Brain network alterations due to cardiometabolic risk factors:insights from population magnetic resonance imaging

This thesis investigated whether life style related risk factors are associated with novel neuronal imaging markers and evaluated the value of structural and functional brain network measures for that purpose. The life style related risk factors, also called cardiometabolic risk factors, studied in this thesis are (pre)diabetes, physical inactivity, high sedentary time, high blood pressure, obesity, and high cholesterol. The research summarized and extended the existing evidence on associations between cardiometabolic risk factors and subtle brain changes as assessed by structural and advanced Magnetic Resonance Imaging (MRI). More specifically, it was found that high blood sugar was associated with structural brain alterations, even in the prediabetes phase. Physical inactivity was also associated with structural brain alteration, especially in brain regions highly specialized in motor function. Furthermore, the research found an interrelation of brain damage in the form of white matter lesions (WML), structural brain alterations, and cognitive function. In particular, WMLs in structural brain connections important for information processing speed were associated with cognitive slowing. Finally, the research observed that neuronal and non-neuronal physiological signals could be recognized in the functional MRI signal, and that this signal is altered in people with cardiometabolic risk factors

Differences in structural connectivity between diabetic and psychological erectile dysfunction revealed by network-based statistic: A diffusion tensor imaging study

IntroductionType 2 diabetes mellitus (T2DM) has been found to be associated with abnormalities of the central and peripheral vascular nervous system, which were considered to be involved in the development of cognitive impairments and erectile dysfunction (ED). In addition, altered brain function and structure were identified in patients with ED, especially psychological ED (pED). However, the similarities and the differences of the central neural mechanisms underlying pED and T2DM with ED (DM-ED) remained unclear.MethodsDiffusion tensor imaging data were acquired from 30 T2DM, 32 ED, and 31 DM-ED patients and 47 healthy controls (HCs). Then, whole-brain structural networks were constructed, which were mapped by connectivity matrices (90 × 90) representing the white matter between 90 brain regions parcellated by the anatomical automatic labeling template. Finally, the method of network-based statistic (NBS) was applied to assess the group differences of the structural connectivity.ResultsOur NBS analysis demonstrated three subnetworks with reduced structural connectivity in DM, pED, and DM-ED patients when compared to HCs, which were predominantly located in the prefrontal and subcortical areas. Compared with DM patients, DM-ED patients had an impaired subnetwork with increased structural connectivity, which were primarily located in the parietal regions. Compared with pED patients, an altered subnetwork with increased structural connectivity was identified in DM-ED patients, which were mainly located in the prefrontal and cingulate areas.ConclusionThese findings highlighted that the reduced structural connections in the prefrontal and subcortical areas were similar mechanisms to those associated with pED and DM-ED. However, different connectivity patterns were found between pED and DM-ED, and the increased connectivity in the frontal–parietal network might be due to the compensation mechanisms that were devoted to improving erectile function

Convolutional Neural Networks for Classification of T2DM Cognitive Impairment Based on Whole Brain Structural Features

PurposeCognitive impairment is generally found in individuals with type 2 diabetes mellitus (T2DM). Although they may not have visible symptoms of cognitive impairment in the early stages of the disorder, they are considered to be at high risk. Therefore, the classification of these patients is important for preventing the progression of cognitive impairment.MethodsIn this study, a convolutional neural network was used to construct a model for classifying 107 T2DM patients with and without cognitive impairment based on T1-weighted structural MRI. The Montreal cognitive assessment score served as an index of the cognitive status of the patients.ResultsThe classifier could identify T2DM-related cognitive decline with a classification accuracy of 84.85% and achieved an area under the curve of 92.65%.ConclusionsThe model can help clinicians analyze and predict cognitive impairment in patients and enable early treatment

Peripheral inflammation and neurocognitive impairment: correlations, underlying mechanisms, and therapeutic implications

Cognitive impairments, such as learning and memory deficits, may occur in susceptible populations including the elderly and patients who are chronically ill or have experienced stressful events, including surgery, infection, and trauma. Accumulating lines of evidence suggested that peripheral inflammation featured by the recruitment of peripheral immune cells and the release of pro-inflammatory cytokines may be activated during aging and these conditions, participating in peripheral immune system-brain communication. Lots of progress has been achieved in deciphering the core bridging mechanism connecting peripheral inflammation and cognitive impairments, which may be helpful in developing early diagnosis, prognosis evaluation, and prevention methods based on peripheral blood circulation system sampling and intervention. In this review, we summarized the evolving evidence on the prevalence of peripheral inflammation-associated neurocognitive impairments and discussed the research advances in the underlying mechanisms. We also highlighted the prevention and treatment strategies against peripheral inflammation-associated cognitive dysfunction

Disease-modifying effects of type 2 diabetes mellitus and bipolar disorder comorbidity

Aim: The aim of this review was to better understand the risks and care issues associated with poorly managed type 2 diabetes mellitus, in relation to poor prognosis of bipolar disorder. Methods: A systematic review of the literature was conducted using combined terms “Type 2 diabetes” OR “Insulin Resistance” AND “Bipolar Disorder” AND “Outcome” AND “Course of illness” in a variety of databases. The publications were all filtered following pre-defined criteria. Results: Nine primary articles were selected. The analysis showed that in patients diagnosed with type 2 diabetes, there was association of higher uncontrolled bipolar symptoms period corresponding with the severity of the bipolar disorder. Individuals with bipolar disorder and diabetes mellitus experienced neurodegenerative disorders with more depressive symptoms. Additionally, higher rate of non-compliance was identified with the use of bipolar disorder medications. Conclusions: Overall results indicated an overlapping clinical pathophysiology relationship between both diabetes mellitus and neuropsychiatric disorders. There is a need for collaborative care among psychiatric and general medical providers

Crosstalk between Depression, Anxiety, and Dementia: Comorbidity in Behavioral Neurology and Neuropsychiatry

This Special Issue highlights the most recent research on depression, anxiety and dementia, with attention to comorbidity in a range of diseases. The symptoms of depression, anxiety and dementia are the most common comorbid manifestations present in patients suffering from neurodegenerative and psychiatric diseases. Together, these illnesses constitute an extremely complex and challenging research field due to their inherent multifactorial causative factors, heterogeneous pathogenesis, and mental and behavioral manifestations. This Special Issue covers laboratory, clinical and statistical studies on the crosstalk between depression, anxiety, dementia, Alzheimer’s disease, multiple sclerosis, schizophrenia, diabetes mellitus, Down’s syndrome, and/or compulsive disorders. It contains contributions from 71 authors, has been reviewed by 25 referees, and edited by three academic editors and one managing editor

Insulin resistance and Parkinson's disease: A new target for disease modification?

There is growing evidence that patients with Type 2 diabetes have an increased risk of developing Parkinson's disease and share similar dysregulated pathways suggesting common underlying pathological mechanisms. Historically insulin was thought solely to be a peripherally acting hormone responsible for glucose homeostasis and energy metabolism. However accumulating evidence indicates insulin can cross the blood-brain-barrier and influence a multitude of processes in the brain including regulating neuronal survival and growth, dopaminergic transmission, maintenance of synapses and pathways involved in cognition. In conjunction, there is growing evidence that a process analogous to peripheral insulin resistance occurs in the brains of Parkinson's disease patients, even in those without diabetes. This raises the possibility that defective insulin signalling pathways may contribute to the development of the pathological features of Parkinson's disease, and thereby suggests that the insulin signalling pathway may potentially be a novel target for disease modification. Given these growing links between PD and Type 2 diabetes it is perhaps not unsurprising that drugs used the treatment of T2DM are amongst the most promising treatments currently being prioritised for repositioning as possible novel treatments for PD and several clinical trials are under way. In this review, we will examine the underlying cellular links between insulin resistance and the pathogenesis of PD and then we will assess current and future pharmacological strategies being developed to restore neuronal insulin signalling as a potential strategy for slowing neurodegeneration in Parkinson's disease

Network Analysis Identifies SOD2 mRNA as a Potential Biomarker for Parkinson's Disease

Increasing evidence indicates that Parkinson's disease (PD) and type 2 diabetes (T2DM) share dysregulated molecular networks. We identified 84 genes shared between PD and T2DM from curated disease-gene databases. Nitric oxide biosynthesis, lipid and carbohydrate metabolism, insulin secretion and inflammation were identified as common dysregulated pathways. A network prioritization approach was implemented to rank genes according to their distance to seed genes and their involvement in common biological pathways. Quantitative polymerase chain reaction assays revealed that a highly ranked gene, superoxide dismutase 2 (SOD2), is upregulated in PD patients compared to healthy controls in 192 whole blood samples from two independent clinical trials, the Harvard Biomarker Study (HBS) and the Diagnostic and Prognostic Biomarkers in Parkinson's disease (PROBE). The results from this study reinforce the idea that shared molecular networks between PD and T2DM provides an additional source of biologically meaningful biomarkers. Evaluation of this biomarker in de novo PD patients and in a larger prospective longitudinal study is warranted

The development and evaluation of exercise, cognitive, and dual-task interventions targeting cognitive dysfunction in type 2 diabetes mellitus

Approximately 3.5 million individuals are diagnosed with diabetes in the UK, with 90% of cases attributed to type 2 diabetes mellitus (T2DM). The worldwide prevalence of T2DM has rapidly increased, rising from 108 million in 1980 to 422 million in 2014. In addition to the well-recognised microvascular and macrovascular complications, emerging evidence suggests that T2DM is also associated with an increased risk of cognitive dysfunction. Considering the increasing prevalence, in addition to the increasing life expectancy of older adults, the development of cognitive dysfunction in this population may seriously challenge future health services. Therefore, there is an urgent need to identify effective strategies that may lead to improved therapy in the future. Whilst exercise, cognitive, and dual-task interventions have previously been identified as successful strategies for targeting cognition in other population groups, little is known regarding the effect of these types of interventions in T2DM. The primary aim of this doctoral thesis was to develop and evaluate exercise, cognitive, and dual-task interventions for targeting cognitive dysfunction in individuals with T2DM. The series of studies presented in this thesis (chapters 2-5) were conducted using a systematic phased approach in accordance with the MRC’s framework for the development and evaluation of complex interventions. The initial study (chapter 2) involved conducting a systematic review and meta-analysis and identified only a limited number of exercise, cognitive, and dual-task trials in T2DM. The overall quality of included trials was mixed, with the majority of trials having a moderate to high risk of bias. Meta-analyses of exercise trials showed small to moderate effects of exercise on executive function (0.31) and memory (0.20), but were not statistically significant. Due to the limited number of cognitive and dual-task trials identified, a narrative synthesis was conducted which showed a positive effect of these types of interventions for improving tasks of global cognition, executive function and memory. It was concluded that larger, more robust trials were needed to further understand the impact of these types of intervention in T2DM. The subsequent study (chapter 3) piloted exercise, cognitive, and dual-task interventions in T2DM to help identify a suitable intervention to test for feasibility and acceptability. The findings of this intervention development study found cognitive training was the most iv enjoyable and preferred. Together, the accumulated evidence identified in study 1 and 2 was used to develop a suitable cognitive training study ready to be evaluated for its feasibility and acceptability in T2DM. The final study as part of this doctoral thesis aimed to explore the feasibility (chapter 4) and acceptability (chapter 5) of a cognitive training study in T2DM. Feasibility was shown in important aspects of the study including the adherence, retention and motivation of participants whilst only minor amendments were recommended to the study design, recruitment pathways, and data collection. Improvements in several cognitive domains including executive function, visual memory, and reaction time were also observed following cognitive training in which serum levels of BDNF were shown to unexpectedly reduce following cognitive training. The acceptability findings suggest that participants found the cognitive training study highly enjoyable and that the study components were well accepted in this population. However, recommendations were made for clearer communication of the study aims and processes in addition to greater involvement for those allotted to the control group. Evidence derived from both the quantitative (chapter 4) and qualitative (chapter 5) elements of this study were used to develop a set of important recommendations that should be considered prior to undertaking a future definitive trial. Overall, the findings from this doctoral thesis provide systematic and convincing evidence for the potential feasibility, acceptability, and efficacy of a randomised controlled trial to evaluate the effectiveness of a cognitive training intervention in T2DM

Investigating cognition in chronic opioid use: Potential role for the gut microbiota

Impairment in cognitive functioning is a core component of opioid dependence due to its importance in the course of addiction and its role in treatment, but the effect of opioid use on cognition in individuals undergoing early stages of treatment is under examined, particularly in the Australian population. Although existing pharmacological options have demonstrated some efficacy in treating opioid dependence, they are limited in their ability to treat the cognitive dysfunction present in opioid dependent individuals. Hence, there is a need for novel treatment options that address these limitations. The commensal gut microbiota can engage in bidirectional communication with the brain and thus influence brain function, including cognition. Dysbiosis of the microbiota has been reported in several areas of addiction and concomitant cognitive impairment, and may serve as a target for potential future novel treatments. The effect of opioid use on the gut microbiota is inconclusive, however. The present thesis aimed to: a) investigate cognition in individuals with a history of chronic opioid use during the early stages of rehabilitation treatment in an Australian setting; b) examine the effect of opioid use on the gut microbiota, and; c) outline the functional potential of the gut microbiota in opioid use and how it may relate to key signalling pathways of the microbiota-gut-brain axis. In Chapter 2, Australian participants at early stages of community-based rehabilitative treatment (including treatment with methadone or buprenorphinenaloxone, BNX) underwent neurocognitive testing. Results demonstrated impaired cognitive functioning compared to the general population, but no significant differences between performance in BNX compared to methadone-treated participants. BNX treatment was associated with a longer length of stay, which could indicate greater treatment adherence. The potential influence of treatment and non-treatment related parameters were also examined. Treatment related factors (e.g., time since last dose, life-time length of treatment) had a significant relationship with cognitive performance in BNX-treated participants, but not methadone treated participants. Neurocognitive performance was also significantly influenced by non-treatment related demographics factors, such as age and BMI. Together, these findings demonstrate cognitive impairment in people undergoing residential rehabilitation for opioid addiction and highlight treatment and demographics parameters that could potentially influence cognitive outcomes and should be considered in future studies. In Chapter 3, a systematic literature review was conducted to investigate the effect of opioids on the gut microbiota. Results demonstrated that opioid use resulted in dysbiosis of the gut microbiota, and identified specific microbes that were repeatedly dysbiotic across clinical and preclinical studies for the first time. Opioid use also resulted in alterations to key signalling pathways of the microbiota-gut-brain axis, suggesting the potential for opioid induced dysbiosis of the gut microbiota to influence cognition. These results may have significant implications for future research aiming to better understand the pathology of opioid dependence, and may inform the development of future novel treatments that improve the lives of people with opioid dependence