Artificial intelligence approaches to investigating nutrition and health in ageing: analysis of data from the TUDA cohort of older adults, with development of novel food solutions for preventing chronic disease

Summary

Globally, the population is ageing rapidly, and it is estimated that the number of people aged over 60 years will reach 2 billion by 2050. As populations age, the prevalence of chronic diseases increases substantially, with older adults accounting for an estimated 23% of the global burden of disease. Chronic diseases of ageing including cardiovascular disease, diabetes, musculoskeletal and neuropsychiatric disorders are the leading causes of disability, reduced quality of life, and mortality among older adults. Furthermore, these conditions frequently coexist, with an estimated 67% of people aged 75 years and older in the UK living with multimorbidity. This demographic transition is a major public health challenge, creating significant economic and health and social care burdens worldwide. Consequently, strategies aimed at preventing, delaying, or better managing chronic diseases are a major global public health priority.

Advancing age and genetic susceptibility are important non-modifiable risk factors for chronic diseases. Genome-wide association studies have identified numerous genetic variants that are associated with age-related conditions. However, genetic variance only accounts for a small proportion of chronic disease risk. A wide range of modifiable health, lifestyle, environmental, and social factors also contribute significantly to the development and progression of disease in ageing. It has been estimated that a substantial proportion of chronic disease burden could be prevented or alleviated through effective modification of these risk factors. Nutrition is a key determinant and modifiable risk factor for healthy ageing as it lays an important role in the prevention and management of multiple chronic diseases. Dietary patterns such as the Mediterranean, DASH and MIND diets, alongside specific nutrients including B-vitamins, vitamin D, omega-3 polyunsaturated fatty acids, and dietary protein, have been associated with better cardiometabolic, musculoskeletal, cognitive health outcomes. However, the majority of research to date has investigated nutrition and other factors individually, whereas chronic diseases arise through complex interactions between biological, genetic, environmental, behavioural, and social determinants. Understanding these multidimensional interactions is essential for developing more effective strategies to promote healthy ageing, reduce the burden of multimorbidity and increase the number of years living with good health and well-being.

This proposal aims to provide a better understanding of the complex interactions between biological, environmental, lifestyle, and genetic factors underpinning chronic diseases of ageing through the application of state-of-the-art Artificial Intelligence (AI) and Geographical Information System (GIS) technologies to an existing Island of Ireland resource for ageing research, namely the Trinity-Ulster, Department of Agriculture (TUDA) study.

PhD Project
This interdisciplinary PhD project will utilise and build substantially upon the North-South of Ireland collaborative ageing and health resource, the TUDA study. The TUDA study was established to investigate nutritional, environmental, and clinical determinants of healthy ageing and includes extensive phenotypic, dietary, biomarker, pharmacological and health data from over 5,000 adults aged 60 years and older across Ireland, with follow up sampling of 20% of the original sample. State-of-the-art genomic methodologies will be used to complete Whole Genome Sequencing on biobanked samples from TUDA participants, providing comprehensive genomic data that can be integrated with existing clinical, nutritional, biochemical, and lifestyle information. AI and machine learning approaches will be applied to these multidimensional datasets to identify complex interactions and predictive patterns associated with major chronic diseases of ageing. GIS technologies will further enable investigation of environmental exposures, geographical variation, and social determinants of health in relation to chronic disease risk and healthy ageing.

The proposed project is highly innovative, integrating genomics, nutrition, environmental science, AI, and geospatial analytics within a unique, very well-characterised ageing cohort. This interdisciplinary approach will provide new insights into the biological, dietary and environmental determinants of chronic disease. The evidence generated will identify new novel food-based solutions for disease prevention and will inform public health strategies aimed at promoting healthy ageing, reducing chronic disease burden, and improving health and wellbeing in older adults.

This studentship is supported by a highly interdisciplinary supervisory team, combining expertise in nutrition and ageing  (Dr Catherine Hughes), nutritional science and metabolism (Prof Helene McNulty), advanced AI and machine learning methodologies (Prof Huiru Zheng). Furthermore, the successful candidate will be based at NICHE, a centre of excellence for Nutrition within the School of Biomedical Science, Ulster University.
https://www.ulster.ac.uk/research/topic/biomedical-sciences/research/nutrition-innovation-centre-for-food-and-health

Essential criteria

Applicants should hold, or expect to obtain, a First or Upper Second Class Honours Degree in a subject relevant to the proposed area of study.

We may also consider applications from those who hold equivalent qualifications, for example, a Lower Second Class Honours Degree plus a Master’s Degree with Distinction.

In exceptional circumstances, the University may consider a portfolio of evidence from applicants who have appropriate professional experience which is equivalent to the learning outcomes of an Honours degree in lieu of academic qualifications.

• Experience using research methods or other approaches relevant to the subject domain
• Sound understanding of subject area as evidenced by a comprehensive research proposal
• A comprehensive and articulate personal statement
• Clearly defined research proposal detailing background, research questions, aims and methodology
• A demonstrable interest in the research area associated with the studentship

Equal Opportunities

The University is an equal opportunities employer and welcomes applicants from all sections of the community, particularly from those with disabilities.

Appointment will be made on merit.

Funding and eligibility

This project is funded by:

• Northern Ireland Landscape partnership in AI for Bioscience (NILAB)

This scholarship will cover tuition fees and provide a maintenance allowance of £21,805 per annum for four years (subject to satisfactory academic performance).  A Research Training Support Grant (RTSG) of approximately £5000 per annum is also available.

To be eligible for these scholarships, applicants must meet the following criteria:

• Be a UK National, or

• Have settled status, or

• Have pre-settled status, or

• Have indefinite leave to remain or enter, or

• be an Irish National

Applicants should also meet the residency criteria which requires that they have lived in the EEA, Switzerland, the UK or Gibraltar for at least the three years preceding the start date of the research degree programme.

Applicants who already hold a doctoral degree or who have been registered on a programme of research leading to the award of a doctoral degree on a full-time basis for more than one year (or part-time equivalent) are NOT eligible to apply for an award.

Due consideration should be given to financing your studies.