Enhancing healthcare impact and patient benefit for trauma survivors with complex mental health problems using face-to-face and digitally assisted Eye-Movement Desensitisation and Reprocessing (EMDR) therapy

Psychosis (including experiences like hearing or seeing things other people do not) and bipolar disorder (including experiencing intense fluctuations in mood) are major causes of disability and suffering in the UK and worldwide. Traumatic experiences (for example, physical or emotional abuse) are common for people with psychosis and bipolar disorder, and people who have had traumatic life events generally suffer from more intense and upsetting symptoms.

Eye Movement Desensitisation and Reprocessing (EMDR) is a therapy that aims to improve mental health difficulties brought about by trauma. Our team has conducted important pilot work in the application of this therapy for people with early psychosis. The study found that EMDR was delivered safely and was well-received by most patients. There were signals that EMDR might help to improve upsetting symptoms that are common in people with early psychosis.

We want to conduct additional research to see whether EMDR can address upsetting experiences in people who have recently developed – or are at risk of developing – psychosis, or bipolar disorder. We first need to further improve the suitability of EMDR therapy to these populations, in preparation for larger-scale research trials, and before making EMDR therapy available across the NHS for people with these types of difficulties.

Over 9 months, we will work with an expert EMDR consultant to produce bespoke EMDR therapy manuals to make sure that the therapy is appropriate for people experiencing these different kinds of difficulties. To do this, we will use our pilot findings, including feedback from people who received the therapy and therapists who delivered it, to amend the EMDR approach to make sure it is suitable for people experiencing early psychosis. We will also build on this work to adapt the therapy to make it suitable for people at high risk of developing psychosis, and people experiencing symptoms of early bipolar disorder.

Supporting Digital Technology Assessment Criteria (DTAC) compliance enabling sight impairment case-finding integration within Pharmacy Software Systems

Background: Medication errors cause an estimated 1,708 deaths each year in England and cost the NHS £98 million. Whilst some medications are more likely to cause errors, there are also some patient groups who are higher risk of errors because of impairments they have. One such group are people with sight impairments (PwSI).

Our solution: Online workshops with PwSI and community pharmacists (CP), explored the issues faced and discussed solutions that could help prevent errors. PwSI and CPs both suggested one-to-one consultations, during which pharmacists could help people distinguish between medications by adding markers recognisable by touch, providing instructions on how to take medication safely and what safety information they need to know in accessible formats (audio, large font). CPs currently have no access to this information, and in our audit 48% PwSI were unknown to their pharmacist.

This proposal: Working with Imago Student Software we co-produced software to search diagnoses on the patients’ electronic health record. When a match occurs, an instruction to display a highly visible ‘shaded’ eye logo is sent, that can be activated on the pharmacy computer. The logo (courtesy of The Partially Sighted Society) will be used to prompt pharmacists to offer a consultation supported by strategies found on our webpage. Pharmacists and PwSI will decide together which will help based on their needs, type and level of sight impairment.

As this process accesses NHS data, we have to illustrate that it is secure, accurate in finding PwSI and is safe. This award funds Safehand Consulting to support DTAC compliance (DCB 0129/0160 & Cyber Essentials) which will allow our software to be used with real NHS patient data, helping achieve our aim of promoting medication safety for PwSI.

Optimisation of a non-invasive RNA-based diagnostic for kidney fibrosis by deep learning

About 15% of UK adults (over 65) are living with a disease that slowly and quietly reduces how well their kidneys work, this is known as chronic kidney disease. Most people do not know they have the disease until their kidneys have been damaged enough to make them feel ill. At the moment, a doctor can only find out exactly how much damage has occurred by requesting a procedure known as biopsy, which is the insertion of a large needle into your kidney through the skin. We have developed an alternative test which is based entirely on urine. We capture kidney cells that are naturally shed into the flow of urine and then measure the activity of all genes in those cells. We currently use a statistical method to transform our measurements of gene activity into a kidney damage score that can then be provided to a patient’s doctor. After measuring gene activity in a set of 100 patient samples we have now found that our statistical method is not flexible enough to work reliably for urine from all patients. This is why we are now creating a more flexible method that can adapt to the measurements coming from different patients to still give a reliable kidney damage score. More specifically, we will be using deep-learning methods–which are often referred to as artificial intelligence or AI–and very powerful computers to create a new model that will adapt to the different kidney damage “signals” which are present in urine across all our patient samples. We believe that this new more flexible method will allow doctors to start using our test for monitoring the health of their patient’s kidneys.

Psoriatic arthritis across the lifecourse: a new data resource for classification and prediction of outcome

What do we already know?

Psoriatic arthritis can begin in childhood or adulthood. The condition varies from person to person. It commonly affects the joints, skin, nails or scalp often causing significant negative impact on quality of life. Despite the similarities in how psoriatic arthritis looks in both children and adults, there are notable differences in how it’s managed. Research, disease labels and treatment guidelines are entirely separate between these two age groups. While there are 14 ‘targeted’ treatments available for adults with psoriatic arthritis, only two are available for children.

What do we need to improve?

Researching psoriatic arthritis as a single disease, no matter what age it started, could help better understand causes of disease. If we could find groups of children who have similar disease to adults, this could speed up access to the ‘adult’ drugs.

The first step is understanding how different the disease is if it started in childhood or adulthood. To do this, we need data from children and adults to compare how the disease unfolds over time.

We have data in childhood psoriatic arthritis housed here at Manchester, as part of the Childhood Arthritis Prospective Study. What we don’t have is similar adult data to compare against. The Norfolk Arthritis Register (NOAR) is a large dataset of adults with arthritis, running since 1989, with up to 20 years of data. This large dataset has a lot of information about arthritis, but needs more information about skin and nail psoriasis.

What are we planning to do?

With help from a data scientist, we will get information about skin and nail psoriasis from the medical records of people already in the NOAR study. We will then explore differences between psoriatic arthritis that started in childhood or adulthood. In the longer-term, we can then use these data for future research on treatments and impacts of psoriatic arthritis across child and adulthood.

How will this research affect people with psoriatic arthritis?

1. More inclusive research including testing of drugs across ages
2. Uncover groups of psoriatic arthritis who have different types of disease, helping guide treatment
3. Help treatment planning for young people with psoriatic arthritis who progress into adult clinics
4. This project will develop a world-leading dataset for future research in psoriatic arthritis.

Investigating lymphocyte signatures of interstitial lung disease in patients with connective tissue diseases: a novel precision medicine approach

Connective tissue diseases (CTDs) are conditions which effect the skin, joints and anything that holds the body together. These include conditions such as systemic sclerosis and lupus. These diseases are caused by the body’s own immune system attacking itself and causing inflammation and irreversible scarring. One organ that can be severely affected by this is the lung. Inflammation and scarring of the connective tissue of the lung is called interstitial lung disease (ILD). When this happens as part of a general CTD, it is called CTD-ILD. CTD-ILD leads to major disability due to breathlessness and can cause premature death in many cases.

At present, we do not know which patients with CTD will develop ILD and how severe the ILD will be. We are also unsure how well patients will respond to the available treatments and urgently need new and better treatments to improve life expectancy in patients with CTD-ILD. To answer some of these questions, we have set up a project to try and find markers in blood which will help us predict which patients may develop CTD-ILD, identify patients with more progressive disease and help predict response to treatment. We will be testing some immune-system markers we have developed in previous experiments. We will look for these markers in blood samples provided by patients with CTD-ILD, ILD not caused by CTD, CTD without ILD and healthy people. These patients will be recruited in hospitals across Greater Manchester. We will compare these blood markers between the groups to find out if they help us predict the presence of CTD-ILD and will also test if they predict patients whose lung disease progresses. We will also test if these markers change after treatment for CTD or ILD. We hope that the results of this project will improve clinical practice in the future through the use of these specific blood markers to guide treatment in patients with CTD-ILD.

Regulators of R loop-formation as therapeutic targets in recurrent glioblastoma

Glioblastoma (GBM) is a grade 4 brain tumour that forms the leading cause of cancer related death in children and adults under the age of 40. It is amongst the most lethal of solid tumours, with median survival rates of only 12-15 months following diagnosis. Despite therapeutic intervention by surgery, chemotherapy, and radiotherapy, the disease invariably reoccurs, with these recurrent tumours harnessing significant treatment resistance, leading to patient death. Further treatment only offers palliation to the patient, with every patient dying of their disease, marking a clear unmet clinical burden to tackle these recurrent and resistant tumours.

The aggressive nature and dismal prognosis of glioblastoma is underpinned by high levels of instability within the genome of the tumour. A stable genome is indispensable for the error-free transfer of genetic information to the next generation through the process of DNA replication and its faithful segregation into healthy daughter cells. Once replicated, DNA is transcribed into mRNA and then translated into functional proteins. Both replication and transcription can generate stress on the DNA double helix that, if not properly dealt with, can lead to genome instability, and unhealthy cells. In healthy cells, the process of DNA replication and transcription is dichotomized to prevent replication-transcription collisions (RTCs). RTCs result in the formation of RNA-DNA hybrid structures called R-loops. These structures are a recurrent source of DNA damage, leading to the high levels of instability found in GBM. The overall understanding of the complex role that R-loops play in the maintenance of genomic stability is limited and we seek to use our patient derived models of GBM to uncover regulators of R-Loops. Through our bespoke R-Loop mapping assay, we aim to identify key occurrences during RTC and signatures of disease recurrence that are therapeutically actionable, with clear translation to the clinic. By identifying key regulators of disease recurrence, we aim to target R-Loops by identifying molecules that will sensitise GBM to existing therapies such as radiotherapy and prevent glioblastoma recurrence and inevitably patient death.

Two hit approach – Using CRISPR screens to identify the key chromatin-related/epigenetic proteins in breast cancer metastasis

Breast cancers are the most common cancers in women across the world and they are majorly driven by female hormones. Due to the highly specific therapies developed against the hormonal receptors, breast cancers are treatable. However, cancer cells evolve to become aggressive and start to move to distant organs which leads to spreading of the cancer, called as metastasis. Metastasis is the greatest challenge to treat any cancers.

There are specific alterations in genes which are present in these metastatic patients, but not in the primary breast disease. Cells with these DNA changes are somehow selected and grow dominantly and aggressively than other cells. These cells usually don’t respond to any existing therapies. Recent studies identified that subunit genes from a chromatin-associated complexes are heavily altered in these metastatic cells alone, leading to absence of the protein and function of the complex. These genes are well-known proteins which control tumour growth. Our recent and collaborative studies identified that the absence of these proteins leads to resistance to treatments and metastasis. In order to treat the metastatic cancers caused by the absence of these proteins, we need to employ the two-hit approach, where loss of another associated protein when the chromatin-associated protein is absent, together can stop metastasis. However, the knowledge about these associated proteins in an unbiased manner is extremely limited.

In this project, we will utilize the Access to Expertise funding to employ gene editing technology focused on chromatin proteins to identify the associated proteins which can be targeted in the metastatic cancers. Our research will attempt to understand the role of the most relevant proteins of chromatin complexes in controlling metastasis leading to the development of precision-based medicine.