Paula Lousie Mcclean

University of Ulster · Biomedical Sciences Research Institute

Introduction: Cellular senescence is the irreversible growth arrest subsequent to oncogenic mutations, DNA damage, or metabolic insult. Senescence is associated with ageing and chronic age associated diseases such as cardiovascular disease and diabetes. The involvement of cellular senescence in acute kidney injury (AKI) and chronic kidney disease (...

Missing Alzheimer's disease (AD) data is prevalent and poses significant challenges for AD diagnosis. Previous studies have explored various data imputation approaches on AD data, but the systematic evaluation of deep learning algorithms for imputing heterogeneous and comprehensive AD data is limited. This study investigates the efficacy of denoisi...

Cellular senescence is the irreversible growth arrest subsequent to oncogenic mutations, DNA damage or metabolic insult. Senescence is associated with aging and chronic age associated diseases such as cardiovascular disease and diabetes. The involvement of cellular senescence in Acute Kidney Injury (AKI) and Chronic Kidney Disease (CKD) is not full...

Making accurate diagnosis of Alzheimer's disease (AD) is crucial for effective treatment and management. Although deep learning has been applied to AD classification, it is typically performed at group level, the data used are not sufficiently heterogeneous and comprehensive, and decision confidence is not evaluated at individual (single patient) l...

Making accurate diagnosis of Alzheimer's disease (AD) is crucial for effective treatment and management. Although deep learning has been applied to AD classification, it is typically performed at group level, the data used are not sufficiently heterogeneous and comprehensive, and decision confidence is not evaluated at individual (single patient) l...

Accurate diagnosis of Alzheimer's disease (AD) relies heavily on the availability of complete and reliable data. Yet, missingness of heterogeneous medical and clinical data are prevalent and pose significant challenges. Previous studies have explored various data imputation strategies and methods on heterogeneous data, but the evaluation of deep le...

Background: The Clinical Dementia Rating Scale Sum of Boxes (CDRSOB) score is known to be highly indicative of cognitive-functional status and is regularly employed for clinical and research purposes. Objective: Our aim is to determine whether CDRSOB is consistent with clinical diagnosis in evaluating drug class associations with risk of progress...

Background Many cardiovascular diseases are associated with chronic kidney disease (CKD) and their burden as comorbidities is high. There is a pressing need to understand the molecular mechanisms by which cardiovascular diseases drive the development of CKD in multimorbidity. Methods and Results We performed an analysis of the risk of CKD onset ac...

Clinical presentation of diseases is complicated by multimorbidity. There is a pressing need to understand the effects of multimorbidity and where interventions should be targeted. We performed a data-driven analysis of whole-cohort UK Biobank hospital inpatient data in women and men and assembled ICD10 disease sequence trajectories. Age-relative 1...

Alzheimer’s disease (AD) is a complex neurodegenerative condition that is characterized by the build-up of amyloid-beta plaques and neurofibrillary tangles. While multiple theories explaining the aetiology of the disease have been suggested, the underlying cause of the disease is still unknown. Despite this, several modifiable and non-modifiable fa...

Abstract Biomarkers for Alzheimer's disease (AD) diagnosis do not always correlate reliably with cognitive symptoms, making clinical diagnosis inconsistent. In this study, the performance of a graphical neural network (GNN) classifier based on data‐driven diagnostic classes from unsupervised clustering on heterogeneous data is compared to the perfo...

Background: Dementia is a group of symptoms that largely affects older people. The majority of patients face behavioural and psychological symptoms (BPSD) during the course of their illness. Alzheimer’s disease (AD) and vascular dementia (VaD) are two of the most prevalent types of dementia. Available medications provide symptomatic benefits and pr...

Dementia with Lewy Bodies (DLB) is the second most common form of dementia, but diagnostic markers for DLB can be expensive and inaccessible, and many cases of DLB are undiagnosed. This work applies machine learning techniques to determine the feasibility of distinguishing DLB from Alzheimer's Disease (AD) using heterogeneous data features. The Rep...

Current machine learning techniques for dementia diagnosis often do not take into account real-world practical constraints, which may include, for example, the cost of diagnostic assessment time and financial budgets. In this work, we built on previous cost-sensitive feature selection approaches by generalising to multiple cost types, while taking...

Biomarkers for Alzheimer's disease (AD) diagnosis do not always correlate reliably with cognitive symptoms, making clinical diagnosis inconsistent. In this study, the performance of a graphical neural network (GNN) classifier based on data-driven diagnostic classes from unsupervised clustering on heterogeneous data, is compared to the performance o...

Current machine learning techniques for dementia diagnosis often do not take into account real-world practical constraints, which may include, for example, the cost of diagnostic assessment time and financial budgets. In this work, we built on previous cost-sensitive feature selection approaches by generalising to multiple cost types, while taking...

Dementia with Lewy Bodies (DLB) is the second most common form of dementia, but diagnostic markers for DLB can be expensive and inaccessible, and many cases of DLB are undiagnosed. This work applies machine learning techniques to determine the feasibility of distinguishing DLB from Alzheimer’s Disease (AD) using heterogeneous data features. The Rep...

Objective: Despite the potential of machine learning techniques to improve dementia diagnostic processes, research outcomes are often not readily translated to or adopted in clinical practice. Importantly, the time taken to administer diagnostic assessment has yet to be taken into account in feature-selection based optimisation for dementia diagno...

Objective Despite the potential of machine learning techniques to improve dementia diagnostic processes, research outcomes are often not readily translated to or adopted in clinical practice. Importantly, the time taken to administer diagnostic assessment has yet to be taken into account in feature-selection based optimisation for dementia diagnosi...

Introduction: Cardiovascular disease (CVD) is the leading cause of mortality in people with Type 2 diabetes mellitus (T2DM). Statins reduce low-density lipoproteins and positively affect CVD outcomes. Statin type and dose have differential effects on glycaemia and risk of incident T2DM; however, the impact of gender, and of individual drugs within...

Introduction: We assessed the association of self-reported hearing impairment and hearing aid use with cognitive decline and progression to mild cognitive impairment (MCI). Methods: We used a large referral-based cohort of 4358 participants obtained from the National Alzheimer's Coordinating Center. The standard covariate-adjusted Cox proportion...

Accurate computational models for clinical decision support systems require clean and reliable data but, in clinical practice, data are often incomplete. Hence, missing data could arise not only from training datasets but also test datasets which could consist of a single undiagnosed case, an individual. This work addresses the problem of extreme m...

The dysregulated immune system represents a major target for improving health outcomes in a range of chronic conditions. This chapter describes key changes in the immune system as we age and showcases its dysregulation across five chronic conditions including diabetes, cardiovascular disease, and cancer, highlighting dysregulated key immune system...

Background There is growing evidence that alterations in the endocannabinoid system (ECS) co‐occur with dementia pathophysiology. Currently, limited literature is available on components of the peripheral ECS as diagnostic markers for dementia. Methods In the present study we analysed the concentrations of the endocannabinoids (eCBs) anandamide (A...

Background: Clinical Dementia Rating Sum of Boxes (CDRSOB) scale is known to be highly indicative of cognitive-functional status, but it is unclear whether it is consistent with clinician diagnosis in evaluating drug class associations with risk of progression to mild cognitive impairment (MCI) and dementia. Methods: We employed multivariate logist...

Introduction Hearing aid usage has been linked to improvements in cognition, communication, and socialization, but the extent to which it can affect the incidence and progression of dementia is unknown. Such research is vital given the high prevalence of dementia and hearing impairment in older adults, and the fact that both conditions often coexis...

The increasing prevalence of dementia in older adults warrants attention to the identification of practices that can delay or reduce likelihood of progression to early forms of cognitive impairment, in particular, to mild cognitive impairment (MCI) which is often considered a transitional stage between healthy aging and dementia. In this study, we...

Background: Dementia is caused by a variety of neurodegenerative disease(s) and is associated with a decline in memory and other cognitive abilities, while inflicting enormous socioeconomic burden. The complexity of dementia and its associated comorbidities, present immense challenges for dementia research and care, particularly in clinical decisi...

Background Hearing loss is the third most commonly reported chronic disease in older adults. Its prevalence ranges from 30% in individuals aged 65‐74 years to 40%‐60% in those aged 75 years or older. Evidence suggests that age‐related hearing impairment is strongly and independently associated with the decline in cognitive abilities and that indivi...

Background: Systems Medicine is a novel approach to medicine, i.e. an interdisciplinary field that considers the human body as a system, composed of multiple parts and of complex relationships at multiple levels, and further integrated into an environment. Exploring Systems Medicine implies understanding and combining concepts coming from diametral...

Introduction: Conflicting results on dementia risk factors have been reported across studies.We hypothesize that variation in data preparationmethods may partially contribute to this issue. Methods: We propose a comprehensive data preparation approach comparing individuals with stable diagnosis over time to those who progress to mild cognitive impa...

INTRODUCTION: Hearing aid usage has been linked to improvements in cognition, communication, and socialization, but the extent to which it can affect the incidence and progression of dementia is unknown. Such research is vital given the high prevalence of dementia and hearing impairment in older adults, and the fact that both conditions often coexi...

Dementia is a collection of symptoms associated with impaired cognition and impedes everyday normal functioning. Dementia, with Alzheimer’s disease constituting its most common type, is highly complex in terms of etiology and pathophysiology. A more quantitative or computational attitude towards dementia research, or more generally in neurology, is...

Accurate computational models for clinical decision support systems require clean and reliable data, but in clinical practice, data are often incomplete. Hence, missing data could arise not only from training datasets but also test datasets which could consist of a single undiagnosed case, an individual. Many popular methods of handling missing dat...

Data imputation is the most popular method of dealing with missing values, but in most real life applications, large missing data can occur and it is difficult or impossible to evaluate whether data has been imputed accurately (lack of ground truth). This paper addresses these issues by proposing an effective and simple principal component based me...

Data imputation is the most popular method of dealing with missing values, but in most real life applications, large missing data can occur and it is difficult or impossible to evaluate whether data has been imputed accurately (lack of ground truth). This paper addresses these issues by proposing an effective and simple principal component based me...

Alzheimer's disease (AD) is an age-specific neurodegenerative disease that compromises cognitive functioning and impacts the quality of life of an individual. Pathologically, AD is characterised by abnormal accumulation of beta-amyloid (A$\beta$) and hyperphosphorylated tau protein. Despite research advances over the last few decades, there is curr...

Dementia is a collection of symptoms associated with impaired cognition and impedes everyday normal functioning. Dementia, with Alzheimer's disease constituting its most common type, is highly complex in terms of etiology and pathophysiology. A more quantitative or computational attitude towards dementia research, or more generally in neurology, is...

Alzheimer's disease (AD) is an age-specific neurodegenerative disease that compromises cognitive functioning and impacts the quality of life of an individual. Pathologically, AD is characterised by abnormal accumulation of beta-amyloid (Ab) and hyperphosphorylated tau protein. Despite research advances over the last few decades, there is currently...

Background Hearing aid usage has been linked to improvements in cognition, communication, and socialization, but the extent to which it can affect the onset and progression of dementia is unknown. This study leveraged the National Alzheimer's Coordinating Center Uniform Data Set to longitudinally examine the association between the use of hearing a...

Background: Systems Medicine is a novel approach to medicine, i.e. an interdisciplinary field that considers the human body as a system, composed of multiple parts and of complex relationships at multiple levels, and further integrated into an environment. Exploring Systems Medicine implies understanding and combining concepts coming from diametral...

Brain functional connectivity (FC) analyses based on magnetoencephalographic (MEG) signals have yet to exploit the intrinsic high-dimensional information. Typically, these analyses are constrained to regions of interest to avoid the curse of dimensionality, which leads to conservative hypothesis testing. We removed such constraint by extending clus...

Computerized clinical decision support systems can help to provide objective, standardized, and timely dementia diagnosis. However, current computerized systems are mainly based on group analysis, discrete classification of disease stages, or expensive and not readily accessible biomarkers, while current clinical practice relies relatively heavily...

Various epidemiological studies have shown an association between high midlife blood pressure and late-life incident dementia and cognitive decline. This study evaluated some of the commonly prescribed antihypertensive drugs and their association with progression to dementia from healthy and mild cognitive impairment (MCI) stages.

Alzheimer’s disease (AD) is of great cause for concern in our ageing population, which currently lacks diagnostic tools to permit accurate and timely diagnosis for affected individuals. The development of such tools could enable therapeutic interventions earlier in the disease course and thus potentially reducing the debilitating effects of AD. Gly...

Certain cardio-metabolic implications are associated with an increased risk for dementia. However, several studies have shown a degree of variability which complicate our understanding of the role of such risk factors on dementia. This study aims to further understand such risk variability by evaluating the association of these risk factors with re...

Cardio-metabolic risk factors have been implicated in dementia risk but with contrasting results reported across studies. For reliable risk prediction, a comprehensive analysis of multiple risk factors is required. This is particularly important in groups that progress from normal and mild cognitive impairment (MCI) to dementia stages. This study e...

Computerized clinical decision support systems can help to provide objective, standardized, and timely dementia diagnosis. However, current computerized systems are mainly based on the group analysis, discrete classification of disease stages, or expensive and not readily accessible biomarkers, while current clinical practice relies relatively heav...

Aims & objectives: Despite increased efforts to develop prognostic models for dementia progression, current frameworks are limited mainly to methodologies that involve either single time point models or are heavily dependent on biomarkers. Our research project aims to develop a prognostic multiple time-point model for assessing the likelihood of de...

As populations age, prevalence of Alzheimer's disease (AD) is rising. Over 100 years of research has provided valuable insights into the pathophysiology of the disease, for which age is the principal risk factor. However, in recent years, a multitude of clinical trial failures has led to pharmaceutical corporations becoming more and more unwilling...

Background: Diabetes and hypertension are accepted risk factors for dementia, despite gaps in knowledge regarding the underlying pathological links. Currently available therapeutics have demonstrated efficient disease management, especially in the case of hypertension, however, contrasting data are available on whether treatment of these conditions...

Background: The growing public health threat posed by dementia raises the urgency to develop reliable prognostic frameworks for early detection of the disease. Moreover, recent direction for dementia drug discovery and development is pointing towards focusing on the pre-symptomatic stage, and hence identifying dementia risk becomes crucial. Despite...

Introduction: Dementia, with Alzheimer’s disease (AD) being its most common form, is one of the most important contributors to dependence and disability of older people and the focus of growing clinical research interest. Along with the intensive search for interventions that can modify progression of dementia symptoms, researchers investigate vari...

INTRODUCTION: Accurate diagnosis is crucial to the treatment and management of Alzheimer’s disease (AD). However, clinical data can be incomplete or inconsistent and the resultant “missing data” can affect any computational algorithms that seek to objectively identify the disease severity level. In this work, we employed several computational metho...

Cognitive dysfunction and neuroinflammation are typical in Alzheimer's disease (AD), but are also associated with normal aging, albeit less severely. Insulin resistance in the brain has been demonstrated in AD patients and is thought to be involved in AD pathophysiology. Using 15-18 month-old APP/PS1 mice, this study measured peripheral and central...

Aims: Metabolic disease increases risk of Alzheimer's disease and cognitive dysfunction. Chronic high fat diet (HFD) feeding leads to cognitive impairment and neuroinflammation. This study demarcated pathological events in brain as a result of short-term to chronic HFD feeding. Efficacy of Xenin-25[Lys(13)PAL] was assessed in chronic HFD-fed mice....

Certain endogenous bile acids have been proposed as potential therapies for ameliorating Alzheimer’s disease (AD) but their role, if any, in the pathophysiology of this disease is not currently known. Given recent evidence of bile acids having protective and anti-inflammatory effects on the brain, it is important to establish how AD affects levels...

Introduction: Management of co- and multi-morbidity continues to represent a major clinical challenge. There remains a lack of understanding of how multiple pathologies or conditions co-evolve or interact and importantly how treatments should be combined to effectively improve outcomes. This review highlights the challenges presented to the clinica...

Introduction The brain metabolome of APP/PS1 double transgenic mice and wild type (WT) littermates was profiled longitudinally (6, 8, 10, 12 and 18 months) using a non-targeted metabolomics methodology. Using LC-MS/MS (Thermo LTQ Orbitrap Elite) a total of 658 spectral features were detected, aligned, quantified and compared in mouse brain. Materi...

Introduction Bile acids play complex roles in cell signalling and immunomodulation and they have been linked to Alzheimer’s disease (AD). This study used LC-MS/MS to comprehensively profile 22 bile acids in brain and plasma from AD patients and APP/PS1 mice. Materials and methods Metabolites in plasma and brain extracts were quantified by an est...

The pathogenesis of Alzheimer's disease (AD) is complex involving multiple contributing factors. The extent to which AD pathology impacts upon the metabolome is still not understood, nor is it known how disturbances change as the disease progresses. For the first time we have profiled longitudinally (6, 8, 10, 12 and 18 months) both the brain and p...

Type 2 diabetes is a risk factor for Alzheimer's disease (AD). Previously, we have shown that the diabetes drug liraglutide is protective in middle aged and in old APP/PS1 mice. Here, we show that liraglutide has prophylactic properties. When injecting liraglutide once-daily ip. in two months old mice for 8 months, the main hallmarks of AD were muc...

Introduction The brain and plasma metabolome of APP/PS1 double transgenic mice and wild type littermates were profiled longitudinally (6, 8, 10, 12 and 18 months) by a targeted metabolomics approach. A total of 184 metabolites including amino acids, biogenic amines, phospholipids and acylcarnitines were quantified by ultra-high performance liquid...

Cerebral microvascular impairments occurring in Alzheimer's disease may reduce amyloid-beta (Aβ) peptide clearance and impact upon circulatory ultrastructure and function. We hypothesised that microvascular pathologies occur in organs responsible for systemic Aβ peptide clearance in a model of Alzheimer's disease and that Liraglutide (Victoza(®) )...

Previously, we have developed a retro-inverso peptide inhibitor (RI-OR2, rGffvlkGr) that blocks the in vitro formation and toxicity of the Aβ oligomers which are thought to be a cause of neurodegeneration and memory loss in Alzheimer's disease. We have now attached a retro-inverted version of the HIV protein transduction domain 'TAT' to RI-OR2 to t...