Population Award

Principal Investigator: Dr Danijela Tatovic
School of Medicine

Type 1 diabetes (T1D) is caused when the T-cells of the immune system destroy insulin-producing cells in the pancreas. Remarkably, identical twins exist where one has T1D and the other does not. We have access to the best cohort of such twins in the world via our collaborator, David Leslie, and will study these individuals to understand the mechanism by which T-cells cause T1D. T-cells recognise their targets through receptors on their surface called T-cell receptors (TCRs). There are billions of different TCRs, which can differ even in genetically identical individuals. The T-cells that react to insulin producing cells in the diseased twin should be absent in the twin without disease. TCRs genes in these T-cells should therefore act as biomarkers of T1D even before the onset of symptoms.

Once we know which TCRs cause disease in identical twins we will aim to extend our studies to other patients to see whether we can predict and understand disease based on TCR analysis. This Population Award will allow generation of important preliminary data and formation of new collaborations to provide a solid foundation for a larger project aimed at early disease prediction and intervention.

Principal Investigator: Professor Kim Graham
School of Psychology

In this project, we will test mothers who are part of a unique birth cohort based in Bristol University (Avon Longitudinal Study of Parents and Children, ALSPAC). The study aims to understand how our genes may influence our memory as we age.

Individuals involved in the study will do three psychology tasks on their home computers using our new Cardiff Web Tools for Cognitive Health (CWTCH) research platform. The tasks test the ability to tell apart and remember different scenes, objects and faces.

This dataset will allow us to understand how differences in our genes may affect our ability to process complex visual scenes (as opposed to other equally complex visual stimuli). Navigation in spatial environments and memory for complex visual scenes is a marker of Alzheimer’s disease, and this project will allow us to test how performance on our CWTCH tasks is affected by genetic risk of Alzheimer’s disease.

Principal Investigator: Dr Kate Langley
School of Psychology

Children with Attention Deficit Hyperactivity Disorder (ADHD) are at increased risk of developing additional mental health problems in early adulthood and using A&E Departments. The reasons for this are unknown with little research on this topic.

One major barrier to researching this topic is that tracking children with ADHD into early adulthood is very difficult as they are poor outpatient attenders. GP data-linkage studies offer an attractive solution. The Wales-based Secure Anonymous Information Linkage (SAIL) databank anonymously collates routinely collected data (from the NHS, Government and schools) for almost everyone in Wales. Using this resource, we plan to identify all children diagnosed with ADHD in Wales, then electronically track their outcomes using routine data from this population dataset to identify predictors of poor outcomes.

We also previously collected a sample of children with ADHD. We’d like to invite them into the data-linkage study and electronically track their outcomes. Because we already have so much information about them, they’re an ideal group to see what predicts later outcomes and inform analyses in the larger population dataset.

Having created these unique datasets in this project, we will apply for further funding to investigate predictors of poor early adult outcomes of childhood ADHD.

Principal Investigator: Professor Mike Robling
School of Medicine

Our research team studied whether visits from specially trained nurses improved the lives of teenage mothers and their babies. By the time children were two years old, mothers reported their children's language to be better developed when compared to families who received only usual NHS care. As a potentially important finding, it is now essential to provide accurate and independent measures of the children's language.

Over 500 video-recordings of the two year olds and their mothers originally collected to assess attachment, now provide a unique opportunity to independently measure children's language, how mothers talk about how their child is feeling and how mothers and children talk with each other. We have established the feasibility of rating these videos. We are also following up all families until their children are six using information from routine health, education and social care. By analysing the videos we will be able to see whether child language and maternal language two years after birth has a longer-term impact, for example on educational performance in primary school. This study brings together our original research team and developmental and clinical psychologists across Cardiff University. It provides a low-cost opportunity to further assess the value of specialist home-visiting.

Principal Investigator: Dr Lisa Hurt
School of Medicine

When someone has more than one long-term illness at the same time, this is called "multimorbidity". More research on this is needed, because we don’t know how best to look after this group of people. Very little is known about multimorbidity in children. For example, we don’t know how many children are affected, which illnesses commonly happen together, or the effect on children’s health and education in the long-term. Without this knowledge, we can’t provide good care.

In this project, we will link records that already exist in Wales to work out which children have one or more long-term illnesses. This includes information from general practice records and hospital admissions. This will create a dataset for future research and funding bids to describe the effects of multimorbidity on children’s lives and identify opportunities for interventions that improve outcomes.

We plan to work with a researcher in Norway on this project. This will help us to understand if patterns of multimorbidity in children are the same in different places. We also plan to work with researchers in York who look at the cost of health care. This will help us to understand how to improve care and reduce costs.

Principal Investigator: Dr Amal Gadalla
School of Medicine

DNA sequencing approaches to identify all bacteria and their resistance genes in urinary tract infections (UTI).  UTI is one of the most common infections in the community, particularly among women. Resistance to the most commonly used antibiotic has reached 34%. Routine microbiology does not reveal a causative agent for all patients with UTI symptoms.

Here we will identify the best experimental methods to describe the collective bacterial populations (microbiome) existing in human urine which are implicated in infection and poor response to antibiotic treatment (resistance). We will use urine samples and associated clinical data (before and after treatment) collected during a previous UTI study in women. Consent was given to use samples for laboratory-based studies.

We will apply advanced DNA sequencing comparing two approaches: direct testing using extracted DNA from urine and DNA extracted from bacteria grown after laboratory culture of urine. Using advanced computational technology, we will identify bacterial microbiome and genes associated with antibiotic resistance in these samples.  We are interested in the individuals’ microbiome variation over time, specifically the presence and effect of prolonged carriage of antibiotic resistant bacteria. This pump-priming study will allow us to determine the most appropriate methods to use in larger studies.

Principal Investigator: Professor Andrew Lawrence
School of Psychology

By the time the core motor symptoms of Parkinson’s disease (PD) emerge and the diagnosis is made, the disease has been present for many years. Starting treatment earlier, in the very earliest (prodromal) stages, would increase the numbers of potentially salvable neurons and prevent symptoms, rather than treating them. For this to be possible, means of diagnosing and tracking the progression of the prodromal disease must be developed.

Rapid Eye Movement (REM) sleep behaviour disorder (RBD) is characterized by unpleasant dreams and loss of normal muscle atonia. Over time, almost all patients with RBD develop an alpha-synucleinopathy, most being diagnosed with PD. Therefore, they give us an unprecedented opportunity to study prodromal PD. We will scan a unique cohort of patients across the spectrum of the disease, recruiting subjects with PD and RBD, and use advanced microstructural brain imaging at CUBRIC in order to establish feasibility and sensitivity of the approach to quantify the nature and degree of early white matter pathology in those patients. We hope this will shed new light on our understanding of the link between RBD and PD, and help us to develop an imaging biomarker to diagnose and track prodromal PD in a large cohort of patients.

Principal Investigator: Dr Joanne Lello
School of Biosciences

Schistosomiasis and malaria are diseases that cause suffering for millions of people and about 640,000 deaths a year, with sub-Saharan Africa most severely affected. The parasites causing these diseases can simultaneously infect the same person (coinfection). At the moment, we do not fully understand how these parasites interact with one another, or how best to treat co-infection. Understanding what happens to young children is particularly important because they are at high risk from both infections.

Using data from a study of schistosomiasis in mothers and infants, we can follow changes in individual parasite levels, and disease status, in 662 Ugandan mothers and 1211 of their young children (<5 years), for up to 18 months. Analysing infection in such young children will help us to see how a first infection with one of these parasites affects the chances of infection by the other and the severity of disease. We can also assess how each parasite responds when the other is treated. Then by comparing responses in children to those in their mothers, we can also see how age influences the parasite interaction. Analysis of these data will help us to design more successful control strategies for both parasite groups.