A $45M PROGRAM

The First 1000 Days

PROMOTING HEALTHY BRAIN NETWORKS

A $45M PROGRAM

The First 1000 Days

PROMOTING HEALTHY BRAIN NETWORKS

A $45M PROGRAM

The First
1000 Days
PROMOTING HEALTHY
BRAIN NETWORKS
We are pleased to announce the selected performers.
Mauro Costa-Mattioli, Baylor College of Medicine
Kirsten Donald, University of Cape Town
Elena Geangu, University of York
Peter Gluckman, Liggins Institute, University of Auckland & Singapore Institute for Clinical Sciences
Uri Hasson, Princeton University
Rebecca Lawson, University of Cambridge
Victoria Leong, Nanyang Technological University
Sergiu Pasca, Stanford University
Guilherme Polanczyk, University of São Paulo
Dustin Scheinost, Yale University

We all know what a difference a day makes. The first 1000 days can make all the difference to a child’s start in life, perhaps more so than we ever understood before.

In this early period, we develop critical cognitive abilities, such as executive function (EF) and self-regulation. By the end of the first 1000 days, a child’s individual EF performance changes their odds of dealing successfully with opportunities and obstacles they face in life. Well-developed EF improves a child’s chances for lifelong physical, neural, and mental health; reduces the pace of aging; and underpins greater productivity and prosperity. Indeed, if EF is underdeveloped it has significant consequences. We know that children with underdeveloped EF at age 3 represent about 20 percent of the population, but make up nearly 80 percent of adults who are likely to require some form of societal or economic assistance. So how do we assess and promote healthy development in the first 1000 days?

We routinely measure height and weight to

assess a child’s physical health.

We routinely measure height and weight to assess a child’s physical health.

We routinely measure height and weight to assess a child’s physical health.

We also need objective, scalable ways to

assess a child’s cognitive health.

We also need objective, scalable ways to assess a child’s cognitive health.

We also need objective, scalable ways to assess a child’s cognitive health.

During the first 1000 days, the brain undergoes extensive network construction and remodeling in response to interactions with the environment, that in turn endows the capacity to successfully live in that environment. For example: a child’s postnatal nutrition influences the health of circuit formation; their physical exploration is key to development of sensorimotor skills; and their social interactions with caregivers are central to language and emotional development. But we lack tools and models that are predictive of the influence and dependency of these factors on individual network development. Without them, we cannot optimise the key ingredients necessary for promoting healthy brain development, nor identify those at risk of being underdeveloped. Timing is critical – because developmental windows are narrow. For example, previously neglected children admitted into foster care before 24 months old versus those admitted after 26 months show significant differences in their ability to regain aspects of cognitive function by adolescence. And the results can be dramatic – if we could accurately predict and improve EF outcomes by 20% in 80% of children before age 3, we could reduce the risk of childhood obesity by nearly 20%, reduce the risk of accelerated ageing by about 12% and potentially reduce the risk of encounters of crime by over 20%.

If we could develop accurate, scalable, early screening methods to predict EF outcomes, risk-stratify children, and predict responses to interventions in the first 1000 days, we could help ensure a healthy and productive life for millions globally. Importantly, this goal may now be within our reach.

Program goals.

1. Develop a fully integrated model and quantitative measurement tools of network development in the first 1000 days, sufficient to predict EF formation before a child’s first birthday, with 80% predictive validity for EF outcomes at age 3.

1a. The model and measures should capture critical windows of network development from sensorimotor to language and prefrontal networks and the connections established between them.

1b. The integrated model should predict contributions of nutrition, the microbiome, and the genome on circuit formation, as well as, sensorimotor and social interactions on network pruning processes, both in relation to EF outcomes at age 3.

1c. Predictive validity should be verified against assessments of network differences and environmental influences in retrospective studies of a statistically relevant number of children.

2. Create scalable methods for optimising promotion, prevention, screening and therapeutic interventions to improve EF by at least 20% in 80% of children before age 3. Of interest are improvements from underdeveloped EF to normative or from normative to well-developed EF across the population to deliver the broadest impact. Techniques that improve EF by 80% or more in 20% of at-risk children are important, but they are not the sole focus of this program.

Advances across models and measures should inform each other to improve and validate predictive markers, environmental influences and optimise the key ingredients necessary for promoting healthy network development. It is not necessary to form a large consortium or team to do this. Synergies and integrated system demonstrations will be facilitated by Wellcome Leap on an annual basis as we make progress together towards the program goals.

Program Director.

Holly Baines, PhD has expertise in developing disruptive strategies and initiatives in the health and life sciences funding sector while at the Wellcome Trust. She has led the development and delivery of multi million pound programs and managed multi-disciplinary teams across a range of areas from mental health to data science. She earned her PhD in Neuroscience and Ageing from Newcastle University, United Kingdom.

Send inquiries to 1kD@wellcomeleap.org

Who are eligible 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 Leap programs is that we actively facilitate collaboration and synergies dynamically among performers as we make progress together toward the program’s goals.

Process and timeline

1kD Program announcement.

30 DAYS FOR PREPARATION AND SUBMISSION OF ABSTRACT

15-Day Abstract review round.

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Day 1

Submission deadline: 8 April 2021

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Day 1

Submission deadline: 8 April 2021

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Day 1

Submission deadline:

8 April 2021

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Day 15

Abstract feedback sent: 23 April 2021

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Day 15

Abstract feedback sent: 23 April 2021

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Day 15

Abstract feedback sent:

23 April 2021

30 DAYS FOR PREPARATION OF FULL PROPOSALS AFTER ABSTRACT FEEDBACK

30-Day Full proposal review round.

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Day 45

Submission deadline: 24 May 2021

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Day 45

Submission deadline: 24 May 2021

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Day 45

Submission deadline:

24 May 2021

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Day 75

Proposal decision sent: 23 June 2021

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Day 75

Proposal decision sent: 23 June 2021

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Day 75

Proposal decision sent:

23 June 2021

Frequently Asked Questions.

If you have questions, please review our FAQ section – updated 21 June.

Send inquiries to 1kD@wellcomeleap.org

[i] Moffit, T.E., Arseneault, L., Belsky, D., et al. A gradient of childhood self-control predicts health, wealth and public safety. PNAS. 108: 2693-2698 (2011).

[ii] Richmond-Rakerd, L.S., Caspi, A., Ambler, A., et al. Childhood self-control forecasts the pace of midlife aging and preparedness for old age. PNAS. 118: (2021). https://doi.org/10.1073/pnas.2010211118

[iii] Caspi, A., Houts, R.M., Belsky, D.W., et al. Childhood forecasting of a small segment of the population with large economic burden. Nat Hum Behav. 1: (2016). doi:10.1038/s41562-016-0005.

[iv] Wade, M., Fox, N. A., Zeanah, C.H., and Nelson, C. A. Long-term effects of institutional rearing, foster care and brain activity on memory and executive functioning. PNAS. 116: (5) 1808-1813 (2019). https://doi.org/10.1073/pnas.1809145116

[v] Fox, N.A., Almas, A.N., Degnan, K.A., et al. The effects of severe psychosocial deprivation and foster care intervention on cognitive development at 8 years of age: findings from the Bucharest Early Intervention Project. Journal of Child Psychology and Psychiatry. 52:9: 919–928 (2011).

[vi] https://openai.com/blog/emergent-tool-use/

[vii] Wang, Q., Zhang, H., Poh, J.S., et al. Sex-Dependent Associations among Maternal Depressive Symptoms, Child Reward Network, and Behaviors in Early Childhood. Cerebral Cortex. 30 (3): 901-912 (2020). doi: 10.1093/cercor/bhz135.

[viii] Roy, B.C., Frank, M.C., DeCamp, P., Miller, M., and Roy, D. Predicting the birth of a spoken word. PNAS. 112: 12663–12668 (2015).  https://doi.org/10.1073/pnas.1419773112

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