Early-life origins of brain resilience to mental illness and cognitive impairment across the life-course

Research in children in North America using brain scanning has shown that the brain develops less well and has a smaller surface area in children of families with less income. This result was not found in a study from Norway, where there is greater socioeconomic equality. Our own research has shown that being poor as a child is associated with more brain abnormalities in later life, which are associated with depression and dementia. Countries such as India are experiencing a rapid rise in what were considered "Western diseases", such as diabetes, combined with an increase in older people. In addition, there remain significant disparities in socioeconomic circumstance, access to education and healthcare. Researchers in the UK, in Mysore and in Mumbai have established groups of normal people (cohorts) at different ages and from different socioeconomic circumstances that have already provided much evidence on the early life origins of later life diseases, such as heart disease and diabetes. Here we will carry out work that will pave the way for a future large-scale study of mental health and thinking (cognitive) abilities in these groups. Concentrating on the Mysore groups in this application, we plan four projects that will help us design our future project to include people in Mysore and Mumbai.

1. We will invite a small number of the younger and older Mysore cohorts to have a brain scan first to find out how acceptable scanning is for them and secondly as a pilot study to test whether early life circumstances influence measurable changes on brain scans. We will investigate what factors in early life (such as your father's job, your birth weight) predict brain scan appearances.

2. By speaking with participants we will find out what people who are part of these informative cohorts think about volunteering for brain scans, blood tests and new computer tests of their thinking (cognitive) abilities. We will ask them how they view keeping information about them on a computer and their opinions of combining this information with other health and education information about them. We will also take account of local permissions, participants' and researchers' views on creation of a future database that allows their information to be securely stored, transferred between institutions in India and anonymously available to future researchers. Such a collection of information would grow over time and allow future research to answer our question about the impact of early life environment on important mental health outcomes.

3. Provided participants agree, we will collect blood samples, cheek scrape samples, repeat tests of thinking abilities and depressive symptoms to add to existing research records and to allow us to calculate how many scans and tests would be needed in a future large-scale study to provide meaningful information. We will also take account of local permissions, participants' and researchers' views on creation of a future database that allows this information to be securely stored, transferred between institutions in India and anonymously available to future researchers.

4. We will host a workshop at the University of Aberdeen for investigators from India and Aberdeen to discuss and plan analysis of the extensive information available in these participants and how we best design a data analysis plan, based on pilot data, existing expertise on "big data" approaches and meaningful statistical analysis for a future large-scale application to address our research question.

The work we propose here will provide the preparatory work for a future study to discover what aspects of early life environment can be modified to reduce mental illness and cognitive decline in India. This addresses three of the Sustainable Development Goals: i) Goal 3-to ensure healthy lives and promote well-being for all at all ages; ii) Goal 4-to promote lifelong learning opportunities for all; iii) Goal 10-to reduce inequalities.

Cortical surface area on Magnetic Resonance Imaging (MRI) from the Paediatric Imaging and NeuroGenetic dataset in North America varies with family income and this relationship is steepest at poorest incomes. This result was not found in Norway, where there is greater equality of socioeconomic circumstance (SEC). Our own research has shown that poorer childhood SEC predicts smaller hippocampi and more brain lesions in late life, which are linked to depressive symptoms and poorer cognition. Here we will extend research to cohorts in Mysore, India, with different SEC and culture, in whom rich life-course and risk factor data exist. We propose pilot work, public engagement and workshops to inform a large-scale future application to investigate hypotheses that early life factors influence risk of subsequent mental illness and cognitive decline. Concentrating on the Mysore groups here, we plan four activities that will inform design of a future project to include cohorts in Mysore and Mumbai. These are deliberately designed around data science, to enable work to be scaled-up and to create a resource for future research:
Imaging - we will invite subsamples of young and older Mysore cohorts for brain MRI to assess feasibility, acceptability and to measure effect size to inform future power calculation.
Health informatics - using public engagement with participants we will determine their views on data linkage of pre-existing data, data to be collected and creation of a bio-resource.
Bioinformatics - we will collect new cognitive data, using a game that tests navigational ability, repeat previous cognitive and depression data, blood samples and buccal smears to obtain DNA and RNA for future analysis.
Computing science - we will host a workshop at the University of Aberdeen to which Indian and UK co-investigators will be invited to brainstorm "big data' management, analysis and machine learning methods to test in pilot data and apply to future large-scale work.

The proposed work is designed to have impact in the short, medium and long term. In the short term the impact will be through development of new collaborations, collection of new brain MRI, cognitive and bio-sample data and exploration of new ways of working. If larger scale funding applications are successful the work proposed here will lead to a bio-repository and infrastructure to support data linkage and facilitate meaningful analysis of large, complex datasets, to answer important questions about modifiable factors to alter mental health outcomes. This will have a positive impact for future research and make the data collected available to researchers across the globe for pooled analyses.
Ultimately this work will have the greatest impact if it contributes to prevention of the massive human burden that is mental illness and cognitive decline.