020- Alfonso Valencia, Céline Vallot, Alexander van Oudenaarden, Marie Vidal, Thierry Voet & 2715-9 (2020). LifeTime Community L Open access C This is a PDF fle of a peer-reviewedI paper that has been accepted for publication. Although unedited, the Tcontent has been subjected to preliminary formatting. Nature is providing this early version of the typeset paper as a service to our authors and readers. The text andR fgures will undergo copyediting and a proof review before the paper is published in its fnal form. Please note that during the production process errors may beA discovered which could afect the content, and all legal disclaimers apply.D E T A R E L E C C A Nature | www.nature.com Perspective LifeTime and improving European healthcare through cell-based interceptive medicine W 1,2,3,4,206 5,206 1,206 https://doi.org/10.1038/s41586-020-2715-9 Nikolaus Rajewsky ✉, Geneviève Almouzni ✉, Stanislaw A. Gorski ✉, 6,7 8 9 10,11,12 E 13 Stein Aerts , Ido Amit , Michela G. Bertero , Christoph Bock , Annelien L. Bredenoord , Received: 29 April 2020 Giacomo Cavalli14, Susanna Chiocca15, Hans Clevers16,17,18,19, Bart De StrooperI6,20,21, Accepted: 25 August 2020 Angelika Eggert3,22, Jan Ellenberg23, Xosé M. Fernández24, Marek Figlerowicz25,26, 27,28 29,2,3,4 30,31 V 32,33 Susan M. Gasser , Norbert Hubner , Jørgen Kjems , Jürgen A. Knoblich , Published online: 7 September 2020 Grietje Krabbe1, Peter Lichter34, Sten Linnarsson35,36, Jean-Christophe Marine37,38, Open access John Marioni39,40,41, Marc A. Marti-Renom9,42,43,44, Mihai G. Netea45,46,47E, Dörthe Nickel24, Marcelo Nollmann48, Halina R. Novak49, Helen Parkinson39, Stefano Piccolo50,51, Inês Pinheiro24, Ana Pombo1,52, Christian Popp1, Wolf Reik41,53,54R, Sergio Roman-Roman55, Philip Rosenstiel56,57, Joachim L. Schultze47,58, Oliver Stegle59,60,39,41, Amos Tanay61, Giuseppe Testa62,63,64, Dimitris Thanos65, Fabian J. TheisP66,67, Maria-Elena Torres-Padilla68,69, Alfonso Valencia70,44, Céline Vallot55,71, Alexander van Oudenaarden16,17,18, Marie Vidal1, Thierry Voet7,41 & LifeTime Community* E LifeTime aims to track, understand andL target human cells during the onset and progression of complex diseasesC and their response to therapy at single-cell resolution. This mission will be implemented through the development and integration of single-cell multi-omicsI and imaging, artifcial intelligence and patient-derived experimentalT disease models during progression from health to disease. Analysis of such large molecular and clinical datasets will discover molecular mechanisms, createR predictive computational models of disease progression, and reveal new drug targets and therapies. Timely detection and interception of disease embedded inA an ethical and patient-centered vision will be achieved through interactions across academia, hospitals, patient-associations, health data managementD systems and industry. Applying this strategy to key medical challenges in cancer, neurological, infectious, chronic infammatory and cardiovascular Ediseases at the single-cell level will usher in cell-based interceptive medicine in T Europe over the next decade. A While advances in medicine have led to spectacular progress in certain molecular causes that trigger deviations from healthy trajectories and disease areas, most chronic disorders still partially or totally escape drive cells and tissues towards disease (Fig 1). Timely detection and cure. This is mainly because Rmost diseases are only detected late once successful treatment of disease will depend crucially on our ability to gross physiological symptoms manifest themselves, when tissues and understand and identify when, why, and how cells deviate from their organs have often undergoneE extensive or irreversible changes. At this normal trajectory. More accurate cellular and molecular diagnostics stage, the choice of interventions is typically quite limited. It is difficult will enable us to intercept disease sufficiently early to prevent irrepa- to predict if a patientL will respond to a particular treatment, which often rable damage. To achieve this interceptive medicine (Fig 1), we need to involve invasive or aggressive therapies that can be of modest benefit, invest in approaches that provide a detailed molecular understanding or if therapyE resistance emerges leading to relapse. The reason for this of the basis of disease heterogeneity in tissues, with sufficient molecu- is that despite technology-driven revolutions that enable a patient’s lar, cellular and temporal resolution. physiologyC to be investigated at the level of molecules1,2 and placed Several challenges need to be overcome to reveal the complex dis- in the context of tissues3,4 in most cases our detection and predictive ease landscapes comprised of vast numbers of potential cellular states Cpower is limited by our incomplete mechanistic understanding of dis- (Fig 1). Firstly, we need to resolve normal cellular heterogeneity across ease at the cellular level. space and time to begin to determine the cell types, states and cell-cell Cells develop and differentiate along specific lineage trajectories interactions in the body. This is a main goal of the Human Cell Atlas A 5 6 forming functionally distinct cell types and states , which together consortium . However, to discover the cellular basis of diseases requires with their neighbouring cells underlie and control normal physiol- that we track cellular heterogeneity and molecular composition of cell ogy (Fig 1). However, we have not been able to systematically detect trajectories in health and during disease progression longitudinally - and understand the molecular changes that propel an individual cell throughout a patient’s lifetime (“LifeTime”). Secondly, we need to under- along these trajectories during normal development or ageing nor the stand the molecular mechanisms and complex networks that define a Affiliations appear at the end of the paper. Nature | www.nature.com | 1 Perspective cell’s state, and control its function, fate and trajectory over time to be builds on and will collaborate with related international initiatives that able to reconstruct a cell’s history and predict its future. This is essential are paving the way by producing reference maps of healthy tissues in for selecting the optimal intervention for an individual patient. Thus the body, such as the Human Cell Atlas (HCA)6 and the NIH Human systematic and longitudinal profiling of samples from many patients is Biomolecular Atlas Program (HuBMAP)9. required. Third, computational frameworks for integrating temporal data as well as patient profiles with large cohorts to identify regulatory changes and to dissect the causes and manifestations of disease remain Technology development and integration elusive. Current attempts to model human disease have not succeeded Single-cell technologies, particularly transcriptomics, are generatingW W in integrating the thousands of molecular phenotypes that are acquired the first reference cell atlases of healthy tissues and organs, revealing a from patients. Finally, we are limited by our lack of knowledge of the previously hidden diversity of cell subtypes and functionally distinct 6 E E underlying causes of disease. Any given patient’s response to a specific cell states . Single-cell analyses of patient samples are beginning to therapy may require testing or modifying cells from the patient in an provide snap-shots of the changes in cell compositionI and pathways I experimental system, a challenge yet to be routinely implemented. associated with diseases including cancer10–15, chronic inflammatory 16,17 18–20 21V 22 V To address these challenges experts from different disciplines came diseases , Alzheimer’s disease heart failure , and sepsis . Since together in 2018 to form the LifeTime Initiative (https://www.lifetime- pathophysiological processes within individual cells involve different initiative.eu). It has since grown to be a pan-European community molecular levels, understanding the underlyingE mechanisms requires E consisting of over 90 research institutions with the support from 80 the integration of current single-cell approaches. LifeTime proposes the companies, several funding agencies and national science academies. integration of several approaches7. ThisR includes combining transcrip- R In 2019 the