Dynamic
Resilience

$60M program jointly funded withTemasek Trust
Decorative curve shape for the Dynamic Resilience program.

We are pleased to announce the selected performers.

Evandro Fei Fang, University of Oslo
Thomas Jackson, University of Birmingham
Gonzalo Jorquera Olave, Universidad de Chile
Yuxin Liu, National University of Singapore
Peter Loskill, NMI Natural and Medical Sciences Institute at the University of Tübingen
Anthony Molina, University of California San Diego
Andrew Philp, Centenary Institute / University of Technology Sydney
Paul Rubin, BioAge Labs, Inc.
Hiroki Sasaguri, RIKEN
Erdinc Sezgin, Karolinska Institutet
Claire Steves, King’s College London
Alexandra Stolzing, Loughborough University
Lian Kah Ti, National University Health System
Chinedu Udeh-Momoh, The Aga Khan University, Kenya

Human life expectancy has doubled in the past 100 years.
But for most people, our health span doesn’t match our life span. What if it could?

One of the greatest success stories of the last 100 years is the doubling in human life expectancy, from a global average of 35 years in 1900 to 70 years today1. Advances in medicine, public health, and infrastructure have greatly reduced the number of children dying before adulthood and increased the chances of most adults reaching old age. The rising number of centenarians and supercentenarians (people over 110 years) shows that it is possible for humans to live well for a very long time. Such exceptional individuals have encountered many challenges to their health over the course of their long lives, but they show a remarkable resilience – an ability to ‘bounce back’ after a significant stress event, whether that is a fall, infection, surgery, or major psychosocial stress. Resilience is the result of complex integrated physiological systems that usually maintain function and homeostasis through a series of feedback and feedforward mechanisms. Such biological resilience integrates several features including baseline reserve, ability to detect and adapt to stress, and the speed and appropriateness of responses including the ability to heal and repair. With a high baseline reserve along with correct and timely integration of other components of the stress response, the body can return to a state of homeostasis after disruption.

For most of us, however, our baseline reserves diminish as we get older and our biological maintenance systems start to fail, resulting in around half of adults over 65 suffering from at least two age-related long-term conditions (multimorbidity), increasing to ~80% of over 80s2. Our ability to cope with stress also decreases as we get older, and this loss of resilience makes us vulnerable to sudden and serious health deterioration when we encounter acute illness or injury. Such loss of reliance or vulnerability is encompassed by the clinical term frailty, with half of people 65 and older either frail or pre-frail (at risk of progressing to frailty)3. The consequence of reduced resilience is that the time we spend in good health (our health span) is much shorter than our overall lifespan4.

With increasing ageing of populations around the world, frailty is an important and growing global health problem. Adults over 65 now account for 16% of the USA and Singaporean populations, 19% in the UK and 28% in Japan. By 2050, it is projected that 1.5 billion people will be over the age of 65, and the number of oldest old – over 85 – is set to triple5. A quarter of older people fall every year, with frailty a major contributing factor. In the US, 285,000 of those who fall are hospitalised with hip fracture and 32,000 die6. In the UK, frailty accounts for over 70% of unplanned hospital admissions and 20% of hospital bed occupancy7, as well as an 8- to 10-fold increase in probability of dying after emergency admission to hospital8. Surgery in frail patients comes with higher risks of increased length of hospital stay and adverse outcomes including loss of independence, discharge to long-term care or death8, 9. The negative impact of frailty and age-related ill health on older people, their families, care-givers and societies is unsustainable10.

Importantly, frailty does not just affect those old in years – many women experience rapid declines in their health including cardiovascular disease11 and osteoporosis12 following menopause, and life-saving cancer treatments can accelerate biological ageing13. Soldiers with traumatic injuries or PTSDx4 and young adults after serious road traffic accidents15 show rapid onset of age-related diseases, equivalent to ageing by ~10 years. Sedentary lifestyles, accompanied by lack of adequate physical exercise, increase frailty prevalence ratio almost threefold16. It is now emerging that viruses such as SARS-CoV-2 can also drive premature aging17. With even mild COVID cases showing accelerated neurodegeneration18 and cardiovascular disease19, as many as 76 million people worldwide may experience early onset of age-related conditions and frailty directly as a consequence of the recent pandemic. 

Resilience as a new framework to promote healthy ageing.

We already have a strong understanding of biological ageing20, with increasing recognition that age-related diseases, multimorbidity, and indeed frailty, result from fundamental cellular and molecular biological changes driven by ageing processes21. Looking through the lens of resilience gives us a new way to understand health as we age, highlighting the need to restore steady-state and dynamic resilience and to reverse loss of homeostasis in order to prevent frailty and age-related multimorbidity.

Development of ‘anti-ageing’ therapies is already garnering multi-billion-dollar investments22, with teams across the world working on interventions to improve health as we age. What we need now to accelerate progress are quantitative, predictive and reliable measures of physiological steady-state maintenance mechanisms, and markers of dynamic resilience in response to stressor events. While frailty scores and indices can provide reasonable predictions of statistical outcomes after a stress event (recovery, infirmity or death), they are poor predictors of outcomes for an individual23. Even highly accurate methylation or immune-based ageing clocks24 measure the steady state at a point in time, but they do not measure dynamic resilience – the ability to respond to and recover from stress.

We need to be able to identify and measure the parameters of resilience and the factors and processes in complex biological systems that maintain and restore homeostasis and health. Such processes may include enhanced immunity, better energy management or improved stress responses, as seen in centenarians25. Such parameters and factors, plus validated models associated with these measures at multiple scales – from molecules to tissues and ultimately the whole body – would help to uncover causal mechanisms, identify individuals at risk of stress-event-induced deterioration in health, and accelerate clinical studies of interventions that aim to maintain or restore resilience.

Why now?

We are now in a position to leverage the power of deeply phenotyped longitudinal human cohorts and biobanks, combined with modern -omics technologies and bioinformatics tools in order to identify dynamic prognostic markers of human resilience. We can exploit new in vitro and in silico platforms to establish physiologically relevant human-derived systems to assess responses to stress/challenge. To accomplish this, we will need to draw together academic, clinical and commercial expertise across multiple disciplines (biology, chemistry, engineering, data science, computation/AI, human clinical sciences and trials) to identify personalised biomarkers of physiological resilience and to develop and test new interventions to improve health outcomes in older people.

The Dynamic Resilience program seeks to identify and validate causal measures and models of dynamic resilience, at multiple scales, with predictive value sufficient to make clinical decisions and to test interventions. Importantly, reducing progression to frailty in those over the age of 65 by 25% would protect over 75,000 adults in the UK alone, and potentially as many as 87 million older adults worldwide. It is realistic to believe that this is possible – frailty can be halted and even reversed26.

Program goals.

We have formulated the program goals below to address key fundamental questions to drive the measurement, modelling and testing capabilities needed to advance new methods of promoting healthy, whole lives: How do we measure and identify who is at greatest risk of health deterioration after a stress event? Why do some people stay in good health and others not? (in particular why is it that people who appear equally frail using steady state measures can show very different dynamic responses to stressor events?) What causes increased risk of health deterioration after a stress event (independent of individual disease states)? And how can we promote dynamic resilience and thus healthy aging for a greater number of people worldwide?

The three program goals are:

  1. Discover and integrate markers of human dynamic resilience that identify individuals prior to a stress event (SE) with prediction accuracy of >85% sensitivity and >90% specificity for clinical outcomes post-SE (e.g., return to health, frailty progression, loss of independence, death). 
  2. Develop multi-scale models that link the biomarkers predictive of loss of steady state and dynamic resilience to mechanism. It will be necessary to show that identified mechanisms (some of which may overlap with known hallmarks of ageing) either promote and maintain homeostasis, or are causative of resilience loss. Such models and demonstration of mechanism can be at the cellular, tissue, system, or whole-body scale.
  3. Validate the clinical and developmental utility of measures, models, and candidate preventative interventions to promote resilience in at-risk populations by undertaking specific, targeted trials. Of particular interest are trials involving preventative interventions in older adults prior to predictable stress events such as elective laparoscopic or orthopaedic surgery, or cancer therapy and that focus both on demonstrating pre-stressor predictive clinical outcome accuracy of >85% sensitivity and >90% specificity with respect to frailty progression and interventions that seek at least a 25% reduction in the number of patients showing frailty progression following the stress event.

Program Director.

Lynne Cox, PhD  is an Associate Professor of Biochemistry at the University of Oxford. She has expertise in the biological underpinnings of ageing and age-related diseases, specifically cell senescence and premature ageing. She earned her PhD at the University of Cambridge followed by a Royal Society of Edinburgh research fellowship at the University of Dundee. She has contributed to the UK’s national strategy on ageing and co-directs the UK Ageing Research Networks.

Who are eligible Wellcome Leap program performers?

Performers are from universities and research institutions: small, medium and large companies (including venture-backed); and government or non-profit research organizations. We encourage individuals, research labs, companies, or small teams to apply in program areas best aligned with their expertise and capabilities. It is not necessary to form a large consortium or a single team to address all thrusts or an entire program goal in an abstract or proposal. Indeed, one of the benefits of our programs is that we actively facilitate collaboration and synergies dynamically among performers as we make progress together toward the program’s goals.

Funding Partner.

This program is jointly funded with Temasek Trust.

Process and timeline
Program announcement.

30 DAYS FOR PREPARATION AND SUBMISSION OF ABSTRACT

15-Day Abstract review round.
/ Day 1
Submission deadline: 25 May 2023
/ Day 15
Abstract feedback sent: 9 June 2023

30 DAYS FOR PREPARATION OF FULL PROPOSALS AFTER ABSTRACT FEEDBACK

30-Day Full proposal review round.
/ Day 45
Submission deadline: 10 July 2023
/ Day 75
Proposal decision sent: 9 August 2023

Frequently asked questions.

If you have questions, please review our FAQ section. – updated 10 July 2023.
Send inquiries to DR@wellcomeleap.org

i https://ourworldindata.org/life-expectancy

ii Barnett et al, Epidemiology of multimorbidity and implications for health care, research, and medical education: a cross-sectional study. The Lancet, 2012. 380(9836): p. 37-43. DOI: 10.1016/S0140-6736(12)60240-2

iii O’Caoimh, R., et al., Prevalence of frailty in 62 countries across the world: a systematic review and meta-analysis of population-level studies. Age and Ageing, 2020. 50(1): p. 96-104. DOI: 10.1093/ageing/afaa219

iv Garmany et al, Longevity leap: mind the healthspan gap. npj Regenerative Medicine, 2021. 6(1): p. 57. DOI: 10.1038/s41536-021-00169-5

v https://www.un.org/en/development/desa/population/publications/pdf/ageing/WorldPopulationAgeing2019-Highlights.pdf

vi https://www.cdc.gov/injury/features/older-adult-falls/index.html

vii https://www.gov.uk/government/publications/falls-applying-all-our-health/falls-applying-all-our-health

viii https://www.scfn.org.uk/clinical-frailty-scale

ix Berian et al, Association of Loss of Independence With Readmission and Death After Discharge in Older Patients After Surgical Procedures. JAMA Surg, 2016. 151(9): p. e161689. DOI: 10.1001/jamasurg.2016.1689

x Financial costs for health and social care for adults over 65 range from 4-13% of national GDP for countries across the world (see https://library.fes.de/pdf-files/ipg/ipg-2002-1/artjacobzone-oxley.pdf), and will only increase further as world populations age.

xi Khoudary et al, Menopause Transition and Cardiovascular Disease Risk: Implications for Timing of Early Prevention: A Scientific Statement From the American Heart Association. Circulation, 2020. 142(25): p. e506-e532. DOI: doi:10.1161/CIR.0000000000000912

xii https://www.endocrine.org/patient-engagement/endocrine-library/menopause-and-bone-loss

xiii Wang, S., et al., Cancer Treatment-Induced Accelerated Aging in Cancer Survivors: Biology and Assessment. Cancers (Basel), 2021. 13(3). DOI: 10.3390/cancers13030427

xiv Wolf et al, Accelerated DNA methylation age: Associations with PTSD and neural integrity. Psychoneuroendocrinology, 2016. 63: p. 155-162. DOI: https://doi.org/10.1016/j.psyneuen.2015.09.020

xv https://www.srmrc.nihr.ac.uk/projects/determination-of-accelerated-ageing-in-trauma-patients-and-the-impact-on-rehabilitation/

xvi da Silva et al, Association between frailty and the combination of physical activity level and sedentary behavior in older adults. BMC Public Health, 2019. 19(1): p. 709. DOI: 10.1186/s12889-019-7062-0

xvii Gioia et al, SARS-CoV-2 infection induces DNA damage, through CHK1 degradation and impaired 53BP1 recruitment, and cellular senescence. Nature Cell Biology, 2023. DOI: 10.1038/s41556-023-01096-x

xviii Douaud et al, SARS-CoV-2 is associated with changes in brain structure in UK Biobank. Nature, 2022. 604(7907): p. 697-707. DOI: 10.1038/s41586-022-04569-5

xix Wang, W., et al., Long-term cardiovascular outcomes in COVID-19 survivors among non-vaccinated population: A retrospective cohort study from the TriNetX US collaborative networks. eClinicalMedicine, 2022. 53. DOI: 10.1016/j.eclinm.2022.101619

xxLópez-Otín, C., et al., The Hallmarks of Aging. Cell, 2013. 153(6): p. 1194-1217. DOI: https://doi.org/10.1016/j.cell.2013.05.039;  ; López-Otín, C., et al., Hallmarks of aging: An expanding universe. Cell, 2023. 186(2): p. 243-278. DOI: 10.1016/j.cell.2022.11.001; Schmauck-Medina, T., et al., New hallmarks of ageing: a 2022 Copenhagen ageing meeting summary. Aging (Albany NY), 2022. 14(16): p. 6829-6839. DOI: 10.18632/aging.204248

xxi Sierra, F., The Emergence of Geroscience as an Interdisciplinary Approach to the Enhancement of Health Span and Life Span. Cold Spring Harb Perspect Med, 2016. 6(4): p. a025163. DOI: 10.1101/cshperspect.a025163

xxii https://investingnews.com/daily/life-science-investing/genetics-investing/top-anti-aging-stocks/

xxiii Stow, D., et al., Evaluating frailty scores to predict mortality in older adults using data from population based electronic health records: case control study. Age Ageing, 2018. 47(4): p. 564-569. DOI: 10.1093/ageing/afy022

xxiv Lu, A.T., et al., DNA methylation GrimAge strongly predicts lifespan and healthspan. Aging (Albany NY), 2019. 11(2): p. 303-327. DOI: 10.18632/aging.101684; Sayed, N., et al., An inflammatory aging clock (iAge) based on deep learning tracks multimorbidity, immunosenescence, frailty and cardiovascular aging. Nature Aging, 2021. 1(7): p. 598-615. DOI: 10.1038/s43587-021-00082-y

xxvSimon, M., et al., A rare human centenarian variant of SIRT6 enhances genome stability and interaction with Lamin A. Embo j, 2022. 41(21): p. e110393. DOI: 10.15252/embj.2021110393; Karagiannis, T.T., et al., Multi-modal profiling of peripheral blood cells across the human lifespan reveals distinct immune cell signatures of aging and longevity. eBioMedicine. DOI: 10.1016/j.ebiom.2023.104514

xxviTravers, J., et al., Building resilience and reversing frailty: a randomised controlled trial of a primary care intervention for older adults. Age Ageing, 2023. 52(2). DOI: 10.1093/ageing/afad012

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